Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2019

• Audrone Virbickaite & Christoph Frey & Demian N. Macedo, 2019, "Sequential Stock Return Prediction Through Copulas," DEA Working Papers, Universitat de les Illes Balears, Departament d'Economía Aplicada, number 91.
• Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019, "Prediction Regions for Interval-valued Time Series," Working Papers, University of California at Riverside, Department of Economics, number 201921, Sep.
• Eva Boj & M. Mercè Claramunt & Anna Castañer & Teresa Costa & Oriol Roch, 2019, "Economic Indicators for automobile claim frequencies," Estudios de Economia, University of Chile, Department of Economics, volume 46, issue 2, pages 245-271, December.
• Dmytro Krukovets & Olesia Verchenko, 2019, "Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 248, pages 11-20, DOI: 10.26531/vnbu2019.248.02.
• Anton Grui & Artem Vdovychenko, 2019, "Quarterly Projection Model for Ukraine," Working Papers, National Bank of Ukraine, number 03/2019, Sep.
• Mohammad Ghaderi & Milosz Kadzinsky, 2019, "Accounting for structural patterns in construction of value functions: a convex optimization approach," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1634, Jan.
• Yiru Wang & Barbara Rossi, 2019, "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1642, Jan.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019, "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1689, Dec.
• Do Van Thanh, 2019, "Macro-Econometric Model For Medium-Term Socio-Economic Development Planning In Vietnam. Part 1: Structure Of The Model," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, volume 1, issue 1, pages 121-136.
• Valery Zh. Dubrovsky & Ekaterina M. Ivanova & Natalia V. Chuprakova, 2019, "Problems of assessing defence contractors’ efficiency," Journal of New Economy, Ural State University of Economics, volume 20, issue 5, pages 92-107, December, DOI: 10.29141/2073-1019-2019-20-5-6.
• Roland Füss & Massimo Guidolin & Christian Koeppel, 2019, "Sentiment Risk Premia In The Cross-Section of Global Equity," Working Papers on Finance, University of St. Gallen, School of Finance, number 1913, Aug, revised May 2020.
• Marco Corazza & Giovanni Fasano & Riccardo Gusso & Raffaele Pesenti, 2019, "A comparison among Reinforcement Learning algorithms in financial trading systems," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2019:33.
• Mariana Kaneva, 2019, "Broadband and e-Commerce in the Balkans - Econometric Analysis," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, volume 8, issue 2, pages 100-109, August, DOI: 10.36997/IJUSV-ESS/2019.8.2.100.
• Szubzda Filip & Chlebus Marcin, 2019, "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, volume 6, issue 53, pages 70-85, January, DOI: 10.2478/ceej-2019-0005.
• Szubzda Filip & Chlebus Marcin, 2019, "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, volume 6, issue 53, pages 70-85, January, DOI: 10.2478/ceej-2019-0005.
• Čižmešija Mirjana & Lukač Zrinka & Novoselec Tomislav, 2019, "Nonlinear optimisation approach to proposing novel Croatian Industrial Confidence Indicator," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 5, issue 2, pages 17-26, December, DOI: 10.2478/crebss-2019-0008.
• Kvainickas Tomas Sovijus & Stankevičienė Jelena, 2019, "Regional Limitations of Stock Indices Prediction Models Based on Macroeconomic Variables," Economics and Culture, Sciendo, volume 16, issue 2, pages 5-20, December, DOI: 10.2478/jec-2019-0018.
• Pelinescu Elena & Simionescu Mihaela, 2019, "Higher Education Policies and Employability of University Graduates in the EU-28," Journal of Intercultural Management, Sciendo, volume 11, issue 3, pages 105-133, September, DOI: 10.2478/joim-2019-0020.
• Bălan Mariana, 2019, "Particularities of the Recent Evolution of Higher Education in Romania. Analysis and Forecasts," Journal of Intercultural Management, Sciendo, volume 11, issue 3, pages 87-104, September, DOI: 10.2478/joim-2019-0019.
• Simionescu Mihaela & Naroș Maria-Simona, 2019, "The Unemployment of Highly Educated People in Romania. A Panel VAR Approach," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, volume 29, issue 3, pages 20-37, September, DOI: 10.2478/sues-2019-0010.
