Research classified by Journal of Economic Literature (JEL) codes

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

2024

• Greyling, Talita & Rossouw, Stephanié, 2024, "Development and validation of a real-time happiness index using Google TrendsTM," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1493.
• Büchel, Jan & Engler, Jan, 2024, "Generative KI in Deutschland: Künstliche Intelligenz in Gesellschaft und Unternehmen," IW-Reports, Institut der deutschen Wirtschaft (IW) / German Economic Institute, number 23/2024.
• Büchel, Jan & Monsef, Roschan, 2024, "Künstliche Intelligenz: Bessere Entlohnung durch Produktivitätsbooster?
  [Artificial Intelligence: Will boosted productivity lead to better pay?]," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 51, issue 2, pages 45-63, DOI: 10.2373/1864-810X.24-02-03.
• Latifi, Albina & Winker, Peter & Lenz, David, 2024, "Identification of innovation drivers based on technology-related news articles," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges, Verein für Socialpolitik / German Economic Association, number 302371.

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, Department of Economics, Auburn University, number auwp2023-02, Feb.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2023, "Superior Predictability of American Factors of the Dollar/Won Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2023-05, Jun.
• Hyeongwoo Kim & Jisoo Son, 2023, "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2023-06, Jul.
• Dorel Mihai Paraschiv & Narciz Balasoiu & Souhir Ben-Amor & Raul Cristian Bag, 2023, "Hybridising Neurofuzzy Model the Seasonal Autoregressive Models for Electricity Price Forecasting on Germany’s Spot Market," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 25, issue 63, pages 463-463, April.
• Ovidiu-Ilie Stofor, 2023, "Quality Analysis Of Learning Improves The Quality Of Learning," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 31, pages 169-182, June, DOI: 10.47743/rebs-2023-1-0010.
• Sanjiv Das & Richard Stanton & Nancy Wallace, 2023, "Algorithmic Fairness," Annual Review of Financial Economics, Annual Reviews, volume 15, issue 1, pages 565-593, November, DOI: 10.1146/annurev-financial-110921-12.
• Elliott Ash & Stephen Hansen, 2023, "Text Algorithms in Economics," Annual Review of Economics, Annual Reviews, volume 15, issue 1, pages 659-688, September, DOI: 10.1146/annurev-economics-082222-07.
• Оливер де Грут // Oliver de Groot & Джозеф Конингс // Jozef Konings, 2023, "Инфляционное таргетирование, денежно-кредитная политика и возврат к таргетированию в Казахстане. // Inflation Targeting, Monetary Policy and the Transition Back to Target in Kazakhstan," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 1 Special, pages 30-56.
• Муканов Н.С. // Mukanov N.S. & Алмагамбетов К.А. // Almagambetov K.A. & Джаржанов М.У. // Jarzhanov M.U. & Ильясов А.Б. // Ilyasov A.B., 2023, "Вопросы установления и достижения целевых ориентиров по инфляции. Выбор оптимальных характеристик цели по инфляции в Казахстане. // Setting and Achieving Inflation Targets. Choosing Optimal Characteristics of the Inflation Target in Kazakhstan," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 1 Special, pages 7-29.
• Lukáš Bernat & Radka Michlová & Helena Mitwallyová, 2023, "Pattern classification on specifics of public sector investments and budgeting principles," International Journal of Economic Sciences, European Research Center, volume 12, issue 1, pages 15-37, May.
• Jia Chen & Degui Li & Yuning Li & Oliver Linton, 2023, "Estimating Time-Varying Networks for High-Dimensional Time Series," Papers, arXiv.org, number 2302.02476, Feb.
• Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023, "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers, arXiv.org, number 2302.03172, Feb.
• Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023, "Disentangling Structural Breaks in Factor Models for Macroeconomic Data," Papers, arXiv.org, number 2303.00178, Feb, revised Nov 2025.
• Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023, "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Papers, arXiv.org, number 2303.10117, Mar, revised Mar 2024.
• Ajit Desai, 2023, "Machine Learning for Economics Research: When What and How?," Papers, arXiv.org, number 2304.00086, Mar, revised Apr 2023.
• Ruben Loaiza-Maya & Didier Nibbering & Dan Zhu, 2023, "Hybrid unadjusted Langevin methods for high-dimensional latent variable models," Papers, arXiv.org, number 2306.14445, Jun.
