Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C5: Econometric Modeling
/ / / C55: Large Data Sets: Modeling and Analysis

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This JEL code is mentioned in the following RePEc Biblio entries:

1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
2. > Econometrics > Forecasting > Nowcasting
3. > Econometrics > Time Series Models > Dynamic Factor Models

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This topic is covered by the following reading lists:

1. SOEP based publications
2. Socio-Economics of Innovation

2023

• Hyeongwoo Kim & Jisoo Son, 2023. "Forecasting Net Charge-Off Rates of Large U.S. Bank Holding Companies using Macroeconomic Latent Factors," Auburn Economics Working Paper Series auwp2023-02, Department of Economics, Auburn University.
• Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in High Dimensional Factor Models," CAMA Working Papers 2023-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in High Dimensional Factor Models," Papers 2303.00178, arXiv.org.
• Todor Krastevich, 2023. "Retargeting Customers Using Uplift Modeling," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 78-99.
• Marta Crispino & Vincenzo Mariani, 2023. "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers) 746, Bank of Italy, Economic Research and International Relations Area.
• Juan Pablo Cote-Barón & Karen L. Pulido-Mahecha & Nicol Valeria Rodríguez-Rodríguez & Carlos D. Rojas-Martínez, 2023. "El ISAE: Un Indicador para Monitorear la Actividad Económica Colombiana en Alta Frecuencia," Borradores de Economia 1225, Banco de la Republica de Colombia.
• Konstantin Boss & Andre Groeger & Tobias Heidland & Finja Krueger & Conghan Zheng, 2023. "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers 1387, Barcelona School of Economics.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023. "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," CESifo Working Paper Series 10223, CESifo.
• Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
• Jorge Barrientos Marin & Laura Marquez Marulanda & Fernando Villada Duque, 2023. "Analyzing Electricity Demand in Colombia: A Functional Time Series Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 75-84, January.
• Aiken, Emily L. & Bedoya, Guadalupe & Blumenstock, Joshua E. & Coville, Aidan, 2023. "Program targeting with machine learning and mobile phone data: Evidence from an anti-poverty intervention in Afghanistan," Journal of Development Economics, Elsevier, vol. 161(C).
• Camacho, Maximo & Caro, Angela & Peña, Daniel, 2023. "What drives industrial energy prices?," Economic Modelling, Elsevier, vol. 120(C).
• Yan, Wan-Lin, 2023. "Stock index futures price prediction using feature selection and deep learning," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
• Hayo, Bernd & Zahner, Johannes, 2023. "What is that noise? Analysing sentiment-based variation in central bank communication," Economics Letters, Elsevier, vol. 222(C).
• Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
  • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Xiong, Ruoxuan & Pelger, Markus, 2023. "Large dimensional latent factor modeling with missing observations and applications to causal inference," Journal of Econometrics, Elsevier, vol. 233(1), pages 271-301.
• Favero, Filippo & Grossi, Luigi, 2023. "Analysis of individual natural gas consumption and price elasticity: Evidence from billing data in Italy," Energy Economics, Elsevier, vol. 118(C).
• Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
• James, Robert & Leung, Henry & Prokhorov, Artem, 2023. "A machine learning attack on illegal trading," Journal of Banking & Finance, Elsevier, vol. 148(C).
• Arendt, Lukasz & Gałecka-Burdziak, Ewa & Núñez, Fernando & Pater, Robert & Usabiaga, Carlos, 2023. "Skills requirements across task-content groups in Poland: What online job offers tell us," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
• Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in High Dimensional Factor Models," Papers 2303.00178, arXiv.org.
  • Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in High Dimensional Factor Models," CAMA Working Papers 2023-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Paulo Rogério Faustino Matos & Felipe Bastos & Hecirlane Martins & Leilyanne Viana, 2023. "On the cross-city growth drivers of the most vulnerable region of Brazil," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 15(2), pages 77-103, January.
• O’Connell, Martin & Smith, Howard & Thomassen, Øyvind, 2023. "A two sample size estimator for large data sets," Discussion Papers 2023/1, Norwegian School of Economics, Department of Business and Management Science.
• Stüber, Heiko & Dauth, Wolfgang & Eppelsheimer, Johann, 2023. "A guide to preparing the sample of integrated labour market biographies (SIAB, version 7519 v1) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 57, pages 1-7.
• Nicodemo, Catia & Orso, Cristina E. & Tealdi, Cristina, 2023. "Overseas GPs and Prescription Behaviour in England," IZA Discussion Papers 15884, Institute of Labor Economics (IZA).
• Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023. "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers 15980, Institute of Labor Economics (IZA).
• Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023. "Remote Work across Jobs, Companies, and Space," NBER Working Papers 31007, National Bureau of Economic Research, Inc.
• Jonathan Hambur, 2023. "Did Labour Market Concentration Lower Wages Growth Pre-COVID?," RBA Research Discussion Papers rdp2023-02, Reserve Bank of Australia.
• Maximo Camacho & Andres Romeu, 2023. "Tourism and Gross Domestic Product short-run causality revisited: A symbolic transfer entropy approach," Tourism Economics, , vol. 29(1), pages 235-247, February.
• Nhung Nghiem & June Atkinson & Binh P. Nguyen & An Tran-Duy & Nick Wilson, 2023. "Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets," Health Economics Review, Springer, vol. 13(1), pages 1-13, December.
• Heiko Stüber & Wolfgang Dauth & Johann Eppelsheimer, 2023. "A guide to preparing the sample of integrated labour market biographies (SIAB, version 7519 v1) for scientific analysis," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-11, December.
• Pawan Kumar & Vipul Kumar Singh, 2023. "Examining the Time Varying Spillover Dynamics of Indian Financial Indictors from Global and Local Economic Uncertainty," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 99-121, March.
• Indra Budi & Yaniasih Yaniasih, 2023. "Understanding the meanings of citations using sentiment, role, and citation function classifications," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 735-759, January.
• Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023. "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, vol. 3(1), pages 1-32, January.
• Sylvia A. Allegretto & Dave Graham-Squire, 2023. "Monopsony in Professional Labor Markets: Hospital System Concentration and Nurse Wages," Working Papers Series inetwp197, Institute for New Economic Thinking.
• Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2302, Department of Economics, University of Missouri.

2022

• Kristoffer Pons Bertelsen, 2022. "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers 2022-05, Department of Economics and Business Economics, Aarhus University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2021-03, Department of Economics, Auburn University.
  • Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2022. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2022-03, Department of Economics, Auburn University.
• Laurence Kotlikoff, 2022. "Does Prediction Machines Predict Our AI Future? A Review," Journal of Economic Literature, American Economic Association, vol. 60(3), pages 1052-1057, September.
• Susanne Schennach, 2022. "Measurement Systems," Journal of Economic Literature, American Economic Association, vol. 60(4), pages 1223-1263, December.
• Gheorghe Zaman & Nicoleta Valentina Florea & Constantin Aurelian Ionescu & Dan Marius Coman & Doina Constanta Mihai & Nicoleta Luminita Gudanescu Nicolau, 2022. "Mathematical Model for Determining Costs of Unsatisfied Customers of HoReCa Industry," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 24(59), pages 268-268.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers 22/061, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022. "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers of the African Governance and Development Institute. 22/061, African Governance and Development Institute..
• Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022. "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN 2022003, Université catholique de Louvain, Louvain Finance (LFIN).
• Stefano Giglio & Bryan Kelly & Dacheng Xiu, 2022. "Factor Models, Machine Learning, and Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 14(1), pages 337-368, November.
• Агамбаева С.Б. // Agambayeva S.B. & Джусангалиева К.Е. // Jussangaliyeva K.E. & Акылбеков А.А. // Akylbekov A.A. & Ханетова А.Б. // Khanetova A.B., 2022. "Таргет по инфляции: формулировка цели и последствия ее смены. Обзор международного опыта. // Inflation target: the formulation of the target and the consequences of its change. Review of international," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 3/4, pages 4-25.
• Аринова Айжан // Arinova Aizhan & Ержан Ислам // Yerzhan Islam, 2022. "Использование транзакционных данных в качестве оперативного показателя экономической активности // Use of transactional data as an operational measure of economic activity," Working Papers #2022-11, National Bank of Kazakhstan.
• Joshua C.C. Chan, 2019. "Large hybrid time-varying parameter VARs," CAMA Working Papers 2019-77, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2022. "Large Hybrid Time-Varying Parameter VARs," Papers 2201.07303, arXiv.org, revised Jun 2022.
• Christophe Bellégo & David Benatia & Louis-Daniel Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Working Papers 2022-08, Center for Research in Economics and Statistics.
  • Christophe Bell'ego & David Benatia & Louis Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Papers 2203.11820, arXiv.org.
• Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
  • Giovanni Urga & Fa Wang, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," Papers 2205.12126, arXiv.org.
• Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  • Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
• Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series 21-09, Swiss Finance Institute.
  • Gaetan Bakalli & St'ephane Guerrier & Olivier Scaillet, 2022. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Papers 2208.00972, arXiv.org.
• Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202213, University of California at Riverside, Department of Economics.
  • Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Papers 2209.01697, arXiv.org.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Working Papers No 08/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Papers 2212.05841, arXiv.org.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series BEMPS97, Faculty of Economics and Management at the Free University of Bozen.
• Emilia VASILE & Danut Octavian SIMION, 2022. "Establishing And Achieving The Objectives Of Economic Information Systems Through Algorithms Specific To Business Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 65(1), pages 9-18, March.
• Danut Octavian SIMION & Emilia VASILE, 2022. "Optimizing Economic Applications By Optimizing Data Flows Present In Different Modules Integrated In Informatics Technology Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 66(2), pages 54-63, September.
• Maxim Ralchenko & Adrian Walton, 2022. "Historical Data on Repurchase Agreements from the Canadian Depository for Securities," Technical Reports 121, Bank of Canada.
• Thibaut Duprey & Daniel E. Rigobon & Philip Schnattinger & Artur Kotlicki & Soheil Baharian & T. R. Hurd, 2022. "Business Closures and (Re)Openings in Real Time Using Google Places," Staff Working Papers 22-1, Bank of Canada.
• James Chapman & Ajit Desai, 2022. "Macroeconomic Predictions Using Payments Data and Machine Learning," Staff Working Papers 22-10, Bank of Canada.
• Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CAMA Working Papers 2022-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," Staff Working Papers 22-38, Bank of Canada.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CESifo Working Paper Series 10034, CESifo.
• Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
• Giuseppe Cascarino & Mirko Moscatelli & Fabio Parlapiano, 2022. "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning," Questioni di Economia e Finanza (Occasional Papers) 674, Bank of Italy, Economic Research and International Relations Area.
• Valerio Astuti & Marta Crispino & Marco Langiulli & Juri Marcucci, 2022. "Textual analysis of a Twitter corpus during the COVID-19 pandemics," Questioni di Economia e Finanza (Occasional Papers) 692, Bank of Italy, Economic Research and International Relations Area.
• Rayane Hanifi & Klodiana Istrefi & Adrian Penalver, 2022. "Central Bank Communication of Uncertainty," Working papers 898, Banque de France.
• Ferran Sancho, 2022. "Stone-Geary Meets CES: An Extended Linear Expenditure System," Working Papers 1328, Barcelona School of Economics.
• Elena Shulyak, 2022. "Macroeconomic Forecasting Using Data from Social Media," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 86-112, December.
• Oyenyinka Sunday Omoshoro‐Jones & Lumengo Bonga‐Bonga, 2022. "Intra‐regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," The World Economy, Wiley Blackwell, vol. 45(1), pages 251-275, January.
  • Omoshoro-Jones, Oyeyinka Sunday & Bonga-Bonga, Lumengo, 2020. "Intra-regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," MPRA Paper 99514, University Library of Munich, Germany.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series BEMPS97, Faculty of Economics and Management at the Free University of Bozen.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Working Papers No 08/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Papers 2212.05841, arXiv.org.
• Takashi Nakazawa, 2022. "Constructing GDP Nowcasting Models Using Alternative Data," Bank of Japan Working Paper Series 22-E-9, Bank of Japan.
• Kakuho Furukawa & Ryohei Hisano & Yukio Minoura & Tomoyuki Yagi, 2022. "A Nowcasting Model of Industrial Production using Alternative Data and Machine Learning Approaches," Bank of Japan Working Paper Series 22-E-16, Bank of Japan.
• Kakuho Furukawa & Ryohei Hisano, 2022. "A Nowcasting Model of Exports Using Maritime Big Data," Bank of Japan Working Paper Series 22-E-19, Bank of Japan.
• Miren Azkarate-Askasua & Miguel Zerecero, 2022. "Correcting Small Sample Bias in Linear Models with Many Covariates," CRC TR 224 Discussion Paper Series crctr224_2022_376, University of Bonn and University of Mannheim, Germany.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Working Papers No 08/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series BEMPS97, Faculty of Economics and Management at the Free University of Bozen.
  • Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Papers 2212.05841, arXiv.org.
• Hannes Mueller & Christopher Rauh, 2022. "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, vol. 48(4), pages 579-596, July.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Janeway Institute Working Papers 2209, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Cambridge Working Papers in Economics 2220, Faculty of Economics, University of Cambridge.
• Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics 2237, Faculty of Economics, University of Cambridge.
• Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2242, Faculty of Economics, University of Cambridge.
• Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics camjip:2214, Faculty of Economics, University of Cambridge.
• Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Cambridge Working Papers in Economics 2220, Faculty of Economics, University of Cambridge.
  • Mueller, H. & Rauh, C., 2022. "Using Past Violence and Current News to Predict Changes in Violence," Janeway Institute Working Papers 2209, Faculty of Economics, University of Cambridge.
• Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2218, Faculty of Economics, University of Cambridge.
• Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Janeway Institute Working Papers camjip:2214, Faculty of Economics, University of Cambridge.
• Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CESifo Working Paper Series 10034, CESifo.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," CAMA Working Papers 2022-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," Staff Working Papers 22-38, Bank of Canada.
• Pilar Rey del Castillo, 2022. "Building Daily Economic Sentiment Indicators," CESifo Working Paper Series 10087, CESifo.
• Damir Filipović & Markus Pelger & Ye Ye, 2022. "Stripping the Discount Curve - a Robust Machine Learning Approach," Swiss Finance Institute Research Paper Series 22-24, Swiss Finance Institute.
• Oksana Bashchenko, 2022. "Bitcoin Price Factors: Natural Language Processing Approach," Swiss Finance Institute Research Paper Series 22-48, Swiss Finance Institute.
• Damir Filipović & Markus Pelger & Ye Ye, 2022. "Shrinking the Term Structure," Swiss Finance Institute Research Paper Series 22-61, Swiss Finance Institute.
• Damir Filipović & Puneet Pasricha, 2022. "Empirical Asset Pricing via Ensemble Gaussian Process Regression," Swiss Finance Institute Research Paper Series 22-95, Swiss Finance Institute.
• Victoria Ateca-Amestoy & Concetta Castiglione, 2022. "Live And Digital Engagement With The Visual Arts," Working Papers 202206, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
• Andrei Dubovik & Adam Elbourne & Bram Hendriks & Mark Kattenberg, 2022. "Forecasting World Trade Using Big Data and Machine Learning Techniques," CPB Discussion Paper 441, CPB Netherlands Bureau for Economic Policy Analysis.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
  • Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.
  • Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
• Andreou, Elena & Gagliardini, Patrick & Ghysels, Eric & Rubin, Mirco, 2022. "Three Common Factors," CEPR Discussion Papers 17225, C.E.P.R. Discussion Papers.
• Simonov, Andrey & Ursu, Raluca & Zheng, Carolina, 2022. "Suspense and Surprise in Media Product Design: Evidence from Twitch.tv," CEPR Discussion Papers 17353, C.E.P.R. Discussion Papers.
• Christophe Bell'ego & David Benatia & Louis Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Papers 2203.11820, arXiv.org.
  • Christophe Bellégo & David Benatia & Louis-Daniel Pape, 2022. "Dealing with Logs and Zeros in Regression Models," Working Papers 2022-08, Center for Research in Economics and Statistics.
• Fresoli, Diego Eduardo & Poncela Blanco, Maria Pilar & Ruiz Ortega, Esther, 2022. "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 36251, Universidad Carlos III de Madrid. Departamento de Estadística.
• Byron Botha & Kevin Kotze & Neil Rankin & Rulof P. Burger, 2022. "Big data forecasting of South African inflation," Working Papers 873, Economic Research Southern Africa.
  • Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
  • Byron Botha & Rulof Burger & Kevin Kotz & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," Working Papers 11022, South African Reserve Bank.
• Ryan, Ellen & Horan, Aoife & Jarmulska, Barbara, 2022. "Commercial real estate and financial stability – new insights from the euro area credit register," Macroprudential Bulletin, European Central Bank, vol. 19.
• Mingarelli, Luca & Ravanetti, Beatrice & Shakir, Tamarah & Wendelborn, Jonas, 2022. "Dawn of the (half) dead: the twisted world of zombie identification," Working Paper Series 2743, European Central Bank.
• Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  • Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
• Anatolyev, Stanislav & Pyrlik, Vladimir, 2022. "Copula shrinkage and portfolio allocation in ultra-high dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
• Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
• Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
• Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
  • Cristina Angelico & Juri Marcucci & Marcello Miccoli & Filippo Quarta, 2021. "Can we measure inflation expectations using Twitter?," Temi di discussione (Economic working papers) 1318, Bank of Italy, Economic Research and International Relations Area.
• Yu, Long & He, Yong & Kong, Xinbing & Zhang, Xinsheng, 2022. "Projected estimation for large-dimensional matrix factor models," Journal of Econometrics, Elsevier, vol. 229(1), pages 201-217.
• Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
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• Tomasz P. Kostyra, 2022. "Yield Curve Modelling with the Nelson-Siegel Method for Poland," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 44-56.
• Dimitar Haralampiev Popov, 2022. "SME Viability Assessment Methodology: Combining Altman's Z-Score with Big Data," Bulgarian Economic Papers bep-2022-04, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, revised Jun 2022.
• Eduardo A. Haddad & Renato S. Vieira & Inácio F. Araújo & Silvio M. Ichihara & Fernando S. Perobelli & Karina S. S. Bugarin, 2022. "COVID-19 crisis monitor: assessing the effectiveness of exit strategies in the State of São Paulo, Brazil," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(2), pages 501-525, April.
  • Haddad, Eduardo & Vieira, Renato & Araújo, Inácio & Ichihara, Silvio & Perobelli, Fernando & Bugarin, Karina, 2020. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," TD NEREUS 6-2020, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
  • Eduardo A Haddad & Renato S Vieira, Inacio F Araujo, Silvio Ichihara, Fernando S Perobelli, Karina Bugarin, 2022. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," Working Papers, Department of Economics 2022_10, University of São Paulo (FEA-USP).
• Jose Antonio Leon & Mario Ordaz, Eduardo A Haddad, Inacio F. Araujo, 2022. "Riesgo Causado por la Propagación de las Pérdidas por Terremoto a través de la Economía Mediante el uso de Modelos CGE Espaciales," Working Papers, Department of Economics 2022_11, University of São Paulo (FEA-USP).
• Eduardo A. Haddad & Renato S. Vieira & Inácio F. Araújo & Silvio M. Ichihara & Fernando S. Perobelli & Karina S. S. Bugarin, 2022. "COVID-19 crisis monitor: assessing the effectiveness of exit strategies in the State of São Paulo, Brazil," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(2), pages 501-525, April.
  • Haddad, Eduardo & Vieira, Renato & Araújo, Inácio & Ichihara, Silvio & Perobelli, Fernando & Bugarin, Karina, 2020. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," TD NEREUS 6-2020, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
  • Eduardo A Haddad & Renato S Vieira, Inacio F Araujo, Silvio Ichihara, Fernando S Perobelli, Karina Bugarin, 2022. "COVID-19 Crisis Monitor: Assessing the Effectiveness of Exit Strategies in the State of São Paulo, Brazil," Working Papers, Department of Economics 2022_10, University of São Paulo (FEA-USP).
• Joseph Junior Aduba, 2022. "Framework for firm-level performance evaluations using multivariate linear correlation with MCDM methods: application to Japanese firms," Asia-Pacific Journal of Regional Science, Springer, vol. 6(1), pages 1-44, February.
• Maral Taşcılar & Kerem Yavuz Arslanlı, 2022. "Forecasting commercial real estate indicators under COVID-19 by adopting human activity using social big data," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1111-1132, October.
• Helmut Wasserbacher & Martin Spindler, 2022. "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, vol. 4(1), pages 63-88, March.
• Sylwia Sysko-Romańczuk & Piotr Zaborek & Anna Wróblewska & Jacek Dąbrowski & Sergiy Tkachuk, 2022. "Data modalities, consumer attributes and recommendation performance in the fashion industry," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1279-1292, September.
• Shuolin Shi & Ralf A. Wilke, 2022. "Variable selection with group structure: exiting employment at retirement age—a competing risks quantile regression analysis," Empirical Economics, Springer, vol. 62(1), pages 119-155, January.
• Matthias Raddant & Hiroshi Takahashi, 2022. "Corporate boards, interorganizational ties and profitability: the case of Japan," Empirical Economics, Springer, vol. 62(3), pages 1365-1406, March.
  • Raddant, Matthias & Takahashi, Hiroshi, 2020. "Corporate boards, interorganizational ties and profitability: The case of Japan," Economics Working Papers 2020-02, Christian-Albrechts-University of Kiel, Department of Economics.
• Mohammad Vesal & Amir Hossein Tavakoli & Mohammad H. Rahmati, 2022. "What do one hundred million transactions tell us about demand elasticity of gasoline?," Empirical Economics, Springer, vol. 62(6), pages 2693-2711, June.
  • Rahmati, Mohammad Hossein & Tavakoli, Amirhossein & Vesal, Mohammad, 2019. "What do one hundred million transactions tell us about demand elasticity of gasoline?," MPRA Paper 97858, University Library of Munich, Germany.
• Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
  • Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
• Nadezhda Baryshnikova & Shannon Davidson & Dennis Wesselbaum, 2022. "Do you feel the heat around the corner? The effect of weather on crime," Empirical Economics, Springer, vol. 63(1), pages 179-199, July.
  • Nadezdha Baryshnikova & Shannon. F. Davidson & Dennis Wesselbaum, 2019. "Do you Feel the Heat Around the Corner? The Effect of Weather on Crime," School of Economics Working Papers 2019-07, University of Adelaide, School of Economics.
• Ioannis A. Nikas & Athanasios Koutras & Alkiviadis Panagopoulos & Anastasios Vasileiadis, 2022. "Exploring Tourists’ Food and Beverage Spots in an Urban Destination Using a Spatial–temporal Approach," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Andreea Claudia Şerban (ed.), Transcending Borders in Tourism Through Innovation and Cultural Heritage, pages 977-989, Springer.
• Oleksandr Bartkoviak & Viktor Shpyrko & Oleksandr Chernyak & Yevgen Chernyak, 2022. "Statistical Arbitrage Using Cointegration and Principal Component Analysis Approach," Springer Proceedings in Business and Economics, in: Pantelis Sklias & Persefoni Polychronidou & Anastasios Karasavvoglou & Victoria Pistikou & Nikolaos (ed.), Business Development and Economic Governance in Southeastern Europe, pages 167-182, Springer.
• Steven T. Joanis & Vivek H. Patil, 2022. "First-author gender differentials in business journal publishing: top journals versus the rest," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(2), pages 733-761, February.
• Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
• Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
  • Joshua Angrist & Brigham Frandsen, 2019. "Machine Labor," NBER Working Papers 26584, National Bureau of Economic Research, Inc.
• Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Papers 2209.01697, arXiv.org.
  • Tae-Hwy Lee & Ekaterina Seregina, 2022. "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers 202213, University of California at Riverside, Department of Economics.
• Waweru David & Mose Naftaly, 2022. "Household Fuel Choice in Urban Kenya: A Multinomial Logit Analysis," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 18(2), pages 30-41, June.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
  • Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers 2020s-47, CIRANO.
• Michael P. Clements, 2022. "Individual forecaster perceptions of the persistence of shocks to GDP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 640-656, April.
  • Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
• Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
  • Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
• Massimo Ferrari Minesso & Frederik Kurcz & Maria Sole Pagliari, 2022. "Do words hurt more than actions? The impact of trade tensions on financial markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1138-1159, September.
  • Ferrari Minesso, Massimo & Pagliari, Maria Sole & Kurcz, Frederik, 2020. "Do words hurt more than actions? The impact of trade tensions on financial markets," Working Paper Series 2490, European Central Bank.
  • Massimo Ferrari & Frederik Kurcz & Maria Sole Pagliari, 2021. "Do Words Hurt More Than Actions? The Impact of Trade Tensions on Financial Markets," Working papers 802, Banque de France.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
  • Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic Forecasting in a Multi-country Context," Working Papers 22-02, Federal Reserve Bank of Cleveland.
  • Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
• Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
  • Jardet Caroline & Meunier Baptiste, 2020. "Nowcasting World GDP Growth with High-Frequency Data," Working papers 788, Banque de France.
  • Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
• Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
  • Saskia ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Narrative monetary policy surprises and the media," Working Papers No 06/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • ter Ellen, Saskia & Larsen, Vegard H. & Thorsrud, Leif Anders, 2019. "Narrative monetary policy surprises and the media," Working Paper 2019/19, Norges Bank.
• Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
  • Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2021. "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers 2111.07170, arXiv.org.
• M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Papers 2109.00408, arXiv.org, revised Aug 2022.
  • M. Hashem Pesaran & Yimeng Xie, 2022. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Working Papers 2022-06-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
  • M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," CESifo Working Paper Series 9234, CESifo.
  • Pesaran, M. H. & Xie, Y., 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Cambridge Working Papers in Economics 2158, Faculty of Economics, University of Cambridge.
• Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 financial crisis: Slow to see, fast to act," Journal of Financial Stability, Elsevier, vol. 60(C).
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," Working Papers 2022-01, Bar-Ilan University, Department of Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," Working Paper series 22-04, Rimini Centre for Economic Analysis.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," MPRA Paper 112008, University Library of Munich, Germany.
• Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
• Porras, María Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun’s law: A metaregression analysis," MPRA Paper 112442, University Library of Munich, Germany.
  • Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2022. "The heterogeneity of Okun's law: A metaregression analysis," GLO Discussion Paper Series 1069, Global Labor Organization (GLO).
• Rossouw, Stephanié & Greyling, Talita, 2022. "Collective emotions and macro-level shocks: COVID-19 vs the Ukrainian war," GLO Discussion Paper Series 1210, Global Labor Organization (GLO).
• Benner, Niklas & Lange, Kai-Robin & Jentsch, Carsten, 2022. "Named entity narratives," Ruhr Economic Papers 962, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Lange, Kai-Robin & Reccius, Matthias & Schmidt, Tobias & Müller, Henrik & Roos, Michael W. M. & Jentsch, Carsten, 2022. "Towards extracting collective economic narratives from texts," Ruhr Economic Papers 963, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