• Mateusz Buczyński & Marcin Chlebus, 2019, "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2019-12.
• Michael W. McCracken & Joseph T. McGillicuddy, 2019, "An empirical investigation of direct and iterated multistep conditional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 2, pages 181-204, March, DOI: 10.1002/jae.2668.
• Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019, "Real‐time forecast combinations for the oil price," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 3, pages 456-462, April, DOI: 10.1002/jae.2673.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019, "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 7, pages 1027-1049, November, DOI: 10.1002/jae.2722.
• Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019, "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 7, pages 1073-1085, November, DOI: 10.1002/jae.2729.
• Philip Hans Franses, 2019, "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., volume 38, issue 2, pages 73-80, March, DOI: 10.1002/for.2557.
• Libero Monteforte & Valentina Raponi, 2019, "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 38, issue 3, pages 207-221, April, DOI: 10.1002/for.2565.
• João H. Gonçalves Mazzeu & Helena Veiga & Massimo B. Mariti, 2019, "Modeling and forecasting the oil volatility index," Journal of Forecasting, John Wiley & Sons, Ltd., volume 38, issue 8, pages 773-787, December, DOI: 10.1002/for.2598.
• Willy Alanya & Gabriel Rodríguez, 2019, "Asymmetries in Volatility: An Empirical Study for the Peruvian Stock and Forex Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., volume 22, issue 01, pages 1-18, March, DOI: 10.1142/S0219091519500036.
• Katarzyna Maciejowska & Rafal Weron, 2019, "Electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/01, Feb.
• Bartosz Uniejewski & Rafal Weron, 2019, "Regularized Quantile Regression Averaging for probabilistic electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/04, Nov.
• Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemyslaw Zaleski & Rafal Weron, 2019, "Balancing RES generation: Profitability of an energy trader," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/07, Dec.
• Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019, "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/08, Dec.
• Li Chen & Jiti Gao & Farshid Vahid, 2019, "Global temperatures and greenhouse gases - a common features approach," Working Papers, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, number 2019-07-15, Jul.
• Alberto Caruso & Laura Coroneo, 2019, "Predicting interest rates in real-time," Discussion Papers, Department of Economics, University of York, number 19/18, Nov.
• Makarewicz, Tomasz, 2019, "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series, Bamberg University, Bamberg Economic Research Group, number 141.
• Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019, "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series, Bamberg University, Bamberg Economic Research Group, number 147.
• Stanisławska, Ewa & Paloviita, Maritta & Łyziak, Tomasz, 2019, "Assessing reliability of aggregated inflation views in the European Commission consumer survey," Bank of Finland Research Discussion Papers, Bank of Finland, number 10/2019.
• Knüppel, Malte & Krüger, Fabian, 2019, "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers, Deutsche Bundesbank, number 28/2019.
• Eraslan, Sercan & Schröder, Maximilian, 2019, "Nowcasting GDP with a large factor model space," Discussion Papers, Deutsche Bundesbank, number 41/2019.
• Jackson, Emerson Abraham & Tamuke, Edmund, 2019, "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 202547.
• Strohsal, Till & Wolf, Elias, 2019, "Data revisions to German national accounts: Are initial releases good nowcasts?," Discussion Papers, Free University Berlin, School of Business & Economics, number 2019/11.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019, "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers, Kiel Institute for the World Economy, number 2019-16.
• Bolgorian, Meysam, 2019, "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers, Kiel Institute for the World Economy, number 2019-2.
• Thompson, Erica L. & Smith, Leonard A., 2019, "Escape from model-land," Economics Discussion Papers, Kiel Institute for the World Economy, number 2019-23.
• Brighton, Henry, 2019, "Beyond quantified ignorance: Rebuilding rationality without the bias bias," Economics Discussion Papers, Kiel Institute for the World Economy, number 2019-25.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019, "Metcalfe's law and log-period power laws in the cryptocurrencies market," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, volume 13, pages 1-26, DOI: 10.5018/economics-ejournal.ja.2019-.
• Thompson, Erica L. & Smith, Leonard A., 2019, "Escape from model-land," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, volume 13, pages 1-17, DOI: 10.5018/economics-ejournal.ja.2019-.
• Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019, "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-003.
• Kostmann, Michael & Härdle, Wolfgang Karl, 2019, "Forecasting in Blockchain-based Local Energy Markets," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-014.
