Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2020

• Castellares, Renzo & Cornejo, Gerson, 2020, "A Leading Indicator for Employment using Big Data," Working Papers, Banco Central de Reserva del Perú, number 2020-009, Jun.
• J. James Reade & Carl Singleton & Leighton Vaughan Williams, 2020, "Betting markets for English Premier League results and scorelines: evaluating a forecasting model," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2020-03, Mar.
• Andrew Clark, 2020, "A Pound Centric look at the Pound vs. Krona Exchange Rate Movement from 1844 to 1965," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2020-22, Oct.
• Michael P. Clements, 2020, "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2020-01, Jan.
• Michael P. Clements, 2020, "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2020-02, Jan.
• Bejarano-Salcedo, Valeria & Cárdenas-Cárdenas, Julián Alonso & Julio-Román, Juan Manuel & Caicedo-García, Edgar, 2020, "Entendiendo, Modelando y Pronosticando los efectos de "El Niño" sobre los precios de los alimentos: el caso colombiano," Working papers, Red Investigadores de Economía, number 50, Jun.
• Avela, Aleksi & Lehmus, Markku, 2020, "It’s in the News: Developing a Real Time Index for Economic Uncertainty Based on Finnish News Titles," ETLA Working Papers, The Research Institute of the Finnish Economy, number 84, Dec.
• Yuri Balagula, 2020, "Forecasting daily spot prices in the Russian electricity market with the ARFIMA model," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 57, pages 89-101.
• Dean Fantazzini, 2020, "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 59, pages 33-54.
• Diana Petrova & Pavel Trunin, 2020, "Revealing the mood of economic agents based on search queries," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 59, pages 71-87.
• Ivan Stankevich, 2020, "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 59, pages 113-127.
• Agata Lozinskaia & Anastasiia Redkina & Evgeniia Shenkman, 2020, "Electricity consumption forecasting for integrated power system with seasonal patterns," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 60, pages 5-25.
• Necmettin Alpay Kocak, 2020, "Analysis of the Relationship between Household and Real Sector Expectations in Turkey (Türkiye’de Hanehalkı ve Reel Sektör Beklentileri Arasındaki İlişkinin Analizi)," Business and Economics Research Journal, Bursa Uludag University, Faculty of Economics and Administrative Sciences, volume 11, issue 4, pages 989-1000.
• Kriti Mahajan & Anand Srinivasan, 2020, "Inflation Forecasting In Emerging Markets: A Machine Learning Approach," Working Papers, Centre for Advanced Financial Research and Learning (CAFRAL), number 022296, Feb.
• Yann Bilodeau, 2020, "Deep limit order book events dynamics," Working Papers, HEC Montreal, Canada Research Chair in Risk Management, number 20-4, Dec.
• S.A Hoseeini Ebrahimabad & Kh Jahangiri & M Ghaemi Asl & H Heydari, 2020, "Investigation of the volatility spillover effect and dynamic conditional correlations in Tehran Stock Exchange using wavelet-based Bayesian conditional variance heteroscedasticity," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 7, issue 1, pages 149-184.
• Leila Eghbali & Reza Ranjpour & Seyed Kamal Sadeghi, 2020, "Granger Causality Analysis of Energy Consumption and Value Added in Industrial Sub-Sectors of Iran: A Bootstrap Panel Approach," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 7, issue 3, pages 99-130.
• David Conaly Martinez Vázques Héctor Pérez Ávila, 2020, "Análisis microeconómico del seguro contra terremoto en México y estimación estocástica de riesgos sísmicos
  [Microeconomic Analysis of Earthquake Insurance in Mexico and Stochastic Estimation of Seismic Risks]," Revista Nicolaita de Estudios Económicos, Universidad Michoacana de San Nicolás de Hidalgo, Instituto de Investigaciones Económicas y Empresariales, volume 0, issue 2, pages 101-118, July, DOI: https://rnee.umich.mx/index.php/rne.
• Yue Qiu & Tian Xie & Jun Yu, 2020, "Forecast combinations in machine learning," Economics and Statistics Working Papers, Singapore Management University, School of Economics, number 13-2020, May.
• Nikola RADIVOJEVIĆ & Luka FILIPOVI & Тomislav D. BRZAKOVIĆ, 2020, "A New Semiparametric Mirrored Historical Simulation Value-At-Risk Model," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 1, pages 5-21, March.
