Research classified by Journal of Economic Literature (JEL) codes

1. Nowcasting
2. Bayesian Vector autoregressions (BVARs)
3. Dynamic Factor Models

2022

• Urga, Giovanni & Wang, Fa, 2022, "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper, University Library of Munich, Germany, number 113172, May.
• Mputu Losala Lomo, Denis-Robert, 2022, "Application de la Classification Ascendante Hiérarchique à la Répartition des Ressources Budgétaires dans la Ville-Province de Kinshasa
  [Application of Hierarchical Ascendant Clustering to the Distribution of Budgetary Ressources in the City-Provi," MPRA Paper, University Library of Munich, Germany, number 113774.
• Urga, Giovanni & Wang, Fa, 2022, "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper, University Library of Munich, Germany, number 117012, May, revised 10 Apr 2023.
• Fantazzini, Dean & Kurbatskii, Alexey & Mironenkov, Alexey & Lycheva, Maria, 2022, "Forecasting oil prices with penalized regressions, variance risk premia and Google data," MPRA Paper, University Library of Munich, Germany, number 118239.
• António Rua & Nuno Lourenço, 2022, "Business cycle clocks: Time to get circular," Working Papers, Banco de Portugal, Economics and Research Department, number w202201.
• Hugo Reis & Paulo M.M. Rodrigues & Filipe B. Caires, 2022, "Survival of the fittest: Tourism Exposure and Firm Survival," Working Papers, Banco de Portugal, Economics and Research Department, number w202206.
• James G. MacKinnon, 2022, "Using Large Samples in Econometrics," Working Paper, Economics Department, Queen's University, number 1482, Feb.
• Byron Botha & Rulof Burger & Kevin Kotz & Neil Rankin & Daan Steenkamp, 2022, "Big data forecasting of South African inflation," Working Papers, South African Reserve Bank, number 11022, Feb.
• Kamalbek Karymshakov & Dina Azhgaliyeva & Ranjeeta Mishra & Dastan Aseinov, 2022, "Evaluating COVID-19’s Impact on Firm Performance in the CAREC Region Using Night-Time Light Data: Azerbaijan, Georgia, Kazakhstan, and Mongolia," ADBI Working Papers, Asian Development Bank Institute, number 1332, Jul.
• Andrei Zubarev & Maria Kirillova, 2022, "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 65, pages 117-138.
• Maria Lycheva & Alexey Mironenkov & Alexey Kurbatskii & Dean Fantazzini, 2022, "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 68, pages 28-49.
• Emily Ocasio & Tristan Potter, 2023, "Demographic Correlates of Humanizing Language in Media Coverage of Crime: Evidence from the Boston Globe, 1976-84," School of Economics Working Paper Series, LeBow College of Business, Drexel University, number 2023-1, Jan.
• Marianna Brunetti & Roberta De Luca, 2022, "Sensitivity of Profitability in Cointegration-Based Pairs Trading," CEIS Research Paper, Tor Vergata University, CEIS, number 540, Apr, revised 11 Apr 2022.
• Riccardo Di Francesco, 2022, "Aggregation Trees," CEIS Research Paper, Tor Vergata University, CEIS, number 546, Dec, revised 20 Nov 2023.
• Eduard van der Merwe & Eleni Yitbarek & Matthew W. Clance, 2022, "Climate change and child health: A Nigerian perspective," ERSA Working Paper Series, Economic Research Southern Africa, number 871, Jan.
• Byron Botha & Kevin Kotze & Neil Rankin & Rulof P. Burger, 2022, "Big data forecasting of South African inflation," ERSA Working Paper Series, Economic Research Southern Africa, number 873, Feb.
• 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, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, number bep-2022-04, Jun, revised Jun 2022.
• 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 Sao Paulo, Brazil," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2022_10, Mar.
