Research classified by Journal of Economic Literature (JEL) codes

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

2023

• 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, Centre for Economic Policy Research, 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, Centre for Economic Policy Research, 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, Centre for Economic Policy Research, number 17931, Feb.
• O'Connell, Martin & Smith, Howard & Thomassen, Oyvind, 2023, "A two sample size estimator for large data sets," CEPR Discussion Papers, Centre for Economic Policy Research, 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, Centre for Economic Policy Research, 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, Centre for Economic Policy Research, number 17990, Mar.
• Ash, Elliott & Hansen, Stephen, 2023, "Text Algorithms in Economics," CEPR Discussion Papers, Centre for Economic Policy Research, number 18125, Apr.
• Ershov, Daniel & He, Yanting & Seiler, Stephan, 2023, "How Much Influencer Marketing is Undisclosed? Evidence from Twitter," CEPR Discussion Papers, Centre for Economic Policy Research, 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.
• 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.
• Cepparulo, Brian, 2023, "Is mobility a good proxy for economic activity?," Greenwich Papers in Political Economy, University of Greenwich, Greenwich Political Economy Research Centre, number 45165, Nov.
• 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.
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• 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.
• C sar P rez L pez & Mar a Jes s Delgado Rodr guez & Sonia de Lucas Santos, 2023, "Modelizaci n de los factores que afectan al fraude fiscal con t cnicas de miner a de datos: aplicaci n al Impuesto de la Renta en Espa a," 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.
• 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, IZA Network @ LISER, 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, IZA Network @ LISER, 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, IZA Network @ LISER, 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, IZA Network @ LISER, 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.
• 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.
• 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.
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• 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.