2021

• Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
• Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021. "Expecting the unexpected: economic growth under stress," CREATES Research Papers 2021-06, Department of Economics and Business Economics, Aarhus University.
  • Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2021-03, Department of Economics, Auburn University.
  • Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2022. "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series auwp2022-03, Department of Economics, Auburn University.
• Nigel E.N. Chitambo & Darren Lee & Sure Mataramvura, 2021. "A Hybrid Neural Network GARCH Approach to Forecasting Zimbabwean Inflation Volatility," The African Finance Journal, Africagrowth Institute, vol. 23(1), pages 56-73.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• Lachlan O'Neill & Nandini Anantharama & Wray Buntine & Simon D Angus, 2021. "Quantitative Discourse Analysis at Scale - AI, NLP and the Transformer Revolution," SoDa Laboratories Working Paper Series 2021-12, Monash University, SoDa Laboratories.
• Nurdaulet Abilov & Aizhan Bolatbayeva, 2021. "Nowcasting GDP growth in Russia with an incomplete dataset: A factor model approach," NAC Analytica Working Paper 18, NAC Analytica, Nazarbayev University, revised Feb 2022.
• Mauricio Gallardo & María Emma Santos & Pablo Villatoro & Vicky Pizarro, 2021. "Measuring vulnerability to multidimensional poverty in Latin America," Working Papers 36, Red Nacional de Investigadores en Economía (RedNIE).
• Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2021. "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers 202101, University of Barcelona, Regional Quantitative Analysis Group, revised Feb 2021.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, Cambridge University Press, vol. 256, pages 71-109, April.
  • Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanovic, Dalibor, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
• Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
  • Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Papers 2107.02512, arXiv.org, revised Sep 2022.
• Pesaran, M. H. & Xie, Y., 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Cambridge Working Papers in Economics 2158, Faculty of Economics, University of Cambridge.
  • M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Papers 2109.00408, arXiv.org, revised Aug 2022.
  • M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," CESifo Working Paper Series 9234, CESifo.
  • M. Hashem Pesaran & Yimeng Xie, 2022. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Working Papers 2022-06-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
• Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
  • Joshua C. C. Chan, 2019. "Asymmetric conjugate priors for large Bayesian VARs," CAMA Working Papers 2019-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Joshua C. C. Chan, 2021. "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers 2111.07170, arXiv.org.
• Emilia VASILE & Danut Octavian SIMION, 2021. "Optimization Of Application Objects Used In The Economic Environments," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 61(1), pages 9-19, March.
• Danut Octavian SIMION & Emilia VASILE, 2021. "Implementing Different Types Of Data In Economic Application," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 62(2), pages 9-18, June.
• Emilia VASILE & Danut Octavian SIMION, 2021. "Methods For Storing And Finding Data In The Business Logic For Economic Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 63(3), pages 9-18, September.
• Sabyasachi Kar & Amaani Bashir & Mayank Jain, 2021. "New Approaches to Forecasting Growth and Inflation: Big Data and Machine Learning," IEG Working Papers 446, Institute of Economic Growth.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021. "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, Cambridge University Press, vol. 256, pages 71-109, April.
  • Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanovic, Dalibor, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Working Papers 21-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers 2021s-09, CIRANO.
  • Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021. "Can Machine Learning Catch the COVID-19 Recession?," Papers 2103.01201, arXiv.org.
• Ali Batuhan Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2021. "Turquía | Big Data y Nowcasting: consumo e inversión de transacciones bancarias [Turkey | Big Data and Nowcasting: Consumption and Investment from Bank Transactions]," Working Papers 21/07, BBVA Bank, Economic Research Department.
• James Chapman & Ajit Desai, 2021. "Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19," Staff Working Papers 21-2, Bank of Canada.
• Tatjana Dahlhaus & Angelika Welte, 2021. "Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data," Staff Working Papers 21-43, Bank of Canada.
• Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
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• Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
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• M. Hashem Pesaran & Yimeng Xie, 2021. "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," Papers 2109.00408, arXiv.org, revised Aug 2022.
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• Torben Andersen & Ilya Archakov & Leon Grund & Nikolaus Hautsch & Yifan Li & Sergey Nasekin & Ingmar Nolte & Manh Cuong Pham & Stephen Taylor & Viktor Todorov, 2021. "A Descriptive Study of High-Frequency Trade and Quote Option Data [Stealth Trading in Options Markets]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(1), pages 128-177.
• Apaar Sadhwani & Kay Giesecke & Justin Sirignano, 2021. "Deep Learning for Mortgage Risk [The Subprime Virus]," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(2), pages 313-368.
• P Gagliardini & C Gourieroux & M Rubin, 2021. "Positional Portfolio Management," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 19(4), pages 650-706.
• Stefano Giglio & Yuan Liao & Dacheng Xiu, 2021. "Thousands of Alpha Tests," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3456, National Bureau of Economic Research, Inc.
  • Stefano Giglio & Yuan Liao & Dacheng Xiu & Wei Jiang, 2021. "Thousands of Alpha Tests [The performance of hedge funds: Risk, return, and incentives]," Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3456-3496.
• Claudiu-Catalin Munteanu & Adina Cristea, 2021. "A Methodological Approach for the Journey through Real-Time Marketing: From Customer Journey Analytics to Personalization Engines," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 849-855, December.
• Alessandro Bitetto & Paola Cerchiello & Charilaos Mertzanis, 2021. "A data-driven approach to measuring epidemiological susceptibility risk around the world," DEM Working Papers Series 200, University of Pavia, Department of Economics and Management.
• Coronado, Hilary & Lahura, Erick & Vega, Marco, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para el Perú usando Big Data," Revista Moneda, Banco Central de Reserva del Perú, issue 188, pages 30-33.
  • Coronado, Hilary & Lahura, Erick & Vega, Marco, 2020. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Working Papers 2020-018, Banco Central de Reserva del Perú.
  • Marco Vega & Erick Lahura & Hilary Coronado, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Documentos de Trabajo / Working Papers 2021-497, Departamento de Economía - Pontificia Universidad Católica del Perú.
• Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019. "Persistent zeros: The extensive margin of trade," Kiel Working Papers 2139, Kiel Institute for the World Economy (IfW Kiel).
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," CEPA Discussion Papers 36, Center for Economic Policy Analysis.
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2020. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," Papers 2004.12655, arXiv.org, revised Jul 2021.
• Kollár, Aladár, 2021. "Betting models using AI: a review on ANN, SVM, and Markov chain," MPRA Paper 106821, University Library of Munich, Germany.
• Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
• Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021. "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, vol. 3(4), pages 1-30, October.
  • Fantazzini, Dean & Pushchelenko, Julia & Mironenkov, Alexey & Kurbatskii, Alexey, 2021. "Forecasting internal migration in Russia using Google Trends: Evidence from Moscow and Saint Petersburg," MPRA Paper 110452, University Library of Munich, Germany.
• Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
• Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(4), pages 230-354, June.
  • Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
  • Korobilis, Dimitris & Shimizu, Kenichi, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," MPRA Paper 111631, University Library of Munich, Germany.
  • Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Paper series 22-02, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Papers 2112.11751, arXiv.org.
• Kombarov, Sayan, 2021. "Action in Economics: Mathematical Derivation of Laws of Economics from the Principle of Least Action in Physics," MPRA Paper 112474, University Library of Munich, Germany.
• Bradrania, Reza & Pirayesh Neghab, Davood, 2021. "State-dependent asset allocation using neural networks," MPRA Paper 115254, University Library of Munich, Germany.
• Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Baumeister, Christiane & Leiva, Danilo & Sims, Eric, 2021. "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers 16317, C.E.P.R. Discussion Papers.
  • Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," Working Papers 2134, Banco de España.
  • Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021. "Tracking weekly state-level economic conditions," CAMA Working Papers 2021-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Mark Braverman & Sylvain Chassang, 2021. "Data-Driven Incentive Alignment in Capitation Schemes," Working Papers 282, Princeton University, Department of Economics, Center for Economic Policy Studies..
• Miyauchi, Yuhei & Nakajima, Kentaro & Redding, Stephen J., 2021. "Consumption Access and Agglomeration: Evidence from Smartphone Data," CEPR Discussion Papers 15839, C.E.P.R. Discussion Papers.
  • Yuhei Miyauchi & Kentaro Nakajima & Stephen J. Redding, 2021. "Consumption Access and Agglomeration: Evidence from Smartphone Data," Working Papers 287, Princeton University, Department of Economics, Center for Economic Policy Studies..
  • Yuhei Miyauchi & Kentaro Nakajima & Stephen J. Redding, 2021. "Consumption access and agglomeration: evidence from smartphone data," CEP Discussion Papers dp1745, Centre for Economic Performance, LSE.
  • Redding, Stephen & Nakajima, Kentaro & Miyauchi, Yuhei, 2021. "Consumption access and agglomeration: evidence from smartphone data," LSE Research Online Documents on Economics 114353, London School of Economics and Political Science, LSE Library.
• Bhumjai Tangsawasdirat & Suranan Tanpoonkiat & Burasakorn Tangsatchanan, 2021. "Credit Risk Database: Credit Scoring Models for Thai SMEs," PIER Discussion Papers 168, Puey Ungphakorn Institute for Economic Research.
• Giulio Marini, 2021. "Joining the European Union as an advantage in science performativity. A quasi-experimental study," DoQSS Working Papers 21-09, Quantitative Social Science - UCL Social Research Institute, University College London.
• Luke Hartigan & Michelle Wright, 2021. "Financial Conditions and Downside Risk to Economic Activity in Australia," RBA Research Discussion Papers rdp2021-03, Reserve Bank of Australia.
• Coronado, Hilary & Lahura, Erick & Vega, Marco, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para el Perú usando Big Data," Revista Moneda, Banco Central de Reserva del Perú, issue 188, pages 30-33.
  • Coronado, Hilary & Lahura, Erick & Vega, Marco, 2020. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Working Papers 2020-018, Banco Central de Reserva del Perú.
  • Marco Vega & Erick Lahura & Hilary Coronado, 2021. "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Documentos de Trabajo / Working Papers 2021-497, Departamento de Economía - Pontificia Universidad Católica del Perú.
• Karen Poghosyan & Ruben Poghosyan, 2021. "On the Applicability of Dynamic Factor Models for Forecasting Real GDP Growth in Armenia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 71(1), pages 52-79, June.
  • Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
• Desjardins, Denise & Dionne, Georges & Lu, Yang, 2021. "Hierarchical random effects model for insurance pricing of vehicles belonging to a fleet," Working Papers 21-2, HEC Montreal, Canada Research Chair in Risk Management.
• Dimingo, Roselyn & Muteba Mwamba, John W. & Bonga-Bonga, Lumengo, 2021. "Prediction of Stock Market Direction: Application of Machine Learning Models," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 74(4), pages 499-536.
• Farag, Markos & Zaki, Chahir, 2021. "On the Determinants of Trade in Natural Gas: A Political Economy Approach," EWI Working Papers 2021-8, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
• Rao, Anitha & Wiendling, Mark & Ridgeway, Paul & Kennedy, Liz & Eyre, Harris A. & Pinho, Paulo, 2021. "Bridging the Gap Between Medicine and Insurance: How to Leverage Data, Artificial Intelligence, and Neuroinformatics for Insurance and Financial Risk Management," Journal of Financial Transformation, Capco Institute, vol. 54, pages 142-147.
• Chow, Hwee Kwan & Han, Daniel, 2021. "Forecast Pooling or Information Pooling During Crises? MIDAS Forecasting of GDP in a Small Open Economy," Economics and Statistics Working Papers 6-2021, Singapore Management University, School of Economics.
• Huaiwen ZHANG & Adnan Khurshid & Xinyu WANG & Alina Mirela BĂLTĂŢEANU, 2021. "Corporate Financial Risk Assessment and Role of Big Data; New Perspective Using Fuzzy Analytic Hierarchy Process," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 181-199, June.
• Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers 2021-035, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1028, Ghent University, Faculty of Economics and Business Administration.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series 930, Global Labor Organization (GLO).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series 9301, CESifo.
• Wojciech Charemza & Michal Lewandowski & Lukasz Wozny, 2021. "Efficiency in rewarding academic journal publications. The case of Poland," Working Papers 2021-062, Warsaw School of Economics, Collegium of Economic Analysis.
• Paolo Nicola Barbieri & Beatrice Bonini, 2021. "Political orientation and adherence to social distancing during the COVID-19 pandemic in Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 483-504, July.
• Christopher Helm & Tim A. Herberger & Marcel Tyrell, 2021. "Demand dynamics across secondary German Book markets: an information aggregation and synthetization approach," Information Systems and e-Business Management, Springer, vol. 19(2), pages 567-596, June.
• Faustino Prieto & José María Sarabia & Enrique Calderín-Ojeda, 2021. "The nonlinear distribution of employment across municipalities," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 287-307, April.
• Hutter, Christian, 2021. "Cyclicality of labour market search: a new big data Approach," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-1.
  • Christian Hutter, 2021. "Cyclicality of labour market search: a new big data approach," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-16, December.
• Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
• Iasonas Papafotikas & Dimitrios Folinas, 2021. "Sentiment Analysis: Relationship Between Customer Sentiment and Online Customer Ratings for Price Comparison Engines. An Empirical Study," Springer Proceedings in Business and Economics, in: Alexandra Horobet & Lucian Belascu & Persefoni Polychronidou & Anastasios Karasavvoglou (ed.), Global, Regional and Local Perspectives on the Economies of Southeastern Europe, pages 257-272, Springer.
• Fu-Hsiang Kuo, 2021. "An Investigation of the Operational Efficiency of School Management through Innovative Teaching via Digital Mobile E-learning: DEA and Data mining Methodology," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(1), pages 1-1.
• Chris van Wyk, 2021. "Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2019: A longitudinal cohort analysis," Working Papers 01/2021, Stellenbosch University, Department of Economics.
• Hanjo Odendaal, 2021. "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers 06/2021, Stellenbosch University, Department of Economics.
• Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
  • Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
• Gonzalez Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2021. "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS 32148, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
  • Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021. "Expecting the unexpected: economic growth under stress," CREATES Research Papers 2021-06, Department of Economics and Business Economics, Aarhus University.
• Guillermo Cabanillas-Jiménez, 2021. "Testing the Permanent Income Hypothesis using the Spanish Christmas Lottery," Studies in Economics 2104, School of Economics, University of Kent.
• Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
• Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2102, Department of Economics, University of Missouri.
  • Dylan Brewer & Alyssa Carlson, 2021. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2114, Department of Economics, University of Missouri.
• Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1028, Ghent University, Faculty of Economics and Business Administration.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers 2021-035, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series 930, Global Labor Organization (GLO).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series 9301, CESifo.
• Jankowiak Maciej, 2021. "The EU Member States’ national healthcare systems compared using the single synthetic index," Economics and Business Review, Sciendo, vol. 7(2), pages 37-49, June.
• Dawid Siwicki, 2021. "The Application of Machine Learning Algorithms for Spatial Analysis: Predicting of Real Estate Prices in Warsaw," Working Papers 2021-05, Faculty of Economic Sciences, University of Warsaw.
• Piotr Borowski & Marcin Chlebus, 2021. "Machine learning in the prediction of flat horse racing results in Poland," Working Papers 2021-13, Faculty of Economic Sciences, University of Warsaw.
• Maaz Khan & Faheem Aslam & Paulo Ferreira, 2021. "Extreme Value Theory and COVID-19 Pandemic: Evidence from India," Economic Research Guardian, Weissberg Publishing, vol. 11(1), pages 2-10, June.
• Mrestyal Khan & Maaz Khan, 2021. "Cryptomarket Volatility in Times of COVID-19 Pandemic: Application of GARCH Models," Economic Research Guardian, Weissberg Publishing, vol. 11(2), pages 170-181, December.
• Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) with Household Survey Data: Methodology and Results for European Countries," wiiw Working Papers 180, The Vienna Institute for International Economic Studies, wiiw.
  • Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2021. "Distributional National Accounts (DINA) with Household Survey Data. Methodology and Results for European Countries," WIFO Working Papers 599, WIFO.
• Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
  • Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting: Why you Can Use the HP Filter," Cowles Foundation Discussion Papers 2212, Cowles Foundation for Research in Economics, Yale University.
  • Peter C. B. Phillips & Zhentao Shi, 2019. "Boosting: Why You Can Use the HP Filter," Papers 1905.00175, arXiv.org, revised Nov 2020.
• Ricketts, Simon, 2021. "Do Political Actors Engage in Strategic Deception on Social Media?," Warwick-Monash Economics Student Papers 16, Warwick Monash Economics Student Papers.
• Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
• Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2020. "The simpler the better: measuring financial conditions for monetary policy and financial stability," Working Paper Series 2451, European Central Bank.
  • Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2021. "The simpler, the better: Measuring financial conditions for monetary policy and financial stability," EIB Working Papers 2021/10, European Investment Bank (EIB).
• Ofori, Isaac K. & Quaidoo, Christopher & Ofori, Pamela E., 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers of the African Governance and Development Institute. 21/074, African Governance and Development Institute..
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers 21/074, European Xtramile Centre of African Studies (EXCAS).
  • Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021. "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Research Africa Network Working Papers 21/074, Research Africa Network (RAN).
• Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers of the African Governance and Development Institute. 21/044, African Governance and Development Institute..
  • Ofori, Isaac Kwesi, 2021. "Catching The Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," EconStor Preprints 235482, ZBW - Leibniz Information Centre for Economics.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Working Papers 21/044, European Xtramile Centre of African Studies (EXCAS).
  • Ofori, Isaac K, 2021. "Catching The Drivers of Inclusive Growth In Sub-Saharan Africa: An Application of Machine Learning," MPRA Paper 108622, University Library of Munich, Germany.
  • Isaac K. Ofori, 2021. "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers 21/044, Research Africa Network (RAN).
• Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, ZBW - Leibniz Information Centre for Economics.
• Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanié, 2021. "A Year of Pandemic: Levels, Changes and Validity of Well-Being Data from Twitter. Evidence from Ten Countries," IZA Discussion Papers 14903, Institute of Labor Economics (IZA).
  • Sarracino, Francesco & Greyling, Talita & O'Connor , Kelsey & Peroni, Chiara & Rossouw, Stephanie, 2021. "A year of pandemic: levels, changes and validity of well-being data from Twitter. Evidence from ten countries," GLO Discussion Paper Series 831, Global Labor Organization (GLO).
• Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1028, Ghent University, Faculty of Economics and Business Administration.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," GLO Discussion Paper Series 930, Global Labor Organization (GLO).
  • Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021. "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series 9301, CESifo.
  • Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2021. "Longing for which home: Evidence from global aspirations to stay, return or migrate onwards," MERIT Working Papers 2021-035, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• Greyling, Talita & Rossouw, Stephanié, 2021. "Anger, fear and everything else: attitudes towards the COVID-19 vaccines," GLO Discussion Paper Series 939, Global Labor Organization (GLO).
• Dörr, Julian Oliver & Kinne, Jan & Lenz, David & Licht, Georg & Winker, Peter, 2021. "An integrated data framework for policy guidance in times of dynamic economic shocks," ZEW Discussion Papers 21-062, ZEW - Leibniz Centre for European Economic Research.