• Jose Antonio Leon & Mario Ordaz & Eduardo A Haddad & Inacio F. Araujo, 2022, "Riesgo Causado por la Propagacion de las Perdidas por Terremoto a traves de la Economia Mediante el uso de Modelos CGE Espaciales," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2022_11, Mar.
• 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, volume 68, issue 2, pages 501-525, April, DOI: 10.1007/s00168-021-01085-8.
• 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, volume 6, issue 1, pages 1-44, February, DOI: 10.1007/s41685-021-00213-8.
• 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, volume 6, issue 3, pages 1111-1132, October, DOI: 10.1007/s41685-022-00254-7.
• Helmut Wasserbacher & Martin Spindler, 2022, "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, volume 4, issue 1, pages 63-88, March, DOI: 10.1007/s42521-021-00046-2.
• 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, volume 32, issue 3, pages 1279-1292, September, DOI: 10.1007/s12525-022-00579-3.
• 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, volume 62, issue 1, pages 119-155, January, DOI: 10.1007/s00181-020-01918-z.
• Matthias Raddant & Hiroshi Takahashi, 2022, "Corporate boards, interorganizational ties and profitability: the case of Japan," Empirical Economics, Springer, volume 62, issue 3, pages 1365-1406, March, DOI: 10.1007/s00181-021-02062-y.
• 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, volume 62, issue 6, pages 2693-2711, June, DOI: 10.1007/s00181-021-02122-3.
• Christian Glocker & Serguei Kaniovski, 2022, "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, volume 63, issue 1, pages 43-91, July, DOI: 10.1007/s00181-021-02129-w.
• Nadezhda Baryshnikova & Shannon Davidson & Dennis Wesselbaum, 2022, "Do you feel the heat around the corner? The effect of weather on crime," Empirical Economics, Springer, volume 63, issue 1, pages 179-199, July, DOI: 10.1007/s00181-021-02130-3.
• 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, Springer, in: Vicky Katsoni & Andreea Claudia Şerban, "Transcending Borders in Tourism Through Innovation and Cultural Heritage", DOI: 10.1007/978-3-030-92491-1_58.
• Oleksandr Bartkoviak & Viktor Shpyrko & Oleksandr Chernyak & Yevgen Chernyak, 2022, "Statistical Arbitrage Using Cointegration and Principal Component Analysis Approach," Springer Proceedings in Business and Economics, Springer, in: Pantelis Sklias & Persefoni Polychronidou & Anastasios Karasavvoglou & Victoria Pistikou & Nikolaos , "Business Development and Economic Governance in Southeastern Europe", DOI: 10.1007/978-3-031-05351-1_9.
• Steven T. Joanis & Vivek H. Patil, 2022, "First-author gender differentials in business journal publishing: top journals versus the rest," Scientometrics, Springer;Akadémiai Kiadó, volume 127, issue 2, pages 733-761, February, DOI: 10.1007/s11192-021-04235-z.
• 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, volume 13, issue 1, pages 397-428, May, DOI: 10.1007/s13209-021-00248-2.
• Reza Bradrania & Davood Pirayesh Neghab, 2022, "State-dependent asset allocation using neural networks," The European Journal of Finance, Taylor & Francis Journals, volume 28, issue 11, pages 1130-1156, July, DOI: 10.1080/1351847X.2021.1960404.
• Hannes Mueller & Christopher Rauh, 2022, "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, volume 48, issue 4, pages 579-596, July, DOI: 10.1080/03050629.2022.2063853.
• Daniel Borup & Erik Christian Montes Schütte, 2022, "In Search of a Job: Forecasting Employment Growth Using Google Trends," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 1, pages 186-200, January, DOI: 10.1080/07350015.2020.1791133.
• Mengheng Li & Marcel Scharth, 2022, "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 1, pages 285-301, January, DOI: 10.1080/07350015.2020.1806853.
• Joshua D. Angrist & Brigham Frandsen, 2022, "Machine Labor," Journal of Labor Economics, University of Chicago Press, volume 40, issue S1, pages 97-140, DOI: 10.1086/717933.
