Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C1: Econometric and Statistical Methods and Methodology: General
/ / / C11: Bayesian Analysis: General

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This JEL code is mentioned in the following RePEc Biblio entries:

1. Bayesian Vector autoregressions (BVARs)

2022

• Rubén Loaiza-Maya & Didier Nibbering, 2022, "Scalable Bayesian Estimation in the Multinomial Probit Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 4, pages 1678-1690, October, DOI: 10.1080/07350015.2021.1961788.
• Wei Huang & Oliver Linton & Zheng Zhang, 2022, "A Unified Framework for Specification Tests of Continuous Treatment Effect Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 4, pages 1817-1830, October, DOI: 10.1080/07350015.2021.1981915.
• Young Min Kim & Seojin Lee, 2022, "Korean exchange rate forecasts using Bayesian variable selection," Asia-Pacific Journal of Accounting & Economics, Taylor & Francis Journals, volume 29, issue 4, pages 1045-1062, July, DOI: 10.1080/16081625.2019.1653777.
• Ivan Huljak & Reiner Martin & Diego Moccero & Cosimo Pancaro, 2022, "Do non-performing loans matter for bank lending and the business cycle in euro area countries?," Journal of Applied Economics, Taylor & Francis Journals, volume 25, issue 1, pages 1050-1080, December, DOI: 10.1080/15140326.2022.2094668.
• Nguyen, BH & Zhang, Bo, 2022, "Forecasting oil Prices: can large BVARs help?," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2022-04.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman van Dijk, 2022, "A Flexible Predictive Density Combination Model for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 22-013/III, Feb.
• Giuseppe De Luca & Jan Magnus & Franco Peracchi, 2022, "Asymptotic properties of the weighted average least squares (WALS) estimator," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 22-022/III, Feb.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2022, "A Flexible Predictive Density Combination for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 22-053/III, Aug.
• Mike Gilraine & Jiaying Gu & Robert McMillan, 2022, "A Nonparametric Approach for Studying Teacher Impacts," Working Papers, University of Toronto, Department of Economics, number tecipa-716, Jan.
• Chih-Sheng Hsieh & Michael D. Konig & Xiaodong Liu, 2022, "A Structural Model for the Coevolution of Networks and Behavior," The Review of Economics and Statistics, MIT Press, volume 104, issue 2, pages 355-367, May, DOI: 10.1162/rest_a_00958.
• Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022, "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, volume 104, issue 4, pages 686-704, October, DOI: 10.1162/rest_a_00974.
• Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022, "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, volume 104, issue 4, pages 828-844, October, DOI: 10.1162/rest_a_00977.
• Décamps, Jean-Paul & Villeneuve, Stéphane, 2022, "Learning about profitability and dynamic cash management," TSE Working Papers, Toulouse School of Economics (TSE), number 22-1301, Feb.
• Behnam Azhdari & Jean Bonnet & Sébastien Bourdin, 2022, "Towards a Causal Model and Causal Inference of Regional Entrepreneurship Development Index, its antecedents and outcomes in European regions," 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 2022-06, Sep.
• Celso José Costa Junior & Anderson Mutter Teixeira & Márcio Francisco da Silva, 2022, "DSGE para Macroeconomia Regional: Uma Aplicação para o Estado de Goiás," Working papers - Textos para Discussao do Curso de Ciencias Economicas da UFG, Curso de Ciencias Economicas da Universidade Federal de Goias - FACE, number 097, May.
• Tuncer Murathan & Akbulut Nesrin & Turhan Miraç Savaş & Ari Yakup, 2022, "Time-Varying Network Connectedness Between the Organizational Ecology of Transportation and Storage Firms and Macroeconomic Variables," Folia Oeconomica Stetinensia, Paradigm, volume 22, issue 2, pages 209-223, December, DOI: 10.2478/foli-2022-0027.
• Sulejmani Artan & Tevdovski Dragan, 2022, "How the Contagion is Transmitted to the Macedonian Stock Market? an Analysis of Co-Exceedances," South East European Journal of Economics and Business, Paradigm, volume 17, issue 1, pages 1-13, June, DOI: 10.2478/jeb-2022-0001.
• Andrzej Kocięcki & Tomasz Łyziak & Ewa Stanisławska, 2022, "Subjective Expectations and Uncertainty," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-10.
