Research classified by Journal of Economic Literature (JEL) codes

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

2021

• Vrigazova Borislava, 2021, "The Proportion for Splitting Data into Training and Test Set for the Bootstrap in Classification Problems," Business Systems Research, Paradigm, volume 12, issue 1, pages 228-242, May, DOI: 10.2478/bsrj-2021-0015.
• Ksenia Mayorova & Nikita Fokin, 2021, "Nowcasting Growth Rates of Russia's Export and Import by Commodity Group," Russian Journal of Money and Finance, Bank of Russia, volume 80, issue 3, pages 34-48, September, DOI: 10.31477/rjmf.202103.34.
• Alexander Plum & Gail Pacheco & Kabir Dasgupta, 2021, "When There is No Way Up: Reconsidering Low‐paid Jobs as Stepping‐stones," The Economic Record, The Economic Society of Australia, volume 97, issue 318, pages 387-409, September, DOI: 10.1111/1475-4932.12609.
• Andreas Joseph & Eleni Kalamara & George Kapetanios & Galina Potjagailo & Chiranjit Chakraborty, 2021, "Forecasting UK inflation bottom up," Bank of England Staff Working Paper series, Bank of England, number 915, Mar.
• Nikoleta Anesti & Eleni Kalamara & George Kapetanios, 2021, "Forecasting UK GDP growth with large survey panels," Bank of England Staff Working Paper series, Bank of England, number 923, May.
• Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021, "Comparing minds and machines: implications for financial stability," Bank of England Staff Working Paper series, Bank of England, number 937, Aug.
• Tim Munday & James Brookes, 2021, "Mark my words: the transmission of central bank communication to the general public via the print media," Bank of England Staff Working Paper series, Bank of England, number 944, Oct.
• Jonathan Benchimol & Sophia Kazinnik & Yossi Saadon, 2021, "Federal Reserve Communication and the COVID-19 Pandemic," Bank of Israel Working Papers, Bank of Israel, number 2021.15, Jul.
• Jouchi Nakajima & Hiroaki Yamagata & Tatsushi Okuda & Shinnosuke Katsuki & Takeshi Shinohara, 2021, "Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis," Bank of Japan Working Paper Series, Bank of Japan, number 21-E-12, Oct.
• Reif Magnus, 2021, "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 25, issue 2, pages 1-20, April, DOI: 10.1515/snde-2019-0073.
• Komla M. Agudze & Monica Billio & Roberto Casarin & Francesco Ravazzolo, 2021, "Markov Switching Panel with Endogenous Synchronization Effects," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS82, Mar.
• Mueller, H. & Rauh, C., 2021, "The Hard Problem of Prediction for Conflict Prevention," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2103, Jan.
• Kang, J. & Reiner, D., 2021, "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2141, May.
• Kang, J. & Reiner, D., 2021, "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2142, May.
• Kang, J. & Reiner, D., 2021, "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2143, May.
• Pesaran, M. H. & Xie, Y., 2021, "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Testy," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2158, Aug.
• Ba Chu & Shafiullah Qureshi, 2021, "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers, Carleton University, Department of Economics, number 21-12, Oct.
• Parle, Conor, 2021, "The financial market impact of ECB monetary policy press conferences - a text based approach," Research Technical Papers, Central Bank of Ireland, number 4/RT/21, May.
• Bernadette Power & Gavin C Reid, 2021, "The Impact of Intellectual Property Types on the Performance of Business Start-ups in the USA," Working Papers, Centre for Business Research, University of Cambridge, number wp523, Apr.
• Stanislav Anatolyev & Vladimir Pyrlik, 2021, "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague, number wp699, Aug.
• Niklas Amberg & Thomas Jansson & Mathias Klein & Anna Rogantini Picco, 2021, "Five Facts about the Distributional Income Effects of Monetary Policy," CESifo Working Paper Series, CESifo, number 9062.
• Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021, "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series, CESifo, number 9165.
• M. Hashem Pesaran & Yimeng Xie, 2021, "A Bias-Corrected CD Test for Error Cross-Sectional Dependence in Panel Data Models with Latent Factors," CESifo Working Paper Series, CESifo, number 9234.