• Dalia STREIMIKIENE & Rizwan Raheem AHMED & Saghir Pervaiz GHAURI & Muhammad AQIL & Justas STREIMIKIS, 2020, "Forecasting and the Causal Relationship of Sectorial Energy Consumptions and GDP of Pakistan by using AR, ARIMA, and Toda-Yamamoto Wald Models," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 131-148, July.
• Krzysztof DRACHAL, 2020, "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 18-34, July.
• Costas Siriopoulos & Maria Skaperda, 2020, "Investing in mutual funds: are you paying for performance or for the ties of the manager?," Bulletin of Applied Economics, Risk Market Journals, volume 7, issue 2, pages 153-164.
• Balazs Pager & Zsuzsanna Zsibókb, 2020, "Regionalizing National-Level Growth Projections in the Visegrad Countries – The Issue Of Ex-Post Rescaling," Romanian Journal of Regional Science, Romanian Regional Science Association, volume 14, issue 1, pages 1-24, JUNE.
• Tommaso Proietti & Alessandro Giovannelli, 2020, "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper, Tor Vergata University, CEIS, number 482, May, revised 12 May 2020.
• Alessandro Giovannelli & Tommaso Proietti & Ambra Citton & Ottavio Ricchi & Cristian Tegami & Cristina Tinti, 2020, "Nowcasting GDP and its Components in a Data-rich Environment: the Merits of the Indirect Approach," CEIS Research Paper, Tor Vergata University, CEIS, number 489, May, revised 30 May 2020.
• Robert Wrathall & Rod Falvey & Gulasekaran Rajaguru, 2020, "Do (Australian) jockeys have hot hands?," Australian Journal of Management, Australian School of Business, volume 45, issue 2, pages 223-239, May, DOI: 10.1177/0312896219883675.
• P. K. Viswanathan & Suresh Srinivasan & N. Hariharan, 2020, "Predicting Financial Health of Banks for Investor Guidance Using Machine Learning Algorithms," Journal of Emerging Market Finance, Institute for Financial Management and Research, volume 19, issue 2, pages 226-261, August, DOI: 10.1177/0972652720913478.
• Mar Delgado-Téllez & Javier J. Pérez, 2020, "Institutional and Economic Determinants of Regional Public Debt in Spain," Public Finance Review, , volume 48, issue 2, pages 212-249, March, DOI: 10.1177/1091142120901672.
• Yu. Beketnova M. & Ю. Бекетнова М., 2020, "Синтез социально-экономических карт и визуализация девиантной деятельности объектов финансового мониторинга // Synthesis of Socio-Economic Maps and Visualization of Deviant Activity Measures of Financial Monitoring of Entities," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, volume 24, issue 4, pages 6-17.
• Yu. Beketnova M. & Ю. Бекетнова М., 2020, "Анализ возможностей автоматизации выявления недобросовестных микрофинансовых организаций на основе методов машинного обучения // Analysis of Possibilities to Automate Detection of Unscrupulous Microfinance Organizations based on Machine learning Meth," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, volume 24, issue 6, pages 38-50.
• Andreas Psimopoulos, 2020, "Forecasting Economic Recessions Using Machine Learning:An Empirical Study in Six Countries," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, volume 18, issue 1, pages 40-99.
• Martínez Vázquez, David Conaly & Pérez Avila, Héctor, 2020, "Proyección Markoviana de riesgos hidrometeorológicos para el cálculo actuarial en México al 2020 / Markovian projection of hydrometeorological risks for actuarial calculation in Mexico up to 2020," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, volume 10, issue 2, pages 163-194, julio-dic.
• Henry Nasses & Rodrigo De Losso, 2020, "Behavior Biases in Macroeconomic Forecasting," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2020_23, Nov.
• Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020, "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, volume 24, issue 2, pages 66-103, June.
• Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020, "Targeting predictors in random forest regression," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2020-03, May.
• Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2020, "A statistical model of the global carbon budget," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2020-18, Dec.
• Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020, "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2020-19, Dec.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2020, "Forecasting the US Dollar-Korean Won Exchange Rate: A Factor-Augmented Model Approach," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2020-02, May.
• Glyn Wittwer & Kym Anderson, 2020, "A Model of Global Beverage Markets," Wine Economics Research Centre Working Papers, University of Adelaide, Wine Economics Research Centre, number 2019-05, Feb.
• Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2020, "Overreaction in Macroeconomic Expectations," American Economic Review, American Economic Association, volume 110, issue 9, pages 2748-2782, September, DOI: 10.1257/aer.20181219.
• Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2020, "Heterogeneity, Inattention, and Bayesian Updates," American Economic Journal: Macroeconomics, American Economic Association, volume 12, issue 1, pages 282-309, January, DOI: 10.1257/mac.20180235.
• Stefano DellaVigna & Nicholas Otis & Eva Vivalt, 2020, "Forecasting the Results of Experiments: Piloting an Elicitation Strategy," AEA Papers and Proceedings, American Economic Association, volume 110, pages 75-79, May, DOI: 10.1257/pandp.20201080.
• Javier Alejo & Antonio F. Galvao & Gabriel Montes-Rojas, 2020, "A first-stage test for instrumental variables quantile regression," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4304, Nov.
• J. Daniel Aromí & Martín Llada, 2020, "Forecasting inflation with twitter," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4308, Nov.
• Emilio Blanco & Laura D’Amato & Fiorella Dogliolo & Lorena Garegnani, 2020, "Nowcasting Macroeconomic Aggregates in Argentina: Comparing the predictive ability of different models," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4335, Nov.
• Maria Morena Rivera, 2020, "Estimación de Demanda de Milanesas de Cerdo y estudio de viabilidad financiera del proyecto: “Elaboración y comercialización de milanesas de cerdo para Piamontesa SA”," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4398, Nov.
• Tamar Mdivnishvili & Shalva Mkhatrishvili & Davit Tutberidze, 2020, "Cash Flow at Risk Assessment for the Banking Sector of Georgia," NBG Working Papers, National Bank of Georgia, number 03/2020, Jul.
• Olivier Damette & Claude Diebolt & Stephane Goutte & Umberto Triacca, 2020, "Cliometrics of Climate Change: A Natural Experiment on the Little Ice Age," Working Papers, Association Française de Cliométrie (AFC), number 02-20.
• Enrico D’Elia & Francesca Faedda & Giacomo Giannone, 2020, "Un modello statistico per il monitoraggio delle entrate tributarie (MoME)," Working Papers, Ministry of Economy and Finance, Department of Finance, number wp2020-5, May.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020, "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/20/01, Feb.
• Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020, "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/20/02, Feb.
• Tao Hong & Pierre Pinson & Yi Wang & Rafal Weron & Dazhi Yang & Hamidreza Zareipour, 2020, "Energy forecasting: A review and outlook," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/20/08, May.
• Tomasz Serafin & Grzegorz Marcjasz & Rafal Weron, 2020, "Trading on short-term path forecasts of intraday electricity prices," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/20/17, Dec.
• Gürcan Aygün, 2020, "Parasal Değişkenler ve Çıktı İlişkisinin Türkiye İçin Tarihsel Ayrıştırma Yöntemi İle Analizi," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 5, issue 2, pages 228-241, DOI: 10.30784/epfad.737602.
• Ceyda Yerdelen Kaygın & Abdulkadir Barut, 2020, "Çifte Kayıtlı Hisse Senetlerinin Fiyatlarını Etkileyen İçsel Faktörlerin Dinamik Panel Veri Analizi İle Belirlenmesi," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 5, issue 3, pages 805-821, DOI: 10.30784/epfad.773057.
• Crăciun Ionuț-Marius, 2020, "Study On The Evolution Of The Number Of People With Disabilities In Romania," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, volume 1, issue 48, pages 71-86, August.
• Ph. D Student Denisa Gae, 2020, "Assessment Of The Risk Of Bankruptcy Of The Companies With The Help Of The Economic-Financial Indicators," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, volume 1, issue 34, pages 38-51, April.
• Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020, "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series, Monash University, number 2020-04, Oct.
• Adolfo Rodríguez-Vargas, 2020, "Forecasting Costa Rican Inflation with Machine Learning Methods," Documentos de Trabajo, Banco Central de Costa Rica, number 2002, Mar.
• Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020, "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 2012001, Jan, revised Jan 2020.
• Ji Hyung Lee & Youngki Shin, 2020, "Complete Subset Averaging for Quantile Regressions," Papers, arXiv.org, number 2003.03299, Mar, revised Jul 2021.
• Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020, "Targeting predictors in random forest regression," Papers, arXiv.org, number 2004.01411, Apr, revised Nov 2020.
• Wei-Zhen Li & Jin-Rui Zhai & Zhi-Qiang Jiang & Gang-Jin Wang & Wei-Xing Zhou, 2020, "Predicting tail events in a RIA-EVT-Copula framework," Papers, arXiv.org, number 2004.03190, Apr, revised Apr 2020.
