Research classified by Journal of Economic Literature (JEL) codes

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

2023

• 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.
• Andrea Ajello & Diego Silva & Travis Adams & Francisco Vazquez-Grande, 2023, "More than Words: Twitter Chatter and Financial Market Sentiment," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2023-034, May, DOI: 10.17016/FEDS.2023.034.
• Mary Chen & Matthew DeHaven & Isabel Kitschelt & Seung Jung Lee & Martin Sicilian, 2023, "Identifying Financial Crises Using Machine Learning on Textual Data," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1374, Mar, DOI: 10.17016/IFDP.2023.1374.
• Katie Baker & Martín Almuzara & Hannah O’Keeffe & Argia M. Sbordone, 2023, "Reintroducing the New York Fed Staff Nowcast," Liberty Street Economics, Federal Reserve Bank of New York, number 20230908, Sep.
• Anna I. Denisova & Dzhamilya A. Sozaeva & Konstantin V. Gonchar & Griegory A. Aleksandrov, 2023, "Improving the Methodology for Assessing the Economic Efficiency of Public E-procurement of Medicines," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 4, pages 63-81, August, DOI: 10.31107/2075-1990-2023-4-63-81.
• James T. E. Chapman & Ajit Desai, 2023, "Macroeconomic Predictions Using Payments Data and Machine Learning," Forecasting, MDPI, volume 5, issue 4, pages 1-32, November.
• Mihnea Constantinescu, 2023, "Sparse Warcasting," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 15-2023, Sep, revised 02 Oct 2023.
• Laurent Ferrara & Anna Simoni, 2023, "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Post-Print, HAL, number hal-03919944, Oct, DOI: 10.1080/07350015.2022.2116025.
• H. Rad & R. Low & J. Miffre & R. Faff, 2023, "The commodity risk premium and neural networks," Post-Print, HAL, number hal-04322519, Dec, DOI: 10.1016/j.jempfin.2023.101433.
• Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2023, "A penalized two-pass regression to predict stock returns with time-varying risk premia," Post-Print, HAL, number hal-04325655, Dec, DOI: 10.1016/j.jeconom.2022.12.004.
• Jérôme Dugast & Thierry Foucault, 2023, "Equilibrium Data Mining and Data Abundance," Post-Print, HAL, number hal-04390474, Jun.
• Jérome Dugast & Thierry Foucault, 2023, "Equilibrium Data Mining and Data Abundance," Post-Print, HAL, number hal-04390540, May.
• Jérôme Dugast & Thierry Foucault, 2023, "Equilibrium Data Mining and Data Abundance," Post-Print, HAL, number hal-04505144, Oct.
• Christophe Hurlin & Christophe Pérignon, 2023, "Machine Learning and IRB Capital Requirements: Advantages, Risks, and Recommendations
  [Machine Learning et Modèles IRB : Avantages, Risques et Préconisations]," Working Papers, HAL, number halshs-04518248, Nov.
• Baum, Christopher F. & Lööf, Hans & Stephan, Andreas & Zimmermann, Klaus F., 2023, "Estimating the wage premia of refugee immigrants: Lessons from Sweden," Working Paper Series in Economics and Institutions of Innovation, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies, number 496, Dec, revised 30 May 2024.
• 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, pages 1-7, DOI: 10.1186/s12651-023-00335-w.
• Oleksandr Lutsii & Oleksandr Helevei, 2023, "Formation of Components of the Marketing Information System for Agricultural Products Using Big Data Methods," Oblik i finansi, Institute of Accounting and Finance, issue 3, pages 145-150, September, DOI: 10.33146/2307-9878-2023-3(101)-145-.
• Marra de Artiñano, Ignacio & Riottini Depetris, Franco & Volpe Martincus, Christian, 2023, "Automatic Product Classification in International Trade: Machine Learning and Large Language Models," IDB Publications (Working Papers), Inter-American Development Bank, number 12962, Jul, DOI: http://dx.doi.org/10.18235/0005012.
• Tatiana Evdokimova & Piroska Nagy Mohacsi & Olga Ponomarenko & Elina Ribakova, 2023, "Central banks and policy communication: How emerging markets have outperformed the Fed and ECB," Working Paper Series, Peterson Institute for International Economics, number WP23-10, Oct.