• Els Bekaert & Amelie F. Constant & Killian Foubert & Ilse Ruyssen, 2021, "Longing for Which Home: Evidence from Global Aspirations to Stay, Return or Migrate Onwards," CESifo Working Paper Series, CESifo, number 9301.
• Gaetan Bakalli & Stéphane Guerrier & Olivier Scaillet, 2021, "A penalized two-pass regression to predict stock returns with time-varying risk premia," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-09, Jan.
• Alexis Marchal, 2021, "Risk & Returns around Fomc Press Conferences: A Novel Perspective from Computer Vision," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-18, Mar.
• Michael Mayer & Steven C. Bourassa & Martin Hoesli & Donato Scognamiglio, 2021, "Structured Additive Regression and Tree Boosting," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-83, Sep.
• Hugo Couture & Dalibor Stevanovic, 2021, "Analyse du marché du travail à l’aide des données de Google Trends," CIRANO Project Reports, CIRANO, number 2021rp-15, Aug.
• Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021, "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers, CIRANO, number 2021s-09, Mar.
• Jorge Rojas-Vallejos & Carmen Gloria Jim�nez Bucarey & Marcela Espinoza & Luis Araya-Castillo, 2021, "The short-term impact of urban air pollution on student achievement," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, volume 87, issue 2.
• Susana Martínez-Restrepo & Lina Tafur & Juan G. Ocio & Caroline Brethenoux & Patrick Furey & Orlando Rivera, 2021, "Análisis de narrativas en línea sobre el empoderamiento de las mujeres sobrevivientes de las violencias basadas en género en Colombia con procesamiento de lenguaje natural," Informes de Investigación, Fedesarrollo, number 19664, Aug.
• Amstad, Marlene & Gambacorta, Leonardo & He, Chao & Xia, Fan Dora, 2021, "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," CEPR Discussion Papers, Centre for Economic Policy Research, number 15682, Jan.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanovic, Dalibor, 2021, "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers, Centre for Economic Policy Research, number 15867, Mar.
• Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano & Mertens, Elmar, 2021, "Measuring Uncertainty and Its Effects in the COVID-19 Era," CEPR Discussion Papers, Centre for Economic Policy Research, number 15965, Mar.
• Moench, Emanuel & Soofi Siavash, Soroosh, 2021, "What Moves Treasury Yields?," CEPR Discussion Papers, Centre for Economic Policy Research, number 15978, Mar.
• Filippou, Ilias & Taylor, Mark & Wang, Zigan, 2021, "Media Sentiment and Currency Reversals," CEPR Discussion Papers, Centre for Economic Policy Research, number 16049, Apr.
• Fernando, Roshen & Liu, Weifeng & Mckibbin, Warwick, 2021, "Global Economic Impacts of Climate Shocks, Climate Policy and Changes in Climate Risk Assessment," CEPR Discussion Papers, Centre for Economic Policy Research, number 16154, May.
• Rao, Justin, 2021, "Demand for Online News under Government Control: Evidence from Russia," CEPR Discussion Papers, Centre for Economic Policy Research, number 16233, Jun.
• Calvo Pardo, Héctor & Olmo, Jose & Mancini, Tullio, 2021, "Machine Learning the Carbon Footprint of Bitcoin Mining," CEPR Discussion Papers, Centre for Economic Policy Research, number 16267, Jun.
• Baumeister, Christiane & Leiva-León, Danilo & Sims, Eric, 2021, "Tracking Weekly State-Level Economic Conditions," CEPR Discussion Papers, Centre for Economic Policy Research, number 16317, Jul.
• Aiken, Emily & Bellue, Suzanne & Karlan, Dean & Udry, Christopher & Blumenstock, Joshua, 2021, "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," CEPR Discussion Papers, Centre for Economic Policy Research, number 16385, Jul.
• Jaumotte, Florence & Liu, Weifeng & Mckibbin, Warwick, 2021, "Mitigating Climate Change: Growth-Friendly Policies to Achieve Net Zero Emissions by 2050," CEPR Discussion Papers, Centre for Economic Policy Research, number 16553, Sep.