• Riccardo Di Francesco, 2023, "Ordered Correlation Forest," Papers, arXiv.org, number 2309.08755, Sep.
• Damian Clarke & Nicol'as Paris & Benjam'in Villena-Rold'an, 2023, "(Frisch-Waugh-Lovell)': On the Estimation of Regression Models by Row," Papers, arXiv.org, number 2311.15829, Nov.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023, "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Papers, arXiv.org, number 2312.15494, Dec, revised Jul 2024.
• DănuÅ£-Octavian SIMION, 2023, "Advanced Methods Of Including Classes And Objects In Application Modules Specific To Business Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 67, issue 1, pages 35-43, March.
• Danut-Octavian SIMION, 2023, "The Support Given By Data Analysis In The Decision-Making Process In Interdependent Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 68, issue 2, pages 17-29, September.
• Ferran Sancho, 2023, "Stone-Geary meets CES:An extended linear expenditure system," UFAE and IAE Working Papers, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), number 971.23, Jun.
• Darab Molkabadi, Saeid, 2023, "Transition and Propagations of Oil Shock in the Oil Exporting Countries: Lessons from Iran (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, volume 28, issue 4, pages 111-139, December.
• Todor Krastevich, 2023, "Retargeting Customers Using Uplift Modeling," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 78-99.
• Sonya Georgieva, 2023, "Application of Artificial Intelligence and Machine Learning in the Conduct of Monetary Policy by Central Banks," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 8, pages 177-199.
• Donald Coletti, 2023, "A Blueprint for the Fourth Generation of Bank of Canada Projection and Policy Analysis Models," Discussion Papers, Bank of Canada, number 2023-23, Oct, DOI: 10.34989/sdp-2023-23.
• Lin Chen & Stephanie Houle, 2023, "Turning Words into Numbers: Measuring News Media Coverage of Shortages," Discussion Papers, Bank of Canada, number 2023-8, Mar, DOI: 10.34989/sdp-2023-8.
• Stephanie Houle & Ryan Macdonald, 2023, "Identifying Nascent High-Growth Firms Using Machine Learning," Staff Working Papers, Bank of Canada, number 23-53, Oct, DOI: 10.34989/swp-2023-53.
• Ajit Desai, 2023, "Machine learning for economics research: when, what and how," Staff Analytical Notes, Bank of Canada, number 2023-16, Oct, DOI: 10.34989/san-2023-16.
• 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), Bank of Italy, Economic Research and International Relations Area, number 746, Feb.
• Crispino Marta & Francesco Paolo Conteduca, 2023, "It's a match! Linking foreign counterparts in Italian customs data to their balance sheets," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 823, Dec.
• 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, Banco de la Republica de Colombia, number 1225, Mar, DOI: 10.32468/be.1225.
• Menzie Chinn & Baptiste Meunier & Sebastian Stumpner, 2023, "Nowcasting World Trade with Machine Learning: a Three-Step Approach," Working papers, Banque de France, number 917.
• Olivier de Bandt & Jean-Charles Bricongne & Julien Denes & Alexandre Dhenin & Annabelle De Gaye & Pierre-Antoine Robert, 2023, "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers, Banque de France, number 921.
• Konstantin Boss & Finja Krueger & Conghan Zheng & Tobias Heidland & Andre Groeger, 2023, "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers, Barcelona School of Economics, number 1387, Mar.
• Pongpitch Amatyakul & Panchanok Jumrustanasan & Pornchanok Tapkham, 2023, "What can 20 billion financial transactions tell us about the impacts of Covid-19 fiscal transfers?," BIS Working Papers, Bank for International Settlements, number 1130, Oct.
• Anastasios Petropoulos & Evangelos Stavroulakis & Panagiotis Lazaris & Vasilis Siakoulis & Nikolaos Vlachogiannakis, 2023, "Is COVID-19 reflected in AnaCredit dataset? A big data - machine learning approach for analysing behavioural patterns using loan level granular information," Working Papers, Bank of Greece, number 315, Mar, DOI: 10.52903/wp2023315.
• Ryuichiro Hashimoto & Kakeru Miura & Yasunori Yoshizaki, 2023, "Application of Machine Learning to a Credit Rating Classification Model: Techniques for Improving the Explainability of Machine Learning," Bank of Japan Working Paper Series, Bank of Japan, number 23-E-6, Apr.