• Pele, Daniel Traian & Wesselhöfft, Niels & Härdle, Wolfgang Karl & Kolossiatis, Michalis & Yatracos, Yannis, 2019, "Phenotypic convergence of cryptocurrencies," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-018.
• Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019, "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-024.
• Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019, "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-027.
• Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019, "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 18/2019.
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019, "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 2/2019.
• Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019, "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 24/2019.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Schult, Christoph & Wieschemeyer, Matthias & Zeddies, Götz, 2019, "Sinkendes Potenzialwachstum in Deutschland, beschleunigter Braunkohleausstieg und Klimapaket: Finanzpolitische Konsequenzen für die Jahre bis 2024," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 7, issue 4, pages 109-120.
• Conrad, Christian & Schienle, Melanie, 2019, "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 121, DOI: 10.5445/IR/1000090371.
• Bormann, Carsten & Schienle, Melanie, 2019, "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 122, DOI: 10.5445/IR/1000092468.
• Behrens, Christoph, 2019, "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 9, DOI: 10.18452/19832.
• Belke, Ansgar & Klose, Jens, 2019, "Forecasting ECB policy rates with different monetary policy rules," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 815, DOI: 10.4419/86788944.
• Döhrn, Roland, 2019, "Comparing forecast accuracy in small samples," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 833, DOI: 10.4419/86788966.
• Hinterlang, Natascha, 2019, "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy, Verein für Socialpolitik / German Economic Association, number 203503.
• Axenbeck, Janna & Breithaupt, Patrick, 2019, "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 19-063.
• Oliver Merz & Raphael Flepp & Egon Franck, 2020, "Sonic Thunder vs. Brian the Snail : Are people affected by uninformative racehorse names?," Working Papers, University of Zurich, Department of Business Administration (IBW), number 384, Nov.
• 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, volume 23, issue 3, pages 56-92, September.
• Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019, "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-04, Mar.
• Søren Kjærgaard & Yunus Emre Ergemen & Malene Kallestrup-Lamb & Jim Oeppen & Rune Lindahl-Jacobsen, 2019, "Forecasting Causes of Death using Compositional Data Analysis: the Case of Cancer Deaths," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-07, May.
• Søren Kjærgaard & Yunus Emre Ergemen & Marie-Pier Bergeron Boucher & Jim Oeppen & Malene Kallestrup-Lamb, 2019, "Longevity forecasting by socio-economic groups using compositional data analysis," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-08, May.
• Daniel Borup & Erik Christian Montes Schütte, 2019, "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-13, Aug.
• Kristoffer Pons Bertelsen, 2019, "Comparing Tests for Identification of Bubbles," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-16, Oct.
• Malene Kallestrup-Lamb & Søren Kjærgaard & Carsten P. T. Rosenskjold, 2019, "Insight into Stagnating Life Expectancy: Analysing Cause of Death Patterns across Socio-economic Groups," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-20, Nov.
• Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019, "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-21, Nov.
• Andrzej JARYNOWSKI, 2019, "Cost-Effectiveness Analysis For Hpv Mitigation Strategies In The Republic Of Moldova Based On Infectious Disease Modelling," Economy and Sociology, The Journal Economy and Sociology, issue 2, pages 50-64.
• Simplice A. Asongu & Joseph Nnanna, 2019, "Foreign aid, instability and governance in Africa," Research Africa Network Working Papers, Research Africa Network (RAN), number 19/022, Jan.
• Hyeongwoo Kim & Kyunghwan Ko, 2019, "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2019-03, Apr.
• Sarthak Behera & Hyeongwoo Kim, 2019, "Forecasting Dollar Real Exchange Rates and the Role of Real Activity Factors," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2019-04, Oct.
• Simplice A. Asongu & Joseph Nnanna, 2019, "Foreign aid, instability and governance in Africa," CEREDEC Working Papers, Centre de Recherche pour le Développement Economique (CEREDEC), number 19/022, Jan.
• T. Bazhenov & D. Fantazzini, 2019, "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISIS, volume 12, issue 1, DOI: 10.17073/2072-1633-2019-1-79-88.