2020

• Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020. "Targeting predictors in random forest regression," Papers 2004.01411, arXiv.org, revised Nov 2020.
  • Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
• Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2020. "Forecasting the US Dollar-Korean Won Exchange Rate: A Factor-Augmented Model Approach," Auburn Economics Working Paper Series auwp2020-02, Department of Economics, Auburn University.
• Maryam Farboodi & Laura Veldkamp, 2020. "Long-Run Growth of Financial Data Technology," American Economic Review, American Economic Association, vol. 110(8), pages 2485-2523, August.
• Janet Currie & Henrik Kleven & Esmée Zwiers, 2020. "Technology and Big Data Are Changing Economics: Mining Text to Track Methods," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 42-48, May.
  • Janet Currie & Henrik Kleven & Esmée Zwiers, 2020. "Technology and Big Data Are Changing Economics: Mining Text to Track Methods," NBER Working Papers 26715, National Bureau of Economic Research, Inc.
• Viorelia LUNGU, 2020. "Some Notes on the Geopolitics and Geo-economics of Russia’s Post-Soviet Neocolonialism in Central Asia," Eastern European Journal for Regional Studies (EEJRS), Center for Studies in European Integration (CSEI), Academy of Economic Studies of Moldova (ASEM), vol. 6(1), pages 87-101, June.
• Edson Zambon Monte & Felipe Fantin Almeida, 2020. "Interrelationships Between The Stock Returns Of Brazilian Companies That Make Up The Sãƒo Paulo Stock Exchange Index," Revista de Economia Mackenzie (REM), Mackenzie Presbyterian University, Social and Applied Sciences Center, vol. 17(1), pages 115-145, January-J.
• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Working Papers halshs-02871927, HAL.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
  • Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Papers 2006.08446, arXiv.org.
• Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020. "Object Recognition for Economic Development from Daytime Satellite Imagery," Papers 2009.05455, arXiv.org.
  • Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020. "Object Recognition for Economic Development from Daytime Satellite Imagery," SoDa Laboratories Working Paper Series 2020-02, Monash University, SoDa Laboratories.
• Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
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• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
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• Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
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• Klaus Ackermann & Alexey Chernikov & Nandini Anantharama & Miethy Zaman & Paul A Raschky, 2020. "Object Recognition for Economic Development from Daytime Satellite Imagery," SoDa Laboratories Working Paper Series 2020-02, Monash University, SoDa Laboratories.
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• Tae-Hwy Lee & Ekaterina Seregina, 2020. "Optimal Portfolio Using Factor Graphical Lasso," Working Papers 202025, University of California at Riverside, Department of Economics.
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• Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combination," Working Papers 202024, University of California at Riverside, Department of Economics.
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• Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series 8702, CESifo.
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• Catalin DUMITRESCU, 2020. "Financial Stability Of Economic Agencies In Conditions Of Economic Crisis," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 57(1), pages 22-33, March.
• Cătălin DUMITRESCU & Matei DUMITRESCU, 2020. "Virtual Currency And Global Business - The New Trend In The Net-Economy," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 58(2), pages 22-32, June.
• Robert HELLVIG & Cătălin DUMITRESCU & Matei DUMITRESCU, 2020. "Management Of Cybercrime In The Financial Field - Perspectives To Combat The Phenomenon," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 59(3), pages 23-33, September.
• DănuÅ£-Octavian SIMION & Emilia VASILE, 2020. "Models Of Classes For Economic Objects In Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 59(3), pages 9-22, September.
• Emilia VASILE & DănuÅ£-Octavian SIMION, 2020. "Polymorphism Of Classes And Reference Of Instances Distribution For Economic Objects In Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 60(4), pages 9-21, December.
• Alexander Plum & Gail Pacheco & Kabir Dasgupta, 2021. "When There is No Way Up: Reconsidering Low‐paid Jobs as Stepping‐stones," The Economic Record, The Economic Society of Australia, vol. 97(318), pages 387-409, September.
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• Cristina Caprara & Daniele Vergari, 2020. "Credit risk analysis and lending decisions: new Machine Learning techniques," BANCARIA, Bancaria Editrice, vol. 1, pages 49-53, January.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020. "Macroeconomic Data Transformations Matter," CIRANO Working Papers 2020s-42, CIRANO.
  • Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Working Papers 20-17, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Mar 2021.
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• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
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• Luis Antonio Espinosa & Juan José Li Ng, 2020. "El riesgo del sargazo para la economía y turismo de Quintana Roo y México [The risk of sargassum to the economy and tourism of Quintana Roo and Mexico]," Working Papers 20/02, BBVA Bank, Economic Research Department.
• Ali Batuhan Barlas & Seda Guler Mert & Alvaro Ortiz & Tomasa Rodrigo, 2020. "Global | Inversión en tiempo real y alta definición: Un enfoque Big Data [Global | Investment in Real Time and High Definition: A Big Data Approach]," Working Papers 20/13, BBVA Bank, Economic Research Department.
• Eddie Gerba & Danilo Leiva-Leon, 2020. "Macro-financial interactions in a changing world," Working Papers 2018, Banco de España.
• Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020. "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers 2042, Banco de España.
• Bradley Shapiro & Günter J. Hitsch & Anna Tuchman, 2020. "Generalizable and Robust TV Advertising Effects," Working Papers 2020-111, Becker Friedman Institute for Research In Economics.
• Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
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• Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," GLO Discussion Paper Series 503, Global Labor Organization (GLO).
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• Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
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• Filipp Ulyankin, 2020. "Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 75-97, December.
• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
  • Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2019. "Taming the Factor Zoo: A Test of New Factors," NBER Working Papers 25481, National Bureau of Economic Research, Inc.
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• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
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• Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
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• Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020. "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
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• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
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• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
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• Hyeongwoo Kim & Soohyon Kim, 2020. "Common Factor Augmented Forecasting Models for the US Dollar-Korean Won Exchange Rate," Working Papers 2020-5, Economic Research Institute, Bank of Korea.
• Andreas Gulyas & Krzysztof Pytka, 2019. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2019_131, University of Bonn and University of Mannheim, Germany.
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• Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
• Rashad Ahmed & M. Hashem Pesaran, 2020. "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series 8615, CESifo.
  • Ahmed, R. & Pesaran, M. H., 2020. "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics 2092, Faculty of Economics, University of Cambridge.
• Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
• Jonas Klos & Tim Krieger & Sven Stöwhase, 2022. "Measuring intra-generational redistribution in PAYG pension schemes," Public Choice, Springer, vol. 190(1), pages 53-73, January.
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• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020. "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series 8475, CESifo.
• Ahmed, R. & Pesaran, M. H., 2020. "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics 2092, Faculty of Economics, University of Cambridge.
  • Rashad Ahmed & M. Hashem Pesaran, 2020. "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series 8615, CESifo.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Paper 2020/14, Norges Bank.
  • Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
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• Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," Papers 2011.11017, arXiv.org.
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  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin 1911, DIW Berlin, German Institute for Economic Research.
• Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
• Roberto Molinari & Gaetan Bakalli & Stéphane Guerrier & Cesare Miglioli & Samuel Orso & O. Scaillet, 2020. "Swag: A Wrapper Method for Sparse Learning," Swiss Finance Institute Research Paper Series 20-49, Swiss Finance Institute.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
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• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
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• Mark Trede & Michael Zimmermann, 2020. "Regional labour migration - Stylized facts for Germany," CQE Working Papers 9320, Center for Quantitative Economics (CQE), University of Muenster.
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• Antonia Grohmann & Steffen Herbold & Friederike Lenel, 2020. "Repayment under Flexible Loan Contracts: Evidence from Tanzania," Discussion Papers of DIW Berlin 1884, DIW Berlin, German Institute for Economic Research.
• Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series 8702, CESifo.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin 1911, DIW Berlin, German Institute for Economic Research.
  • Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," Papers 2011.11017, arXiv.org.
• Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
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• Matthias Raddant & Hiroshi Takahashi, 2022. "Corporate boards, interorganizational ties and profitability: the case of Japan," Empirical Economics, Springer, vol. 62(3), pages 1365-1406, March.
  • Raddant, Matthias & Takahashi, Hiroshi, 2020. "Corporate boards, interorganizational ties and profitability: The case of Japan," Economics Working Papers 2020-02, Christian-Albrechts-University of Kiel, Department of Economics.
• Vrigazova, Borislava, 2020. "Tenfold Bootstrap as Resampling Method in Classification Problems," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 74-83, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• Zinn, Sabine & Würbach, Ariane & Steinhauer, Hans Walter, 2020. "Attrition and Selectivity of the NEPS Starting Cohorts: An Overview of the Past 8 Years," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 163-206.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers 2020-01, Bar-Ilan University, Department of Economics.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints 214194, ZBW - Leibniz Information Centre for Economics.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Paper series 20-05, Rimini Centre for Economic Analysis.
  • Daniel Levy & Tamir Mayer & Alon Raviv, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers hal-02488796, HAL.
  • Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020. "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper 98785, University Library of Munich, Germany.
• Martínez-Hernández, Catalina, 2020. "Disentangling the effects of multidimensional monetary policy on inflation and inflation expectations in the euro area," Discussion Papers 2020/18, Free University Berlin, School of Business & Economics.
• Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Economics Discussion Papers em-dp2020-02, Department of Economics, University of Reading.
  • Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," GLO Discussion Paper Series 503, Global Labor Organization (GLO).
  • Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020. "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Discussion Papers 20-03, Department of Economics, University of Birmingham.
• Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020. "Happiness-lost: Did Governments make the right decisions to combat Covid-19?," GLO Discussion Paper Series 556, Global Labor Organization (GLO).
• Rossouw, Stephanie & Greyling, Talita & Adhikari, Tamanna & Morrison, Phillip S., 2020. "Markov switching models for happiness during a pandemic: The New-Zealand experience," GLO Discussion Paper Series 573, Global Labor Organization (GLO).
• Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020. "A tale of three countries: How did Covid-19 lockdown impact happiness?," GLO Discussion Paper Series 584, Global Labor Organization (GLO).
• Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
  • Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
• Poncela, Pilar & Ruiz, Esther, 2020. "A comment on the dynamic factor model with dynamic factors," Economics Discussion Papers 2020-7, Kiel Institute for the World Economy (IfW Kiel).
• Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-14.
  • Lucchetti, Riccardo & Venetis, Ioannis A., 2020. "A replication of "A quasi-maximum likelihood approach for large, approximate dynamic factor models" (Review of Economics and Statistics, 2012)," Economics Discussion Papers 2020-5, Kiel Institute for the World Economy (IfW Kiel).
• Sami Diaf & Jörg Döpke & Ulrich Fritsche & Ida Rockenbach, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Macroeconomics and Finance Series 202001, University of Hamburg, Department of Socioeconomics.
  • Diaf, Sami & Döpke, Jörg & Fritsche, Ulrich & Rockenbach, Ida, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Working Papers 24, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Bluhm, Benjamin & Cutura, Jannic, 2020. "Econometrics at scale: Spark up big data in economics," SAFE Working Paper Series 266, Leibniz Institute for Financial Research SAFE.
• Kugler, Philipp & Biewen, Martin, 2020. "Two-Stage Least Squares Random Forests with a Replication of Angrist and Evans (1998)," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224538, Verein für Socialpolitik / German Economic Association.
• Jonas Klos & Tim Krieger & Sven Stöwhase, 2022. "Measuring intra-generational redistribution in PAYG pension schemes," Public Choice, Springer, vol. 190(1), pages 53-73, January.
  • Jonas Klos & Tim Krieger & Sven Stöwhase, 2020. "Measuring Intra-Generational Redistribution in PAYG Pension Schemes," CESifo Working Paper Series 8200, CESifo.
  • Klos, Jonas & Krieger, Tim & Stöwhase, Sven, 2020. "Measuring intra-generational redistribution in PAYG pension schemes," Discussion Paper Series 2020-01, University of Freiburg, Wilfried Guth Endowed Chair for Constitutional Political Economy and Competition Policy.

2019

• Bunjira Makond & Mayuening Eso, 2019. "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand’s Deep South," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 56-92, September.
• Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
• Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021. "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, vol. 96(C).
  • Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019. "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers 2019-21, Department of Economics and Business Economics, Aarhus University.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Sarthak Behera & Hyeongwoo Kim, 2019. "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series auwp2019-04, Department of Economics, Auburn University.
• Nadezhda Baryshnikova & Shannon Davidson & Dennis Wesselbaum, 2022. "Do you feel the heat around the corner? The effect of weather on crime," Empirical Economics, Springer, vol. 63(1), pages 179-199, July.
  • Nadezdha Baryshnikova & Shannon. F. Davidson & Dennis Wesselbaum, 2019. "Do you Feel the Heat Around the Corner? The Effect of Weather on Crime," School of Economics Working Papers 2019-07, University of Adelaide, School of Economics.
• Matthew Harding & Carlos Lamarche, 2019. "Penalized Estimation of a Quantile Count Model for Panel Data," Annals of Economics and Statistics, GENES, issue 134, pages 177-206.
• Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2019. "The Impact of Big Data on Firm Performance: An Empirical Investigation," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 33-37, May.
  • Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2018. "The Impact of Big Data on Firm Performance: An Empirical Investigation," NBER Working Papers 24334, National Bureau of Economic Research, Inc.
• Dmitri K. Koustas, 2019. "What Do Big Data Tell Us about Why People Take Gig Economy Jobs?," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 367-371, May.
• Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
  • Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," NBER Working Papers 25515, National Bureau of Economic Research, Inc.
  • Farboodi, Maryam & Mihet, Roxana & Philippon, Thomas & Veldkamp, Laura, 2019. "Big Data and Firm Dynamics," CEPR Discussion Papers 13489, C.E.P.R. Discussion Papers.
• Matthew Gentzkow & Bryan Kelly & Matt Taddy, 2019. "Text as Data," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 535-574, September.
• Ellen Hughes-Cromwick & Julia Coronado, 2019. "The Value of US Government Data to US Business Decisions," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 131-146, Winter.
• Bunjira Makond & Mayuening Eso, 2019. "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand’s Deep South," International Association of Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 56-92, September.
• Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, vol. 217(2), pages 431-470.
  • Hafner, C. & Linton, O. & Tang, H., 2018. "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1878, Faculty of Economics, University of Cambridge.
  • Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
• Жузбаев А.М. // Zhuzbayev A.M. & Орлов К.В. // Orlov K.V., 2019. "Использование квартальной прогностической модели и сателлитных моделей в системе анализа и прогнозирования НБ РК // Use of the quarterly predictive model and satellite models in the analysis and forec," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue special, pages 3-14.
• Орлов Константин // Orlov Konstantin, 2019. "Оценка и анализ эффективности применения динамической факторной модели для оценивания и прогнозирования ВВП на примере Казахстан // Evaluation and analysis of the effectiveness of the use of a dynamic," Working Papers #2019-4, National Bank of Kazakhstan.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.
  • Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019. "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers 12081, Institute of Labor Economics (IZA).
  • Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
  • Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting: Why you Can Use the HP Filter," Cowles Foundation Discussion Papers 2212, Cowles Foundation for Research in Economics, Yale University.
  • Peter C. B. Phillips & Zhentao Shi, 2019. "Boosting: Why You Can Use the HP Filter," Papers 1905.00175, arXiv.org, revised Nov 2020.
• Robert Donnelly & Francisco J.R. Ruiz & David Blei & Susan Athey, 2021. "Counterfactual inference for consumer choice across many product categories," Quantitative Marketing and Economics (QME), Springer, vol. 19(3), pages 369-407, December.
  • Rob Donnelly & Francisco R. Ruiz & David Blei & Susan Athey, 2019. "Counterfactual Inference for Consumer Choice Across Many Product Categories," Papers 1906.02635, arXiv.org.
• Michael A. Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Discussion Papers of DIW Berlin 1803, DIW Berlin, German Institute for Economic Research.
  • Michael Allan Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers 1906.03044, arXiv.org.
  • Michael Allan Ribers & Hannes Ullrich, 2019. "Battling antibiotic resistance: can machine learning improve prescribing?," CESifo Working Paper Series 7654, CESifo.
• Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2018. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper Series of the Department of Economics, University of Konstanz 2018-07, Department of Economics, University of Konstanz.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2020. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper series 20-03, Rimini Centre for Economic Analysis.
  • Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2019. "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Papers 1906.05545, arXiv.org.
• Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," NBER Working Papers 26165, National Bureau of Economic Research, Inc.
  • Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Papers 1908.11498, arXiv.org, revised Oct 2019.
  • Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Working Papers 2019-056, Human Capital and Economic Opportunity Working Group.
  • Albanesi, Stefania & Vamossy, Domonkos, 2019. "Predicting Consumer Default: A Deep Learning Approach," CEPR Discussion Papers 13914, C.E.P.R. Discussion Papers.
• Evan Munro & Serena Ng, 2022. "Latent Dirichlet Analysis of Categorical Survey Responses," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 256-271, January.
  • Evan Munro & Serena Ng, 2019. "Latent Dirichlet Analysis of Categorical Survey Responses," Papers 1910.04883, arXiv.org, revised Jul 2020.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "The Management Information Systems Reengineering Through Economic Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 53(1), pages 9-22, March.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "The Role Of Information Systems In Economic Organizations For The Strategic Management," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 54(2), pages 9-24, June.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "Applications For Economic Organizations Built On Enterprise Javabeans Technologies," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 55(3), pages 9-23, September.
• Emilia VASILE & Danut-Octavian SIMION, 2019. "Implementations Of Classes And Objects In Applications For Economic Organizations," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 56(4), pages 9-20, December.
• Catalin DUMITRESCU, 2019. "Contributions To Modeling The Behavior Of Chaotic Systems With Applicability In Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 56(4), pages 98-107, December.
• Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
  • Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.
  • Jaqueson K. Galimberti, 2020. "Forecasting GDP growth from outer space," Working Papers 2020-02, Auckland University of Technology, Department of Economics.
• Guillermo Jr. Cardenas Salgado & Luis Antonio Espinosa & Juan Jose Li Ng & Carlos Serrano, 2019. "México | La crisis por escasez de gasolina: un análisis de Big Data [Mexico | The gasoline shortage crisis: A Big Data analysis]," Working Papers 19/09, BBVA Bank, Economic Research Department.
• Diego Bodas & Juan R. García López & Tomasa Rodrigo López & Pep Ruiz de Aguirre & Camilo A. Ulloa & Juan Murillo Arias & Juan de Dios Romero Palop & Heribert Valero Lapaz & Matías J. Pacce, 2019. "Measuring retail trade using card transactional data," Working Papers 1921, Banco de España.
• Massimo Gallo & Sonia Soncin & Andrea Venturini, 2019. "Ven-ICE: a new indicator for the economy of the Veneto region," Questioni di Economia e Finanza (Occasional Papers) 498, Bank of Italy, Economic Research and International Relations Area.