• Byrne, David & Goodhead, Robert & McMahon, Michael & Parle, Conor, 2023, "The Central Bank Crystal Ball: Temporal information in monetary policy communication," Research Technical Papers, Central Bank of Ireland, number 1/RT/23, Feb.
• Byrne, David & Goodhead, Robert & McMahon, Michael & Parle, Conor, 2023, "Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches," Research Technical Papers, Central Bank of Ireland, number 2/RT/23, Feb.
• Martha Cruz Zuniga & Dawit Senbet, 2023, "Does the Effectiveness of Monetary Policy Depend on the Choice of Policy Instrument? Empirical Evidence from South Korea," Journal of Central Banking Theory and Practice, Central bank of Montenegro, volume 12, issue 2, pages 239-265.
• Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023, "Remote work across jobs, companies and space," CEP Discussion Papers, Centre for Economic Performance, LSE, number dp1935, Jul.
• Nicholas Bloom & Steven J. Davis & Stephen Hansen & Peter Lambert & Raffaella Sadun & Bledi Taska, 2023, "Remote work across jobs, companies and space," POID Working Papers, Centre for Economic Performance, LSE, number 067, Mar.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2023, "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," CESifo Working Paper Series, CESifo, number 10223.
• Donia Kamel & Laura Pollacci, 2023, "Academic Migration and Academic Networks: Evidence from Scholarly Big Data and the Iron Curtain," CESifo Working Paper Series, CESifo, number 10377.
• Anna Kerkhof & Valentin Reich, 2023, "Gender Stereotypes in User-Generated Content," CESifo Working Paper Series, CESifo, number 10578.
• Daniel Ershov & Yanting, He & Stephan Seiler, 2023, "How Much Influencer Marketing Is Undisclosed? Evidence from Twitter," CESifo Working Paper Series, CESifo, number 10743.
• Eugenia Gonzalez Ehlinger & Fabian Stephany, 2023, "Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs," CESifo Working Paper Series, CESifo, number 10817.
• Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2023, "Distributional and climate implications of policy responses to energy price shocks," CAGE Online Working Paper Series, Competitive Advantage in the Global Economy (CAGE), number 671.
• Bryan Kelly & Semyon Malamud & Mohammad Pourmohammadi & Fabio Trojani, 2023, "Universal Portfolio Shrinkage," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 23-119, Dec.
• Nicolas Camenzind & Damir Filipović, 2023, "Stripping the Swiss Discount Curve," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 23-97, Oct.
• Oscar Espinosa & Jhonathan Rodr√≠guez & Diego √Åvila & Paul Rodr√≠guez-Lesmes & Sergio Basto & Giancarlo Romano & Lorena Mesa & Hern√°n Enr√≠quez, 2023, "The impact of updating health benefits plans on health technologies usage and expenditures: the case of Colombia," Documentos de Trabajo, Universidad del Rosario, number 20821, Jul.
• Sauvenier, Mathieu & Van Bellegem, Sébastien, 2023, "Direction Identification and Minimax Estimation by Generalized Eigenvalue Problem in High Dimensional Sparse Regression," LIDAM Discussion Papers CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE), number 2023005, Jan.
• Battaglini, Marco & Guiso, Luigi & Lacava, Chiara & Miller , Douglas L. & Patacchini, Eleonora, 2023, "Refining Public Policies with Machine Learning: The Case of Tax Auditing," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 17796, Jan.
• Byrne, David & Goodhead, Robert & Mcmahon, Michael & Parle, Conor, 2023, "The Central Bank Crystal Ball: Temporal information in monetary policy communication," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 17930, Feb.
• Byrne, David & Goodhead, Robert & Mcmahon, Michael & Parle, Conor, 2023, "Measuring the Temporal Dimension of Text: An Application to Policymaker Speeches," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 17931, Feb.
• O'Connell, Martin & Smith, Howard & Thomassen, Oyvind, 2023, "A two sample size estimator for large data sets," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 17941, Feb.
• Hansen, Stephen & Lambert, Peter & Bloom, Nicholas & Davis, Steven & Sadun, Raffaella & Taska, Bledi, 2023, "Remote Work across Jobs, Companies, and Space," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 17964, Mar.
• Fetzer, Thiemo & Gazzè, Ludovica & Bishop, Menna, 2023, "Distributional and climate implications of policy responses to the energy crisis: Lessons from the UK," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 17990, Mar.