• Tae-Hwy Lee & Ekaterina Seregina, 2022, "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers, University of California at Riverside, Department of Economics, number 202213, Sep.
• Tetiana Yukhymenko, 2022, "The Role of the Media in the Inflation Expectation Formation Process," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 253, pages 4-26, DOI: 10.26531/vnbu2022.253.01.
• Waweru David & Mose Naftaly, 2022, "Household Fuel Choice in Urban Kenya: A Multinomial Logit Analysis," Financial Internet Quarterly (formerly e-Finanse), Paradigm, volume 18, issue 2, pages 30-41, June, DOI: 10.2478/fiqf-2022-0011.
• 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, volume 55, issue S1, pages 379-405, February, DOI: 10.1111/caje.12551.
• Michael P. Clements, 2022, "Individual forecaster perceptions of the persistence of shocks to GDP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 3, pages 640-656, April, DOI: 10.1002/jae.2884.
• 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., volume 37, issue 5, pages 896-919, August, DOI: 10.1002/jae.2907.
• 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., volume 37, issue 5, pages 920-964, August, DOI: 10.1002/jae.2910.
• 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., volume 37, issue 6, pages 1138-1159, September, DOI: 10.1002/jae.2924.
• 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., volume 37, issue 6, pages 1230-1255, September, DOI: 10.1002/jae.2923.
• Caroline Jardet & Baptiste Meunier, 2022, "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 6, pages 1181-1200, September, DOI: 10.1002/for.2858.
• 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, volume 54, issue 5, pages 1525-1549, August, DOI: 10.1111/jmcb.12868.
• Joshua C. C. Chan, 2022, "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, volume 13, issue 3, pages 1145-1169, July, DOI: 10.3982/QE1381.
• 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, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, number 2022-06-10, Jun.
• 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, issue Forthcomi.
• Hauber, Philipp, 2022, "Real-time nowcasting with sparse factor models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 251551.
• Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2022, "The heterogeneity of Okun's law: A metaregression analysis," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1069.
• Rossouw, Stephanié & Greyling, Talita, 2022, "Collective emotions and macro-level shocks: COVID-19 vs the Ukrainian war," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1210.
• Bender, Benedikt & Bruinsma, Bastiaan, 2022, "Patterns in the Press Releases of Trade Unions: How to Use Structural Topic Models in the Field of Industrial Relations
  [Muster in Pressemitteilungen von Gewerkschaften. Die Anwendung von Structural Topic Models im Feld der industriellen Beziehung," Industrielle Beziehungen. Zeitschrift für Arbeit, Organisation und Management, Verlag Barbara Budrich, volume 29, issue 2, pages 91-116, DOI: 10.3224/indbez.v29i2.02.
• Benner, Niklas & Lange, Kai-Robin & Jentsch, Carsten, 2022, "Named entity narratives," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 962, DOI: 10.4419/96973126.
• 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, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 963, DOI: 10.4419/96973127.
• 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, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 964, DOI: 10.4419/96973128.

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, Department of Economics and Business Economics, Aarhus University, number 2021-02, Jan.
• Gloria González-Rivera & Carlos Vladimir Rodríguez-Caballero & Esther Ruiz Ortega, 2021, "Expecting the unexpected: economic growth under stress," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2021-06, Mar.
• Isaac K. Ofori, 2021, "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers, Research Africa Network (RAN), number 21/044, Jan.
• 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, Research Africa Network (RAN), number 21/074, Jan.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2021, "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2021-03, Jul.
• 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, volume 23, issue 1, pages 56-73.
• 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., African Governance and Development Institute., number 21/044, Jan.
• 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., African Governance and Development Institute., number 21/074, Jan.