• Guerino Ardizzi & Simone Emiliozzi & Juri Marcucci & Libero Monteforte, 2019. "News and consumer card payments," Temi di discussione (Economic working papers) 1233, Bank of Italy, Economic Research and International Relations Area.
• Mirko Moscatelli & Simone Narizzano & Fabio Parlapiano & Gianluca Viggiano, 2019. "Corporate default forecasting with machine learning," Temi di discussione (Economic working papers) 1256, Bank of Italy, Economic Research and International Relations Area.
• Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers 2019-04, Center for Research in Economics and Statistics.
  • Laurent Ferrara & Anna Simoni, 2019. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers 717, Banque de France.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
  • Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
• Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  • Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Nikita Fokin & Andrey Polbin, 2019. "Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model," Russian Journal of Money and Finance, Bank of Russia, vol. 78(2), pages 67-93, June.
• Qi Ge & Benjamin Ho, 2019. "Energy Use And Temperature Habituation: Evidence From High Frequency Thermostat Usage Data," Economic Inquiry, Western Economic Association International, vol. 57(2), pages 1196-1214, April.
• Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
  • Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Dario Sansone, 2019. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(2), pages 456-485, April.
  • Dario Sansone, 2017. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Working Papers gueconwpa~17-17-09, Georgetown University, Department of Economics.
• Hilde C. Bj�rnland & Julia Zhulanova, 2018. "The Shale Oil Boom and the U.S. Economy: Spillovers and Time-Varying Effects," Working Papers No 8/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the US economy: Spillovers and time-varying effects," CAMA Working Papers 2019-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
  • Saskia ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Narrative monetary policy surprises and the media," Working Papers No 06/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • ter Ellen, Saskia & Larsen, Vegard H. & Thorsrud, Leif Anders, 2019. "Narrative monetary policy surprises and the media," Working Paper 2019/19, Norges Bank.
• Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
  • ter Ellen, Saskia & Larsen, Vegard H. & Thorsrud, Leif Anders, 2019. "Narrative monetary policy surprises and the media," Working Paper 2019/19, Norges Bank.
  • Saskia ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Narrative monetary policy surprises and the media," Working Papers No 06/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 185-202.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The Long-Run Information Effect of Central Bank Communication," CEPR Discussion Papers 13438, C.E.P.R. Discussion Papers.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2019. "The long-run information effect of central bank communication," Bank of England working papers 777, Bank of England.
  • Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2020. "The long-run information effect of central bank communication," Working Paper Series 2363, European Central Bank.
• Meeks, Roland & Monti, Francesca, 2019. "Heterogeneous beliefs and the Phillips curve," Bank of England working papers 807, Bank of England.
• Bracke, Philippe & Datta, Anupam & Jung, Carsten & Sen, Shayak, 2019. "Machine learning explainability in finance: an application to default risk analysis," Bank of England working papers 816, Bank of England.
• Yosuke Uno & Ko Adachi, 2019. ""Don't know" Tells: Calculating Non-Response Bias in Firms' Inflation Expectations Using Machine Learning Techniques," Bank of Japan Working Paper Series 19-E-17, Bank of Japan.
• Andreas Gulyas & Krzysztof Pytka, 2019. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2019_131, University of Bonn and University of Mannheim, Germany.
  • Pytka, Krzysztof & Gulyas, Andreas, 2021. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242402, Verein für Socialpolitik / German Economic Association.
  • Andreas Gulyas & Krzysztof Pytka, 2020. "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series crctr224_2020_131v2, University of Bonn and University of Mannheim, Germany.
• Jianjun Miao, 2019. "Multivariate LQG Control under Rational Inattention in Continuous Time," Boston University - Department of Economics - Working Papers Series WP2019-06, Boston University - Department of Economics.
• Gabriel E. Kreindler & Yuhei Miyauchi, 2019. "Measuring Commuting and Economic Activity inside Cities with Cell Phone Records," Boston University - Department of Economics - Working Papers Series WP2020-006, Boston University - Department of Economics, revised Apr 2020.
• Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Revue d'économie financière, Association d'économie financière, vol. 0(3), pages 21-50.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," Working Papers halshs-02377886, HAL.
  • Christophe HURLIN & Christophe PERIGNON, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," LEO Working Papers / DR LEO 2739, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Christophe Hurlin & Christophe Pérignon, 2019. "Machine learning et nouvelles sources de données pour le scoring de crédit," Post-Print hal-03532418, HAL.
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• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
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• Alacevich, Caterina & Nicodemo, Catia, 2019. "Immigration and Work-Related Injuries: Evidence from Italian Administrative Data," IZA Discussion Papers 12510, Institute of Labor Economics (IZA).
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• Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
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• Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
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• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
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• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
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• Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
• Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2021. "From Transaction Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 115-145, National Bureau of Economic Research, Inc.
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy E. Dunn & Laura J. Feiveson & Paul Lengermann & Claudia R. Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," Finance and Economics Discussion Series 2019-057, Board of Governors of the Federal Reserve System (U.S.).
  • Aditya Aladangady & Shifrah Aron-Dine & Wendy Dunn & Laura Feiveson & Paul Lengermann & Claudia Sahm, 2019. "From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending," NBER Working Papers 26253, National Bureau of Economic Research, Inc.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Victor Chernozhukov & Jerry Hausman & Whitney K. Newey, 2019. "Demand analysis with many prices," CeMMAP working papers CWP59/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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• Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
• Joshua D. Angrist & Brigham Frandsen, 2022. "Machine Labor," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 97-140.
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• Ulrich K. Müller & James H. Stock & Mark W. Watson, 2019. "An Econometric Model of International Long-run Growth Dynamics," NBER Working Papers 26593, National Bureau of Economic Research, Inc.
• Jens Mehrhoff, 2019. "Introduction – The Value Chain of Scanner and Web Scraped Data," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 509, pages 5-11.
• Seán Kennedy, 2019. "The potential of tax microdata for tax policy," OECD Taxation Working Papers 45, OECD Publishing.
• Arnaud Pincet & Shu Okabe & Martin Pawelczyk, 2019. "Linking Aid to the Sustainable Development Goals – a machine learning approach," OECD Development Co-operation Working Papers 52, OECD Publishing.
• Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2019. "Identification of Global and Local Shocks in International Financial Markets via General Dynamic Factor Models," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 17(3), pages 462-494.
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• Simona Vasilica Oprea & Adela Bâra, 2019. "Big Data Solutions for Efficient Operation of Microgrids," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 266-271, August.
• Simona-Vasilica Oprea & Adela Bâra & Dan PreoÈ›escu, 2019. "NoSQL Data Storage and Clustering Large Volume of Data from Smart Metering Systems with Impact on Electricity Consumption Peak and Tariff Settings," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 327-333, December.
• Mora Rodríguez, Jhon James & González Terán, Ángela María, 2019. "Progresos educativos intergeneracionales: un análisis para Colombia || Intergenerational educational progress: an analysis for Colombia," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 28(1), pages 143-159, December.
• Joanna Olbrys, 2019. "Intra-market commonality in liquidity: new evidence from the Polish stock exchange," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 14(2), pages 251-275, June.
• Alifatussaadah, Ardiana & Primariesty, Anindya Diva & Soleh, Agus Mohamad & Andriansyah, Andriansyah, 2019. "Nowcasting Indonesia's GDP Growth: Are Fiscal Data Useful?," MPRA Paper 105252, University Library of Munich, Germany.
• Yang, Bill Huajian, 2019. "Monotonic Estimation for the Survival Probability over a Risk-Rated Portfolio by Discrete-Time Hazard Rate Models," MPRA Paper 93398, University Library of Munich, Germany.
• Yang, Bill Huajian, 2019. "Monotonic Estimation for Probability Distribution and Multivariate Risk Scales by Constrained Minimum Generalized Cross-Entropy," MPRA Paper 93400, University Library of Munich, Germany.
• Benedikt Maas, 2020. "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 394-411, April.
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• Genge, Ewa & Bartolucci, Francesco, 2019. "Are attitudes towards immigration changing in Europe? An analysis based on bidimensional latent class IRT models," MPRA Paper 94672, University Library of Munich, Germany.
• Loermann, Julius & Maas, Benedikt, 2019. "Nowcasting US GDP with artificial neural networks," MPRA Paper 95459, University Library of Munich, Germany.
• Indaco, Agustín, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).
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• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
• Maas, Benedikt, 2019. "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper 96408, University Library of Munich, Germany.
• Mohammad Vesal & Amir Hossein Tavakoli & Mohammad H. Rahmati, 2022. "What do one hundred million transactions tell us about demand elasticity of gasoline?," Empirical Economics, Springer, vol. 62(6), pages 2693-2711, June.
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• Cepni, Oguzhan & Gul, Selcuk & Gupta, Rangan, 2020. "Local currency bond risk premia of emerging markets: The role of local and global factors," Finance Research Letters, Elsevier, vol. 33(C).
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• Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
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• Rangan Gupta & Xiaojin Sun, 2019. "Forecasting Economic Policy Uncertainty of BRIC Countries Using Bayesian VARs," Working Papers 201961, University of Pretoria, Department of Economics.
• Paweł Lula & Anna Kovaleva & Renata Oczkowska & Małgorzata Tyrańska & Sylwia Wiśniewska, 2019. "Bipartite Competency Schemas on Polish Labor Market," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 1-25.
• Pavel Jasek & Lenka Vrana & Lucie Sperkova & Zdenek Smutny & Marek Kobulsky, 2019. "Predictive Performance of Customer Lifetime Value Models in E-Commerce and the Use of Non-Financial Data," Prague Economic Papers, Prague University of Economics and Business, vol. 2019(6), pages 648-669.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
  • Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
  • Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
  • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
  • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
• Längst, Gerhard & Elsner, Jürgen & Berzhanin, Anastasia, 2019. "Data Quality Imperatives for Data Migration Initiatives: A Guide for Data Practicioners," Journal of Financial Transformation, Capco Institute, vol. 50, pages 118-125.
• Pfarrhofer, Michael, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Working Papers in Economics 2019-3, University of Salzburg.
• Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
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• Badruddoza, Syed & Amin, Modhurima & McCluskey, Jill, 2019. "Assessing the Importance of an Attribute in a Demand SystemStructural Model versus Machine Learning," Working Papers 2019-5, School of Economic Sciences, Washington State University.
• Paolo Andreini & Donato Ceci, 2019. "A Horse Race in High Dimensional Space," CEIS Research Paper 452, Tor Vergata University, CEIS, revised 14 Feb 2019.
• Massimo Franchi & Paolo Paruolo, 2021. "Cointegration, Root Functions and Minimal Bases," Econometrics, MDPI, vol. 9(3), pages 1-27, August.
  • Massimo Franchi & Paolo Paruolo, 2019. "Cointegration, root functions and minimal bases," DSS Empirical Economics and Econometrics Working Papers Series 2019/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Benjamin Anderegg & Didier Sornette & Florian Ulmann, 2019. "Quantification of feedback effects in FX options markets," Working Papers 2019-03, Swiss National Bank.
• Yoshiaki Ogura & Ryo Okui & Yukiko Umeno Saito, 2019. "Network-motivated Lending Decisions: A Rationale for Forbearance," Working Paper Series no127, Institute of Economic Research, Seoul National University.
• James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.
• Petra Burdejová & Wolfgang K. Härdle, 2019. "Dynamic semi-parametric factor model for functional expectiles," Computational Statistics, Springer, vol. 34(2), pages 489-502, June.
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• Peter N. Posch & Daniel Ullmann & Dominik Wied, 2019. "Detecting structural changes in large portfolios," Empirical Economics, Springer, vol. 56(4), pages 1341-1357, April.
• Qing Wang & Dan Zhao, 2019. "Penalization methods with group-wise sparsity: econometric applications to eBay Motors online auctions," Empirical Economics, Springer, vol. 57(2), pages 683-704, August.
• Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
• Tomáš Gajdošík, 2019. "Big Data Analytics in Smart Tourism Destinations. A New Tool for Destination Management Organizations?," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Marival Segarra-Oña (ed.), Smart Tourism as a Driver for Culture and Sustainability, chapter 0, pages 15-33, Springer.
• Athanasios Koutras & Ioannis A. Nikas & Alkiviadis Panagopoulos, 2019. "Towards Developing Smart Cities: Evidence from GIS Analysis on Tourists’ Behavior Using Social Network Data in the City of Athens," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Marival Segarra-Oña (ed.), Smart Tourism as a Driver for Culture and Sustainability, chapter 0, pages 407-418, Springer.
• Daria Maltseva & Vladimir Batagelj, 2019. "Social network analysis as a field of invasions: bibliographic approach to study SNA development," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 1085-1128, November.
• Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: A network analysis," Working Paper Series in Economics 125, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  • Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series 90, European Systemic Risk Board.
• Bruno, Randolph Luca & Douarin, Elodie & Korosteleva, Julia & Radosevic, Slavo, 2019. "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," IZA Discussion Papers 12542, Institute of Labor Economics (IZA).
  • Randolph Luca Bruno & Elodie Douarin & Julia Korosteleva & Slavo Radosevic, 2019. "Determinants of Productivity Gap in the European Union: A Multilevel Perspective," LEM Papers Series 2019/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
• Rachida Ouysse, 2017. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12, School of Economics, The University of New South Wales.
  • Rachida Ouysse, 2019. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12a, School of Economics, The University of New South Wales.
• Chloé van Biljon & Cobus Burger, 2019. "The period effect: the effect of menstruation on absenteeism of school girls in Limpopo," Working Papers 20/2019, Stellenbosch University, Department of Economics.
• Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
  • Simon Beyeler & Sylvia Kaufmann, 2019. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08R, Swiss National Bank, Study Center Gerzensee.
  • Kaufmann, Sylvia & Beyeler, Simon, 2018. "Factor augmented VAR revisited - A sparse dynamic factor model approach," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181602, Verein für Socialpolitik / German Economic Association.
• Massimo Franchi & Paolo Paruolo, 2019. "A general inversion theorem for cointegration," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1176-1201, November.
  • Massimo Franchi & Paolo Paruolo, 2017. "A general inversion theorem for cointegration," DSS Empirical Economics and Econometrics Working Papers Series 2017/3, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Yacine Aït-Sahalia & Dacheng Xiu, 2019. "Principal Component Analysis of High-Frequency Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(525), pages 287-303, January.
  • Yacine Aït-Sahalia & Dacheng Xiu, 2015. "Principal Component Analysis of High Frequency Data," NBER Working Papers 21584, National Bureau of Economic Research, Inc.
• Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019. "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 831-843, April.
  • Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
  • Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
• Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Other publications TiSEM 83a4ca9e-c0cd-4786-ac8c-9, Tilburg University, School of Economics and Management.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Discussion Paper 2019-005, Tilburg University, Center for Economic Research.
• Jens Prüfer & Patricia Prüfer, 2020. "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, vol. 55(3), pages 651-672, October.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Discussion Paper 2019-005, Tilburg University, Center for Economic Research.
  • Prüfer, Jens & Prüfer, Patricia, 2019. "Data Science for Entrepreneurship Research : Studying Demand Dynamics for Entrepreneurial Skills in the Netherlands," Other publications TiSEM 83a4ca9e-c0cd-4786-ac8c-9, Tilburg University, School of Economics and Management.
• Aragón, Fernando M. & Restuccia, Diego & Rud, Juan Pablo, 2022. "Are small farms really more productive than large farms?," Food Policy, Elsevier, vol. 106(C).
  • Fernando M. Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," NBER Working Papers 26331, National Bureau of Economic Research, Inc.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," Working Papers tecipa-647, University of Toronto, Department of Economics.
  • Fernando Aragon Sanchez & Diego Restuccia & Juan Pablo Rud, 2019. "Are Small Farms Really more Productive than Large Farms?," 2019 Meeting Papers 1230, Society for Economic Dynamics.
  • Fernando Aragon, Diego Restuccia, Juan Pablo Rud & Diego Restuccia & Juan Pablo Rud, 2019. "Are small farms really more productive than large farms?," Discussion Papers dp19-05, Department of Economics, Simon Fraser University.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers tecipa-708, University of Toronto, Department of Economics.
  • Fernando M. Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," IFS Working Papers W21/35, Institute for Fiscal Studies.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2020. "Are small farms really more productive than large farms?," Working Papers tecipa-675, University of Toronto, Department of Economics.
  • Fernando Aragon & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Discussion Papers dp21-11, Department of Economics, Simon Fraser University.
  • Fernando Aragón & Diego Restuccia & Juan Pablo Rud, 2021. "Are small farms really more productive than large farms?," Working Papers 44, Red Nacional de Investigadores en Economía (RedNIE).
• Chiara Elena Dalla & Menon Martina & Perali Federico, 2019. "An Integrated Database to Measure Living Standards," Journal of Official Statistics, Sciendo, vol. 35(3), pages 531-576, September.
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• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
• Timo Bettendorf, 2019. "Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 296-312, January.
  • Bettendorf, Timo, 2016. "Spillover effects of credit default risk in the euro area and the effects on the euro: A GVAR approach," Discussion Papers 42/2016, Deutsche Bundesbank.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
  • Kapetanios, George & Marcellino, Massimiliano & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
  • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
• Hauber, Philipp & Schumacher, Christian & Zhang, Jiachun, 2019. "A flexible state-space model with lagged states and lagged dependent variables: Simulation smoothing," Discussion Papers 15/2019, Deutsche Bundesbank.
• Krstić, Živko & Seljan, Sanja & Zoroja, Jovana, 2019. "Visualization of Big Data Text Analytics in Financial Industry: A Case Study of Topic Extraction for Italian Banks," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2019), Rovinj, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019, pages 67-75, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
• Dragotă, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-35.
  • Dragota, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics Discussion Papers 2019-41, Kiel Institute for the World Economy (IfW Kiel).
• Doanh Khanh Nguyen & Van Ngoc Thi Pham & Heo, Yoon, 2019. "Impact of institutional and cultural distance on ASEAN's trade efficiency," Economics Discussion Papers 2019-57, Kiel Institute for the World Economy (IfW Kiel).
• Dragotă, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-35.
  • Dragota, Victor & Pele, Daniel Traian & Yaseen, Hanaan, 2019. "Dividend payout ratio follows a Tweedie distribution: International evidence," Economics Discussion Papers 2019-41, Kiel Institute for the World Economy (IfW Kiel).
• Hinz, Julian & Stammann, Amrei & Wanner, Joschka, 2019. "Persistent zeros: The extensive margin of trade," Kiel Working Papers 2139, Kiel Institute for the World Economy (IfW Kiel).
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2020. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," Papers 2004.12655, arXiv.org, revised Jul 2021.
  • Julian Hinz & Amrei Stammann & Joschka Wanner, 2021. "State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade," CEPA Discussion Papers 36, Center for Economic Policy Analysis.
• Härdle, Wolfgang Karl & Schulz, Rainer & Xie, Taojun, 2019. "Cooling Measures and Housing Wealth: Evidence from Singapore," IRTG 1792 Discussion Papers 2019-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Qian, Ya & Tu, Jun & Härdle, Wolfgang Karl, 2019. "Information Arrival, News Sentiment, Volatilities and Jumps of Intraday Returns," IRTG 1792 Discussion Papers 2019-002, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: a network analysis," ESRB Working Paper Series 90, European Systemic Risk Board.
  • Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: A network analysis," Working Paper Series in Economics 125, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
• Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
  • Bertsche, Dominik & Brüggemann, Ralf & Kascha, Christian, 2019. "Directed Graph and Variable Selection in Large Vector Autoregressive Models," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203656, Verein für Socialpolitik / German Economic Association.
  • Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2018-08, Department of Economics, University of Konstanz.