• Ash, Elliott & Hansen, Stephen, 2023, "Text Algorithms in Economics," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18125, Apr.
• Ershov, Daniel & He, Yanting & Seiler, Stephan, 2023, "How Much Influencer Marketing is Undisclosed? Evidence from Twitter," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18554, Oct.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023, "Deep Dynamic Factor Models," Working Papers, Center for Research in Economics and Statistics, number 2023-08, May.
• Gerard J. van den Berg & Max Kunaschk & Julia Lang & Gesine Stephan & Arne Uhlendorf, 2023, "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," Working Papers, Center for Research in Economics and Statistics, number 2023-09, Aug.
• Espasa, Antoni & Carlomagno Real, Guillermo, 2023, "Tall big data time series of high frequency: stylized facts and econometric modelling," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 37746, Jul.
• Fuwei Jiang & Wei Ning & Hao Xue, 2023, "Factor Timing with Investor Sentiment," Annals of Economics and Finance, Society for AEF, volume 24, issue 2, pages 401-437, November.
• Pfarrhofer, Michael, 2023, "Measuring International Uncertainty Using Global Vector Autoregressions with Drifting Parameters," Macroeconomic Dynamics, Cambridge University Press, volume 27, issue 3, pages 770-793, April.
• Micocci, Francesca & Rungi, Armando, 2023, "Predicting Exporters with Machine Learning," World Trade Review, Cambridge University Press, volume 22, issue 5, pages 584-607, December.
• Heike Link & Dennis Gaus & Neil Murray & Maria Fernanda Guajardo Ortega & Flavien Gervois & Frederik von Waldow & Sofia Eigner, 2023, "Combining GPS Tracking and Surveys for a Mode Choice Model: Processing Data from a Quasi-Natural Experiment in Germany," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 2047.
• Dorinth van Dijk & Jasper de Winter, 2023, "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers, DNB, number 766, Mar.
• Hurlin, Christophe & Pérignon, Christophe, 2023, "Machine Learning and IRB Capital Requirements: Advantages, Risks, and Recommendations," HEC Research Papers Series, HEC Paris, number 1480, Jun, DOI: 10.2139/ssrn.4483793.
• Emambakhsh, Tina & Fuchs, Maximilian & Kördel, Simon & Kouratzoglou, Charalampos & Lelli, Chiara & Pizzeghello, Riccardo & Salleo, Carmelo & Spaggiari, Martina, 2023, "The Road to Paris: stress testing the transition towards a net-zero economy," Occasional Paper Series, European Central Bank, number 328, Sep.
• Lelli, Chiara & Parisi, Laura & Heemskerk, Irene & Boldrini, Simone & Ceglar, Andrej, 2023, "Living in a world of disappearing nature: physical risk and the implications for financial stability," Occasional Paper Series, European Central Bank, number 333, Nov.
• Ceglar, Andrej & Boldrini, Simone & Lelli, Chiara & Parisi, Laura & Heemskerk, Irene, 2023, "The impact of the euro area economy and banks on biodiversity," Occasional Paper Series, European Central Bank, number 335, Dec.
• Horan, Aoife & Jarmulska, Barbara & Ryan, Ellen, 2023, "Asset prices, collateral and bank lending: the case of Covid-19 and real estate," Working Paper Series, European Central Bank, number 2823, Jun.
• Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023, "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series, European Central Bank, number 2836, Aug.
• 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, volume 13, issue 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, volume 161, issue C, DOI: 10.1016/j.jdeveco.2022.103016.
• Camacho, Maximo & Caro, Angela & Peña, Daniel, 2023, "What drives industrial energy prices?," Economic Modelling, Elsevier, volume 120, issue C, DOI: 10.1016/j.econmod.2022.106158.
• Rasciute, Simona & Downward, Paul & Simmons, Nick, 2023, "Valuation of subjective wellbeing and the role of marital status: Linear versus ordinal estimators," Economic Modelling, Elsevier, volume 123, issue C, DOI: 10.1016/j.econmod.2023.106260.
• Mao Takongmo, Charles-O. & Touré, Adam, 2023, "Trade openness and connectedness of national productions: Do financial openness, economic specialization, and the size of the country matter?," Economic Modelling, Elsevier, volume 125, issue C, DOI: 10.1016/j.econmod.2023.106340.