• Ali Babikir & Mohammed Elamin Hassan & Henry Mwambi, 2019, "Asymmetry, Fat-tail and Autoregressive Conditional Density in Daily Stocks Return Data," Annals of Economics and Statistics, GENES, issue 135, pages 57-68, DOI: 10.15609/annaeconstat2009.135.0057.
• Lukas Kremens & Ian Martin, 2019, "The Quanto Theory of Exchange Rates," American Economic Review, American Economic Association, volume 109, issue 3, pages 810-843, March.
• Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019, "Vulnerable Growth," American Economic Review, American Economic Association, volume 109, issue 4, pages 1263-1289, April.
• Daniel J. Wilson, 2019, "Clearing the Fog: The Predictive Power of Weather for Employment Reports and Their Asset Price Responses," American Economic Review: Insights, American Economic Association, volume 1, issue 3, pages 373-388, December.
• 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, volume 109, pages 33-37, May.
• Cristiana Chiriac & Laura Daniela RoÈ™ca, 2019, "Automotive Industry Video-Commercials – A Pluralistic Research Based on an Eye-Tracking Experiment," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, volume 1, issue 1, pages 327-336, November.
• Simplice A. Asongu & Joseph Nnanna, 2019, "Foreign aid, instability and governance in Africa," Working Papers of the African Governance and Development Institute., African Governance and Development Institute., number 19/022, Jan.
• Tomasz Serafin & Bartosz Uniejewski & Rafal Weron, 2019, "Averaging predictive distributions across calibration windows for day-ahead electricity price forecasting," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/19/08, Jun, revised 06 Jul 2019.
• Nuno Goncalves & Domingos Seward, 2019, "Forecasting unemployment in Portugal: A labour market flows approach," CFP Working Papers, Portuguese Public Finance Council, number 01/2019, Nov.
• Chermat Tahar & Bouaichaoui Youcef, 2019, "A Predictive Study of Electricity Consumption Fluctuations Using the Autoregressive-Moving-Average Models: Wilaya of Medea as a Case Study (2011-2017)," Management & Economics Research Journal, Faculty of Economics, Commercial and Management Sciences, Ziane Achour University of Djelfa, volume 1, issue 1, pages 190-211, March, DOI: 10.48100/merj.v1i1.23.
• Anindya Banerjee & Victor Bystrov & Paul Mizen, 2019, "Structural Factor Analysis of Interest Rate Pass Through in Four Large Euro Area Economies," Lodz Economics Working Papers, University of Lodz, Faculty of Economics and Sociology, number 1/2019, May.
• 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 forecasting system of the NBK," 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 factor model for estimating and forecasting GDP o," Working Papers, National Bank of Kazakhstan, number #2019-4.
• Adolfo Rodríguez-Vargas, 2019, "Univariate Forecasts for Costa Rican Inflation With Stochastic Volatility and GARCH Effects," Documentos de Trabajo, Banco Central de Costa Rica, number 1604, Jul.
• Alonso Alfaro-Ureña & Aarón Mora-Meléndez, 2019, "The Information Rigidities and Rationality of Costa Rican Inflation Expectations," Documentos de Trabajo, Banco Central de Costa Rica, number 1705, Jul.
• Douglas Laxton & Asya Kostanyan & Akaki Liqokeli & Gevorg Minasyan & Tamta Sopromadze & Armen Nurbekyan, 2019, "Mind the Gaps! Financial-Cycle Output Gaps and Monetary-Policy-Relevant Output Gaps," Working Papers, Central Bank of Armenia, number 19, Dec.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019, "lassopack: Model selection and prediction with regularized regression in Stata," Papers, arXiv.org, number 1901.05397, Jan.
• Matteo Mogliani & Anna Simoni, 2019, "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers, arXiv.org, number 1903.08025, Mar, revised Jun 2020.
• Ali Habibnia & Esfandiar Maasoumi, 2019, "Forecasting in Big Data Environments: an Adaptable and Automated Shrinkage Estimation of Neural Networks (AAShNet)," Papers, arXiv.org, number 1904.11145, Apr.
• Jozef Barunik & Pavel Fiser, 2019, "Co-jumping of Treasury Yield Curve Rates," Papers, arXiv.org, number 1905.01541, May.
• Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019, "Testing Forecast Rationality for Measures of Central Tendency," Papers, arXiv.org, number 1910.12545, Oct, revised Jul 2024.