• Ha Nguyen, 2023, "Beyond the Annual Averages: Impact of Seasonal Temperature on Employment Growth in US Counties," IMF Working Papers, International Monetary Fund, number 2023/142, Jun.
• Caterina Lepore & Roshen Fernando, 2023, "Global Economic Impacts of Physical Climate Risks," IMF Working Papers, International Monetary Fund, number 2023/183, Sep.
• Nicodemo, Catia & Orso, Cristina E. & Tealdi, Cristina, 2023, "Overseas GPs and Prescription Behaviour in England," IZA Discussion Papers, Institute of Labor Economics (IZA), number 15884, Jan.
• Hansen, Stephen & Lambert, Peter John & Bloom, Nicholas & Davis, Steven J. & Sadun, Raffaella & Taska, Bledi, 2023, "Remote Work across Jobs, Companies, and Space," IZA Discussion Papers, Institute of Labor Economics (IZA), number 15980, Feb.
• 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, Institute of Labor Economics (IZA), number 16426, Sep.
• Clarke, Damian & Torres, Nicolás Paris & Villena-Roldan, Benjamin, 2023, "(Frisch-Waugh-Lovell)' On the Estimation of Regression Models by Row," IZA Discussion Papers, Institute of Labor Economics (IZA), number 16630, Nov.
• 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.
• Becker, Annette & Di Girolamo, Francesca & Rho, Caterina, 2023, "Loan pricing and biodiversity exposure: Nature-related spillovers to the financial sector," JRC Working Papers in Economics and Finance, Joint Research Centre, European Commission, number 2023-11, Dec.
• 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.
• Ba Chu & Shafiullah Qureshi, 2023, "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Computational Economics, Springer;Society for Computational Economics, volume 62, issue 4, pages 1567-1609, December, DOI: 10.1007/s10614-022-10312-z.
• 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.
• Kris Boud & Arno De Block & Geert Langenus & Peter Reusens, 2023, "Nowcasting GDP through the lens of economic states," Working Paper Research, National Bank of Belgium, number 445, Dec.
• Stephen Hansen & Peter John Lambert & Nicholas Bloom & Steven J. Davis & Raffaella Sadun & Bledi Taska, 2023, "Remote Work across Jobs, Companies, and Space," NBER Working Papers, National Bureau of Economic Research, Inc, number 31007, Mar.
• Bryan T. Kelly & Dacheng Xiu, 2023, "Financial Machine Learning," NBER Working Papers, National Bureau of Economic Research, Inc, number 31502, Jul.
• Bryan S. Graham & Andrin Pelican, 2023, "Scenario Sampling for Large Supermodular Games," NBER Working Papers, National Bureau of Economic Research, Inc, number 31511, Jul.
• Emily Aiken & Suzanne Bellue & Joshua Blumenstock & Dean Karlan & Christopher R. Udry, 2023, "Estimating Impact with Surveys versus Digital Traces: Evidence from Randomized Cash Transfers in Togo," NBER Working Papers, National Bureau of Economic Research, Inc, number 31751, Oct.
• 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.
• Dzyuba, Yu. & Bakalova, I., 2023, "CGE models for resource-based economy: A comprehensive bibliometric analysis," Journal of the New Economic Association, New Economic Association, volume 61, issue 4, pages 12-50, DOI: 10.31737/22212264_2023_4_12-50.
• 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.
• Martin O’Connell & Howard Smith & Øyvind Thomassen, 2023, "A two sample size estimator for large data sets," Economics Series Working Papers, University of Oxford, Department of Economics, number 1001, Feb.
• Chengyan Gu, 2023, "Market segmentation and dynamic price discrimination in the U.S. airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, volume 22, issue 5, pages 338-361, October, DOI: 10.1057/s41272-022-00407-5.
• Mansur, Alfan & Nizar, Muhammad Afdi, 2023, "Supply-leading or demand-following financial sector and economic development nexus: evidence from data-rich Indonesia," MPRA Paper, University Library of Munich, Germany, number 119132, Nov, revised 10 Nov 2023.
• Pal, Hemendra, 2023, "The Impact of Russia-Ukraine conflict on Global Commodity Brent Crude Prices," MPRA Paper, University Library of Munich, Germany, number 124770, Aug, revised 02 Oct 2024.