• Porras-Arena, M. Sylvina & Martín-Román, Ángel L., 2023, "The heterogeneity of Okun's law: A metaregression analysis," Economic Modelling, Elsevier, volume 128, issue C, DOI: 10.1016/j.econmod.2023.106490.
• McKibbin, Warwick & Fernando, Roshen, 2023, "The global economic impacts of the COVID-19 pandemic," Economic Modelling, Elsevier, volume 129, issue C, DOI: 10.1016/j.econmod.2023.106551.
• Yan, Wan-Lin, 2023, "Stock index futures price prediction using feature selection and deep learning," The North American Journal of Economics and Finance, Elsevier, volume 64, issue C, DOI: 10.1016/j.najef.2022.101867.
• Hayo, Bernd & Zahner, Johannes, 2023, "What is that noise? Analysing sentiment-based variation in central bank communication," Economics Letters, Elsevier, volume 222, issue C, DOI: 10.1016/j.econlet.2022.110962.
• Agarwal, Shivam & Muckley, Cal B. & Neelakantan, Parvati, 2023, "Countering racial discrimination in algorithmic lending: A case for model-agnostic interpretation methods," Economics Letters, Elsevier, volume 226, issue C, DOI: 10.1016/j.econlet.2023.111117.
• Fresoli, Diego & Poncela, Pilar & Ruiz, Esther, 2023, "Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models," Economics Letters, Elsevier, volume 230, issue C, DOI: 10.1016/j.econlet.2023.111246.
• Berger, Tino & Morley, James & Wong, Benjamin, 2023, "Nowcasting the output gap," Journal of Econometrics, Elsevier, volume 232, issue 1, pages 18-34, DOI: 10.1016/j.jeconom.2020.08.011.
• Xiong, Ruoxuan & Pelger, Markus, 2023, "Large dimensional latent factor modeling with missing observations and applications to causal inference," Journal of Econometrics, Elsevier, volume 233, issue 1, pages 271-301, DOI: 10.1016/j.jeconom.2022.04.005.
• He, Yi & Jaidee, Sombut & Gao, Jiti, 2023, "Most powerful test against a sequence of high dimensional local alternatives," Journal of Econometrics, Elsevier, volume 234, issue 1, pages 151-177, DOI: 10.1016/j.jeconom.2021.10.015.
• Kueck, Jannis & Luo, Ye & Spindler, Martin & Wang, Zigan, 2023, "Estimation and inference of treatment effects with L2-boosting in high-dimensional settings," Journal of Econometrics, Elsevier, volume 234, issue 2, pages 714-731, DOI: 10.1016/j.jeconom.2022.02.005.
• Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023, "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, volume 235, issue 2, pages 1114-1143, DOI: 10.1016/j.jeconom.2022.08.008.
• Lu, Xun & Su, Liangjun, 2023, "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, volume 235, issue 2, pages 694-719, DOI: 10.1016/j.jeconom.2022.07.002.
• MacKinnon, James G., 2023, "Using large samples in econometrics," Journal of Econometrics, Elsevier, volume 235, issue 2, pages 922-926, DOI: 10.1016/j.jeconom.2022.05.005.
• Chang, Jinyuan & Jiang, Qing & Shao, Xiaofeng, 2023, "Testing the martingale difference hypothesis in high dimension," Journal of Econometrics, Elsevier, volume 235, issue 2, pages 972-1000, DOI: 10.1016/j.jeconom.2022.09.001.
• Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023, "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, volume 236, issue 1, DOI: 10.1016/j.jeconom.2023.05.005.
• Caner, Mehmet, 2023, "Generalized linear models with structured sparsity estimators," Journal of Econometrics, Elsevier, volume 236, issue 2, DOI: 10.1016/j.jeconom.2023.105478.
• Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023, "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2022.11.007.
• Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023, "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, volume 237, issue 2, DOI: 10.1016/j.jeconom.2022.12.004.
• Lippi, Marco & Deistler, Manfred & Anderson, Brian, 2023, "High-Dimensional Dynamic Factor Models: A Selective Survey and Lines of Future Research," Econometrics and Statistics, Elsevier, volume 26, issue C, pages 3-16, DOI: 10.1016/j.ecosta.2022.03.008.