• Alain Hecq & Elisa Voisin, 2019, "Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models," Papers, arXiv.org, number 1911.10916, Nov, revised May 2022.
• Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019, "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," Papers, arXiv.org, number 1912.05228, Dec, revised Dec 2021.
• Francis X. Diebold & Glenn D. Rudebusch, 2019, "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers, arXiv.org, number 1912.10774, Dec, revised Jul 2021.
• Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2019, "Focused Bayesian Prediction," Papers, arXiv.org, number 1912.12571, Dec, revised Aug 2020.
• Roland Fuess & Massimo Guidolin & Christian Koeppel, 2019, "Sentiment Risk Premia in the Cross-Section of Global Equity and Currency Returns," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 19116.
• Ekaterina Tzvetanova, 2019, "Adaptation of the Altman’s Corporate Insolvency Prediction Model – The Bulgarian Case," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 125-142.
• Hartl, Tobias & Weigand, Roland, 2019, "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems, University of Regensburg, Department of Economics, number 38283.
• Dany Brouillette & Marie-Noëlle Robitaille & Laurence Savoie-Chabot & Pierre St-Amant & Bassirou Gueye & Elise Martin, 2019, "The Trend Unemployment Rate in Canada: Searching for the Unobservable," Staff Working Papers, Bank of Canada, number 19-13, Mar, DOI: 10.34989/swp-2019-13.
• Gergely Ganics & Eva Ortega, 2019, "Las previsiones macroeconómicas del Banco de España a la luz de un modelo econométrico," Boletín Económico, Banco de España, issue SEP.
• Gergely Ganics & Eva Ortega, 2019, "Banco de España macroeconomic projections: comparison with an econometric model," Economic Bulletin, Banco de España, issue SEP.
• Luis Julián Álvarez, 2019, "El índice de precios de consumo: usos y posibles vías de mejora," Occasional Papers, Banco de España, number 1910, May.
• Mar Delgado-Téllez & Enrique Moral-Benito & Javier J. Pérez, 2019, "Outsourcing and public expenditure: an aggregate perspective with regional data," Working Papers, Banco de España, number 1939, Nov.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019, "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers, Banco de España, number 1947, Dec.
• Gergely Ganics & Florens Odendahl, 2019, "Bayesian VAR forecasts, survey information and structural change in the euro area," Working Papers, Banco de España, number 1948, Dec.
• Franecsca Carta, 2019, "Timely indicators for labour income inequality," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 503, Jul.
• Angela Capolongo & Claudia Pacella, 2019, "Forecasting inflation in the euro area: countries matter!," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1224, Jun.
• Fabio Busetti & Michele Caivano & Davide Delle Monache, 2019, "Domestic and global determinants of inflation: evidence from expectile regression," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1225, Jun.
• Valentina Aprigliano & Danilo Liberati, 2019, "Using credit variables to date business cycle and to estimate the probabilities of recession in real time," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1229, Jul.
• Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019, "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia, Banco de la Republica de Colombia, number 1073, May, DOI: 10.32468/be.1073.
• María Fernanda Meneses-González & Javier Eliecer Pirateque-Niño & Santiago David Segovia-Baquero, 2019, "Indicadores de alerta temprana para el sector corporativo privado colombiano," Borradores de Economia, Banco de la Republica de Colombia, number 1084, Jul, DOI: 10.32468/be.1084.
• Carlos León, 2019, "Detecting anomalous payments networks: A dimensionality reduction approach," Borradores de Economia, Banco de la Republica de Colombia, number 1098, Dec, DOI: https://doi.org/10.32468/be.1098.
• Matteo Mogliani, 2019, "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers, Banque de France, number 713.
• Laurent Ferrara & Anna Simoni, 2019, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working papers, Banque de France, number 717.
• Gergely Ganics & Florens Odendahl, 2019, "Bayesian VAR Forecasts, Survey Information and Structural Change in the Euro Area," Working papers, Banque de France, number 733.
• Yiru Wang & Barbara Rossi, 2019, "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers, Barcelona School of Economics, number 1083, Apr.
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019, "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, Bank for International Settlements, in: Bank for International Settlements, "The use of big data analytics and artificial intelligence in central banking".