• Castaing,Pauline & Gazeaud,Jules, 2022, "Do Index Insurance Programs Live Up to Their Promises ? Aggregating Evidence from Multiple Experiments," Policy Research Working Paper Series, The World Bank, number 10161, Sep.
• Timothy B. Armstrong & Michal Kolesár & Mikkel Plagborg‐Møller, 2022, "Robust Empirical Bayes Confidence Intervals," Econometrica, Econometric Society, volume 90, issue 6, pages 2567-2602, November, DOI: 10.3982/ECTA18597.
• Malin Gardberg & Lorenzo Pozzi, 2022, "Aggregate consumption and wealth in the long run: The impact of financial liberalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 1, pages 161-186, January, DOI: 10.1002/jae.2870.
• Martijn van Hasselt & Christopher R. Bollinger & Jeremy W. Bray, 2022, "A Bayesian approach to account for misclassification in prevalence and trend estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 2, pages 351-367, March, DOI: 10.1002/jae.2879.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022, "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 3, pages 583-602, April, DOI: 10.1002/jae.2889.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022, "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 6, pages 1230-1255, September, DOI: 10.1002/jae.2923.
• Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2022, "Bayesian estimation of multivariate panel probits with higher‐order network interdependence and an application to firms' global market participation in Guangdong," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 7, pages 1356-1378, November, DOI: 10.1002/jae.2934.
• Na Guo & Bo Zhang & Jamie L. Cross, 2022, "Time‐varying trend models for forecasting inflation in Australia," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 2, pages 316-330, March, DOI: 10.1002/for.2814.
• Oguzhan Cepni & Riza Demirer & Rangan Gupta & Ahmet Sensoy, 2022, "Interest rate uncertainty and the predictability of bank revenues," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 8, pages 1559-1569, December, DOI: 10.1002/for.2884.
• Martin Mandler & Michael Scharnagl & Ute Volz, 2022, "Heterogeneity in Euro Area Monetary Policy Transmission: Results from a Large Multicountry BVAR Model," Journal of Money, Credit and Banking, Blackwell Publishing, volume 54, issue 2-3, pages 627-649, March, DOI: 10.1111/jmcb.12859.
• Neville Francis & Michael T. Owyang & Daniel Soques, 2022, "Business Cycles across Space and Time," Journal of Money, Credit and Banking, Blackwell Publishing, volume 54, issue 4, pages 921-952, June, DOI: 10.1111/jmcb.12860.
• Hirokuni Iiboshi & Mototsugu Shintani & Kozo Ueda, 2022, "Estimating a Nonlinear New Keynesian Model with the Zero Lower Bound for Japan," Journal of Money, Credit and Banking, Blackwell Publishing, volume 54, issue 6, pages 1637-1671, September, DOI: 10.1111/jmcb.12908.
• Joshua C. C. Chan, 2022, "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, volume 13, issue 3, pages 1145-1169, July, DOI: 10.3982/QE1381.
• Jinshun Wu & Taps Maiti, 2022, "A Frequency-Domain Analysis Of Medium-Scale Dsge Models," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., volume 67, issue 06, pages 1951-1986, December, DOI: 10.1142/S0217590822500229.
• Chen Zhang & Ying Fang & Linlin Niu, 2022, "Changing anchor of the renminbi: A Bayesian learning approach to the decade-long transition," Working Papers, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, number 2022-08-24, Aug.
• Nyholm, Juho & Silvo, Aino, 2022, "A model for predicting Finnish household loan stocks," BoF Economics Review, Bank of Finland, number 4/2022.
• Hartwig, Benny, 2022, "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers, Deutsche Bundesbank, number 52/2022.
• Hauber, Philipp, 2022, "Real-time nowcasting with sparse factor models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 251551.
• Yang, Zheyu, 2022, "Risk-taking and monetary policy," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 263253.
• Diegel, Max, 2022, "Time-varying credibility, anchoring and the Fed's inflation target," Discussion Papers, Free University Berlin, School of Business & Economics, number 2022/9, DOI: 10.17169/refubium-36967.
• Böhl, Gregor, 2022, "Ensemble MCMC sampling for robust Bayesian inference," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 177.
• Prüser, Jan & Blagov, Boris, 2022, "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 960, DOI: 10.4419/96973124.