2018

• Ogerta Elezaj & Dhimitri Tole, 2018. "Big Data: Potential, Challenges, And Implications In Official Statistics," CBU International Conference Proceedings, ISE Research Institute, vol. 6(0), pages 95-99, September.
• Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," Working Papers halshs-01944588, HAL.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
  • Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating univariate fractional integration within a large VAR(1)," Post-Print hal-01980783, HAL.
• Jan Vavřina & Lubor Lacina, 2018. "Profitability of foodstuff processing companies in V4 countries during the 2008-2012 economic crisis," Society and Economy, Akadémiai Kiadó, Hungary, vol. 40(2), pages 245-270, June.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
  • Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
  • Bok, Brandyn & Caratelli, Daniele & Giannone, Domenico & Sbordone, Argia & Tambalotti, Andrea, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers XREAP2018-4, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2018.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," IREA Working Papers 201806, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," AQR Working Papers 201803, University of Barcelona, Regional Quantitative Analysis Group, revised Jun 2018.
• Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2018. "Ill-posed Estimation in High-Dimensional Models with Instrumental Variables," Papers 1806.00666, arXiv.org, revised Aug 2020.
  • Christoph Breunig & Enno Mammen & Anna Simoni, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print hal-03089879, HAL.
• Zhan Gao & Zhentao Shi, 2021. "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1127-1135, December.
  • Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.
• Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
  • Matthew Harding & Carlos Lamarche, 2018. "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment," Papers 1808.03364, arXiv.org.
• Smeekes, Stephan & Wijler, Etienne, 2021. "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, vol. 221(1), pages 247-276.
  • Stephan Smeekes & Etienne Wijler, 2018. "An Automated Approach Towards Sparse Single-Equation Cointegration Modelling," Papers 1809.08889, arXiv.org, revised Jul 2020.
• Harold D. Chiang, 2018. "Many Average Partial Effects: with An Application to Text Regression," Papers 1812.09397, arXiv.org, revised Jan 2022.
  • Harold D. Chiang, 2019. "Many Average Partial Effects: with an Application to Text Regression," 2019 Papers pch1836, Job Market Papers.
• Emilia VASILE & Danut-Octavian SIMION & George CALOTA, 2018. "Propositional calculation for expert systems in economics," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 50(2), pages 9-19, June.
• Danut-Octavian SIMION & Emilia VASILE, 2018. "Usage of informational systems in economic applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 51(3), pages 9-23, September.
• Emilia VASILE, 2018. "The Strategy Of Improving Informational Systems Through Economic Applications," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 52(4), pages 9-21, December.
• Dario Buono & George Kapetanios & Massimiliano Marcellino & Gianluigi Mazzi & Fotis Papailias, 2018. "Big Data Econometrics: Now Casting and Early Estimates," BAFFI CAREFIN Working Papers 1882, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Heather L.R. Tierney & Jiyoon Kim & Zafar Nazarov, 2018. "The Effects of Temporal Aggregation on Search Engine Data," Review of Economics & Finance, Better Advances Press, Canada, vol. 12, pages 57-71, May.
• Diego Bodas & Juan Ramon Garcia & Juan Murillo & Matias Pacce & Tomasa Rodrigo & Juan de Dios Romero & Pep Ruiz & Camilo Ulloa & Heribert Valero, 2018. "Measuring Retail Trade Using Card Transactional Data," Working Papers 18/03, BBVA Bank, Economic Research Department.
  • Diego Bodas & Juan R. García López & Tomasa Rodrigo López & Pep Ruiz de Aguirre & Camilo A. Ulloa & Juan Murillo Arias & Juan de Dios Romero Palop & Heribert Valero Lapaz & Matías J. Pacce, 2019. "Measuring retail trade using card transactional data," Working Papers 1921, Banco de España;Working Papers Homepage.
• Hicham Ganga & Javier Alonso & Vincenzo Spiezia & Jan Tscheke, 2018. "Patterns of domestic and cross-border e-commerce in Spain: A gravitational model approach," Working Papers 18/18, BBVA Bank, Economic Research Department.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
• Bulusu, Narayan & Guérin, Pierre, 2019. "What drives interbank loans? Evidence from Canada," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 427-444.
  • Narayan Bulusu & Pierre Guérin, 2018. "What Drives Interbank Loans? Evidence from Canada," Staff Working Papers 18-5, Bank of Canada.
• Sandra García-Uribe, 2018. "Multidimensional media slant: complementarities in news reporting by US newspapers," Working Papers 1817, Banco de España.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
• José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
  • Cordero, José Manuel & Cristobal, Victor & Santín, Daniel, 2017. "Causal Inference on Education Policies: A Survey of Empirical Studies Using PISA, TIMSS and PIRLS," MPRA Paper 76295, University Library of Munich, Germany.
• Vegard H�ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
  • Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
• Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
  • Vegard H�ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
• Hilde C. Bj�rnland & Julia Zhulanova, 2018. "The Shale Oil Boom and the U.S. Economy: Spillovers and Time-Varying Effects," Working Papers No 8/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the US economy: Spillovers and time-varying effects," CAMA Working Papers 2019-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
• Shakeeb Khan & Denis Nekipelov & Justin Rao, 2018. "Measuring the Return to Online Advertising: Estimation and Inference of Endogenous Treatment Effects," Boston College Working Papers in Economics 946, Boston College Department of Economics.
• Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
  • Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
• Turrell, Arthur & Speigner, Bradley & Djumalieva, Jyldyz & Copple, David & Thurgood, James, 2018. "Using job vacancies to understand the effects of labour market mismatch on UK output and productivity," Bank of England working papers 737, Bank of England.
• Turrell, Arthur & Thurgood, James & Djumalieva, Jyldyz & Copple, David & Speigner, Bradley, 2018. "Using online job vacancies to understand the UK labour market from the bottom-up," Bank of England working papers 742, Bank of England.
• Lazarov, Vladimir & Hinterschweiger, Marc, 2018. "Determinants of distress in the UK owner-occupier and buy-to-let mortgage markets," Bank of England working papers 760, Bank of England.
• Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  • Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
  • Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland, Institute for Economies in Transition.
• Wucherpfennig, Julian & Kachi, Aya & Bormann, Nils-Christian & Hunziker, Philipp, 2018. "Estimating Interdependence Across Space, Time and Outcomes in Binary Choice Models Using Pseudo Maximum Likelihood Estimators," Working papers 2018/11, Faculty of Business and Economics - University of Basel.
• Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
• Guo, P. & Lam, J. & Li, V., 2018. "A novel machine learning approach for identifying the drivers of domestic electricity users’ price responsiveness," Cambridge Working Papers in Economics 1844, Faculty of Economics, University of Cambridge.
• O'Neill, E. & Weeks, M., 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Cambridge Working Papers in Economics 1865, Faculty of Economics, University of Cambridge.
• Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, vol. 217(2), pages 431-470.
  • Hafner, C. & Linton, O. & Tang, H., 2018. "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1878, Faculty of Economics, University of Cambridge.
  • Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
• George Kapetanios & M. Hashem Pesaran & Simon Reese, 2018. "A Residual-based Threshold Method for Detection of Units that are Too Big to Fail in Large Factor Models," CESifo Working Paper Series 7401, CESifo.
• Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
  • Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Anesti, Nikoleta & Galvão, Ana & Miranda-Agrippino, Silvia, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England, revised 31 Jan 2020.
  • Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: Nowcasting GDP and its Revisions," Discussion Papers 1824, Centre for Macroeconomics (CFM).
  • Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
• Dhruv Grover & Sebastian Bauhoff & Jed Friedman, 2018. "Using Supervised Learning to Select Audit Targets in Performance-Based Financing in Health: An Example from Zambia," Working Papers 481, Center for Global Development.
• J-C Gerlach & Guilherme Demos & Didier Sornette, 2018. "Dissection of Bitcoin's Multiscale Bubble History," Swiss Finance Institute Research Paper Series 18-30, Swiss Finance Institute.
• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
  • Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
  • Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
• Hausmann, Ricardo & Hinz, Julian & Yildirim, Muhammed A., 2018. "Measuring Venezuelan emigration with Twitter," Kiel Working Papers 2106, Kiel Institute for the World Economy (IfW Kiel).
  • Ricardo Hausmann & Julian Hinz & Muhammed A. Yildirim, 2018. "Measuring Venezuelan Emigration with Twitter," CID Working Papers 342, Center for International Development at Harvard University.
• Martin Gurtler, 2018. "What Influences Private Investment? The Case of the Czech Republic," Working Papers 2018/14, Czech National Bank.
• Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
  • Gallego, J & Rivero, G & Martínez, J.D., 2018. "Preventing rather than Punishing: An Early Warning Model of Malfeasance in Public Procurement," Documentos de Trabajo 016724, Universidad del Rosario.
• Eduardo Rosas Rojas & Mónica C. Mimbrera Delgado, 2018. "Inflación y volatilidad cambiaria en México (1969-2017)," Ensayos de Economía 017297, Universidad Nacional de Colombia Sede Medellín.
• Henry Sebastián Rangel Quinonez, & Gabriel Yáñez Canal, 2018. "Clasificación por capitales de una muestra de microempresarios del Área Metropolitana de Bucaramanga a partir del Análisis de Correspondencia Múltiple," Ensayos de Economía 017302, Universidad Nacional de Colombia Sede Medellín.
• Eduardo Rosas Rojas & Teresa López González, 2018. "Inflación e incertidumbre inflacionaria: la postura del Banco de México, 1969-2017," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 10(2), pages 349-372, November.
• Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018. "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series 8, Bank of Lithuania.
  • WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020. "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance 2001, University of St. Gallen, School of Finance.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
  • Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017. "Macroeconomic nowcasting and forecasting with big data," Staff Reports 830, Federal Reserve Bank of New York.
  • Bok, Brandyn & Caratelli, Daniele & Giannone, Domenico & Sbordone, Argia & Tambalotti, Andrea, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," CEPR Discussion Papers 12589, C.E.P.R. Discussion Papers.
• Gonzalo Villa-Cox & Everardo Quezada & Joseph Aguilar-Bohorquez & Ivanna Valverde-Bajana & Paul Vera-Gilces, 2018. "Diseño experimental para la entrada de una firma en un mercado monopolístico con efectos de red: caso de estudio con estudiantes de pregrado en un rol empresarial," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, vol. 41(115), pages 130-139, Enero.
• Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling And Estimating Individual And Firm Effects With Count Panel Data," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1049-1078, September.
  • Jean-François Angers & Denise Desjardins & Georges Dionne & François Guertin, 2015. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Cahiers de recherche 1506, CIRPEE.
• Bruce Headey & Gert G. Wagner, 2018. "Alternative Values-Based 'Recipes' for Life Satisfaction: German Results with an Australian Replication," CESifo Working Paper Series 7234, CESifo.
  • Bruce Headey & Gert G. Wagner, 2018. "Alternative Values-Based ‘Recipes’ for Life Satisfaction: German Results with an Australian Replication," SOEPpapers on Multidisciplinary Panel Data Research 982, DIW Berlin, The German Socio-Economic Panel (SOEP).
  • Headey, Bruce & Wagner, Gert G., 2018. "Alternative Values-Based 'Recipes' for Life Satisfaction: German Results with an Australian Replication," IZA Discussion Papers 11818, Institute of Labor Economics (IZA).
• Schaefer, Maximilian & Sapi, Geza & Lorincz, Szabolcs, 2018. "The effect of big data on recommendation quality: The example of internet search," DICE Discussion Papers 284, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
  • Maximilian Schäfer & Geza Sapi & Szabolcs Lorincz, 2018. "The Effect of Big Data on Recommendation Quality: The Example of Internet Search," Discussion Papers of DIW Berlin 1730, DIW Berlin, German Institute for Economic Research.
• Fornaro, Paolo & Luomaranta, Henri, 2018. "Aggregate fluctuations and the effect of large corporations: Evidence from Finnish monthly data," Economic Modelling, Elsevier, vol. 70(C), pages 245-258.
• Jones, Benjamin A., 2018. "Forest-attacking Invasive Species and Infant Health: Evidence From the Invasive Emerald Ash Borer," Ecological Economics, Elsevier, vol. 154(C), pages 282-293.
• Xiang, Jingjie & Li, Kunpeng & Cui, Guowei, 2018. "A note on the asymptotic properties of least squares estimation in high dimensional constrained factor models," Economics Letters, Elsevier, vol. 171(C), pages 144-148.
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• Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018. "The U.S. Syndicated Loan Market: Matching Data," Research Working Paper RWP 18-9, Federal Reserve Bank of Kansas City.
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• Gregory J. Cohen & Melanie Friedrichs & Kamran Gupta & William Hayes & Seung Jung Lee & W. Blake Marsh & Nathan Mislang & Maya Shaton & Martin Sicilian, 2018. "The U.S. Syndicated Loan Market : Matching Data," Finance and Economics Discussion Series 2018-085, Board of Governors of the Federal Reserve System (U.S.).
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• Niels Framroze Møller & Laura Mørch Andersen & Lars Gårn Hansen & Carsten Lynge Jensen, 2018. "Can pecuniary and environmental incentives via SMS messaging make households adjust their intra-day electricity demand to a fluctuating production?," IFRO Working Paper 2018/06, University of Copenhagen, Department of Food and Resource Economics.
• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
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• Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Econometrics and Machine Learning," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 147-169.
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• Chevillon, Guillaume & Hecq, Alain & Laurent, Sébastien, 2018. "Generating univariate fractional integration within a large VAR(1)," Journal of Econometrics, Elsevier, vol. 204(1), pages 54-65.
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• Baum, Christopher F & Lööf, Hans & Perez, Luis & Stephan, Andreas, 2018. "Offshoring and Innovation Capabilities: Evidence from Swedish Manufacturing," Working Paper Series in Economics and Institutions of Innovation 469, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
• Trapp, Andrew C. & Teytelboym, Alexander & Martinello, Alessandro & Andersson, Tommy & Ahani, Narges, 2018. "Placement Optimization in Refugee Resettlement," Working Papers 2018:23, Lund University, Department of Economics, revised 20 Mar 2020.
• Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Maxim Kotsemir & Alina Lavrynenko, 2018. "Mapping the Radical Innovations in Food Industry: A Text Mining Study," HSE Working papers WP BRP 80/STI/2018, National Research University Higher School of Economics.
• Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Irina V. Loginova, 2018. "Detecting and Validating Global Technology Trends Using Quantitative and Expert-Based Foresight Techniques," HSE Working papers WP BRP 82/STI/2018, National Research University Higher School of Economics.
• Ilya Kuzminov & Irina Loginova & Elena Khabirova, 2018. "Stress Scenario Development: Global Challenges For The Russian Agricultural Sector," HSE Working papers WP BRP 88/STI/2018, National Research University Higher School of Economics.
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• Susana Santos & Tanya Araújo, 2018. "The network of inter-industry flows in a SAM framework," Working Papers REM 2018/40, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
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• Susan Dynarski & Brian Jacob & Daniel Kreisman, 2018. "How important are fixed effects and time trends in estimating returns to schooling? Evidence from a replication of Jacobson, Lalonde, and Sullivan, 2005," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1098-1108, November.
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• Jonathan Hersh & Matthew Harding, 2018. "Big Data in economics," IZA World of Labor, Institute of Labor Economics (IZA), pages 451-451, September.
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• WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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• Montero, José-María, 2018. "Geostatistics: Unde venis et quo vadis? /Geoestadística:¿De dónde vienes y a dónde vas?," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 81-106, Enero.
• Ian Borg & Germano Ruisi, 2018. "Forecasting using Bayesian VARs: A Benchmark for STREAM," CBM Working Papers WP/04/2018, Central Bank of Malta.
• Priyanga Dilini Talagala & Rob J Hyndman & Kate Smith-Miles & Sevvandi Kandanaarachchi & Mario A Munoz, 2018. "Anomaly detection in streaming nonstationary temporal data," Monash Econometrics and Business Statistics Working Papers 4/18, Monash University, Department of Econometrics and Business Statistics.
• Dominic Coey & Bradley Larsen & Kane Sweeney & Caio Waisman, 2018. "The Simple Empirics of Optimal Online Auctions," NBER Working Papers 24698, National Bureau of Economic Research, Inc.
• Steven F. Lehrer & Tian Xie, 2018. "The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success," NBER Working Papers 24755, National Bureau of Economic Research, Inc.
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• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
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• Lorie Dudoignon & Fabienne Le Sager & Aurélie Vanheuverzwyn, 2018. "Big Data and Audience Measurement: A Marriage of Convenience?," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 133-146.
• Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Econometrics and Machine Learning," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 147-169.
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• Paul Labonne & Martin Weale, 2018. "Temporal disaggregation of overlapping noisy quarterly data using state space models: Estimation of monthly business sector output from Value Added Tax data in the UK," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-18, Economic Statistics Centre of Excellence (ESCoE).
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• Oprea Simona Vasilica & Bâra Adela & Elefterescu LuminiÈ›a, 2018. "Decision Support System Design for Photovoltaic Systems Operation and Maintenance by using Big Data Technologies," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 104-110, July.
• Bâra Adela & Oprea Simona Vasilica & PreoÈ›escu Dan, 2018. "Data Management for Photovoltaic Power Plants Operation and Maintenance," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 70-75, July.
• David Troncoso-Ponce, 2018. "Estimation of competing risks duration models with unobserved heterogeneity using hsmlogit," Working Papers 18.03, Universidad Pablo de Olavide, Department of Economics.
• Garanasvili, Antanina & Kazimierczak, Michal & Lazaridis, George, 2018. "The Use of Intellectual Property Right Bundles by Firms in Copyright Intensive Industries," MPRA Paper 109493, University Library of Munich, Germany, revised 2021.
• Tierney, Heather L.R. & Kim, Jiyoon (June) & Nazarov, Zafar, 2018. "The Effects of Temporal Aggregation on Search Engine Data," MPRA Paper 84474, University Library of Munich, Germany.
• Chakraborty, Lekha S & Singh, Yadawendra, 2018. "Fiscal Policy, as the “Employer of Last Resort”: Impact of Direct fiscal transfer (MGNREGA) on Labour Force Participation Rates in India," MPRA Paper 85225, University Library of Munich, Germany.
• Verstappen, Ksenia, 2018. "Economics of big data: review of best papers for January 2018," MPRA Paper 85520, University Library of Munich, Germany.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
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• Asante Gyamerah, Samuel & Ngare, Philip & Ikpe, Dennis, 2018. "A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives," MPRA Paper 89680, University Library of Munich, Germany, revised 10 Jul 2018.
• bailek, Alexandra, 2018. "Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning," MPRA Paper 89875, University Library of Munich, Germany.
• Ogunlesi, Ayodeji, 2018. "Agricultural Productivity, Fiscal and Trade Policies Nexus in Sub-Saharan Africa: A Panel Structural Vector Error Correction Model Analysis," MPRA Paper 90202, University Library of Munich, Germany.
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• Chantawit Tantasith & Nasha Ananchotikul & Chatlada Chotanakarn & Vorada Limjaroenrat & Runchana Pongsaparn, 2018. "The Impact of LTV policy on Bank Lending: Evidence from Disaggregate Housing Loan Data," PIER Discussion Papers 90, Puey Ungphakorn Institute for Economic Research.
• Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
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• Łukasz Lipiński & Michał Bernardelli, 2018. "Anonimowość w Internecie – identyfikacja płci użytkowników na podstawie historii odwiedzanych stron internetowych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 53, pages 147-162.
• Philipp Otto & Wolfgang Schmid, 2018. "Spatiotemporal analysis of German real-estate prices," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 41-72, January.
• Milena Stróżyna & Gerd Eiden & Witold Abramowicz & Dominik Filipiak & Jacek Małyszko & Krzysztof Węcel, 2018. "A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(2), pages 219-233, May.
• Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
• Grégoire Lagasnerie & Anne-Sophie Aguadé & Pierre Denis & Anne Fagot-Campagna & Christelle Gastaldi-Menager, 2018. "The economic burden of diabetes to French national health insurance: a new cost-of-illness method based on a combined medicalized and incremental approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(2), pages 189-201, March.
• Valerie Moran & Rowena Jacobs, 2018. "Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(5), pages 709-718, June.
• Gordon H. Dash & Nina Kajiji & Domenic Vonella, 2018. "The role of supervised learning in the decision process to fair trade US municipal debt," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 139-168, June.
• Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
• Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
  • Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
• Tanya Araújo & Elsa Fontainha, 2018. "Are scientific memes inherited differently from gendered authorship?," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 953-972, November.
• Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020. "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
  • Nicolaas Johannes Odendaal & Monique Reid, 2018. "Media based sentiment indices as an alternative measure of consumer confidence," Working Papers 17/2018, Stellenbosch University, Department of Economics.
• Jochen Lüdering, 2018. "Standing and ‘survival’ in the adult film industry," Applied Economics, Taylor & Francis Journals, vol. 50(16), pages 1812-1823, April.
  • Jochen Lüdering, 2016. "Standing and “Survival” in the Adult Film Industry," MAGKS Papers on Economics 201626, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Mahmut Gunay, 2018. "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 149-161.
  • Mahmut Gunay, 2018. "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers 1805, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Mahmut Gunay, 2018. "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 149-161.
  • Mahmut Gunay, 2018. "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers 1805, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
• Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
  • Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Giacomo Caterini, 2018. "Classifying Firms with Text Mining," DEM Working Papers 2018/09, Department of Economics and Management.
• Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2019. "Variable Selection in Sparse Semiparametric Single Index Models," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B, volume 40, pages 65-88, Emerald Group Publishing Limited.
  • Tae-Hwy Lee & Jianghao Chu & Aman Ullah, 2018. "Variable Selection in Sparse Semiparametric Single Index Models," Working Papers 201908, University of California at Riverside, Department of Economics.
• Tae-Hwy Lee & Yundong Tu, 2018. "Forecasting Using Supervised Factor Models," Working Papers 201909, University of California at Riverside, Department of Economics.
• Oleksandr Faryna & Oleksandr Talavera & Tetiana Yukhymenko, 2018. "What Drives the Difference between Online and Official Price Indexes?," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 243, pages 21-32.
• Aslanidis, Nektarios & Christiansen, Charlotte & Cipollini, Andrea, 2019. "Predicting bond betas using macro-finance variables," Finance Research Letters, Elsevier, vol. 29(C), pages 193-199.
  • Nektarios Aslanidis & Charlotte Christiansen & Andrea Cipollini, 2017. "Predicting Bond Betas using Macro-Finance Variables," CREATES Research Papers 2017-01, Department of Economics and Business Economics, Aarhus University.
  • Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
• Mengheng Li & Marcel Scharth, 2018. "Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model," Working Paper Series 49, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
• Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018. "Credit Risk Analysis using Machine and Deep learning models," Working Papers 2018:08, Department of Economics, University of Venice "Ca' Foscari".
• Brito Rui Pedro & Sebastião Helder & Godinho Pedro, 2018. "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business, Sciendo, vol. 65(4), pages 365-383, December.
• Zekić-Sušac Marijana & Scitovski Rudolf & Has Adela, 2018. "Cluster analysis and artificial neural networks in predicting energy efficiency of public buildings as a cost-saving approach," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 4(2), pages 57-66, November.
• Oliver Reiter & Robert Stehrer, 2018. "Trade Policies and Integration of the Western Balkans," wiiw Working Papers 148, The Vienna Institute for International Economic Studies, wiiw.
• A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models," Globalization Institute Working Papers 290, Federal Reserve Bank of Dallas.
  • Chudik, A. & Kapetanios, G. & Pesaran, Hashem, 2016. "A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models," Cambridge Working Papers in Economics 1677, Faculty of Economics, University of Cambridge.
• Susan Dynarski & Brian Jacob & Daniel Kreisman, 2018. "How important are fixed effects and time trends in estimating returns to schooling? Evidence from a replication of Jacobson, Lalonde, and Sullivan, 2005," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1098-1108, November.
  • Dynarski, Susan & Jacob, Brian A. & Kreisman, Daniel, 2018. "How Important Are Fixed Effects and Time Trends in Estimating Returns to Schooling? Evidence from a Replication of Jacobson, Lalonde and Sullivan, 2005," IZA Discussion Papers 11935, Institute of Labor Economics (IZA).
• Carriero, Andrea & Galvao, Ana Beatriz & Marcellino, Massimiliano, 2018. "Credit Conditions and the Asymmetric Effects of Monetary Policy Shocks," EMF Research Papers 17, Economic Modelling and Forecasting Group.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers XREAP2018-4, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2018.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
• Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
  • Chen, J. & Li, D. & Linton, O., 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Cambridge Working Papers in Economics 1876, Faculty of Economics, University of Cambridge.
  • Jia Chen & Degui Li & Oliver Linton, 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers 18/14, Department of Economics, University of York.
• Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2019. "Can media and text analytics provide insights into labour market conditions in China?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2019. "Can media and text analytics provide insights into labour market conditions in China?," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1118-1130.
  • Jeannine Bailliu & Xinfen Han & Mark Kruger & Yu-Hsien Liu & Sri Thanabalasingam, 2018. "Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?," Staff Working Papers 18-12, Bank of Canada.
  • Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018. "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers 9/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
• Maximilian Schäfer & Geza Sapi & Szabolcs Lorincz, 2018. "The Effect of Big Data on Recommendation Quality: The Example of Internet Search," Discussion Papers of DIW Berlin 1730, DIW Berlin, German Institute for Economic Research.
  • Schaefer, Maximilian & Sapi, Geza & Lorincz, Szabolcs, 2018. "The effect of big data on recommendation quality: The example of internet search," DICE Discussion Papers 284, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
• Ricardo Hausmann & Julian Hinz & Muhammed A. Yildirim, 2018. "Measuring Venezuelan Emigration with Twitter," CID Working Papers 342, Center for International Development at Harvard University.
  • Hausmann, Ricardo & Hinz, Julian & Yildirim, Muhammed A., 2018. "Measuring Venezuelan emigration with Twitter," Kiel Working Papers 2106, Kiel Institute for the World Economy (IfW Kiel).
• Daniel, Volker & Neubert, Magnus & Orban, Agnes, 2018. "Fictional expectations and the global media in the Greek debt crisis: A topic modeling approach," Working Papers 4, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Klos, Jonas & Krieger, Tim & Stöwhase, Sven, 2018. "A New Measure of Intra-generational Redistribution within PAYG Pension Schemes and its Application to German Micro-data," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181580, Verein für Socialpolitik / German Economic Association.
• Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
  • Kaufmann, Sylvia & Beyeler, Simon, 2018. "Factor augmented VAR revisited - A sparse dynamic factor model approach," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181602, Verein für Socialpolitik / German Economic Association.
  • Simon Beyeler & Sylvia Kaufmann, 2019. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08R, Swiss National Bank, Study Center Gerzensee.
• Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2018. "Marginal jobs and job surplus: a test of the efficiency of separations," ECON - Working Papers 314, Department of Economics - University of Zurich.
  • Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," NBER Working Papers 25492, National Bureau of Economic Research, Inc.
  • Jäger, Simon & Schoefer, Benjamin & Zweimüller, Josef, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," IZA Discussion Papers 12127, Institute of Labor Economics (IZA).
  • Jäger, Simon & Schoefer, Benjamin & Zweimüller, Josef, 2019. "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," CEPR Discussion Papers 13473, C.E.P.R. Discussion Papers.