• Hallin, Marc & Trucíos, Carlos, 2023, "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, volume 27, issue C, pages 1-15, DOI: 10.1016/j.ecosta.2021.04.006.
• Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2023, "The commodity risk premium and neural networks," Journal of Empirical Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.jempfin.2023.101433.
• Favero, Filippo & Grossi, Luigi, 2023, "Analysis of individual natural gas consumption and price elasticity: Evidence from billing data in Italy," Energy Economics, Elsevier, volume 118, issue C, DOI: 10.1016/j.eneco.2022.106484.
• Kraschewski, Tobias & Brauner, Tim & Heumann, Maximilian & Breitner, Michael H., 2023, "Disentangle the price dispersion of residential solar photovoltaic systems: Evidence from Germany," Energy Economics, Elsevier, volume 121, issue C, DOI: 10.1016/j.eneco.2023.106649.
• Saâdaoui, Foued & Ben Jabeur, Sami, 2023, "Analyzing the influence of geopolitical risks on European power prices using a multiresolution causal neural network," Energy Economics, Elsevier, volume 124, issue C, DOI: 10.1016/j.eneco.2023.106793.
• Okhrin, Yarema & Uddin, Gazi Salah & Yahya, Muhammad, 2023, "Nonlinear and asymmetric interconnectedness of crude oil with financial and commodity markets," Energy Economics, Elsevier, volume 125, issue C, DOI: 10.1016/j.eneco.2023.106853.
• Kovvuri, Veera Raghava Reddy & Fu, Hsuan & Fan, Xiuyi & Seisenberger, Monika, 2023, "Fund performance evaluation with explainable artificial intelligence," Finance Research Letters, Elsevier, volume 58, issue PB, DOI: 10.1016/j.frl.2023.104419.
• Zhao, Chencheng & Yuan, Xianghui & Long, Jun & Jin, Liwei & Guan, Bowen, 2023, "Financial indicators analysis using machine learning: Evidence from Chinese stock market," Finance Research Letters, Elsevier, volume 58, issue PD, DOI: 10.1016/j.frl.2023.104590.
• 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, volume 82, issue C, DOI: 10.1016/j.intfin.2022.101684.
• Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023, "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, volume 39, issue 1, pages 266-278, DOI: 10.1016/j.ijforecast.2021.11.005.
• Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023, "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, volume 39, issue 2, pages 791-808, DOI: 10.1016/j.ijforecast.2022.02.006.
• Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023, "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, volume 39, issue 2, pages 841-868, DOI: 10.1016/j.ijforecast.2022.02.010.
• Kohns, David & Bhattacharjee, Arnab, 2023, "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, volume 39, issue 3, pages 1384-1412, DOI: 10.1016/j.ijforecast.2022.05.002.
• James, Robert & Leung, Henry & Prokhorov, Artem, 2023, "A machine learning attack on illegal trading," Journal of Banking & Finance, Elsevier, volume 148, issue C, DOI: 10.1016/j.jbankfin.2022.106735.
• Krivorotov, George, 2023, "Machine learning-based profit modeling for credit card underwriting - implications for credit risk," Journal of Banking & Finance, Elsevier, volume 149, issue C, DOI: 10.1016/j.jbankfin.2023.106785.
• Schilpzand, Annemiek & de Jong, Eelke, 2023, "Do market societies undermine civic morality? An empirical investigation into market societies and civic morality across the globe," Journal of Economic Behavior & Organization, Elsevier, volume 208, issue C, pages 39-60, DOI: 10.1016/j.jebo.2023.01.020.
• Fe, Hao, 2023, "Social networks and consumer behavior: Evidence from Yelp," Journal of Economic Behavior & Organization, Elsevier, volume 209, issue C, pages 1-14, DOI: 10.1016/j.jebo.2023.02.009.
• Qiu, Yue & Xie, Tian & Xie, Wenjing & Zheng, Xiangzhong, 2023, "Federal policy announcements and capital reallocation: Insights from inflow and outflow trends in the U.S," Journal of International Money and Finance, Elsevier, volume 139, issue C, DOI: 10.1016/j.jimonfin.2023.102936.
• Schade, Philipp & Schuhmacher, Monika C., 2023, "Predicting entrepreneurial activity using machine learning," Journal of Business Venturing Insights, Elsevier, volume 19, issue C, DOI: 10.1016/j.jbvi.2022.e00357.