• Pietro Battiston & Simona Gamba, 2020, "COVID-19: $R_0$ is lower where outbreak is larger," Papers, arXiv.org, number 2004.07827, Apr.
• Dimitris Korobilis, 2020, "High-dimensional macroeconomic forecasting using message passing algorithms," Papers, arXiv.org, number 2004.11485, Apr.
• Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020, "A dynamic conditional approach to portfolio weights forecasting," Papers, arXiv.org, number 2004.12400, Apr.
• Andreas Dibiasi & Samad Sarferaz, 2020, "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers, arXiv.org, number 2006.09007, Jun, revised Dec 2020.
• Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2020, "A Model of the Fed's View on Inflation," Papers, arXiv.org, number 2006.14110, Jun.
• Laurent Ferrara & Anna Simoni, 2020, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers, arXiv.org, number 2007.00273, Jul, revised Sep 2022.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020, "Deep Dynamic Factor Models," Papers, arXiv.org, number 2007.11887, Jul, revised May 2023.
• Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020, "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers, arXiv.org, number 2007.13566, Jul, revised Dec 2022.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020, "Macroeconomic Data Transformations Matter," Papers, arXiv.org, number 2008.01714, Aug, revised Mar 2021.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020, "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers, arXiv.org, number 2008.12477, Aug.
• Florian Huber & Gary Koop & Luca Onorante & Michael Pfarrhofer & Josef Schreiner, 2020, "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Papers, arXiv.org, number 2008.12706, Aug, revised Dec 2020.
• Mykola Babiak & Jozef Barunik, 2020, "Deep Learning, Predictability, and Optimal Portfolio Returns," Papers, arXiv.org, number 2009.03394, Sep, revised Feb 2026.
• Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020, "Optimal probabilistic forecasts: When do they work?," Papers, arXiv.org, number 2009.09592, Sep.
• Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020, "Robust Forecasting," Papers, arXiv.org, number 2011.03153, Nov, revised Dec 2020.
• Oren Barkan & Jonathan Benchimol & Itamar Caspi & Eliya Cohen & Allon Hammer & Noam Koenigstein, 2020, "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Papers, arXiv.org, number 2011.07920, Nov, revised Feb 2022.
• Dario Sansone & Anna Zhu, 2020, "Using Machine Learning to Create an Early Warning System for Welfare Recipients," Papers, arXiv.org, number 2011.12057, Nov, revised May 2021.
• Victor Olkhov, 2020, "Business Cycles as Collective Risk Fluctuations," Papers, arXiv.org, number 2012.04506, Dec.
• Ricardo Cris'ostomo, 2020, "Estimating real-world probabilities: A forward-looking behavioral framework," Papers, arXiv.org, number 2012.09041, Dec, revised Jan 2021.
• Monica Billio & Roberto Casarin & Enrica De Cian & Malcolm Mistry & Anthony Osuntuyi, 2020, "The impact of Climate on Economic and Financial Cycles: A Markov-switching Panel Approach," Papers, arXiv.org, number 2012.14693, Dec.
• Fatemi Ardestani, Seyed Farshad & Barakchian, Seyed Mahdi & Shokoohian, Hamideh, 2020, "Short-term Forecast of Hourly Electricity Demand in Iran Using a Forecast Combination Method (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, volume 24, issue 4, pages 57-73, February.
• Massimo Guidolin & Manuela Pedio, 2020, "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 20145.
• Massimo Guidolin & Alexei Orlov, 2020, "Are Unconventional Monetary Policies a Priced Risk Factor for Hedge Fund Strategies?," BAFFI CAREFIN Working Papers, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy, number 20146.
• Olga Palamarchuk, 2020, "The Use Of Fuzzy Logic While Modeling The Creditworthiness Of Legal Entities," Green, Blue & Digital Economy Journal, Publishing house "Baltija Publishing", volume 1, issue 2, DOI: 10.30525/2661-5169/2020-2-10.
• Nataliya Vnukova & Sergii Kavun & Oleh Kolodiziev & Svitlana Achkasova & Daria Hontar, 2020, "Indicators-Markers for Assessment of Probability of Insurance Companies Relatedness in Implementation of Risk-Oriented Approach," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 151-173.
• Anton Gerunov, 2020, "Classification algorithms for modeling economic choice," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 45-67.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020, "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-01, Apr, revised Aug 2020.