2017

• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
• Martin M. Andreasen & Jens H. E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," Working Paper Series 2017-21, Federal Reserve Bank of San Francisco.
  • Martin M. Andreasen & Jens H.E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," CREATES Research Papers 2017-31, Department of Economics and Business Economics, Aarhus University.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
  • Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2017-03, Department of Economics, Auburn University.
  • Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
  • Kim, Hyeongwoo & Ko, Kyunghwan, 2018. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper 89449, University Library of Munich, Germany.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2016. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2016-33, Center for Research in Economics and Statistics.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2017-10, Center for Research in Economics and Statistics.
• Luis Alejandro Lopez-Agudo & John Jerrim & Oscar David Marcenaro Gutierrez & Nikki Shure, 2017. "To weight or not to weight?: the case of PISA data," Investigaciones de Economía de la Educación volume 12, in: Juan Cándido Gómez Gallego & María Concepción Pérez Cárceles & Laura Nieto Torrejón (ed.), Investigaciones de Economía de la Educación 12, edition 1, volume 12, chapter 13, pages 285-302, Asociación de Economía de la Educación.
• Sorin Manole & Laura Panoiu & Adriana Paunescu, 2017. "Impact of Migration upon a Receiving Country’s Economic Development," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(46), pages 670-670, August.
• T. Tony Cai & Wenguang Sun, 2017. "Large-Scale Global and Simultaneous Inference: Estimation and Testing in Very High Dimensions," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 411-439, September.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
• Franchi, Massimo & Paruolo, Paolo, 2020. "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 803-839, October.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," DSS Empirical Economics and Econometrics Working Papers Series 2017/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," Papers 1712.07522, arXiv.org, revised Oct 2018.
• Danut-Octavian SIMION & Emilia VASILE, 2017. "Applications For Businesses That Uses Relational Databases:," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 45(1), pages 61-72, March.
• Danut-Octavian SIMION, 2017. "Evaluation Of The Economic Activity Through Experts Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 46(2), pages 63-75, June.
• Nelu BURCEA & Danut-Octavian SIMION, 2017. "The Management Of Software Products Through Economic Information Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 47(3), pages 111-124, Supplemen.
• Emilia VASILE & Danut-Octavian SIMION, 2017. "Representation Of Knowledge And Algorithms For Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, vol. 48(4), pages 7-20, December.
• Lidiya Guryanova & Tamara Klebanova & Tetiana Trunova, 2017. "Modeling the Financial Strategy of the Enterprise in an Unstable Environment," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 91-109.
• Carlos Casanova & Alvaro Ortiz & Tomasa Rodrigo & Le Xia & Joaquín Iglesias, 2017. "Tracking chinese vulnerability in real time using Big Data," Working Papers 17/13, BBVA Bank, Economic Research Department.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
  • Kapetanios, George & Marcellino, Massimiliano & Venditti, Fabrizio, 2016. "Large Time-Varying Parameter VARs: A Non-Parametric Approach," CEPR Discussion Papers 11560, C.E.P.R. Discussion Papers.
  • George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
• Dario Sansone, 2017. "Beyond Early Warning Indicators: High School Dropout and Machine Learning," Working Papers gueconwpa~17-17-09, Georgetown University, Department of Economics.
  • Dario Sansone, 2017. "Now You See Me: High School Dropout and Machine Learning," 2017 Stata Conference 5, Stata Users Group.
• Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
• Bholat, David & Brookes, James & Cai, Chris & Grundy, Katy & Lund, Jakob, 2017. "Sending firm messages: text mining letters from PRA supervisors to banks and building societies they regulate," Bank of England working papers 688, Bank of England.
• Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers 2017-14, Economic Research Institute, Bank of Korea.
• Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
  • Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using Survey Data to Forecast Real Activity with Evolutionary Algorithms. a Cross-Country Analysis," Journal of Applied Economics, Taylor & Francis Journals, vol. 20(2), pages 329-349, November.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 329-349, November.
• Matthew Bursnall & Vahé Nafilyan & Stefan Speckesser, 2017. "An analysis of the duration and achievement of apprenticeships in England," CVER Briefing Notes 004, Centre for Vocational Education Research.
• Sophie Hedges & Vahé Nafilyan & Stefan Speckesser & Augustin de Coulon, 2017. "Young people in low level vocational education: characteristics, trajectories and labour market outcomes," CVER Research Papers 004, Centre for Vocational Education Research.
• Vahé Nafilyan & Stefan Speckesser, 2017. "The longer the better? The impact of the 2012 apprenticeship reform in England on achievement and other outcomes," CVER Research Papers 006, Centre for Vocational Education Research.
• Grajzl, Peter & Murrell, Peter, 2019. "Toward understanding 17th century English culture: A structural topic model of Francis Bacon's ideas," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 111-135.
  • Peter Grajzl & Peter Murrell, 2017. "Toward Understanding 17th Century English Culture: A Structural Topic Model of Francis Bacon's Ideas," CESifo Working Paper Series 6443, CESifo.
• Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," EconomiX Working Papers 2017-5, University of Paris Nanterre, EconomiX.
  • Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
• Ariadne M. Checo & Salomé Pradel & Francisco A. Ramírez, 2017. "The Effects of USA Monetary Policy on Central America and the Dominican Republic," Investigación Conjunta-Joint Research, in: Ángel Estrada García & Alberto Ortiz Bolaños (ed.), International Spillovers of Monetary Policy, edition 1, chapter 7, pages 189-222, Centro de Estudios Monetarios Latinoamericanos, CEMLA.
• Ángel Estrada García & Alberto Ortiz Bolaños (ed.), 2017. "International Spillovers of Monetary Policy," Investigación Conjunta-Joint Research, Centro de Estudios Monetarios Latinoamericanos, CEMLA, edition 1, volume 1, number 3, Enero-mar.
• Alvaro J. Riascos & Mauricio Romero & Natalia Serna, 2017. "Risk Adjustment Revisited using Machine Learning Techniques," Documentos CEDE 015601, Universidad de los Andes – Facultad de Economía – CEDE.
• Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
  • Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
  • Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2016. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2016-33, Center for Research in Economics and Statistics.
  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2017-10, Center for Research in Economics and Statistics.
• Max Nathan & Anna Rosso, 2017. "Innovative events," Development Working Papers 429, Centro Studi Luca d'Agliano, University of Milano, revised 08 Apr 2019.
  • Max Nathan & Anna Rosso, 2019. "Innovative events," CEP Discussion Papers dp1607, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," IZA Discussion Papers 12213, Institute of Labor Economics (IZA).
  • Nathan, Max & Rosso, Anna, 2019. "Innovative events," LSE Research Online Documents on Economics 102626, London School of Economics and Political Science, LSE Library.
  • Nathan, Max & Rosso, Anna, 2019. "Innovative Events," SocArXiv t3jrq, Center for Open Science.
• Alvarez Iturri, Silvana Valeria, 2017. "Pricing the quality of an innovative idea," INDEM - Working Paper Business Economic Series 24183, Instituto para el Desarrollo Empresarial (INDEM).
• Benjamin David, 2017. "Model economic phenomena with CART and Random Forest algorithms," EconomiX Working Papers 2017-46, University of Paris Nanterre, EconomiX.
• Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
  • Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," EconomiX Working Papers 2017-5, University of Paris Nanterre, EconomiX.
• Ciccarelli, Matteo & García, Juan Angel & Montes-Galdón, Carlos, 2017. "Unconventional monetary policy and the anchoring of inflation expectations," Working Paper Series 1995, European Central Bank.
• K. Benkovskis & B. Bluhm & E. Bobeica & C. Osbat & S. Zeugner, 2020. "What drives export market shares? It depends! An empirical analysis using Bayesian model averaging," Empirical Economics, Springer, vol. 59(2), pages 817-869, August.
  • Konstantins Benkovskis & Benjamin Bluhm & Elena Bobeica & Chiara Osbat & Stefan Zeugner, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Papers 2017/02, Latvijas Banka.
  • Osbat, Chiara & Benkovskis, Konstantins & Bluhm, Benjamin & Bobeica, Elena & Zeugner, Stefan, 2017. "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Paper Series 2090, European Central Bank.
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• Ya Qian & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Industry Interdependency Dynamics in a Network Context," SFB 649 Discussion Papers SFB649DP2017-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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• Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
• Jean-Pierre Dubé & Sanjog Misra, 2017. "Personalized Pricing and Consumer Welfare," NBER Working Papers 23775, National Bureau of Economic Research, Inc.
• Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2020. "Machine Learning from Schools about Energy Efficiency," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(6), pages 1181-1217.
  • Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2017. "Machine Learning from Schools about Energy Efficiency," NBER Working Papers 23908, National Bureau of Economic Research, Inc.
• Alexander M. Chinco & Adam D. Clark-Joseph & Mao Ye, 2017. "Sparse Signals in the Cross-Section of Returns," NBER Working Papers 23933, National Bureau of Economic Research, Inc.
• Jacob Assa, 2017. "Leveraged Growth: Endogenous Money and Speculative Credit in a Stock-flow Consistent Measure of Output," Working Papers 1727, New School for Social Research, Department of Economics.
• O. Borzykh., 2017. "The impact of banks’ capital adequacy ratio on bank lending channel of monetary transmission in Russia," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 7.
• Thilo Klein & Stefaan Verhulst, 2017. "Access to new data sources for statistics: Business models and incentives for the corporate sector," OECD Statistics Working Papers 2017/6, OECD Publishing.
• Jayson L. Lusk, 2017. "Consumer Research with Big Data: Applications from the Food Demand Survey (FooDS)," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(2), pages 303-320.
• Marisa Hidalgo-Hidalgo & Iñigo Iturbe-Ormaetxe, 2018. "Long-run effects of public expenditure on poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(1), pages 1-22, March.
  • Marisa Hidalgo-Hidalgo & Iñigo Iturbe-Ormaetxe, 2018. "Long-run effects of public expenditure on poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(1), pages 1-22, March.
  • Marisa Hidalgo-Hidalgo & Iñigo Iturbe-Ormaetxe, 2017. "Long-run Effects of Public Expenditure on Poverty," Working Papers 17.09, Universidad Pablo de Olavide, Department of Economics.
• Yolanda F. Rebollo-Sanz, 2017. "Decomposing the structure of wages into firm and worker effects: some insights from a high unemployment economy," Working Papers 17.10, Universidad Pablo de Olavide, Department of Economics.
• Annette O. Balaoing-Pelkmans, 2017. "A new look at Philippine export performance-a firm-level view," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 54(1), pages 1-31, June.
• José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
  • Cordero, José Manuel & Cristobal, Victor & Santín, Daniel, 2017. "Causal Inference on Education Policies: A Survey of Empirical Studies Using PISA, TIMSS and PIRLS," MPRA Paper 76295, University Library of Munich, Germany.
• Chu, Ba, 2017. "Composite Quasi-Maximum Likelihood Estimation of Dynamic Panels with Group-Specific Heterogeneity and Spatially Dependent Errors," MPRA Paper 79709, University Library of Munich, Germany.
• Tagiew, Rustam & Ignatov, Dmitry I., 2017. "Behavior Mining in h-index Ranking Game," MPRA Paper 82795, University Library of Munich, Germany.
• Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
  • Antoine A. Djogbenou, 2017. "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper 1391, Economics Department, Queen's University.
• Antoine A. Djogbenou, 2020. "Comovements in the real activity of developed and emerging economies: A test of global versus specific international factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 344-370, April.
  • Antoine A. Djogbenou, 2018. "Comovements In The Real Activity Of Developed And Emerging Economies: A Test Of Global Versus Specific International Factors," Working Paper 1392, Economics Department, Queen's University.
• Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017. "What happens when econometrics and psychometrics collide? An example using the PISA data," Economics of Education Review, Elsevier, vol. 61(C), pages 51-58.
  • Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using the PISA Data," IZA Discussion Papers 10847, Institute of Labor Economics (IZA).
  • John Jerrim & Luis Alejandro Lopez-Agudo & Oscar D. Marcenaro-Gutierrez & Nikki Shure, 2017. "What Happens When Econometrics and Psychometrics Collide? An Example Using PISA Data," DoQSS Working Papers 17-04, Quantitative Social Science - UCL Social Research Institute, University College London.
• Fornaro, Paolo & Luomaranta, Henri & Saarinen, Lauri, 2017. "Nowcasting Finnish Turnover Indexes Using Firm-Level Data," ETLA Working Papers 46, The Research Institute of the Finnish Economy.
• Frieling, Julius & Madlener, Reinhard, 2017. "The Turning Tide: How Energy has Driven the Transformation of the British Economy Since the Industrial Revolution," FCN Working Papers 7/2017, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
• Michal Antoszewski, 2017. "Panel estimation of sectoral substitution elasticities for CES production functions," EcoMod2017 10160, EcoMod.
  • Antoszewski, Michal, 2017. "Panel estimation of sectoral substitution elasticities for CES production functions," MF Working Papers 28, Ministry of Finance in Poland.
• Andreea – Cristina PETRICA & Stelian STANCU, 2017. "Empirical Results of Modeling EUR/RON Exchange Rate using ARCH, GARCH, EGARCH, TARCH and PARCH models," Romanian Statistical Review, Romanian Statistical Review, vol. 65(1), pages 57-72, March.
• Tommaso Proietti & Alessandro Giovannelli, 2018. "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, vol. 105(4), pages 783-795.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers 2017-20, Department of Economics and Business Economics, Aarhus University.
  • Tommaso Proietti & Alessandro Giovannelli, 2017. "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper 410, Tor Vergata University, CEIS, revised 19 Jul 2017.
• Di Iorio, Francesca & Fachin, Stefano, 2021. "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, vol. 17(C), pages 64-75.
  • Francesca Di Iorio & Stefano Fachin, 2017. "Evaluating Restricted Common Factor models for non-stationary data," DSS Empirical Economics and Econometrics Working Papers Series 2017/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Massimo Franchi & Paolo Paruolo, 2019. "A general inversion theorem for cointegration," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1176-1201, November.
  • Massimo Franchi & Paolo Paruolo, 2017. "A general inversion theorem for cointegration," DSS Empirical Economics and Econometrics Working Papers Series 2017/3, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Franchi, Massimo & Paruolo, Paolo, 2020. "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 803-839, October.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," Papers 1712.07522, arXiv.org, revised Oct 2018.
  • Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," DSS Empirical Economics and Econometrics Working Papers Series 2017/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
• Emilia Vasile & Danut Octavian Simion, 2017. "The Management of Businesses through Information Systems," Working papers Globalization - Economic, Social and Moral Implications, April 2017 20, Research Association for Interdisciplinary Studies.
• Alain Galli, 2018. "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(2), pages 179-218, November.
  • Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
• Júlia Gallego Ziero Uhr & André Luis Squarize Chagas, Daniel de Abreu Pereira Uhr, Renan Porn Peres, 2017. "A study on environmental infractions for Brazilian municipalities: a spatial dynamic panel approach," Working Papers, Department of Economics 2017_13, University of São Paulo (FEA-USP).
• Hocine Mokhtar-Kharroubi, 2017. "Convex and convex-like optimization over a range inclusion problem and first applications," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 277-299, November.
• Ricardo Buettner, 2017. "Predicting user behavior in electronic markets based on personality-mining in large online social networks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 247-265, August.
• Eric. W. K. See-To & Yang Yang, 2017. "Market sentiment dispersion and its effects on stock return and volatility," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 283-296, August.
• Júlia Varga, 2017. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011): the case of Hungary," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1079-1093, December.
  • Júlia Varga, 2016. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011). The case of Hungary," Budapest Working Papers on the Labour Market 1604, Institute of Economics, Centre for Economic and Regional Studies.
• Thomas Reutterer & Kurt Hornik & Nicolas March & Kathrin Gruber, 2017. "A data mining framework for targeted category promotions," Journal of Business Economics, Springer, vol. 87(3), pages 337-358, April.
• Sebastian Voigt & Oliver Hinz, 2017. "Assessing the economic effects of server launches in free-to-play MMO games," Journal of Business Economics, Springer, vol. 87(4), pages 421-464, May.
  • Voigt, Sebastian & Hinz, Oliver, 2016. "Assessing the Economic Effects of Server Launches in Free-to-Play MMO Games," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84846, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
  • Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
• Jessica Petersen & Fabian Hattke & Rick Vogel, 2017. "Editorial governance and journal impact: a study of management and business journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1593-1614, September.
• Scott French, 2017. "A Gravity-Based Revealed Comparative Advantage Estimator," Discussion Papers 2017-05, School of Economics, The University of New South Wales.
• Rachida Ouysse, 2017. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12, School of Economics, The University of New South Wales.
  • Rachida Ouysse, 2019. "Constrained principal components estimation of large approximate factor models," Discussion Papers 2017-12a, School of Economics, The University of New South Wales.
• Chris van Wyk & Anderson Gondwe & Pierre de Villiers, 2017. "Learner flow through patterns in the Western Cape using CEMIS datasets from 2007 to 2014: A longitudinal cohort analysis," Working Papers 02/2017, Stellenbosch University, Department of Economics.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 329-349, November.
  • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using Survey Data to Forecast Real Activity with Evolutionary Algorithms. a Cross-Country Analysis," Journal of Applied Economics, Taylor & Francis Journals, vol. 20(2), pages 329-349, November.
• Michael Greenacre, 2017. "Towards a pragmatic approach to compositional data analysis," Economics Working Papers 1554, Department of Economics and Business, Universitat Pompeu Fabra.
• Michael Greenacre, 2017. "Data reporting and visualization in ecology," Economics Working Papers 1558, Department of Economics and Business, Universitat Pompeu Fabra.
• Brady, Ryan R. & Insler, Michael A., 2019. "Order of play advantage in sequential tournaments: Evidence from randomized settings in professional golf," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 79(C), pages 79-92.
  • Ryan Brady & Michael Insler, 2017. "Order of Play Advantage in Sequential Tournaments: Evidence from randomized settings in professional golf," Departmental Working Papers 54, United States Naval Academy Department of Economics.
• Kjosev Sasho & Novkovska Blagica, 2017. "Developing Social Accounting Matrix for Macedonia: a challenge ahead," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 3(2), pages 10-19, December.
• Eryk Kopczyński & Dorota Celińska, 2017. "Hyperbolic grids and discrete random graphs," Working Papers 2017-20, Faculty of Economic Sciences, University of Warsaw.
• Rangan Gupta & Eric Olson & Mark E. Wohar, 2017. "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 640-650, September.
  • Rangan Gupta & Eric Olson & Mark E. Wohar, 2015. "Forecasting Key US Macroeconomic Variables with a Factor-Augmented Qual VAR," Working Papers 201585, University of Pretoria, Department of Economics.
• Foos, Daniel & Lütkebohmert, Eva & Markovych, Mariia & Pliszka, Kamil, 2017. "Euro area banks' interest rate risk exposure to level, slope and curvature swings in the yield curve," Discussion Papers 24/2017, Deutsche Bundesbank.
• Momanyi, Kevin, 2017. "An Econometric Analysis of The Impact of Telecare on The Length of Stay in Hospital," EconStor Preprints 168559, ZBW - Leibniz Information Centre for Economics.
• Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
  • Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
  • Heinisch, Katja & Scheufele, Rolf, 2017. "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers 5/2017, Halle Institute for Economic Research (IWH).
• Haskamp, Ulrich, 2017. "Improving the forecasts of European regional banks' profitability with machine learning algorithms," Ruhr Economic Papers 705, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