• Zhao, Jing, 2023, "Time-varying impact of geopolitical risk on natural resources prices: Evidence from the hybrid TVP-VAR model with large system," Resources Policy, Elsevier, volume 82, issue C, DOI: 10.1016/j.resourpol.2023.103467.
• Vieira, Duarte Saldanha & Carvalho, Paulo Viegas de & Curto, José Dias & Laureano, Luís, 2023, "Gold's hedging and safe haven properties for European stock and bond markets," Resources Policy, Elsevier, volume 85, issue PA, DOI: 10.1016/j.resourpol.2023.103817.
• Foglia, Matteo & Palomba, Giulio & Tedeschi, Marco, 2023, "Disentangling the geopolitical risk and its effects on commodities. Evidence from a panel of G8 countries," Resources Policy, Elsevier, volume 85, issue PB, DOI: 10.1016/j.resourpol.2023.104056.
• Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023, "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, volume 4, issue 2, DOI: 10.1016/j.latcb.2023.100087.
• Meeks, Roland & Monti, Francesca, 2023, "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, volume 139, issue C, pages 41-54, DOI: 10.1016/j.jmoneco.2023.06.003.
• Auer, Benjamin R. & Schuhmacher, Frank & Niemann, Sebastian, 2023, "Cloning mutual fund returns," The Quarterly Review of Economics and Finance, Elsevier, volume 90, issue C, pages 31-37, DOI: 10.1016/j.qref.2023.04.006.
• 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, volume 187, issue C, DOI: 10.1016/j.techfore.2022.122245.
• Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023, "Disentangling Structural Breaks in Factor Models for Macroeconomic Data," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2023-15, Mar, revised Nov 2025.
• Roshen Fernando & Caterina Lepore, 2023, "Global Economic Impacts of Physical Climate Risks," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2023-50, Oct.
• Roshen Fernando, 2023, "Impact of Demographic Trends on Antimicrobial Resistance," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2023-60, Nov.
• Roshen Fernando, 2023, "Impact of Physical Climate Risks on Antimicrobial Resistance," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2023-61, Nov.
• Cesar Ramos, 2023, "Machine Learning Insights into Bolivia’s Economic Downturns," Cuadernos de Investigación Económica Boliviana, Ministerio de Economía y Finanzas Públicas de Bolivia, volume 6, issue 2, pages 5-33, December.
• Ahmet Keser & Ibrahim Cutcu & Sunil Tiwari & Mehmet Vahit Eren & S.S. Askar & Mohamed Abouhawwash, 2023, "How does terrorism hollow out the sustainable economic growth in Big Ten Countries?," International Journal of Emerging Markets, Emerald Group Publishing Limited, volume 20, issue 3, pages 1148-1169, June, DOI: 10.1108/IJOEM-03-2023-0384.
• Elaheh Fatemi Pour & Seyed Ali Madnanizdeh & Hosein Joshaghani, 2023, "Accept or reject a ride? This is the problem," Journal of Economic Studies, Emerald Group Publishing Limited, volume 50, issue 7, pages 1346-1374, January, DOI: 10.1108/JES-12-2021-0617.
• 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, volume 15, issue 2, pages 77-103, January, DOI: 10.1108/JFEP-01-2022-0013.
• Michael D. Plante, 2023, "Investing in the Batteries and Vehicles of the Future: A View Through the Stock Market," Working Papers, Federal Reserve Bank of Dallas, number 2314, Sep, revised 25 Mar 2024, DOI: 10.24149/wp2314r1.
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• J. van den Berg, Gerard & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023, "Predicting re-employment: machine learning versus assessments by unemployed workers and by their caseworkers," Working Paper Series, IFAU - Institute for Evaluation of Labour Market and Education Policy, number 2023:22, Nov.
• O’Connell, Martin & Smith, Howard & Thomassen, Øyvind, 2023, "A two sample size estimator for large data sets," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2023/1, Feb.
• César Pérez López & María Jesús Delgado Rodríguez & Sonia de Lucas Santos, 2023, "Modelización de los factores que afectan al fraude fiscal con técnicas de minería de datos: aplicación al Impuesto de la Renta en España," Hacienda Pública Española / Review of Public Economics, IEF, volume 246, issue 3, pages 137-164, September.
• 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], volume 57, issue , pages 1-007, DOI: 10.1186/s12651-023-00335-w.