• María Gil & Javier J. Pérez & Alberto Urtasun, 2019, "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, Bank for International Settlements, in: Bank for International Settlements, "The use of big data analytics and artificial intelligence in central banking".
• Burcu Erik & Marco Jacopo Lombardi & Dubravko Mihaljek & Hyun Song Shin, 2019, "Financial conditions and purchasing managers' indices: exploring the links," BIS Quarterly Review, Bank for International Settlements, September.
• Michael Brei & Claudio Borio, 2019, "Bank intermediation activity in a low interest rate environment," BIS Working Papers, Bank for International Settlements, number 807, Aug.
• Heiner Mikosch & Laura Solanko, 2019, "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, volume 78, issue 1, pages 19-35, March, DOI: 10.31477/rjmf.201901.19.
• Konstantin Styrin, 2019, "Forecasting Inflation in Russia Using Dynamic Model Averaging," Russian Journal of Money and Finance, Bank of Russia, volume 78, issue 1, pages 3-18, March, DOI: 10.31477/rjmf.201901.03.
• 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, volume 78, issue 2, pages 67-93, June, DOI: 10.31477/rjmf.201901.67.
• Denis Shibitov & Mariam Mamedli, 2019, "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series, Bank of Russia, number wps43, Aug.
• Sergei Seleznev, 2019, "Truncated priors for tempered hierarchical Dirichlet process vector autoregression," Bank of Russia Working Paper Series, Bank of Russia, number wps47, Oct.
• Ramis Khabibullin, 2019, "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series, Bank of Russia, number wps50, Oct.
• 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, volume 20, issue 4, pages 170-200, November, DOI: 10.1111/geer.12163.
• 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, volume 81, issue 2, pages 456-485, April, DOI: 10.1111/obes.12277.
• André K. Anundsen, 2019, "Detecting Imbalances in House Prices: What Goes Up Must Come Down?," Scandinavian Journal of Economics, Wiley Blackwell, volume 121, issue 4, pages 1587-1619, October, DOI: 10.1111/sjoe.12349.
• Stavros Degiannakis & George Filis, 2019, "Forecasting European economic policy uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, volume 66, issue 1, pages 94-114, February, DOI: 10.1111/sjpe.12174.
• Laurent Ferrara & Clément Marsilli, 2019, "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, volume 42, issue 3, pages 846-875, March, DOI: 10.1111/twec.12708.
• Juan Carlos Carlo Santos, 2019, "Pronósticos del PIB mediante modelos de factores dinámicos," Revista de Análisis del BCB, Banco Central de Bolivia, volume 30, issue 1, pages 125-174, January -.
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• Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019, "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper, Norges Bank, number 2019/12, Aug.
• Joel Suss & Henry Treitel, 2019, "Predicting bank distress in the UK with machine learning," Bank of England working papers, Bank of England, number 831, Oct.
• Jonathan Benchimol & Lahcen Bounader, 2019, "Optimal Monetary Policy under Bounded Rationality," Bank of Israel Working Papers, Bank of Israel, number 2019.07, Jul.
• Jonathan Benchimol & Makram El-Shagi, 2019, "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers, Bank of Israel, number 2019.08, Jul.
• Bruno Deschamps & Christos Ioannidis & Kook Ka, 2019, "High-Frequency Credit Spread Information and Macroeconomic Forecast Revision," Working Papers, Economic Research Institute, Bank of Korea, number 2019-17, May.
• Rahul Roy & Santhakumar Shijin, 2019, "The nexus of anomalies-stock returns-asset pricing models: The international evidence," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, volume 19, issue 1, pages 1-14, March.
• Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Peck, 2019, "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series, Boston University - Department of Economics, number dp-328, Feb.
• Fugazza Carolina, 2019, "Anatomy of Non-Employment Risk," The B.E. Journal of Economic Analysis & Policy, De Gruyter, volume 19, issue 3, pages 1-19, July, DOI: 10.1515/bejeap-2018-0070.
• 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, volume 20, issue 4, pages 170-200, December, DOI: 10.1111/geer.12163.
• Bruttel Oliver & Baumann Arne & Dütsch Matthias, 2019, "Beschäftigungseffekte des gesetzlichen Mindestlohns: Prognosen und empirische Befunde," Perspektiven der Wirtschaftspolitik, De Gruyter, volume 20, issue 3, pages 237-253, September, DOI: 10.1515/pwp-2018-0035.