• D.V. Firsov & T.C. Chernyshevа, 2021, "Review of Successful Practices of Applying Nowcasting in Socio-Economic Forecasting," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, volume 20, issue 2, pages 269-293, DOI: http://dx.doi.org/10.15826/vestnik..
• 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, Monash University, number 2021-12, Dec.
• Nurdaulet Abilov & Aizhan Bolatbayeva, 2021, "Nowcasting GDP growth in Russia with an incomplete dataset: A factor model approach," NAC Analytica Working Paper, NAC Analytica, Nazarbayev University, number 18, Dec, revised Feb 2022.
• Mauricio Gallardo & María Emma Santos & Pablo Villatoro & Vicky Pizarro, 2021, "Measuring vulnerability to multidimensional poverty in Latin America," Working Papers, Red Nacional de Investigadores en Economía (RedNIE), number 36, Mar.
• Oscar Claveria & Enric Monte & Salvador Torra, 2021, "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 202101, Feb, revised Feb 2021.
• Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021, "Can Machine Learning Catch the COVID-19 Recession?," Papers, arXiv.org, number 2103.01201, Mar.
• Mehmet Caner, 2021, "Generalized Linear Models with Structured Sparsity Estimators," Papers, arXiv.org, number 2104.14371, Apr.
• Francesca Micocci & Armando Rungi, 2021, "Predicting Exporters with Machine Learning," Papers, arXiv.org, number 2107.02512, Jul, revised Sep 2022.
• M. Hashem Pesaran & Yimeng Xie, 2021, "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Test," Papers, arXiv.org, number 2109.00408, Sep, revised Jan 2026.
• Joshua C. C. Chan, 2021, "Asymmetric Conjugate Priors for Large Bayesian VARs," Papers, arXiv.org, number 2111.07170, Nov.
• Minseog Oh & Donggyu Kim, 2021, "Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective," Papers, arXiv.org, number 2111.09655, Nov.
• Emilia VASILE & Danut Octavian SIMION, 2021, "Optimization Of Application Objects Used In The Economic Environments," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 61, issue 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, volume 62, issue 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, volume 63, issue 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, Institute of Economic Growth, number 446, Oct.
• Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021, "Can Machine Learning Catch the COVID-19 Recession?," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 21-01, Mar.
• 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, BBVA Bank, Economic Research Department, number 21/07, Jul.
• James Chapman & Ajit Desai, 2021, "Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19," Staff Working Papers, Bank of Canada, number 21-2, Jan, DOI: 10.34989/swp-2021-2.
• Tatjana Dahlhaus & Angelika Welte, 2021, "Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data," Staff Working Papers, Bank of Canada, number 21-43, Sep, DOI: 10.34989/swp-2021-43.
• Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021, "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series, Central Bank of Brazil, Research Department, number 544, Feb.
• Levent GUNTAY & Mehmet AKTUNA, 2021, "Scenario Based Anomaly Detection in Financial Institutions: A Study on the Turkish Factoring Sector," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 15, issue 1, pages 83-113.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021, "Tracking weekly state-level economic conditions," Working Papers, Banco de España, number 2134, Aug.
• Cristina Angelico & Juri Marcucci & Marcello Miccoli & Filippo Quarta, 2021, "Can we measure inflation expectations using Twitter?," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1318, Feb.
• Valentina Aprigliano & Simone Emiliozzi & Gabriele Guaitoli & Andrea Luciani & Juri Marcucci & Libero Monteforte, 2021, "The power of text-based indicators in forecasting the Italian economic activity," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1321, Mar.
• Rangel González Erick & Llamosas-Rosas Irving, 2021, "Observing the Evolution of the Informal Sector from Space: A Municipal Approach 2013-2020," Working Papers, Banco de México, number 2021-18, Dec.
• Massimo Ferrari & Frederik Kurcz & Maria Sole Pagliari, 2021, "Do Words Hurt More Than Actions? The Impact of Trade Tensions on Financial Markets," Working papers, Banque de France, number 802.