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• van den Berg, Gerard J. & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023, "Predicting Re-Employment: Machine Learning versus Assessments by Unemployed Workers and by Their Caseworkers," IZA Discussion Papers, IZA Network @ LISER, number 16426, Sep.
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• Baumgartner Christoph & Srhoj Stjepan & Walde Janette, 2023, "Harmonization of Product Classifications: A Consistent Time Series of Economic Trade Activities," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, volume 243, issue 6, pages 643-662, December, DOI: 10.1515/jbnst-2022-0034.
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• Barbaglia, Luca & Fatica, Serena & Rho, Caterina, 2023, "Flooded credit markets: physical climate risk and small business lending," JRC Working Papers in Economics and Finance, Joint Research Centre, European Commission, number 2023-14, Nov.
• Jan G. De Gooijer, 2023, "Penalized Averaging of Quantile Forecasts from GARCH Models with Many Exogenous Predictors," Computational Economics, Springer;Society for Computational Economics, volume 62, issue 1, pages 407-424, June, DOI: 10.1007/s10614-022-10289-9.
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• Victoria Ateca-Amestoy & Concetta Castiglione, 2023, "Live and digital engagement with the visual arts," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, volume 47, issue 4, pages 643-692, December, DOI: 10.1007/s10824-022-09466-3.
• Ateeb Akhter Shah Syed & Hassan Raza & Mohsin Waheed, 2023, "Easydata-MD: A Monthly Dataset for Macroeconomic Research on Pakistan," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, volume 28, issue 1, pages 63-88, Jan-June.
• Bo Zhang & Jiti Gao & Guangming Pan & Yanrong Yang, 2023, "Eigen-Analysis for High-Dimensional Time Series Clustering," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 22/23.
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• Bryan T. Kelly & Semyon Malamud & Mohammad Pourmohammadi & Fabio Trojani, 2023, "Universal Portfolio Shrinkage," NBER Working Papers, National Bureau of Economic Research, Inc, number 32004, Dec.
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• C. Welter-Medee & S.Quantin, 2023, "Estimate of hidden activity for the 2020 benchmark revision of national accounts," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number 2023-18.
• Sina Smid, 2023, "Understanding cultural differences and extreme attitudes in the 2021 OECD Trust Survey: Text analysis of open-ended responses," OECD Working Papers on Public Governance, OECD Publishing, number 57, Mar, DOI: 10.1787/ef25d883-en.
• Rachida Ouysse, 2023, "Asset Pricing with Endogenous Beliefs-Dependent Risk Aversion," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 2, pages 368-411.
• Dillon Huddleston & Fred Liu & Lars Stentoft, 2023, "Intraday Market Predictability: A Machine Learning Approach," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 2, pages 485-527.
• Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023, "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 2, pages 569-596.
• Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023, "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 3, pages 915-958.
• Ye ChenCapital & Peter C B Phillips & Shuping Shi, 2023, "Common Bubble Detection in Large Dimensional Financial Systems," Journal of Financial Econometrics, Oxford University Press, volume 21, issue 4, pages 989-1063.
• Sendhil Mullainathan & Ziad Obermeyer, 2023, "Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care," The Quarterly Journal of Economics, President and Fellows of Harvard College, volume 137, issue 2, pages 679-727.
• Ron Bekkerman & Eliezer M Fich & Natalya V Khimich & Jeffrey Pontiff, 2023, "The Effect of Innovation Similarity on Asset Prices: Evidence from Patents’ Big Data," The Review of Asset Pricing Studies, Society for Financial Studies, volume 13, issue 1, pages 99-145.
• Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2023, "Marginal Jobs and Job Surplus: A Test of the Efficiency of Separations," The Review of Economic Studies, Review of Economic Studies Ltd, volume 90, issue 3, pages 1265-1303.
• Simona-Vasilica Oprea & Adela Bara & Niculae Oprea, 2023, "Big Data Management and NoSQL Databases," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 466-475, August.
• Alin-Gabriel Vaduva & Simona-Vasilica Oprea & Dragos-Catalin Barbu, 2023, "Understanding Customers' Opinion using Web Scraping and Natural Language Processing," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 537-544, August.
• Andreea-Maria Tanasa & Simona-Vasilica Oprea & Adela Bara, 2023, "Web Scraping and Review Analytics. Extracting Insights from Commercial Data," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 2, pages 370-379, December.