• Iaria, Alessandro & Wang, Ao, 2021, "An Empirical Model of Quantity Discounts with Large Choice Sets," CEPR Discussion Papers, Centre for Economic Policy Research, number 16666, Oct.
• González Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2021, "Expecting the unexpected: economic growth under stress," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 32148, Mar.
• Miranda Gualdrón, Karen Alejandra & Poncela, Pilar & Ruiz Ortega, Esther, 2021, "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 32210, Mar.
• Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021, "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, volume 37, issue 4, pages 794-816, August.
• Goulet Coulombe, Philippe & Marcellino, Massimiliano & Stevanović, Dalibor, 2021, "Can Machine Learning Catch The Covid-19 Recession?," National Institute Economic Review, National Institute of Economic and Social Research, volume 256, issue , pages 71-109, May.
• Shan Huang & Michael Allan Ribers & Hannes Ullrich, 2021, "Der gesellschaftliche Mehrwert verknüpfter Daten: Algorithmen als Entscheidungshilfen bei Antibiotikaverschreibungen," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 88, issue 13/14, pages 239-246.
• Shan Huang & Michael Allan Ribers & Hannes Ullrich, 2021, "The Value of Data for Prediction Policy Problems: Evidence from Antibiotic Prescribing," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1939.
• Dugast, Jerome & Foucault, Thierry, 2021, "Equilibrium Data Mining and Data Abundance," HEC Research Papers Series, HEC Paris, number 1393, Jan, DOI: 10.2139/ssrn.3710495.
• Hurlin, Christophe & Pérignon, Christophe & Saurin, Sébastien, 2021, "The Fairness of Credit Scoring Models," HEC Research Papers Series, HEC Paris, number 1411, Feb, DOI: 10.2139/ssrn.3785882.
• Hirschbühl, Dominik & Onorante, Luca & Saiz, Lorena, 2021, "Using machine learning and big data to analyse the business cycle," Economic Bulletin Articles, European Central Bank, volume 5.
• Alogoskoufis, Spyros & Dunz, Nepomuk & Emambakhsh, Tina & Hennig, Tristan & Kaijser, Michiel & Kouratzoglou, Charalampos & Muñoz, Manuel A. & Parisi, Laura & Salleo, Carmelo, 2021, "ECB’s economy-wide climate stress test," Occasional Paper Series, European Central Bank, number 281, Sep.
• Bobasu, Alina & Geis, André & Quaglietti, Lucia & Ricci, Martino, 2021, "Tracking global economic uncertainty: implications for the euro area," Working Paper Series, European Central Bank, number 2541, Apr.
• Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021, "Economic predictions with big data: the illusion of sparsity," Working Paper Series, European Central Bank, number 2542, Apr.
• Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021, "The time-varying evolution of inflation risks," Working Paper Series, European Central Bank, number 2600, Oct.
• Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021, "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series, European Central Bank, number 2616, Nov.
• Santiago Gall n & Jorge Barrientos, 2021, "Forecasting the Colombian Electricity Spot Price under a Functional Approach," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 11, issue 2, pages 67-74.
• Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021, "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 11, issue 6, pages 489-502.
• Nakamura, Nobuyuki & Suzuki, Aya, 2021, "COVID-19 and the intentions to migrate from developing countries: Evidence from online search activities in Southeast Asia," Journal of Asian Economics, Elsevier, volume 76, issue C, DOI: 10.1016/j.asieco.2021.101348.
• Camacho, Maximo & Romeu, Andres & Ruiz-Marin, Manuel, 2021, "Symbolic transfer entropy test for causality in longitudinal data," Economic Modelling, Elsevier, volume 94, issue C, pages 649-661, DOI: 10.1016/j.econmod.2020.02.007.
• Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021, "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, volume 96, issue C, pages 445-454, DOI: 10.1016/j.econmod.2020.03.030.
• Bastianin, Andrea & Manera, Matteo, 2021, "A test of symmetry based on L-moments with an application to the business cycles of the G7 economies," Economics Letters, Elsevier, volume 198, issue C, DOI: 10.1016/j.econlet.2020.109662.