• Henri Fraisse & Matthias Laporte, 2021, "Return on Investment on AI: The Case of Capital Requirement," Working papers, Banque de France, number 809.
• Marlene Amstad & Leonardo Gambacorta & Chao He & Dora Xia, 2021, "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," BIS Working Papers, Bank for International Settlements, number 917, Jan.
• Vrigazova Borislava, 2021, "The Proportion for Splitting Data into Training and Test Set for the Bootstrap in Classification Problems," Business Systems Research, Paradigm, volume 12, issue 1, pages 228-242, May, DOI: 10.2478/bsrj-2021-0015.
• Ksenia Mayorova & Nikita Fokin, 2021, "Nowcasting Growth Rates of Russia's Export and Import by Commodity Group," Russian Journal of Money and Finance, Bank of Russia, volume 80, issue 3, pages 34-48, September, DOI: 10.31477/rjmf.202103.34.
• 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, volume 97, issue 318, pages 387-409, September, DOI: 10.1111/1475-4932.12609.
• Andreas Joseph & Eleni Kalamara & George Kapetanios & Galina Potjagailo & Chiranjit Chakraborty, 2021, "Forecasting UK inflation bottom up," Bank of England Staff Working Paper series, Bank of England, number 915, Mar.
• Nikoleta Anesti & Eleni Kalamara & George Kapetanios, 2021, "Forecasting UK GDP growth with large survey panels," Bank of England Staff Working Paper series, Bank of England, number 923, May.
• Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021, "Comparing minds and machines: implications for financial stability," Bank of England Staff Working Paper series, Bank of England, number 937, Aug.
• Tim Munday & James Brookes, 2021, "Mark my words: the transmission of central bank communication to the general public via the print media," Bank of England Staff Working Paper series, Bank of England, number 944, Oct.
• Jonathan Benchimol & Sophia Kazinnik & Yossi Saadon, 2021, "Federal Reserve Communication and the COVID-19 Pandemic," Bank of Israel Working Papers, Bank of Israel, number 2021.15, Jul.
• Jouchi Nakajima & Hiroaki Yamagata & Tatsushi Okuda & Shinnosuke Katsuki & Takeshi Shinohara, 2021, "Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis," Bank of Japan Working Paper Series, Bank of Japan, number 21-E-12, Oct.
• Reif Magnus, 2021, "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 25, issue 2, pages 1-20, April, DOI: 10.1515/snde-2019-0073.
• Komla M. Agudze & Monica Billio & Roberto Casarin & Francesco Ravazzolo, 2021, "Markov Switching Panel with Endogenous Synchronization Effects," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS82, Mar.
• Mueller, H. & Rauh, C., 2021, "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2103, Jan.
• Kang, J. & Reiner, D., 2021, "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2141, May.
• Kang, J. & Reiner, D., 2021, "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2142, May.
• Kang, J. & Reiner, D., 2021, "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2143, May.
• Pesaran, M. H. & Xie, Y., 2021, "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Testy," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2158, Aug.
• Ba Chu & Shafiullah Qureshi, 2021, "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers, Carleton University, Department of Economics, number 21-12, Oct.
• Parle, Conor, 2021, "The financial market impact of ECB monetary policy press conferences - a text based approach," Research Technical Papers, Central Bank of Ireland, number 4/RT/21, May.
• Bernadette Power & Gavin C Reid, 2021, "The Impact of Intellectual Property Types on the Performance of Business Start-ups in the USA," Working Papers, Centre for Business Research, University of Cambridge, number wp523, Apr.
• Stanislav Anatolyev & Vladimir Pyrlik, 2021, "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague, number wp699, Aug.
• Niklas Amberg & Thomas Jansson & Mathias Klein & Anna Rogantini Picco, 2021, "Five Facts about the Distributional Income Effects of Monetary Policy," CESifo Working Paper Series, CESifo, number 9062.
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• 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, Swiss Finance Institute, number 21-09, Jan.