• Rachidi Kotchoni & Dalibor Stevanovic, 2020, "GDP Forecast Accuracy During Recessions," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-06, May.
• Claudia Foroni & Massimiliano Marcellino & Dalibor Stevanovic, 2020, "Forecasting the COVID-19 recession and recovery: Lessons from the financial crisis," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-14, Jun, revised Nov 2020.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020, "Macroeconomic Data Transformations Matter," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-17, Aug, revised Mar 2021.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Toure, 2020, "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 20-18, Sep, revised Dec 2020.
• Ionut Laurentiu Gavris & Valentin Toader, 2020, "Romania’S Long-Term Growth Perspectives," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
• Jinyue Dong, 2020, "China | Forecasting modeling for China\'s inflation," Working Papers, BBVA Bank, Economic Research Department, number 20/05, Mar.
• Félix Lores & Pep Ruiz & Angie Suárez & Alfonso Ugarte, 2020, "Spain | Model for housing prices. A regional perspective," Working Papers, BBVA Bank, Economic Research Department, number 20/12, Oct.
• Amor Aniss Benmoussa & Reinhard Ellwanger & Stephen Snudden, 2020, "The New Benchmark for Forecasts of the Real Price of Crude Oil," Staff Working Papers, Bank of Canada, number 20-39, Sep, DOI: 10.34989/swp-2020-39.
• Necmettin Alpay KOCAK, 2020, "Are CBRT’s Monetary Policy Statements Affected by ECB and FED Statements?," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 14, issue 2, pages 205-226.
• Banco de España, 2020, "Escenarios macroeconómicos de referencia para la economía española tras el Covid-19," Boletín Económico, Banco de España, issue 2/2020.
• Pablo Aguilar, 2020, "La persistencia de la inflación en el área del euro: el papel de las expectativas," Boletín Económico, Banco de España, issue 4/2020.
• Banco de España, 2020, "Reference macroeconomic scenarios for the Spanish economy after Covid-19," Economic Bulletin, Banco de España, issue 2/2020.
• Pablo Aguilar, 2020, "Inflation persistence in the euro area: the role of expectations," Economic Bulletin, Banco de España, issue 4/2020.
• Eduardo Gutiérrez & Enrique Moral-Benito, 2020, "Medidas de contención, evolución del empleo y propagación del Covid-19 en los municipios españoles," Occasional Papers, Banco de España, number 2022, Aug.
• Eduardo Gutiérrez & Enrique Moral-Benito, 2020, "Containment measures, employment and the spread of COVID-19 in Spanish municipalities," Occasional Papers, Banco de España, number 2022, Aug.
• Mar Delgado-Téllez & Esther Gordo & Iván Kataryniuk & Javier J. Pérez, 2020, "The decline in public investment: “social dominance” or too-rigid fiscal rules?," Working Papers, Banco de España, number 2025, Jul.
• Pablo Aguilar & Corinna Ghirelli & Matías Pacce & Alberto Urtasun, 2020, "Can news help measure economic sentiment? An application in COVID-19 times," Working Papers, Banco de España, number 2027, Aug.
• Andrés Alonso & José Manuel Carbó, 2020, "Machine learning in credit risk: measuring the dilemma between prediction and supervisory cost," Working Papers, Banco de España, number 2032, Oct.
• Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020, "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers, Banco de España, number 2042, Dec.
• Ivan Faiella & Alessandro Mistretta, 2020, "Energy costs and competitiveness in Europe," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1259, Feb.
• Fabio Busetti & Michele Caivano & Davide Delle Monache & Claudia Pacella, 2020, "The time-varying risk of Italian GDP," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1288, Jul.
• Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020, "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1296, Sep.
• Lelo de Larrea Alejandra, 2020, "Forecast Comparison of the Term Structure of Interest Rates of Mexico for Different Specifications of the Affine Model," Working Papers, Banco de México, number 2020-01, Mar.
• Hernández Juan R., 2020, "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," Working Papers, Banco de México, number 2020-02, Mar.
• Benavides Guillermo, 2020, "Asymmetric Volatility Effects in Risk Management: An Empirical Analysis using a Stock Index Futures," Working Papers, Banco de México, number 2020-10, Sep.
• Aguilar-Argaez Ana María & Diego-Fernández Forseck María & Elizondo Rocío & Roldán-Peña Jessica, 2020, "Term Premium Dynamics and its Determinants: The Mexican Case," Working Papers, Banco de México, number 2020-18, Dec.
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