• Milan Cibuľa & Michal Tkáč, 2023, "Porovnanie algoritmov strojového učenia pre tvorbu predikčného modelu ceny bitcoinu
  [Comparison of Machine Learning Algorithms for Creation of a Bitcoin Price Prediction Model]," Politická ekonomie, Prague University of Economics and Business, volume 2023, issue 5, pages 496-517, DOI: 10.18267/j.polek.1397.
• Teona Shugliashvili, 2023, "The words have power: the impact of news on exchange rates," FFA Working Papers, Prague University of Economics and Business, number 5.006, Jun, revised 31 Jul 2023.
• António Rua & Nuno Lourenço & João Quelhas, 2023, "Navigating with a compass: Charting the course of underlying inflation," Working Papers, Banco de Portugal, Economics and Research Department, number w202317.
• Jonathan Hambur, 2023, "Did Labour Market Concentration Lower Wages Growth Pre-COVID?," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2023-02, Mar, DOI: 10.47688/rdp2023-02.
• Jonathan Hambur & Dan Andrews, 2023, "Doing Less, with Less: Capital Misallocation, Investment and the Productivity Slowdown in Australia," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2023-03, Mar, DOI: 10.47688/rdp2023-03.
• Maximo Camacho & Andres Romeu, 2023, "Tourism and Gross Domestic Product short-run causality revisited: A symbolic transfer entropy approach," Tourism Economics, , volume 29, issue 1, pages 235-247, February, DOI: 10.1177/13548166211045756.
• Jan Janků & Zuzana KuÄ erová & FrantiÅ¡ek DaÅ™ena, 2023, "Behavioral Insights from Crowdfunding Financing: What Do Social Media Ties, Emotional Cues and Sentiment Tell Us?," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, volume 71, issue 2, pages 89-118, February.
• Laura Felber & Simon Beyeler, 2023, "Nowcasting economic activity using transaction payments data," Working Papers, Swiss National Bank, number 2023-01.
• Marie-Catherine Bieri, 2023, "Assessing economic sentiment with newspaper text indices: evidence from Switzerland," Working Papers, Swiss National Bank, number 2023-07.
• Byron Botha & Rulof Burger & Kevin Kotzé & Neil Rankin & Daan Steenkamp, 2023, "Big data forecasting of South African inflation," Empirical Economics, Springer, volume 65, issue 1, pages 149-188, July, DOI: 10.1007/s00181-022-02329-y.
• Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023, "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, volume 65, issue 2, pages 805-829, August, DOI: 10.1007/s00181-022-02356-9.
• Francisco Corona & Elio Atenógenes Villaseñor & Jesús López-Pérez & Ranyart R. Suárez, 2023, "Estimating Mexican municipal-level economic activity indicators using nighttime lights," Empirical Economics, Springer, volume 65, issue 3, pages 1197-1214, September, DOI: 10.1007/s00181-023-02376-z.
• Bhanu Pratap & Nalin Priyaranjan, 2023, "Macroeconomic effects of uncertainty: a Google trends-based analysis for India," Empirical Economics, Springer, volume 65, issue 4, pages 1599-1625, October, DOI: 10.1007/s00181-023-02392-z.
• Nuno Lourenço & António Rua, 2023, "Business cycle clocks: Time to get circular," Empirical Economics, Springer, volume 65, issue 4, pages 1513-1541, October, DOI: 10.1007/s00181-023-02405-x.
• Seyed Ali Madanizadeh & Hosein Joshaghani & Reza Moradi, 2023, "Ride-hailing demand elasticity: a regression discontinuity method," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, volume 50, issue 4, pages 907-932, December, DOI: 10.1007/s40812-022-00225-1.
• India Flint & Jasmina Medjedovic & Ewa Drogon O’Flaherty & Elena Alvarez-Baron & Karthinathan Thangavelu & Natasa Savic & Aurelie Meunier & Louise Longworth, 2023, "Mapping analysis to predict SF-6D utilities from health outcomes in people with focal epilepsy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 24, issue 7, pages 1061-1072, September, DOI: 10.1007/s10198-022-01519-w.
• James Yae & Yang Luo, 2023, "Robust monitoring machine: a machine learning solution for out-of-sample R $$^2$$ 2 -hacking in return predictability monitoring," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 9, issue 1, pages 1-28, December, DOI: 10.1186/s40854-023-00497-z.
• Nhung Nghiem & June Atkinson & Binh P. Nguyen & An Tran-Duy & Nick Wilson, 2023, "Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets," Health Economics Review, Springer, volume 13, issue 1, pages 1-13, December, DOI: 10.1186/s13561-023-00422-1.