• Lyu, Yifei & Nie, Jun & Yang, Shu-Kuei X., 2021, "Forecasting US economic growth in downturns using cross-country data," Economics Letters, Elsevier, volume 198, issue C, DOI: 10.1016/j.econlet.2020.109668.
• Biewen, Martin & Kugler, Philipp, 2021, "Two-stage least squares random forests with an application to Angrist and Evans (1998)," Economics Letters, Elsevier, volume 204, issue C, DOI: 10.1016/j.econlet.2021.109893.
• Smeekes, Stephan & Wijler, Etienne, 2021, "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, volume 221, issue 1, pages 247-276, DOI: 10.1016/j.jeconom.2020.07.021.
• Yang, Xinxin & Zheng, Xinghua & Chen, Jiaqi, 2021, "Testing high-dimensional covariance matrices under the elliptical distribution and beyond," Journal of Econometrics, Elsevier, volume 221, issue 2, pages 409-423, DOI: 10.1016/j.jeconom.2020.05.017.
• Kapetanios, G. & Pesaran, M.H. & Reese, S., 2021, "Detection of units with pervasive effects in large panel data models," Journal of Econometrics, Elsevier, volume 221, issue 2, pages 510-541, DOI: 10.1016/j.jeconom.2020.05.001.
• Ding, Yi & Li, Yingying & Zheng, Xinghua, 2021, "High dimensional minimum variance portfolio estimation under statistical factor models," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 502-515, DOI: 10.1016/j.jeconom.2020.07.013.
• Jin, Sainan & Miao, Ke & Su, Liangjun, 2021, "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 745-777, DOI: 10.1016/j.jeconom.2020.08.002.
• Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021, "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, volume 225, issue 1, pages 2-26, DOI: 10.1016/j.jeconom.2021.03.012.
• Di Iorio, Francesca & Fachin, Stefano, 2021, "Evaluating restricted common factor models for non-stationary data," Econometrics and Statistics, Elsevier, volume 17, issue C, pages 64-75, DOI: 10.1016/j.ecosta.2020.10.004.
• Cavallari, Lilia & Romano, Simone & Naticchioni, Paolo, 2021, "The original sin: Firms’ dynamics and the life-cycle consequences of economic conditions at birth," European Economic Review, Elsevier, volume 138, issue C, DOI: 10.1016/j.euroecorev.2021.103844.
• Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021, "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, volume 63, issue C, pages 252-269, DOI: 10.1016/j.jempfin.2021.07.009.
• Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021, "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, volume 102, issue C, DOI: 10.1016/j.eneco.2021.105494.
• Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021, "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, volume 96, issue C, DOI: 10.1016/j.eneco.2021.105118.
• Nam, Kyungsik, 2021, "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, volume 96, issue C, DOI: 10.1016/j.eneco.2021.105123.
• Strauss, Ilan & Yang, Jangho, 2021, "Slowing investment rates in developing economies: Evidence from a Bayesian hierarchical model," International Review of Financial Analysis, Elsevier, volume 77, issue C, DOI: 10.1016/j.irfa.2021.101843.
• Shynkevich, Andrei, 2021, "Bitcoin arbitrage," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101698.
• Joo, Young C. & Park, Sung Y., 2021, "Optimal portfolio selection using a simple double-shrinkage selection rule," Finance Research Letters, Elsevier, volume 43, issue C, DOI: 10.1016/j.frl.2021.102019.
• Avanzi, Benjamin & Taylor, Greg & Wang, Melantha & Wong, Bernard, 2021, "SynthETIC: An individual insurance claim simulator with feature control," Insurance: Mathematics and Economics, Elsevier, volume 100, issue C, pages 296-308, DOI: 10.1016/j.insmatheco.2021.06.004.
• Avanzi, Benjamin & Taylor, Greg & Wong, Bernard & Yang, Xinda, 2021, "On the modelling of multivariate counts with Cox processes and dependent shot noise intensities," Insurance: Mathematics and Economics, Elsevier, volume 99, issue C, pages 9-24, DOI: 10.1016/j.insmatheco.2021.01.002.
• Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021, "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, volume 37, issue 1, pages 360-377, DOI: 10.1016/j.ijforecast.2020.06.006.
• Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021, "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, volume 37, issue 2, pages 941-948, DOI: 10.1016/j.ijforecast.2020.10.005.
• Chan, Joshua C.C., 2021, "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, volume 37, issue 3, pages 1212-1226, DOI: 10.1016/j.ijforecast.2021.01.002.
• Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021, "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, volume 37, issue 4, pages 1338-1354, DOI: 10.1016/j.ijforecast.2021.05.005.
• Hillen, Judith & Fedoseeva, Svetlana, 2021, "E-commerce and the end of price rigidity?," Journal of Business Research, Elsevier, volume 125, issue C, pages 63-73, DOI: 10.1016/j.jbusres.2020.11.052.
• Brettschneider, Julia & Burro, Giovanni & Henderson, Vicky, 2021, "Wide framing disposition effect: An empirical study," Journal of Economic Behavior & Organization, Elsevier, volume 185, issue C, pages 330-347, DOI: 10.1016/j.jebo.2021.03.003.
• Painter, Marcus & Qiu, Tian, 2021, "Political beliefs affect compliance with government mandates," Journal of Economic Behavior & Organization, Elsevier, volume 185, issue C, pages 688-701, DOI: 10.1016/j.jebo.2021.03.019.
• Godzinski, Alexandre & Suarez Castillo, Milena, 2021, "Disentangling the effects of air pollutants with many instruments," Journal of Environmental Economics and Management, Elsevier, volume 109, issue C, DOI: 10.1016/j.jeem.2021.102489.
• Hirche, Martin & Farris, Paul W. & Greenacre, Luke & Quan, Yiran & Wei, Susan, 2021, "Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship," Journal of Retailing, Elsevier, volume 97, issue 4, pages 697-714, DOI: 10.1016/j.jretai.2021.04.002.
• Martins, Pedro S., 2021, "Working to get fired? Unemployment benefits and employment duration," Journal of Policy Modeling, Elsevier, volume 43, issue 5, pages 1016-1030, DOI: 10.1016/j.jpolmod.2021.03.004.
• Turrell, Arthur & Speigner, Bradley & Copple, David & Djumalieva, Jyldyz & Thurgood, James, 2021, "Is the UK’s productivity puzzle mostly driven by occupational mismatch? An analysis using big data on job vacancies," Labour Economics, Elsevier, volume 71, issue C, DOI: 10.1016/j.labeco.2021.102013.
• Brownlees, Christian & Hans, Christina & Nualart, Eulalia, 2021, "Bank credit risk networks: Evidence from the Eurozone," Journal of Monetary Economics, Elsevier, volume 117, issue C, pages 585-599, DOI: 10.1016/j.jmoneco.2020.03.014.
• Tissaoui, Kais & Zaghdoudi, Taha, 2021, "Dynamic connectedness between the U.S. financial market and Euro-Asian financial markets: Testing transmission of uncertainty through spatial regressions models," The Quarterly Review of Economics and Finance, Elsevier, volume 81, issue C, pages 481-492, DOI: 10.1016/j.qref.2020.10.020.
• Garciga, Christian & Verbrugge, Randal, 2021, "Robust covariance matrix estimation and identification of unusual data points: New tools," Research in Economics, Elsevier, volume 75, issue 2, pages 176-202, DOI: 10.1016/j.rie.2021.03.001.
• Roshen Fernando & Weifeng Liu & Warwick J McKibbin, 2021, "Global economic impacts of climate shocks, climate policy and changes in climate risk assessment," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-37, Apr.
• Christiane Baumeister & Danilo Leiva-León & Eric Sims, 2021, "Tracking weekly state-level economic conditions," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-55, Jul.
• Hanol Lee & Jong-Wha Lee, 2021, "Why East Asian students perform better in mathematics than their peers: An investigation using a machine learning approach," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-66, Jul.
• Florence Jaumotte & Weifeng Liu & Warwick J. McKibbin, 2021, "Mitigating climate change: Growth-friendly policies to achieve net zero emissions by 2050," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2021-75, Aug.