• Alexis Marchal, 2021, "Risk & Returns around Fomc Press Conferences: A Novel Perspective from Computer Vision," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-18, Mar.
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• Jorge Rojas-Vallejos & Carmen Gloria Jim�nez Bucarey & Marcela Espinoza & Luis Araya-Castillo, 2021, "The short-term impact of urban air pollution on student achievement," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, volume 87, issue 2.
• Susana Martínez-Restrepo & Lina Tafur & Juan G. Ocio & Caroline Brethenoux & Patrick Furey & Orlando Rivera, 2021, "Análisis de narrativas en línea sobre el empoderamiento de las mujeres sobrevivientes de las violencias basadas en género en Colombia con procesamiento de lenguaje natural," Informes de Investigación, Fedesarrollo, number 19664, Aug.
• Gambacorta, Leonardo & Amstad, Marlene & He, Chao & XIA, Fan Dora, 2021, "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," CEPR Discussion Papers, Centre for Economic Policy Research, number 15682, Jan.
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• Moench, Emanuel & Soofi Siavash, Soroosh, 2022, "What Moves Treasury Yields?," CEPR Discussion Papers, Centre for Economic Policy Research, number 15978, Mar.
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• Mckibbin, Warwick & Fernando, Roshen & Liu, Weifeng, 2021, "Global Economic Impacts of Climate Shocks, Climate Policy and Changes in Climate Risk Assessment," CEPR Discussion Papers, Centre for Economic Policy Research, number 16154, May.
• Rao, Justin, 2021, "Demand for Online News under Government Control: Evidence from Russia," CEPR Discussion Papers, Centre for Economic Policy Research, number 16233, Jun.
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• Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021, "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers, Centre for Economic Policy Research, number 16317, Jul.
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• Mckibbin, Warwick & Jaumotte, Florence & Liu, Weifeng, 2021, "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers, Centre for Economic Policy Research, number 16553, Sep.
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• Miranda Gualdrón, Karen Alejandra & Poncela, Pilar & Ruiz Ortega, Esther, 2021, "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 32210, Mar.
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• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021, "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, National Institute of Economic and Social Research, volume 256, issue , pages 71-109, May.
• Shan Huang & Michael Allan Ribers & Hannes Ullrich, 2021, "Der gesellschaftliche Mehrwert verknüpfter Daten: Algorithmen als Entscheidungshilfen bei Antibiotikaverschreibungen," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 88, issue 13/14, pages 239-246.
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• Santiago Gall n & Jorge Barrientos, 2021, "Forecasting the Colombian Electricity Spot Price under a Functional Approach," International Journal of Energy Economics and Policy, Econjournals, volume 11, issue 2, pages 67-74.
• Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021, "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, Econjournals, volume 11, issue 6, pages 489-502.
• Nakamura, Nobuyuki & Suzuki, Aya, 2021, "COVID-19 and the intentions to migrate from developing countries: Evidence from online search activities in Southeast Asia," Journal of Asian Economics, Elsevier, volume 76, issue C, DOI: 10.1016/j.asieco.2021.101348.
• Camacho, Maximo & Romeu, Andres & Ruiz-Marin, Manuel, 2021, "Symbolic transfer entropy test for causality in longitudinal data," Economic Modelling, Elsevier, volume 94, issue C, pages 649-661, DOI: 10.1016/j.econmod.2020.02.007.
• Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021, "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, volume 96, issue C, pages 445-454, DOI: 10.1016/j.econmod.2020.03.030.
• Bastianin, Andrea & Manera, Matteo, 2021, "A test of symmetry based on L-moments with an application to the business cycles of the G7 economies," Economics Letters, Elsevier, volume 198, issue C, DOI: 10.1016/j.econlet.2020.109662.
• Lyu, Yifei & Nie, Jun & Yang, Shu-Kuei X., 2021, "Forecasting US economic growth in downturns using cross-country data," Economics Letters, Elsevier, volume 198, issue C, DOI: 10.1016/j.econlet.2020.109668.