2016

• Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
  • Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
• Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," American Economic Review, American Economic Association, vol. 106(5), pages 152-156, May.
  • Bloom, Nicholas & Lemos, Renata & Sadun, Raffaella & Scur, Daniela & Van Reenen, John, 2016. "International data on measuring management practices," LSE Research Online Documents on Economics 67379, London School of Economics and Political Science, LSE Library.
  • Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," CEP Occasional Papers 46, Centre for Economic Performance, LSE.
• Liran Einav & Amy Finkelstein & Raymond Kluender & Paul Schrimpf, 2016. "Beyond Statistics: The Economic Content of Risk Scores," American Economic Journal: Applied Economics, American Economic Association, vol. 8(2), pages 195-224, April.
  • Liran Einav & Amy Finkelstein & Raymond Kluender & Paul Schrimpf, "undated". "Beyond Statistics: The Economic Content of Risk Scores," Discussion Papers 15-024, Stanford Institute for Economic Policy Research.
  • Liran Einav & Amy Finkelstein & Raymond Kluender & Paul Schrimpf, 2015. "Beyond Statistics: The Economic Content of Risk Scores," NBER Working Papers 21304, National Bureau of Economic Research, Inc.
• Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
  • Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," NBER Working Papers 22111, National Bureau of Economic Research, Inc.
• Emmanuel Olusegun STOBER, 2016. "Crude Oil Price Shocks And Macroeconomic Behavior In Nigeria," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 5(1), pages 56-66, JULY.
• Ufuk Çelik & Eyüp Akçetin & Abdulkadir Yaldır, 2016. "Analysis of Volvo IT's Closed Problem Management Processes By Using Process Mining Software ProM and Disco," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 4(2), pages 171-182, December.
• Gordon Rausser & David A. Bessler, 2016. "Information Recovery and Causality: A Tribute to George Judge," Annual Review of Resource Economics, Annual Reviews, vol. 8(1), pages 7-23, October.
• Jushan Bai & Peng Wang, 2016. "Econometric Analysis of Large Factor Models," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 53-80, October.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials [Microcredit impacts: Evidence from a randomized microcredit program placement experiment by Compartamos Banco]," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," MPRA Paper 71670, University Library of Munich, Germany.
  • Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," Papers 1606.00142, arXiv.org.
• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-effect regressions on network data," CeMMAP working papers CWP32/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2018. "Fixed-effect regressions on network data," CeMMAP working papers CWP44/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2017. "Fixed-effect regressions on network data," CeMMAP working papers CWP26/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Koen Jochmans & Martin Weidner, 2019. "Fixed-effect regressions on network data," CeMMAP working papers CWP16/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
• Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," MPRA Paper 73622, University Library of Munich, Germany.
  • Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," Papers 1609.03344, arXiv.org, revised Sep 2016.
• Matthias Raddant & Friedrich Wagner, 2016. "Multivariate Garch with dynamic beta," Papers 1609.07051, arXiv.org, revised Nov 2019.
• Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  • Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  • Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers CWP50/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
  • Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
  • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Kan Chen & Mario Crucini, 2016. "Trends & Cycles in Small Open Economies:Making the Case for a General Equilibrium Approach," Working Papers 16/12, BBVA Bank, Economic Research Department.
• Burdeau, E. & Potier, L., 2016. "Crédits à l’habitat : taux d’intérêt, durée des crédits et profil des emprunteurs," Bulletin de la Banque de France, Banque de France, issue 206, pages 5-18.
• Tor Korneliussen & Michael Greenacre, 2016. "Information sources used by European tourists: A cross-cultural study," Economics Working Papers 1527, Department of Economics and Business, Universitat Pompeu Fabra.
  • Tor Korneliussen & Michael Greenacre, 2016. "Information Sources Used by European Tourists: A Cross-Cultural Study," Working Papers 915, Barcelona School of Economics.
• Bilandžić Ana & Marina Jeger & Šarlija Nataša, 2016. "Dealing with Interpretability Issues in Predicting Firm Growth: Factor Analysis Approach," Business Systems Research, Sciendo, vol. 7(2), pages 23-34, September.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bj�rnland & Leif Anders Thorsrud & Sepideh K. Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Papers No 8/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020. "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 285-310, April.
  • Hilde C. Bjørnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Paper 2016/19, Norges Bank.
  • Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017. "Do central banks respond timely to developments in the global economy?," CAMA Working Papers 2017-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Hilde C. Bj�rnland & Leif Anders Thorsrud & Sepideh K. Zahiri, 2016. "Do central banks respond timely to developments in the global economy?," Working Papers No 8/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
• Hacioglu, Sinem & Tuzcuoglu, Kerem, 2016. "Interpreting the latent dynamic factors by threshold FAVAR model," Bank of England working papers 622, Bank of England.
• François-Xavier Meunier & Célia Zyla, 2016. "Firm growth and knowledge flows: comparative analysis between defence and civil areas," Journal of Innovation Economics, De Boeck Université, vol. 0(2), pages 89-108.
• Étienne Chamayou & Ronan Le Saout, 2016. "Changement d’enseigne sur le marché français des carburants : effets sur la concurrence locale d’une baisse des prix," Revue économique, Presses de Sciences-Po, vol. 67(5), pages 1085-1105.
• Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo.
  • A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," Cambridge Working Papers in Economics 1611, Faculty of Economics, University of Cambridge.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
• HAFNER, Christian & LINTON, Oliver B. & TANG, Haihan, 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," LIDAM Discussion Papers CORE 2016044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Hafner, C. M. & Linton, O., 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1664, Faculty of Economics, University of Cambridge.
  • Christian M. Hafner & Oliver Linton & Haihan Tang, 2016. "Estimation of a multiplicative covariance structure in the large dimensional case," CeMMAP working papers CWP52/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models," Globalization Institute Working Papers 290, Federal Reserve Bank of Dallas.
  • Chudik, A. & Kapetanios, G. & Pesaran, Hashem, 2016. "A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models," Cambridge Working Papers in Economics 1677, Faculty of Economics, University of Cambridge.
• Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," American Economic Review, American Economic Association, vol. 106(5), pages 152-156, May.
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  • Nicholas Bloom & Renata Lemos & Raffaella Sadun & Daniela Scur & John Van Reenen, 2016. "International Data on Measuring Management Practices," CEP Occasional Papers 46, Centre for Economic Performance, LSE.
• Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo.
  • A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," Cambridge Working Papers in Economics 1611, Faculty of Economics, University of Cambridge.
• Rachidi Kotchoni & Dalibor Stevanovic, 2016. "Prévision de l’activité économique au Québec," CIRANO Project Reports 2016rp-08, CIRANO.
• Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
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• Luis Arturo Bárcenas & Lorena Barreiro & Carolina Pagliacci, 2016. "What Is the Role of Size in Latin American Banks’ Performancein Response to External Shocks?," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(2), pages 233-273, july-dece.
• Luis Arturo Bárcenas & Lorena Barreiro & Carolina Pagliacci, 2016. "¿Cuál es el papel del tamaño de los bancos en su desempeño en América Latina ante choques externos?," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(2), pages 251-296, julio-dic.
• Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
• Gustavo Peralta, 2016. "The Nature of Volatility Spillovers across the International Capital Markets," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
• Hafner, C. M. & Linton, O., 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1664, Faculty of Economics, University of Cambridge.
  • HAFNER, Christian & LINTON, Oliver B. & TANG, Haihan, 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," LIDAM Discussion Papers CORE 2016044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Christian M. Hafner & Oliver Linton & Haihan Tang, 2016. "Estimation of a multiplicative covariance structure in the large dimensional case," CeMMAP working papers CWP52/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
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• Jérémy L'Hour, 2016. "Distinguishing the Confounding Factors: Policy Evaluation, High-Dimension and Variable Selection," Working Papers 2016-23, Center for Research in Economics and Statistics.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017. "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
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• Sebastian Voigt & Oliver Hinz, 2017. "Assessing the economic effects of server launches in free-to-play MMO games," Journal of Business Economics, Springer, vol. 87(4), pages 421-464, May.
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• Garcí­a, Juan Angel & Werner, Sebastian E. V., 2016. "Bond risk premia, macroeconomic factors and financial crisis in the euro area," Working Paper Series 1938, European Central Bank.
• Hyndman, Rob J. & Lee, Alan J. & Wang, Earo, 2016. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 16-32.
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• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
• Byun, Sung Je, 2016. "The usefulness of cross-sectional dispersion for forecasting aggregate stock price volatility," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 162-180.
• Bernstein, Paul & Tuladhar, Sugandha D. & Yuan, Mei, 2016. "Economics of U.S. natural gas exports: Should regulators limit U.S. LNG exports?," Energy Economics, Elsevier, vol. 60(C), pages 427-437.
• Avanzi, Benjamin & Wong, Bernard & Yang, Xinda, 2016. "A micro-level claim count model with overdispersion and reporting delays," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 1-14.
• Butaru, Florentin & Chen, Qingqing & Clark, Brian & Das, Sanmay & Lo, Andrew W. & Siddique, Akhtar, 2016. "Risk and risk management in the credit card industry," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 218-239.
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• Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
• Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
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• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
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• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Kurt Unger & Fernando Varela, 2016. "Complejidad, competitividad e innovación en los estados mexicanos: La urgencia de una Política Industrial integral y diferenciada," Working papers DTE 605, CIDE, División de Economía.
• Breitung Jörg & Eickmeier Sandra, 2016. "Analyzing International Business and Financial Cycles using Multi-Level Factor Models: A Comparison of Alternative Approaches," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 177-214, Emerald Group Publishing Limited.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
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  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• R. Kelley Pace & James P. LeSage, 2016. "Fast Simulated Maximum Likelihood Estimation of the Spatial Probit Model Capable of Handling Large Samples," Advances in Econometrics, in: Spatial Econometrics: Qualitative and Limited Dependent Variables, volume 37, pages 3-34, Emerald Group Publishing Limited.
• Sumana Chaudhuri & Shovan Ray & Ganesh-Kumar, 2018. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Journal of Infrastructure Development, India Development Foundation, vol. 10(1-2), pages 96-125, June.
  • Shovan Ray & A. Ganesh Kumar & Sumana Chaudhuri, 2016. "Integrated model of computable general equilibrium and social cost benefit analysis of an Indian oil refinery: Future projections and macroeconomic effects," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2016-024, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Shovan Ray & A. Ganesh-Kumar & Sumana Chaudhuri, 2016. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Working Papers id:11381, eSocialSciences.
• Jushan Bai & Xu Han, 2016. "Structural Changes in High Dimensional Factor Models," Frontiers of Economics in China, IAR, Shanghai University of Finance and Economics, vol. 11(1), pages 9-39, March.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
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  • Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
• Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big data analytics: a new perspective," Globalization Institute Working Papers 268, Federal Reserve Bank of Dallas.
  • A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," Cambridge Working Papers in Economics 1611, Faculty of Economics, University of Cambridge.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
• A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018. "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, vol. 86(4), pages 1479-1512, July.
  • Chudik, A. & Kapetanios, G. & Pesaran, Hashem, 2016. "A One-Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models," Cambridge Working Papers in Economics 1677, Faculty of Economics, University of Cambridge.
  • Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "A one-covariate at a time, multiple testing approach to variable selection in high-dimensional linear regression models," Globalization Institute Working Papers 290, Federal Reserve Bank of Dallas.
• R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
  • Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
• Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
  • Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," FHFA Staff Working Papers 16-04, Federal Housing Finance Agency.
  • Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," Working Papers 2016-010, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
  • Sébastien GALANTI, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," LEO Working Papers / DR LEO 2413, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Post-Print hal-01724241, HAL.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Working Papers hal-01392253, HAL.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
  • Sébastien GALANTI, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," LEO Working Papers / DR LEO 2413, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Working Papers hal-01392253, HAL.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Post-Print hal-01724241, HAL.
• Júlia Varga, 2017. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011): the case of Hungary," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(9), pages 1079-1093, December.
  • Júlia Varga, 2016. "Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011). The case of Hungary," Budapest Working Papers on the Labour Market 1604, Institute of Economics, Centre for Economic and Regional Studies.
• Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," Working Papers 2016-010, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," FHFA Staff Working Papers 16-04, Federal Housing Finance Agency.
• Wolfgang K. Härdle & Chen Huang & Shih-Kang Chao, 2016. "Calculating Joint Confidence Bands for Impulse Response Functions using Highest Density Regions," SFB 649 Discussion Papers SFB649DP2016-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
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• Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021. "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
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  • Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Grazia Biorci & Antonella Emina & Michelangelo Puliga & Lisa Sella & Gianna Vivaldo, 2016. "Tweet-tales: moods of socio-economic crisis?," Working Papers 04/2016, IMT School for Advanced Studies Lucca, revised Jul 2016.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials [Microcredit impacts: Evidence from a randomized microcredit program placement experiment by Compartamos Banco]," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
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  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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• Koen Jochmans & Martin Weidner, 2019. "Fixed‐Effect Regressions on Network Data," Econometrica, Econometric Society, vol. 87(5), pages 1543-1560, September.
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• Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
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  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• HAFNER, Christian & LINTON, Oliver B. & TANG, Haihan, 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," LIDAM Discussion Papers CORE 2016044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Christian M. Hafner & Oliver Linton & Haihan Tang, 2016. "Estimation of a multiplicative covariance structure in the large dimensional case," CeMMAP working papers CWP52/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Hafner, C. M. & Linton, O., 2016. "Estimation of a Multiplicative Covariance Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1664, Faculty of Economics, University of Cambridge.
• Sumana Chaudhuri & Shovan Ray & Ganesh-Kumar, 2018. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Journal of Infrastructure Development, India Development Foundation, vol. 10(1-2), pages 96-125, June.
  • Shovan Ray & A. Ganesh-Kumar & Sumana Chaudhuri, 2016. "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Working Papers id:11381, eSocialSciences.
  • Shovan Ray & A. Ganesh Kumar & Sumana Chaudhuri, 2016. "Integrated model of computable general equilibrium and social cost benefit analysis of an Indian oil refinery: Future projections and macroeconomic effects," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2016-024, Indira Gandhi Institute of Development Research, Mumbai, India.
• Marco Di Zio & Ugo Guarnera & Roberta Varriale, 2016. "Estimation of the main variables of the economic account of small and medium enterprises based on administrative sources," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 71-81.
• Paolo Righi, 2016. "Estimation procedure and inference for component totals of the economic aggregates in the “Frame SBS”," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 83-97.
• Pedro S. Martins, 2015. "Working to get fired? Regression discontinuity effects of unemployment benefit eligibility on prior employment duration," Working Papers 61, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
  • Martins, Pedro S., 2016. "Working to Get Fired? Regression Discontinuity Effects of Unemployment Benefit Eligibility on Prior Employment Duration," IZA Discussion Papers 10262, Institute of Labor Economics (IZA).
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials [Microcredit impacts: Evidence from a randomized microcredit program placement experiment by Compartamos Banco]," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP15/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2019. "Optimal Data Collection for Randomized Control Trials," CeMMAP working papers CWP21/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
  • Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2016. "Optimal Data Collection for Randomized Control Trials," Papers 1603.03675, arXiv.org, revised Aug 2016.
  • Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers CWP45/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Nikolaos Askitas, 2016. "Big Data is a big deal but how much data do we need? [Big Data gut und schön. Aber wie viel Data brauchen wir?]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 113-125, October.
  • Askitas, Nikos, 2016. "Big Data Is a Big Deal But How Much Data Do We Need?," IZA Discussion Papers 9988, Institute of Labor Economics (IZA).
• Varga, Júlia, 2016. "Hova lettek az orvosok?. Az orvosok külföldre vándorlása és pályaelhagyása Magyarországon, 2003-2011 [Where have all the doctors gone?. Migration and attrition of physicians and dentists in Hungary," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(1), pages 1-26.
• Galanti, Sébastien, 2016. "Archival data of financial analysts' earnings forecasts in the euro zone: Problems with euro conversions," Research in International Business and Finance, Elsevier, vol. 38(C), pages 466-473.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Working Papers hal-01392253, HAL.
  • Sébastien GALANTI, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," LEO Working Papers / DR LEO 2413, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  • Sébastien Galanti, 2016. "Archival data of financial analysts' earnings forecasts in the Euro zone: problems with euro conversions," Post-Print hal-01724241, HAL.
• Jochen Lüdering, 2018. "Standing and ‘survival’ in the adult film industry," Applied Economics, Taylor & Francis Journals, vol. 50(16), pages 1812-1823, April.
  • Jochen Lüdering, 2016. "Standing and “Survival” in the Adult Film Industry," MAGKS Papers on Economics 201626, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
• György Inzelt & Gábor Szappanos & Zsolt Armai, 2016. "Supervision by robust risk monitoring – a cycle-independent Hungarian corporate credit rating system," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(3), pages 51-78.
• Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate, 2017. "Visualising forecasting algorithm performance using time series instance spaces," International Journal of Forecasting, Elsevier, vol. 33(2), pages 345-358.
  • Yanfei Kang & Rob J. Hyndman & Kate Smith-Miles, 2016. "Visualising forecasting Algorithm Performance using Time Series Instance Spaces," Monash Econometrics and Business Statistics Working Papers 10/16, Monash University, Department of Econometrics and Business Statistics.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Radoslav Tusan, 2016. "Using Benford'S Law To The Detection Of Misrepresentation Of Financial Statements Data," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 737-745, July.
• Vipul Kumar Singh, 2016. "Pricing and hedging competitiveness of the tree option pricing models: Evidence from India," Journal of Asset Management, Palgrave Macmillan, vol. 17(6), pages 453-475, October.
• Daniel Kaimann & Nadja Maraun & Joe Cox, 2016. "Identifying the preferences and heterogeneity of consumer groups in multiplayer video games," Working Papers CIE 94, Paderborn University, CIE Center for International Economics.
• Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
  • Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, Tampere University, School of Management and Business, Economics.
  • Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
• Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," Papers 1606.00142, arXiv.org.
  • Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso," MPRA Paper 71670, University Library of Munich, Germany.
• Einian, Majid & Nili, Masoud, 2016. "Consumption Smoothing and Borrowing Constraints: Evidence from Household Surveys of Iran," MPRA Paper 72461, University Library of Munich, Germany.
• Ning Xu & Jian Hong & Timothy C. G. Fisher, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," Papers 1609.03344, arXiv.org, revised Sep 2016.
  • Xu, Ning & Hong, Jian & Fisher, Timothy, 2016. "Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression," MPRA Paper 73622, University Library of Munich, Germany.
• Cordero, José Manuel & Gil, María & Pedraja Chaparro, Francisco, 2016. "Exploring the effect of financial literacy courses on student achievement: a cross-country approach using PISA 2012 data," MPRA Paper 75474, University Library of Munich, Germany.
• Bonga-Bonga, Lumengo & Mabe, Queen Magadi, 2020. "How financially integrated are trading blocs in Africa?," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 84-94.
  • Bonga-Bonga, Lumengo & Mabe, Queen Magadi, 2016. "How financially integrated are trading blocs in Africa?," MPRA Paper 75716, University Library of Munich, Germany.
  • Lumengo Bonga-Bonga, 2017. "How financially integrated are trading blocs in Africa?," EcoMod2017 10580, EcoMod.
• Nikitinsky, Nikita & Shashev, Sergey & Kachurina, Polina & Bespalov, Aleksander, 2016. "Big Data and Machine Learning in Government Projects: Expert Evaluation Case," MPRA Paper 82865, University Library of Munich, Germany.
• Mitrofanova, Ekaterina S. & Artamonova, Alyona V., 2016. "Studying Family Formation Trajectories’ Deinstitutionalization in Russia Using Sequence Analysis," MPRA Paper 82877, University Library of Munich, Germany.
• Trabelsi, Mohamed Ali, 2016. "Analyse des données : Résumé de cours avec exercices d’application [Data analysis: course summary with case studies]," MPRA Paper 82947, University Library of Munich, Germany, revised 03 May 2016.
• Pallara, Kevin, 2016. "The dynamic effects of government spending: a FAVAR approach," MPRA Paper 92283, University Library of Munich, Germany.
• Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
• Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
• Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
• Borzykh, Olga, 2016. "Bank lending channel in Russia: A TVP-FAVAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 96-117.
• Rebouças, Sílvia & Oliveira, Daniele & Soares, Rômulo & Ferreira, Eugénia & Gouveia, Maria José, 2016. "Classification Of The Financial Sustainability Of Health Insurance Beneficiaries Through Data Mining Techniques," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 4(3), pages 229-242.
• Vincenzo Atella & Federico Belotti & Valentina Conti & Claudio Cricelli & Joanna Kopinska & Andrea Piano Mortari, 2016. "Modeling public health care expenditure using patient level data: Empirical evidence from Italy," CEIS Research Paper 367, Tor Vergata University, CEIS, revised 10 Feb 2016.
• Michał Bernardelli, 2016. "Econometric modeling of panel data using parallel computing with Apache Spark," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 41, pages 189-202.
• Pietro Battiston, 2016. "Constrained Network Formation," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(3), pages 347-362, November.
• Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
  • Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
• Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019. "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 831-843, April.
  • Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
  • Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
• Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
  • Simon Beyeler & Sylvia Kaufmann, 2019. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08R, Swiss National Bank, Study Center Gerzensee.
  • Kaufmann, Sylvia & Beyeler, Simon, 2018. "Factor augmented VAR revisited - A sparse dynamic factor model approach," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181602, Verein für Socialpolitik / German Economic Association.
• Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
  • Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
  • Jari Hännikäinen, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers 1603, Tampere University, School of Management and Business, Economics.
• Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
  • Tom Boot & Didier Nibbering, 2016. "Forecasting Using Random Subspace Methods," Tinbergen Institute Discussion Papers 16-073/III, Tinbergen Institute, revised 11 Aug 2017.
• Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
  • Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
• Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  • Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
• Jushan Bai & Kunpeng Li, 2016. "Maximum Likelihood Estimation and Inference for Approximate Factor Models of High Dimension," The Review of Economics and Statistics, MIT Press, vol. 98(2), pages 298-309, May.
  • Bai, Jushan & Li, Kunpeng, 2012. "Maximum likelihood estimation and inference for approximate factor models of high dimension," MPRA Paper 42099, University Library of Munich, Germany, revised 19 Oct 2012.
• Zhong, Sheng, 2016. "The dynamics of vehicle energy efficiency: Evidence from the Massachusetts Vehicle Census," MERIT Working Papers 2016-014, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• Tor Korneliussen & Michael Greenacre, 2016. "Information Sources Used by European Tourists: A Cross-Cultural Study," Working Papers 915, Barcelona School of Economics.
  • Tor Korneliussen & Michael Greenacre, 2016. "Information sources used by European tourists: A cross-cultural study," Economics Working Papers 1527, Department of Economics and Business, Universitat Pompeu Fabra.
• Ritchie, Felix & Veliziotis, Michail & Drew, Hilary & Whittard, Damian, 2017. "Measuring compliance with minimum wages," Journal of Economic and Social Measurement, IOS Press, issue 3-4, pages 249-270.
  • Felix Ritchie & Michail Veliziotis & Hilary Drew & Damian Whittard, 2016. "Measuring compliance with minimum wages," Working Papers 20161608, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
• Tim Oliver Berg, 2016. "Multivariate Forecasting with BVARs and DSGE Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(8), pages 718-740, December.
  • Berg, Tim Oliver, 2015. "Multivariate Forecasting with BVARs and DSGE Models," MPRA Paper 62405, University Library of Munich, Germany.
• Timo Bettendorf, 2019. "Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 296-312, January.
  • Bettendorf, Timo, 2016. "Spillover effects of credit default risk in the euro area and the effects on the euro: A GVAR approach," Discussion Papers 42/2016, Deutsche Bundesbank.
• Raddant, Matthias & Wagner, Friedrich, 2016. "Multivariate GARCH for a large number of stocks," Kiel Working Papers 2049, Kiel Institute for the World Economy (IfW Kiel).
• Kaeding, Matthias, 2016. "Fast, approximate MCMC for Bayesian analysis of large data sets: A design based approach," Ruhr Economic Papers 660, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Christian Hansen & Damian Kozbur & Sanjog Misra, 2016. "Targeted undersmoothing," ECON - Working Papers 282, Department of Economics - University of Zurich, revised Apr 2018.