• Olimpia NEAGU, 2019, "Digital Divide Gap Convergence Across European Union: The Role Of Urbanisation," Contemporary Economy Journal, Constantin Brancoveanu University, volume 4, issue 1, pages 43-48.
• Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019, "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS59, Feb.
• Ahmed, M. F. & Satchell, S, 2019, "Some Dynamic and Steady-State Properties of Threshold Autoregressions with Applications to Stationarity and Local Explosivity," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1923, Mar.
• Han, Y. & Li, V. & Lam, J. & Pollitt, M., 2019, "How BLUE is the Sky? Estimating the Air Quality Data in Beijing During the Blue Sky Day Period (2008-2012) by the Bayesian LSTM Approach," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1929, Mar.
• Miroslav Klucik, 2019, "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers, Council for Budget Responsibility, number Working Paper No. 1/2019, Jan.
• de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019, "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers, Central Bank of Ireland, number 15/RT/19, Dec.
• Congressional Budget Office, 2019, "An Evaluation of CBO’s Past Deficit and Debt Projections," Reports, Congressional Budget Office, number 55234, Sep.
• Congressional Budget Office, 2019, "CBO’s Economic Forecasting Record: 2019 Update," Reports, Congressional Budget Office, number 55505, Oct.
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• Hylke Vandenbussche & William Connell & Wouter Simons, 2019, "Global Value Chains, Trade Shocks and Jobs: An Application to Brexit," CESifo Working Paper Series, CESifo, number 7473.
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• Paul Schneider, 2019, "A Theory of Scenario Generation," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-17, Mar.
• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019, "A Flexible Regime Switching Model for Asset Returns," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-27, May, revised May 2019.
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• Marc S. Paolella & Pawel Polak & Patrick S. Walker, 2019, "A Non-Elliptical Orthogonal GARCH Model for Portfolio Selection under Transaction Costs," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-51, Sep.
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• Mateo Dulce Rubio, 2019, "Predicting criminal behavior with L√©vy flights using real data from Bogot√°," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 17198, Feb.
• Alfredo Trespalacios & Lina M. Cort�s & Javier Perote, 2019, "Uncertainty in Electricity Markets from a seminonparametric Approach," Documentos de Trabajo de Valor Público, Universidad EAFIT, number 17304, Jun.
• Luis Sánchez & Karina Caballero, 2019, "La curva de Kuznets ambiental y su relación con el cambio climático en América Latina y el Caribe: un análisis de cointegración con panel, 1980-2015," Revista de Economía del Rosario, Universidad del Rosario, volume 22, issue 1, pages 101-142.
• Juan Pablo Alfonso Zorro, 2019, "Efectos de las variaciones del IPC en las decisiones financieras," Econógrafos, Escuela de Economía, Universidad Nacional de Colombia, FCE, CID, number 17329, Jul.
• Jorge Iván Pérez García & Mauricio Lopera Casta�o & Fredy Alonso V�squez Bedoya, 2019, "Una breve aplicación a la predicción de la fragilidad de empresas colombianas, mediante el uso de modelos estadísticos," Borradores Departamento de Economía, Universidad de Antioquia, CIE, number 17525, Sep.
• José Manuel Leguizamón Tiusabá, 2019, "Estímulos tributarios y hotelería en Colombia," Revista Economía y Región, Universidad Tecnológica de Bolívar, volume 13, issue 1, pages 177-198.
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• Blattman, Christopher & Dube, Oeindrila & Bazzi, Samuel & Gudgeon, Matthew & Peck, Richard & Blair, Robert, 2019, "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13829, Jun.
• Gambacorta, Leonardo & Brei, Michael & Borio, Claudio, 2019, "Bank intermediation activity in a low interest rate environment," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13980, Sep.
• Petrella, Ivan & Delle Monache, Davide & Venditti, Fabrizio, 2019, "Price Dividend Ratio and Long-Run Stock Returns: a Score Driven State Space Model," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14107, Nov.
• Mawuli Segnon & Stelios Bekiros, 2019, "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 7919, Mar.
• Laurent Ferrara & Anna Simoni, 2019, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers, Center for Research in Economics and Statistics, number 2019-04, Feb.
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