• Jieyi Kang & David Reiner, 2021, "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG2112, May.
• Jieyi Kang & David Reiner, 2021, "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG2113, May.
• Jieyi Kang & David Reiner, 2021, "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG2114, May.
• Krzysztof Marcjan & Lucjan Gucma & Kotkowska Diana, 2021, "The Collision Risk Management Method for Ships Navigating on Coastal Waters Based on Ship Domain and Near-Miss Concept," European Research Studies Journal, European Research Studies Journal, volume 0, issue 4 - Part , pages 127-146.
• Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2021, "Commodity price uncertainty comovement: Does it matter for global economic growth?," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 30945, Aug.
• Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021, "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers, European Xtramile Centre of African Studies (EXCAS), number 21/074, Jan.
• Lenka Nechvatalova, 2021, "Multi-Horizon Equity Returns Predictability via Machine Learning," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2021/02, Feb, revised Feb 2021.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022, "Macroeconomic Forecasting in a Multi-country Context," Working Papers, Federal Reserve Bank of Cleveland, number 22-02, Feb, DOI: 10.26509/frbc-wp-202202.
• Hie Joo Ahn & Matteo Luciani, 2021, "Relative prices and pure inflation since the mid-1990s," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2021-069, Oct, DOI: 10.17016/FEDS.2021.069.
• Simon Freyaldenhoven, 2021, "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers, Federal Reserve Bank of Philadelphia, number 21-15, Apr, DOI: 10.21799/frbp.wp.2021.15.
• Massimo Franchi & Paolo Paruolo, 2021, "Cointegration, Root Functions and Minimal Bases," Econometrics, MDPI, volume 9, issue 3, pages 1-27, August.
• Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021, "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, volume 3, issue 4, pages 1-30, October.
• Joelle Noailly; Laura Nowzohour; Matthias van den Heuvel, 2021, "Heard the News? Environmental Policy and Clean Investments," CIES Research Paper series, Centre for International Environmental Studies, The Graduate Institute, number 70-2021, Nov.
• Hager Ben Romdhane, 2021, "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 11-2021, Jun.
• Tetiana Yukhymenko, 2021, "Role of the Media in the Inflation Expectation Formation Process," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 13-2021, Jun.
• Christophe Hurlin & Christophe Perignon & Sébastien Saurin, 2021, "The Fairness of Credit Scoring Models," Working Papers, HAL, number hal-03501452, May, DOI: 10.2139/ssrn.3785882.
• Hansson, Magnus, 2021, "Evolution of topics in central bank speech communication," Working Papers in Economics, University of Gothenburg, Department of Economics, number 811, Oct.
• Amberg, Niklas & Jansson, Thomas & Klein, Mathias & Rogantini Picco, Anna, 2021, "Five Facts about the Distributional Income Effects of Monetary Policy," Working Paper Series, Sveriges Riksbank (Central Bank of Sweden), number 403, May.
• Camino Gonz lez Vasco & Mar a Jes s Delgado Rodr guez & Sonia de Lucas Santos, 2021, "Segmentation of Potential Fraud Taxpayers and Characterization in Personal Income Tax Using Data Mining Techniques," Hacienda Pública Española / Review of Public Economics, IEF, volume 239, issue 4, pages 127-157, November.
• Hartl, Tobias & Hutter, Christian & Weber, Enzo, 2021, "Matching for three: big data evidence on search activity of workers, firms, and employment service," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202101, Jan.
• Hutter, Christian, 2021, "Cyclicality of labour market search: a new big data Approach," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], volume 55, issue , pages 1-001, DOI: 10.1186/s12651-020-00283-9.
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• François Gardes, 2021, "Endogenous Prices in a Riemannian Geometry Framework," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 21026, Jul.
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• Vasil Marchev, 2021, "Self-Perfecting Model for Managing Individualized Investment Portfolios," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 86-97, December.
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• Şeuleanu Dragoş, 2021, "The Communication Dimension of the Business Model Applied to the ELI-NP Project," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 02, June.
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