2015

• Lorenzo Boldrini & Eric Hillebrand, 2015. "Supervision in Factor Models Using a Large Number of Predictors," CREATES Research Papers 2015-38, Department of Economics and Business Economics, Aarhus University.
• Jakob Guldbæk Mikkelsen & Eric Hillebrand & Giovanni Urga, 2015. "Maximum Likelihood Estimation of Time-Varying Loadings in High-Dimensional Factor Models," CREATES Research Papers 2015-61, Department of Economics and Business Economics, Aarhus University.
• Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Machine Learning Methods for Demand Estimation," American Economic Review, American Economic Association, vol. 105(5), pages 481-485, May.
• Burns, Christopher & Prager, Daniel & Ghosh, Sujit & Goodwin, Barry, 2015. "Imputing for Missing Data in the ARMS Household Section: A Multivariate Imputation Approach," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205291, Agricultural and Applied Economics Association.
• Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "Farm-level economic impacts of EU-CAP greening measures," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205309, Agricultural and Applied Economics Association.
• Ferto, Imre & Bojnec, Stefan, 2015. "Quality upgrading in the European-Union agri-food exports," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204225, Agricultural Economics Society.
• Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
  • Jan Witajewski-Baltvilks & Elena Verdolini & Massimo Tavoni, 2015. "Bending The Learning Curve," Working Papers 2015.65, Fondazione Eni Enrico Mattei.
  • Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending The Learning Curve," Climate Change and Sustainable Development 206836, Fondazione Eni Enrico Mattei (FEEM).
• Hristov, Jordan, 2015. "An exploratory analysis of the impact of climate change on Macedonian agriculture," 2015 Conference, August 9-14, 2015, Milan, Italy 211747, International Association of Agricultural Economists.
• Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "EU-wide individual Farm Model for CAP Analysis (IFM-CAP): Application to Crop Diversification Policy," 2015 Conference, August 9-14, 2015, Milan, Italy 212155, International Association of Agricultural Economists.
• Martinez, Pilar & Blanco, Maria & Van Doorslaer, Benjamin & Ramos, Fabien & Stanca, Lucian, 2015. "What role does climate change play in agricultural market uncertainty? An integrated assessment taking into account market-driven adjustments," 2015 Conference, August 9-14, 2015, Milan, Italy 212230, International Association of Agricultural Economists.
• Ibrahim Onur Oz & Tezer Yelkenci, 2015. "The Generalizability of Financial Distress Prediction Models: Evidence from Turkey," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 14(4), pages 685-703, December.
• Aysun Kapucugil İkiz & Güzin Özdağoğlu, 2015. "Text Mining as a Supporting Process for VoC Clarification," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(1), pages 25-40, June.
• Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
  • Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Raphael Douady & Antoine Kornprobst, 2018. "An Empirical Approach To Financial Crisis Indicators Based On Random Matrices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(03), pages 1-22, May.
  • Antoine Kornprobst & Raphael Douady, 2015. "An Empirical Approach to Financial Crisis Indicators Based on Random Matrices," Papers 1506.00806, arXiv.org, revised Sep 2017.
  • Raphaël Douady & Antoine Kornprobst, 2018. "An empirical approach to financial crisis indicators based on random matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03265045, HAL.
  • Raphaël Douady & Antoine Kornprobst, 2018. "An empirical approach to financial crisis indicators based on random matrices," Post-Print hal-03265045, HAL.
• Mumtaz Hussain Shah & Anum Gul Afridi, 2015. "Significance of Good Governance for FDI Inflows in SAARC Countries," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 7(2), pages 31-52, October.
• Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
• Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
  • Hilde C. Bj�rnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
  • Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Claudia Foroni & Francesco Ravazzolo & Pinho J. Ribeiro, 2015. "Forecasting commodity currencies: the role of fundamentals with short-lived predictive content," Working Paper 2015/14, Norges Bank.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
  • Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Paper 2015/05, Norges Bank.
  • Hilde C. Bj�rnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Hilde C. Bjornland & Francesco Ravazzolo & Leif Anders Thorsrud, 2016. "Forecasting GDP with global components. This time is different," CAMA Working Papers 2016-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• David Bholat & Stephen Hans & Pedro Santos & Cheryl Schonhardt-Bailey, 2015. "Text mining for central banks," Handbooks, Centre for Central Banking Studies, Bank of England, number 33, December.
• Jeremiah Dittmar & Skipper Seabold, 2015. "Media, Markets and Institutional Change: Evidence from the Protestant Reformation," CEP Discussion Papers dp1367, Centre for Economic Performance, LSE.
• Dong, Zhengbin & Wu, Wenjie, 2015. "Exploring the geography of China's airport networks: a hybrid complex-network approach," LSE Research Online Documents on Economics 64508, London School of Economics and Political Science, LSE Library.
  • Zhengbin Dong & Wenjie Wu, 2015. "Exploring the Geography of China's Airport Networks: A Hybrid Complex-Network Approach," SERC Discussion Papers 0173, Centre for Economic Performance, LSE.
• Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
  • Tim Oliver Berg, 2015. "Forecast Accuracy of a BVAR under Alternative Specifications of the Zero Lower Bound," ifo Working Paper Series 203, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Pedro S. Martins, 2015. "Working to get fired? Regression discontinuity effects of unemployment benefit eligibility on prior employment duration," Working Papers 61, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
  • Martins, Pedro S., 2016. "Working to Get Fired? Regression Discontinuity Effects of Unemployment Benefit Eligibility on Prior Employment Duration," IZA Discussion Papers 10262, Institute of Labor Economics (IZA).
• Gheorghe MILITARU & Massimo POLLIFRONI & Alexandra IOANID, 2015. "Big Data In Supply Chain Management: An Exploratory Study," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 6, pages 103-108, December.
• Gustavo Nicolás Páez, 2015. "Prediciendo decisiones de agentes económicos: ¿Cómo determina el Banco de la República de Colombia la tasa de interés?," Documentos CEDE 012567, Universidad de los Andes – Facultad de Economía – CEDE.
• Christian Hutter & Joachim Möller & Marion Penninger, 2015. "Reducing the Need for Heuristic Rules - An Iterative Algorithm for Imputing the Education Variable in SIAB," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 135(3), pages 355-388.
• Kutluk Kaðan SÜMER, 2015. "Effectiveness of technical analysis indicators over stock return: A Panel Data Approach," Eurasian Eononometrics, Statistics and Emprical Economics Journal, Eurasian Academy Of Sciences, vol. 1(1), pages 43-56, April.
• Christopoulos, Dimitris K. & McAdam, Peter, 2019. "Efficiency, Inefficiency, And The Mena Frontier," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 489-521, March.
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• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
• Breitung, Jörg & Eickmeier, Sandra, 2015. "Analyzing business cycle asymmetries in a multi-level factor model," Economics Letters, Elsevier, vol. 127(C), pages 31-34.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
• Castelli, Mauro & Vanneschi, Leonardo & De Felice, Matteo, 2015. "Forecasting short-term electricity consumption using a semantics-based genetic programming framework: The South Italy case," Energy Economics, Elsevier, vol. 47(C), pages 37-41.
• Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
  • Jan Witajewski-Baltvilks & Elena Verdolini & Massimo Tavoni, 2015. "Bending The Learning Curve," Working Papers 2015.65, Fondazione Eni Enrico Mattei.
  • Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending The Learning Curve," Climate Change and Sustainable Development 206836, Fondazione Eni Enrico Mattei (FEEM).
• Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
• Nathan, Max & Rosso, Anna, 2015. "Mapping digital businesses with big data: Some early findings from the UK," Research Policy, Elsevier, vol. 44(9), pages 1714-1733.
  • Nathan, Max & Rosso, Anna, 2015. "Mapping digital businesses with big data: some early findings from the UK," LSE Research Online Documents on Economics 65211, London School of Economics and Political Science, LSE Library.
• Chia-Lin Chang & Michael McAleer, 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Documentos de Trabajo del ICAE 2015-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Chang, C-L. & McAleer, M.J., 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Econometric Institute Research Papers EI2015-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Michael McAleer, 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Documentos de Trabajo del ICAE 2015-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • McAleer, M.J., 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Econometric Institute Research Papers EI2015-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Ogura, Yoshiaki & Okui, Ryo & Saito, Yukiko Umeno, 2015. "Network-Motivated Lending Decisions," HIT-REFINED Working Paper Series 29, Institute of Economic Research, Hitotsubashi University.
  • OGURA Yoshiaki & OKUI Ryo & SAITO Yukiko, 2015. "Network-motivated Lending Decisions," Discussion papers 15057, Research Institute of Economy, Trade and Industry (RIETI).
• Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
  • Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending The Learning Curve," Climate Change and Sustainable Development 206836, Fondazione Eni Enrico Mattei (FEEM).
  • Jan Witajewski-Baltvilks & Elena Verdolini & Massimo Tavoni, 2015. "Bending The Learning Curve," Working Papers 2015.65, Fondazione Eni Enrico Mattei.
• Whitaker, Stephan D., 2018. "Big Data versus a survey," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 285-296.
  • Stephan Whitaker, 2015. "Big Data versus a Survey," Working Papers (Old Series) 1440, Federal Reserve Bank of Cleveland.
• Alessandro Barbarino & Efstathia Bura, 2015. "Forecasting with Sufficient Dimension Reductions," Finance and Economics Discussion Series 2015-74, Board of Governors of the Federal Reserve System (U.S.).
• Stephanie M. Wilshusen, 2015. "Exploring the use of anonymized consumer credit information to estimate economic conditions: an application of big data," Consumer Finance Institute discussion papers 15-5, Federal Reserve Bank of Philadelphia.
• António Alberto Santos, 2015. "The evolution of the Volatility in Financial Returns: Realized Volatility vs Stochastic Volatility Measures," GEMF Working Papers 2015-10, GEMF, Faculty of Economics, University of Coimbra.
• António A. F. Santos, 2015. "On the Forecasting of Financial Volatility Using Ultra-High Frequency Data," GEMF Working Papers 2015-17, GEMF, Faculty of Economics, University of Coimbra.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Post-Print halshs-01169307, HAL.
  • Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169307, HAL.
  • Antoine Kornprobst & Raphael Douady, 2015. "A Practical Approach to Financial Crisis Indicators Based on Random Matrices," Documents de travail du Centre d'Economie de la Sorbonne 15049, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
• Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169307, HAL.
  • Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Post-Print halshs-01169307, HAL.
  • Antoine Kornprobst & Raphael Douady, 2015. "A Practical Approach to Financial Crisis Indicators Based on Random Matrices," Documents de travail du Centre d'Economie de la Sorbonne 15049, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
• Matias Quiroz & Robert Kohn & Mattias Villani & Minh-Ngoc Tran, 2019. "Speeding Up MCMC by Efficient Data Subsampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 831-843, April.
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  • Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
• Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Scalable Mcmc For Large Data Problems Using Data Subsampling And The Difference Estimator," Working Paper Series 306, Sveriges Riksbank (Central Bank of Sweden).
• Quiroz, Matias, 2015. "Speeding Up Mcmc By Delayed Acceptance And Data Subsampling," Working Paper Series 307, Sveriges Riksbank (Central Bank of Sweden).
• OGURA Yoshiaki & OKUI Ryo & SAITO Yukiko, 2015. "Network-motivated Lending Decisions," Discussion papers 15057, Research Institute of Economy, Trade and Industry (RIETI).
  • Ogura, Yoshiaki & Okui, Ryo & Saito, Yukiko Umeno, 2015. "Network-Motivated Lending Decisions," HIT-REFINED Working Paper Series 29, Institute of Economic Research, Hitotsubashi University.
• Hoxby, Caroline M. & Bulman, George B., 2016. "The effects of the tax deduction for postsecondary tuition: Implications for structuring tax-based aid," Economics of Education Review, Elsevier, vol. 51(C), pages 23-60.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," NBER Working Papers 21554, National Bureau of Economic Research, Inc.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," Economics Working Papers 15114, Hoover Institution, Stanford University.
• Shih-Kang Chao & Wolfgang K. Härdle & Ming Yuan, 2015. "Factorisable Sparse Tail Event Curves," SFB 649 Discussion Papers SFB649DP2015-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
• Koomen, Miriam & Backes-Gellner, Uschi, 2022. "Occupational tasks and wage inequality in West Germany: A decomposition analysis," Labour Economics, Elsevier, vol. 79(C).
  • Rinawi, Miriam & Backes-Gellner, Uschi, 2015. "Occupational Skills and the Evolution of Wages," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112801, Verein für Socialpolitik / German Economic Association.
  • Miriam Koomen & Uschi Backes-Gellner, 2015. "Occupational Tasks and Wage Inequality in West Germany: A Decomposition Analysis," Economics of Education Working Paper Series 0112, University of Zurich, Department of Business Administration (IBW), revised Oct 2022.
• John P. Robinson & Elena Tracy & Yoonjoo Lee, 2015. "Cruising through the millennium - 2003-13 changes in American Daily life," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 12(1), pages 133-152, December.
• Montero, José-María & Fernández-Avilés, Gema, 2015. "Functional Kriging Prediction of Pollution Series: The Geostatistical Alternative for Spatially-fixed Data/Predicción de series de contaminación mediante kriging funcional. La alternativa geoestadísti," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 145-179, Enero.
• Angers, Jean-François & Desjardins, Denise & Dionne, Georges & Guertin, François, 2018. "Modelling And Estimating Individual And Firm Effects With Count Panel Data," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1049-1078, September.
  • Jean-François Angers & Denise Desjardins & Georges Dionne & François Guertin, 2015. "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Cahiers de recherche 1506, CIRPEE.
• Catherine Doz & Anna Petronevich, 2016. "Dating Business Cycle Turning Points for the French Economy: An MS-DFM approach," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 481-538, Emerald Group Publishing Limited.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Post-Print hal-01159200, HAL.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Documents de travail du Centre d'Economie de la Sorbonne 15009, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Catherine Doz & Anna Petronevich, 2015. "Dating Business Cycle Turning Points for the French Economy: a MS-DFM approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01159200, HAL.
• Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169307, HAL.
  • Antoine Kornprobst & Raphael Douady, 2015. "A Practical Approach to Financial Crisis Indicators Based on Random Matrices," Documents de travail du Centre d'Economie de la Sorbonne 15049, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Antoine Kornprobst & Raphaël Douady, 2015. "A Pratical Approach to Financial Crisis Indicators Based on Random Matrices," Post-Print halshs-01169307, HAL.
• Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
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• Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Demand Estimation with Machine Learning and Model Combination," NBER Working Papers 20955, National Bureau of Economic Research, Inc.
• Carlos A. Manzanares & Ying Jiang & Patrick Bajari, 2015. "Improving Policy Functions in High-Dimensional Dynamic Games," NBER Working Papers 21124, National Bureau of Economic Research, Inc.
• Hoxby, Caroline M. & Bulman, George B., 2016. "The effects of the tax deduction for postsecondary tuition: Implications for structuring tax-based aid," Economics of Education Review, Elsevier, vol. 51(C), pages 23-60.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," Economics Working Papers 15114, Hoover Institution, Stanford University.
  • Caroline M. Hoxby & George B. Bulman, 2015. "The Effects of the Tax Deduction for Postsecondary Tuition: Implications for Structuring Tax-Based Aid," NBER Working Papers 21554, National Bureau of Economic Research, Inc.
• Yacine Aït-Sahalia & Dacheng Xiu, 2019. "Principal Component Analysis of High-Frequency Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(525), pages 287-303, January.
  • Yacine Aït-Sahalia & Dacheng Xiu, 2015. "Principal Component Analysis of High Frequency Data," NBER Working Papers 21584, National Bureau of Economic Research, Inc.
• Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," Harvard Business School Working Papers 16-065, Harvard Business School.
  • Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life," NBER Working Papers 21778, National Bureau of Economic Research, Inc.
  • Glaeser, Edward L. & Kominers, Scott Duke & Luca, Michael & Naik, Nikhil, 2015. "Big Data and Big Cities: The Promises and Limitations of Improved Measures for Urban Life," Working Paper Series 15-075, Harvard University, John F. Kennedy School of Government.
• Lenarčič, Črt & Damjanović, Milan, 2015. "Slovene Residential Property Prices Misalignment with Fundamentals," MPRA Paper 101198, University Library of Munich, Germany.
• Byambasuren, Tsenguunjav & Gochoo, Munkh-Erdene, 2015. "Optimizing the Structure of Mongolian Foreign Trade and the Alternative Policy of Successful Transition," MPRA Paper 61803, University Library of Munich, Germany.
• Tim Oliver Berg, 2016. "Multivariate Forecasting with BVARs and DSGE Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(8), pages 718-740, December.
  • Berg, Tim Oliver, 2015. "Multivariate Forecasting with BVARs and DSGE Models," MPRA Paper 62405, University Library of Munich, Germany.
• Situngkir, Hokky, 2015. "Indonesia embraces the Data Science," MPRA Paper 66048, University Library of Munich, Germany.
• Ben Jebli, Mehdi, 2015. "The Impact of Combustible Renewables and Waste Consumption and Transport on the Environmental Degradation: The Case of Tunisia," MPRA Paper 68038, University Library of Munich, Germany.
• Kausik Gangopadhyay & Abhishek Jangir & Rudra Sensarma, 2014. "Forecasting the price of gold: An error correction approach," Working papers 155, Indian Institute of Management Kozhikode.
  • Gangopadhyay, Kausik & Jangir, Abhishek & Sensarma, Rudra, 2015. "Forecasting the price of gold: An error correction approach," MPRA Paper 81066, University Library of Munich, Germany.
• Braaksma, Barteld & Zeelenberg, Kees, 2015. "“Re-make/Re-model”: Should big data change the modelling paradigm in official statistics?," MPRA Paper 87741, University Library of Munich, Germany.
• Rangan Gupta & Eric Olson & Mark E. Wohar, 2017. "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(6), pages 640-650, September.
  • Rangan Gupta & Eric Olson & Mark E. Wohar, 2015. "Forecasting Key US Macroeconomic Variables with a Factor-Augmented Qual VAR," Working Papers 201585, University of Pretoria, Department of Economics.
• Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
  • Rangan Gupta & Mark E. Wohar, 2015. "Forecasting Oil and Stock Returns with a Qual VAR using over 150 Years of Data," Working Papers 201589, University of Pretoria, Department of Economics.
• Chris Godfrey & Chris Brooks, 2015. "The Negative Credit Risk Premium Puzzle: A Limits to Arbitrage Story," ICMA Centre Discussion Papers in Finance icma-dp2015-07, Henley Business School, University of Reading.
• Mao Takongmo, Charles Olivier & Stevanovic, Dalibor, 2015. "Selection Of The Number Of Factors In Presence Of Structural Instability: A Monte Carlo Study," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 177-233, Mars-Juin.
  • Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.
• Francesco Lautizi, 2015. "Large Scale Covariance Estimates for Portfolio Selection," CEIS Research Paper 353, Tor Vergata University, CEIS, revised 07 Aug 2015.
• Ülle Säälik, 2015. "Reading performance, learning strategies, gender and school language as related issues ? PISA 2009 findings in Finland and Estonia," Proceedings of International Academic Conferences 1003055, International Institute of Social and Economic Sciences.
• Ülle Säälik, 2015. "Reading performance, learning strategies, gender and school language as related issues ? PISA 2009 findings in Finland and Estonia," International Journal of Teaching and Education, International Institute of Social and Economic Sciences, vol. 3(2), pages 17-30, June.
• Michał Bernardelli, 2015. "Cheater detection in Real Time Bidding system – panel approach," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 39, pages 11-24.
• Luke Hartigan, 2015. "Changes in the Factor Structure of the U.S. Economy: Permanent Breaks or Business Cycle Regimes?," Discussion Papers 2015-17, School of Economics, The University of New South Wales.
• Thomas Peeters & Steven Salaga & Matthew Juravich, 2015. "Matching and Winning? The Impact of Upper and Middle Managers on Team Performance in Major League Baseball," Tinbergen Institute Discussion Papers 15-115/VII, Tinbergen Institute, revised 03 Mar 2020.
• Chang, C-L. & McAleer, M.J., 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Econometric Institute Research Papers EI2015-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Chia-Lin Chang & Michael McAleer, 2015. "Research Ideas for the Journal of Health & Medical Economics: Opinion," Documentos de Trabajo del ICAE 2015-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• McAleer, M.J., 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Econometric Institute Research Papers EI2015-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2015. "Research Ideas for the Journal of Informatics and Data Mining: Opinion," Documentos de Trabajo del ICAE 2015-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
• Ronald Miranda & Gabriela Mordecki, 2015. "Real exchange rate volatility impact on exports: A comparative study 1990-2013," Documentos de Trabajo (working papers) 15-18, Instituto de Economía - IECON.
• Chiara Elena Dalla & Menon Martina & Perali Federico, 2019. "An Integrated Database to Measure Living Standards," Journal of Official Statistics, Sciendo, vol. 35(3), pages 531-576, September.
  • Elena Dalla Chiara & Martina Menon & Federico Perali, 2015. "An Integrated Data Base to Measure Living Standards," Working Papers 28/2015, University of Verona, Department of Economics.
• Taro Takimoto & Kazuya Sakata & Kazunori Nakajima & Masaki Narukawa & Naoki Sakamoto, 2015. "Disparity in emergency medical services across Japan," ERSA conference papers ersa15p526, European Regional Science Association.
• Wenjie Wu & Jianghao Wang, 2015. "Exploring city social interaction ties in the big data era: Evidence based on location-based social media data from China," ERSA conference papers ersa15p798, European Regional Science Association.
• Crespo Cuaresma, Jesus & Grün, Bettina & Hofmarcher, Paul & Humer, Stefan & Moser, Mathias, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Paper Series 193, WU Vienna University of Economics and Business.
  • Jesus Crespo Cuaresma & Bettina Grün & Paul Hofmarcher & Stefan Humer & Mathias Moser, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Papers wuwp193, Vienna University of Economics and Business, Department of Economics.
• Jesus Crespo Cuaresma & Bettina Grün & Paul Hofmarcher & Stefan Humer & Mathias Moser, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Papers wuwp193, Vienna University of Economics and Business, Department of Economics.
  • Crespo Cuaresma, Jesus & Grün, Bettina & Hofmarcher, Paul & Humer, Stefan & Moser, Mathias, 2015. "A Comprehensive Approach to Posterior Jointness Analysis in Bayesian Model Averaging Applications," Department of Economics Working Paper Series 193, WU Vienna University of Economics and Business.
• Adam Nowak & Patrick Smith, 2015. "Textual Analysis in Real Estate," Working Papers 15-34, Department of Economics, West Virginia University.
• Köhler, Ekkehard, 2015. "Fiscal Sustainability in Cross-Dependent Panels: Evidence from the German L nder," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113104, Verein für Socialpolitik / German Economic Association.
• Damian Kozbur, 2017. "Testing-Based Forward Model Selection," American Economic Review, American Economic Association, vol. 107(5), pages 266-269, May.
  • Damian Kozbur, 2015. "Testing-Based Forward Model Selection," ECON - Working Papers 283, Department of Economics - University of Zurich, revised Apr 2018.

2014

• Anders Bredahl Kock & Haihan Tang, 2014. "Inference in High-dimensional Dynamic Panel Data Models," CREATES Research Papers 2014-58, Department of Economics and Business Economics, Aarhus University.
• Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
• David W. Nickerson & Todd Rogers, 2014. "Political Campaigns and Big Data," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 51-74, Spring.
• Ori Heffetz & Katrina Ligett, 2014. "Privacy and Data-Based Research," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 75-98, Spring.
  • Ori Heffetz & Katrina Ligett, 2013. "Privacy and Data-Based Research," NBER Working Papers 19433, National Bureau of Economic Research, Inc.
• Cooper, Joseph & Delbecq, Benoît, 2014. "A multi-region approach to assessing fiscal and farm level consequences of government support for farm risk management," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 3(3), pages 1-23, December.
  • Cooper, Joseph & Delbecq, Benoit, 2014. "A Multi-Region Approach to Assessing Fiscal and Farm Level Consequences of Government Support for Farm Risk Management," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173108, Italian Association of Agricultural and Applied Economics (AIEAA).
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Working Papers 2014.21, Fondazione Eni Enrico Mattei.
  • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Climate Change and Sustainable Development 165791, Fondazione Eni Enrico Mattei (FEEM).
  • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-Gasoline Price Relationship: Should We Care About the Rockets and the Feathers?," IEFE Working Papers 62, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
• Zekić-Sušac Marijana & Pfeifer Sanja & Šarlija Nataša, 2014. "A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem," Business Systems Research, Sciendo, vol. 5(3), pages 82-96, September.
• McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• Nathan, Max & Rosso, Anna & Bouet, Francois, 2014. "Mapping 'Information Economy' Businesses with Big Data: Findings for the UK," IZA Discussion Papers 8662, Institute of Labor Economics (IZA).
  • Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Businesses with Big Data: Findings for the UK," CEP Occasional Papers 44, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
• Mao Takongmo, Charles Olivier & Stevanovic, Dalibor, 2015. "Selection Of The Number Of Factors In Presence Of Structural Instability: A Monte Carlo Study," L'Actualité Economique, Société Canadienne de Science Economique, vol. 91(1-2), pages 177-233, Mars-Juin.
  • Dalibor Stevanovic & Charles Olivier Mao Takongmo, 2014. "Selection of the number of factors in presence of structural instability: a Monte Carlo study," CIRANO Working Papers 2014s-44, CIRANO.
• Dante Amengual & Luca Repetto, 2014. "Testing a Large Number of Hypotheses in Approximate Factor Models," Working Papers wp2014_1410, CEMFI.
• Daas, Piet J.H. & Puts, Marco J.H., 2014. "Social media sentiment and consumer confidence," Statistics Paper Series 5, European Central Bank.
• Gillen, Benjamin J., 2014. "An empirical Bayesian approach to stein-optimal covariance matrix estimation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 402-420.
• Breitung, Jörg & Eickmeier, Sandra, 2014. "Analyzing business and financial cycles using multi-level factor models," Discussion Papers 11/2014, Deutsche Bundesbank.
  • Jörg Breitung & Sandra Eickmeier, 2014. "Analyzing business and financial cycles using multi-level factor models," CAMA Working Papers 2014-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Chen, Kan & Crucini, Mario J., 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Journal of Economic Dynamics and Control, Elsevier, vol. 72(C), pages 159-168.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 217, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario Crucini, 2016. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," NBER Working Papers 22460, National Bureau of Economic Research, Inc.
  • Kan Chen & Mario Crucini, 2016. "Trends and cycles in small open economies: Making the case for a general equilibrium approach," CAMA Working Papers 2016-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Kan Chen & Mario J. Crucini, 2016. "Trends and cycles in small open economies: making the case for a general equilibrium approach," Globalization Institute Working Papers 279, Federal Reserve Bank of Dallas.
  • Kan Chen & Mario J. Crucini, 2014. "Trends and Cycles in Small Open Economies: Making The Case For A General Equilibrium Approach," CAMA Working Papers 2014-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
  • Aleksandra Halka & Grzegorz Szafrański, 2014. "What common factors are driving inflation in CEE countries?," EcoMod2014 6977, EcoMod.
  • Aleksandra Hałka & Grzegorz Szafrański, 2015. "What common factors are driving inflation in CEE countries?," NBP Working Papers 225, Narodowy Bank Polski, Economic Research Department.
• Benjamin J. Gillen & Matthew Shum & Hyungsik Roger Moon, 2014. "Demand Estimation with High-Dimensional Product Characteristics," Advances in Econometrics, in: Bayesian Model Comparison, volume 34, pages 301-323, Emerald Group Publishing Limited.
• Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
  • McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2018. "On The Sources Of Uncertainty In Exchange Rate Predictability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(1), pages 329-357, February.
  • Byrne, Joseph P & Korobilis, Dimitris & Ribeiro, Pinho J, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," MPRA Paper 58956, University Library of Munich, Germany.
  • Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," Working Papers 2014_16, Business School - Economics, University of Glasgow.
  • Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," SIRE Discussion Papers 2015-24, Scottish Institute for Research in Economics (SIRE).
• Davor Kunovac & Borna Špalat, 2014. "Nowcasting GDP Using Available Monthly Indicators," Working Papers 39, The Croatian National Bank, Croatia.
• Kausik Gangopadhyay & Abhishek Jangir & Rudra Sensarma, 2014. "Forecasting the price of gold: An error correction approach," Working papers 155, Indian Institute of Management Kozhikode.
  • Gangopadhyay, Kausik & Jangir, Abhishek & Sensarma, Rudra, 2015. "Forecasting the price of gold: An error correction approach," MPRA Paper 81066, University Library of Munich, Germany.
• Cathal O'Donoghue & Karyn Morrissey & John Lennon, 2014. "Spatial Microsimulation Modelling: a Review of Applications and Methodological Choices," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 26-75.
• Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Businesses with Big Data: Findings for the UK," CEP Occasional Papers 44, Centre for Economic Performance, LSE.
  • Nathan, Max & Rosso, Anna & Bouet, Francois, 2014. "Mapping 'Information Economy' Businesses with Big Data: Findings for the UK," IZA Discussion Papers 8662, Institute of Labor Economics (IZA).
  • Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
• Inske Pirschel & Maik Wolters, 2014. "Forecasting German Key Macroeconomic Variables Using Large Dataset Methods," Kiel Working Papers 1925, Kiel Institute for the World Economy.
• Reinhold Decker, 2014. "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, LAR Center Press, vol. 4(11), pages 60-70, November.
• Reinhold Decker, 2014. "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(11), pages 60-70, November.
• Hyndman, Rob J. & Lee, Alan J. & Wang, Earo, 2016. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 16-32.
  • Rob J Hyndman & Alan Lee & Earo Wang, 2014. "Fast computation of reconciled forecasts for hierarchical and grouped time series," Monash Econometrics and Business Statistics Working Papers 17/14, Monash University, Department of Econometrics and Business Statistics.
• Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
  • Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Business with Big Data: Findings from the UK," National Institute of Economic and Social Research (NIESR) Discussion Papers 442, National Institute of Economic and Social Research.
• Popovici Alexandru, 2014. "Philosophy of the Multilevel Reality. Applications in Economics (I) [Filozofia realitǎţii multinivel. Aplicaţii în economie (I)]," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 03, September.
• Popovici Alexandru, 2014. "Philosophy of the Multilevel Reality. Applications in Economics (II) [Filozofia realitǎţii multinivel. Aplicaţii în economie (II)]," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 04, December.
• Cezary A. Kapuscinski & Kyle Thomson, 2014. "Experiment Estimates of Indigenous Employment from Administrative Data," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 17(2), pages 139-161.
• Estrada, Fernando, 2014. "El capital en el siglo XXI de Thomas Piketty [Thomas Piketty’s Capital in the 21st century]," MPRA Paper 60662, University Library of Munich, Germany.
• Gerunov, Anton, 2014. "Big Data Approaches to Modeling the Labor Market," MPRA Paper 68798, University Library of Munich, Germany.
• Carbajal De Nova, Carolina, 2014. "Synthetic data: an endogeneity simulation," MPRA Paper 79158, University Library of Munich, Germany, revised 11 May 2017.
  • Carbajal De Nova, Carolina, 2014. "Synthetic data: an endogeneity simulation," MPRA Paper 79067, University Library of Munich, Germany, revised 10 May 2017.
• Ramadas, Sendhil & Palanisamy, Ramasundaram & Kuruvila, Anil & Chandrasekaran, Sundaramoorthy & Singh, Randhir & Sharma, Indu, 2014. "Food Price Volatility in India – Drivers, Impact and Policy Response," MPRA Paper 91131, University Library of Munich, Germany.
• Michael Toedt, 2014. "The Development of a Response-Function for Customer Relationship Marketing," Proceedings of International Academic Conferences 0100789, International Institute of Social and Economic Sciences.
• Mehmet Fedai KAYA & Muslu Kaz?m KÖREZ & Süleyman DÜNDAR, 2014. "Estimation of the Distribution of Remaning Life Time of the People in Turkey," Proceedings of International Academic Conferences 0201556, International Institute of Social and Economic Sciences.
• Duo Qin & Sophie van H¸llen & Qing-Chao Wang, 2014. "What Happens to Wage Elasticities When We Strip Playometrics? Revisiting Married Women Labour Supply Model," Working Papers 190, Department of Economics, SOAS University of London, UK.
• Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
  • McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• Matthias Weber & Martin Schumacher & Harald Binder, 2014. "Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs," Tinbergen Institute Discussion Papers 14-089/I, Tinbergen Institute.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
• Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Documentos de Trabajo del ICAE 2014-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • McAleer, M.J., 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Econometric Institute Research Papers EI 2014-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Working Papers in Economics 14/09, University of Canterbury, Department of Economics and Finance.
• Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Tinbergen Institute Discussion Papers 14-153/III, Tinbergen Institute.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Documentos de Trabajo del ICAE 2014-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
• Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
  • Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
• Jörg Breitung & Sandra Eickmeier, 2014. "Analyzing business and financial cycles using multi-level factor models," CAMA Working Papers 2014-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Breitung, Jörg & Eickmeier, Sandra, 2014. "Analyzing business and financial cycles using multi-level factor models," Discussion Papers 11/2014, Deutsche Bundesbank.
• Pirschel, Inske & Wolters, Maik, 2014. "Forecasting German key macroeconomic variables using large dataset methods," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100587, Verein für Socialpolitik / German Economic Association.
  • Pirschel, Inske & Wolters, Maik H., 2014. "Forecasting German key macroeconomic variables using large dataset methods," Kiel Working Papers 1925, Kiel Institute for the World Economy (IfW Kiel).

2013

• Mota, Rui Pedro & Domingos, Tiago, 2013. "Assessment of the theory of comprehensive national accounting with data for Portugal," Ecological Economics, Elsevier, vol. 95(C), pages 188-196.
• Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
  • Boivin, Jean & Giannoni, Marc & Stevanovic, Dalibor, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CEPR Discussion Papers 9470, C.E.P.R. Discussion Papers.
  • Jean Boivin & Marc Giannoni & Dalibor Stevanovic, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2016. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2016s-55, CIRANO.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," CIRANO Working Papers 2013s-11, CIRANO.
  • Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Cahiers de recherche 1324, CIRPEE.
• Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
  • Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Anna Gloria Billé, 2013. "Computational Issues in the Estimation of the Spatial Probit Model: A Comparison of Various Estimators," The Review of Regional Studies, Southern Regional Science Association, vol. 43(2,3), pages 131-154, Winter.

2012

• Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & Elisabet E. Rutstroem & Vjollca Sadiraj, 2011. "Asset Integration and Attitudes to Risk: Theory and Evidence," Working Papers 2011_10, Department of Economics, University of Durham.
  • Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & E. Elisabet Rutström & Vjollca Sad