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• Smeekes, Stephan & Wijler, Etienne, 2021, "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, volume 221, issue 1, pages 247-276, DOI: 10.1016/j.jeconom.2020.07.021.
• Yang, Xinxin & Zheng, Xinghua & Chen, Jiaqi, 2021, "Testing high-dimensional covariance matrices under the elliptical distribution and beyond," Journal of Econometrics, Elsevier, volume 221, issue 2, pages 409-423, DOI: 10.1016/j.jeconom.2020.05.017.
• Kapetanios, G. & Pesaran, M.H. & Reese, S., 2021, "Detection of units with pervasive effects in large panel data models," Journal of Econometrics, Elsevier, volume 221, issue 2, pages 510-541, DOI: 10.1016/j.jeconom.2020.05.001.
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• Jin, Sainan & Miao, Ke & Su, Liangjun, 2021, "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 745-777, DOI: 10.1016/j.jeconom.2020.08.002.
• Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021, "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, volume 225, issue 1, pages 2-26, DOI: 10.1016/j.jeconom.2021.03.012.
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• Cavallari, Lilia & Romano, Simone & Naticchioni, Paolo, 2021, "The original sin: Firms’ dynamics and the life-cycle consequences of economic conditions at birth," European Economic Review, Elsevier, volume 138, issue C, DOI: 10.1016/j.euroecorev.2021.103844.
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021, "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, volume 63, issue C, pages 252-269, DOI: 10.1016/j.jempfin.2021.07.009.
• 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, volume 102, issue C, DOI: 10.1016/j.eneco.2021.105494.
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• Nam, Kyungsik, 2021, "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, volume 96, issue C, DOI: 10.1016/j.eneco.2021.105123.
• Strauss, Ilan & Yang, Jangho, 2021, "Slowing investment rates in developing economies: Evidence from a Bayesian hierarchical model," International Review of Financial Analysis, Elsevier, volume 77, issue C, DOI: 10.1016/j.irfa.2021.101843.
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• 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, volume 37, issue 1, pages 360-377, DOI: 10.1016/j.ijforecast.2020.06.006.
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• Chan, Joshua C.C., 2021, "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, volume 37, issue 3, pages 1212-1226, DOI: 10.1016/j.ijforecast.2021.01.002.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021, "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, volume 37, issue 4, pages 1338-1354, DOI: 10.1016/j.ijforecast.2021.05.005.
• Hillen, Judith & Fedoseeva, Svetlana, 2021, "E-commerce and the end of price rigidity?," Journal of Business Research, Elsevier, volume 125, issue C, pages 63-73, DOI: 10.1016/j.jbusres.2020.11.052.
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• Hirche, Martin & Farris, Paul W. & Greenacre, Luke & Quan, Yiran & Wei, Susan, 2021, "Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship," Journal of Retailing, Elsevier, volume 97, issue 4, pages 697-714, DOI: 10.1016/j.jretai.2021.04.002.
• Martins, Pedro S., 2021, "Working to get fired? Unemployment benefits and employment duration," Journal of Policy Modeling, Elsevier, volume 43, issue 5, pages 1016-1030, DOI: 10.1016/j.jpolmod.2021.03.004.
• Turrell, Arthur & Speigner, Bradley & Copple, David & Djumalieva, Jyldyz & Thurgood, James, 2021, "Is the UK’s productivity puzzle mostly driven by occupational mismatch? An analysis using big data on job vacancies," Labour Economics, Elsevier, volume 71, issue C, DOI: 10.1016/j.labeco.2021.102013.
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• Roshen Fernando & Weifeng Liu & Warwick J McKibbin, 2021, "Global economic impacts of climate shocks, climate policy and changes in climate risk assessment," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-37, Apr.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021, "Tracking weekly state-level economic conditions," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-55, Jul.
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