• Saulius Jokubaitis & Dmitrij Celov, 2023, "Business Cycle Synchronization in the EU: A Regional-Sectoral Look through Soft-Clustering and Wavelet Decomposition," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 19, issue 3, pages 311-371, November, DOI: 10.1007/s41549-023-00090-4.
• Andrei Shynkevich, 2023, "Law of one price and return on Arbitrage Trading: Bitcoin vs. Ethereum," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 47, issue 3, pages 763-792, September, DOI: 10.1007/s12197-023-09631-0.
• Heiko Stüber & Wolfgang Dauth & Johann Eppelsheimer, 2023, "A guide to preparing the sample of integrated labour market biographies (SIAB, version 7519 v1) for scientific analysis," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), volume 57, issue 1, pages 1-11, December, DOI: 10.1186/s12651-023-00335-w.
• Pawan Kumar & Vipul Kumar Singh, 2023, "Examining the Time Varying Spillover Dynamics of Indian Financial Indictors from Global and Local Economic Uncertainty," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 21, issue 1, pages 99-121, March, DOI: 10.1007/s40953-022-00333-8.
• Ioannis A. Nikas & Athanasios Koutras & Alkiviadis Panagopoulos, 2023, "Dynamic Areas of Interest Inside an Urban Destination Using Visitors’ Geolocation," Springer Proceedings in Business and Economics, Springer, in: Vicky Katsoni, "Tourism, Travel, and Hospitality in a Smart and Sustainable World", DOI: 10.1007/978-3-031-26829-8_18.
• Indra Budi & Yaniasih Yaniasih, 2023, "Understanding the meanings of citations using sentiment, role, and citation function classifications," Scientometrics, Springer;Akadémiai Kiadó, volume 128, issue 1, pages 735-759, January, DOI: 10.1007/s11192-022-04567-4.
• Nataliya Matveeva & Vladimir Batagelj & Anuška Ferligoj, 2023, "Scientific collaboration of post-Soviet countries: the effects of different network normalizations," Scientometrics, Springer;Akadémiai Kiadó, volume 128, issue 8, pages 4219-4242, August, DOI: 10.1007/s11192-023-04752-z.
• Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023, "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, volume 3, issue 1, pages 1-32, January, DOI: 10.1007/s43546-022-00384-2.
• Antonio Marsi, 2023, "Predicting European stock returns using machine learning," SN Business & Economics, Springer, volume 3, issue 7, pages 1-25, July, DOI: 10.1007/s43546-023-00487-4.
• Jiexiang Li, 2023, "Estimation of the scale parameter in truncated Rayleigh distribution," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, volume 12, issue 4, pages 1-3.
• Odd E. Nygård & Thor O. Thoresen, 2023, "Controlling for fixed effects in studies of income underreporting," Discussion Papers, Statistics Norway, Research Department, number 1000, May.
• Filipe B. Caires & Hugo Reis & Paulo M. M. Rodrigues, 2023, "Survival of the fittest: tourism exposure and firm survival," Applied Economics, Taylor & Francis Journals, volume 55, issue 60, pages 7150-7177, December, DOI: 10.1080/00036846.2023.2208858.
• Joshua C. C. Chan, 2023, "Large Hybrid Time-Varying Parameter VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 3, pages 890-905, July, DOI: 10.1080/07350015.2022.2080683.
• Laurent Ferrara & Anna Simoni, 2023, "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 41, issue 4, pages 1188-1202, October, DOI: 10.1080/07350015.2022.2116025.
• Sylvia A. Allegretto & Dave Graham-Squire, 2023, "Monopsony in Professional Labor Markets: Hospital System Concentration and Nurse Wages," Working Papers Series, Institute for New Economic Thinking, number inetwp197, Jan, DOI: 10.36687/inetwp197.
• Jacques Minlend, 2023, "European Low-Carbon Policy: Impact on fossil energy markets," Economics Working Paper Archive (University of Rennes & University of Caen), Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS, number 2023-04, Feb.
• Tae-Hwy Lee & Ekaterina Seregina, 2023, "Optimal Portfolio Using Factor Graphical Lasso," Working Papers, University of California at Riverside, Department of Economics, number 202302, Mar.
• Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2023, "Asymmetric AdaBoost for High-dimensional Maximum Score Regression," Working Papers, University of California at Riverside, Department of Economics, number 202306, Aug.
• Saman Banafti & Tae-Hwy Lee, 2023, "Inferential Theory for Granular Instrumental Variables in High Dimensions," Working Papers, University of California at Riverside, Department of Economics, number 202308, Sep.
• Tae-Hwy Lee & Ekaterina Seregina, 2023, "Combining Forecasts under Structural Breaks Using Graphical LASSO," Working Papers, University of California at Riverside, Department of Economics, number 202310, Sep.
• Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2023, "Expecting the unexpected: Stressed scenarios for economic growth," Working Papers, University of California at Riverside, Department of Economics, number 202314, Nov.
• Tetiana Yukhymenko & Oleh Sorochan, 2023, "Impact of the Central Bank's Communication on FX Market Dynamics," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 255, pages 4-21, DOI: 10.26531/vnbu2023.255.01.
• Mihnea Constantinescu, 2023, "Sparse Warcasting," Working Papers, National Bank of Ukraine, number 01/2023, Jun.
• Dylan Brewer & Alyssa Carlson, 2023, "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers, Department of Economics, University of Missouri, number 2302, Mar.
• Dylan Brewer & Alyssa Carlson, 2023, "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers, Department of Economics, University of Missouri, number 2310, Jun.
• Matevosova Anastasia, 2023, "Modeling the impact of sanctions on inflation expectations," Working Papers, Moscow State University, Faculty of Economics, number 0053, May.
• Matevosova Anastasia, 2023, "The research of Russian’s inflation expectations under sanctions based on big data," Working Papers, Moscow State University, Faculty of Economics, number 0057, May.
• Luca Mingarelli & Jonas Wendelborn & Tamarah Shakir, 2023, "On the identification of zombie firms," Aussenwirtschaft, University of St. Gallen, School of Economics and Political Science, Swiss Institute for International Economics and Applied Economics Research, volume 73, issue 01, pages 57-64, December.
• Fengler, Matthias & Phan, Minh Tri, 2023, "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series, University of St. Gallen, School of Economics and Political Science, number 2307, Aug.
• Bogner Alexandra & Jerger Jürgen, 2023, "Big data in monetary policy analysis—a critical assessment," Economics and Business Review, Sciendo, volume 9, issue 2, pages 27-40, April, DOI: 10.18559/ebr.2023.2.733.
• Gere István, 2023, "Mapping the Parameter Space of Simulated Lotteries," Journal of Social and Economic Statistics, Sciendo, volume 12, issue 2, pages 38-52, December, DOI: 10.2478/jses-2023-0008.
• Brudan Adrian & Gorski Teodora & Mihailoaie Cristina & Pentek Borbala, 2023, "Towards Effective Performance Management Systems: A Case Study on Integrated Performance Management Maturity Model Deployment," Timisoara Journal of Economics and Business, Sciendo, volume 16, issue 2, pages 119-140, DOI: 10.2478/tjeb-2023-0007.
• Denise Desjardins & Georges Dionne & Yang Lu, 2023, "Hierarchical random‐effects model for the insurance pricing of vehicles belonging to a fleet," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 38, issue 2, pages 242-259, March, DOI: 10.1002/jae.2949.
• Fetzer, Thiemo & Gazze, Ludovica & Bishop, Menna, 2023, "Distributional and climate implications of policy responses to energy price shocks," The Warwick Economics Research Paper Series (TWERPS), University of Warwick, Department of Economics, number 1467.
• Szydlo, Jan, 2023, "Forecasting Credit Dynamics : VAR, VECM or modern Factor-Augmented VAR approach?," Warwick-Monash Economics Student Papers, Warwick Monash Economics Student Papers, number 63.
• Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023, "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers, Deutsche Bundesbank, number 34/2023.
• Fridgen, Gilbert & Kräussl, Roman & Papageorgiou, Orestis & Tugnetti, Alessandro, 2023, "The fundamental value of art NFTs," CFS Working Paper Series, Center for Financial Studies (CFS), number 709, DOI: 10.2139/ssrn.4337173.
• Büchel, Jan & Engler, Jan & Mertens, Armin, 2023, "Gesuchte Datenkompetenzen in Deutschland
  [The demand for data skills in Germany]," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 50, issue 2, pages 3-17, DOI: 10.2373/1864-810X.23-02-01.
• Lavko, Matus & Klein, Tony & Walther, Thomas, 2023, "Reinforcement Learning and Portfolio Allocation: Challenging Traditional Allocation Methods," QBS Working Paper Series, Queen's University Belfast, Queen's Business School, number 2023/01, DOI: 10.2139/ssrn.4346043.
• Bagnara, Matteo & Goodarzi, Milad, 2023, "Clustering-based sector investing," SAFE Working Paper Series, Leibniz Institute for Financial Research SAFE, number 397.
• Iva Tolic Mandic & Sanja Tisma & Daniela Angelina Jelincic & Damir Demonja, 2023, "Smart Solutions for Sustainable Tourism Pearls: How to Live Between Culture and Tourism in Dubrovnik," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 21, issue 3, pages 272-296.

2022

• Kristoffer Pons Bertelsen, 2022, "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2022-05, Jan.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2022, "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2022-03, Jul.
• Laurence Kotlikoff, 2022, "Does Prediction Machines Predict Our AI Future? A Review," Journal of Economic Literature, American Economic Association, volume 60, issue 3, pages 1052-1057, September, DOI: 10.1257/jel.20191519.
• Susanne Schennach, 2022, "Measurement Systems," Journal of Economic Literature, American Economic Association, volume 60, issue 4, pages 1223-1263, December, DOI: 10.1257/jel.20211355.
• Gheorghe Zaman & Nicoleta Valentina Florea & Constantin Aurelian Ionescu & Dan Marius Coman & Doina Constanta Mihai & Nicoleta Luminita Gudanescu Nicolau, 2022, "Mathematical Model for Determining Costs of Unsatisfied Customers of HoReCa Industry," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 24, issue 59, pages 268-268.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022, "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers of the African Governance and Development Institute., African Governance and Development Institute., number 22/061, Jan.
• Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022, "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN, Université catholique de Louvain, Louvain Finance (LFIN), number 2022003, May.
• Andrada LASCÄ‚U, 2022, "Ï»¿Audit Digitalization And Data Mining," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, volume 1, issue 24, pages 1-10.
• Stefano Giglio & Bryan Kelly & Dacheng Xiu, 2022, "Factor Models, Machine Learning, and Asset Pricing," Annual Review of Financial Economics, Annual Reviews, volume 14, issue 1, pages 337-368, November, DOI: 10.1146/annurev-financial-101521-10.
• Агамбаева С.Б. // Agambayeva S.B. & Джусангалиева К.Е. // Jussangaliyeva K.E. & Акылбеков А.А. // Akylbekov A.A. & Ханетова А.Б. // Khanetova A.B., 2022, "Таргет по инфляции: формулировка цели и последствия ее смены. Обзор международного опыта. // Inflation Target: Formulation of the Goal and Implications of its Change. Overview of international experie," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 3/4, pages 4-25.
• Аринова Айжан // Arinova Aizhan & Ержан Ислам // Yerzhan Islam, 2022, "Использование транзакционных данных в качестве оперативного показателя экономической активности // Use of transactional data as an operational measure of economic activity," Working Papers, National Bank of Kazakhstan, number #2022-11.
• Christina Carty & Oscar Claveria, 2022, "“The nexus between variable renewable energy, economy and climate: Evidence from European countries by means of exploratory graphical analysis”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 202205, May, revised May 2022.
• Saman Banafti & Tae-Hwy Lee, 2022, "Inferential Theory for Granular Instrumental Variables in High Dimensions," Papers, arXiv.org, number 2201.06605, Jan, revised Sep 2023.
• Joshua C. C. Chan, 2022, "Large Hybrid Time-Varying Parameter VARs," Papers, arXiv.org, number 2201.07303, Jan, revised Jun 2022.
• David Benatia & Christophe Bell'ego & Louis Pape, 2022, "Dealing with Logs and Zeros in Regression Models," Papers, arXiv.org, number 2203.11820, Mar, revised Sep 2025.
• Christophe Hurlin & Christophe P'erignon & S'ebastien Saurin, 2022, "The Fairness of Credit Scoring Models," Papers, arXiv.org, number 2205.10200, May, revised Feb 2024.
• Giovanni Urga & Fa Wang, 2022, "Estimation and Inference for High Dimensional Factor Model with Regime Switching," Papers, arXiv.org, number 2205.12126, May, revised Apr 2023.