2021

• Gregor Bäurle & Matthias Gubler & Diego R. Känzig, 2021, "International Inflation Spillovers: The Role of Different Shocks," International Journal of Central Banking, International Journal of Central Banking, volume 17, issue 1, pages 191-230, March.
• Nicoletta Batini & Mario di Serio & Matteo Fragetta & Mr. Giovanni Melina, 2021, "Building Back Better: How Big Are Green Spending Multipliers?," IMF Working Papers, International Monetary Fund, number 2021/087, Mar.
• Boris Chafwehé & Charles de Beauffort & Rigas Oikonomou, 2021, "Debt Management in a World of Fiscal Dominance," JRC Working Papers on Taxation & Structural Reforms, Joint Research Centre, number 2021-11, Jul.
• Belaïd, Fateh & Rault, Christophe, 2021, "Energy Expenditure in Egypt: Empirical Evidence Based on a Quantile Regression Approach," IZA Discussion Papers, IZA Network @ LISER, number 14011, Jan.
• Kline, Patrick & Rose, Evan K. & Walters, Christopher R., 2021, "Systemic Discrimination among Large U.S. Employers," IZA Discussion Papers, IZA Network @ LISER, number 14634, Aug.
• Rabia Ã-zdemir & Munevver Turanli, 2021, "Comparison of machine learning classification algorithms for purchasing forecast," JOURNAL OF LIFE ECONOMICS, Holistence Publications, volume 8, issue 1, pages .59-68, January, DOI: 10.15637/jlecon.8.1.06.
• Prüser Jan & Hanck Christoph, 2021, "A Comparison of Approaches to Select the Informativeness of Priors in BVARs," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, volume 241, issue 4, pages 501-525, August, DOI: 10.1515/jbnst-2020-0050.
• Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021, "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," JRC Working Papers in Economics and Finance, Joint Research Centre, European Commission, number 2021-01, Mar.
• Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco, 2021, "Efficient and robust inference of models with occasionally binding constraints," JRC Working Papers in Economics and Finance, Joint Research Centre, European Commission, number 2021-03, Apr.
• Cardani, Roberta & Croitorov, Olga & Giovannini, Massimo & Pfeiffer, Philipp & Ratto, Marco & Vogel, Lukas, 2021, "The Euro Area's pandemic recession: A DSGE interpretation," JRC Working Papers in Economics and Finance, Joint Research Centre, European Commission, number 2021-10, Oct.
• Kai Barron, 2021, "Belief updating: does the ‘good-news, bad-news’ asymmetry extend to purely financial domains?," Experimental Economics, Springer;Economic Science Association, volume 24, issue 1, pages 31-58, March, DOI: 10.1007/s10683-020-09653-z.
• Jinzhi Li, 2021, "Bayesian estimation of the stochastic volatility model with double exponential jumps," Review of Derivatives Research, Springer, volume 24, issue 2, pages 157-172, July, DOI: 10.1007/s11147-020-09173-1.
• A. Hachicha & F. Hachicha, 2021, "Analysis of the bitcoin stock market indexes using comparative study of two models SV with MCMC algorithm," Review of Quantitative Finance and Accounting, Springer, volume 56, issue 2, pages 647-673, February, DOI: 10.1007/s11156-020-00905-w.
• Florian Eckert & Nina Mühlebach, 2021, "Global and Local Components of Output Gaps," KOF Working papers, KOF Swiss Economic Institute, ETH Zurich, number 21-497, Nov, DOI: 10.3929/ethz-b-000514977.
• Fateh BELAID & Christophe RAULT, 2021, "Energy Expenditure in Egypt: Empirical Evidence Based on a Quantile Regression Approach," LEO Working Papers / DR LEO, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans, number 2893.
• Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2021, "Robust Dynamic Panel Data Models Using 𝛆𝛆-Contamination," Center for Policy Research Working Papers, Center for Policy Research, Maxwell School, Syracuse University, number 240, Oct.
• Didier Nibbering & Coos van Buuren & Wei Wei, 2021, "Real Options Valuation of Wind Energy Based on the Empirical Production Uncertainty," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 19/21.
• David T. Frazier & Ruben Loaiza-Maya & Gael M. Martin & Bonsoo Koo, 2021, "Loss-Based Variational Bayes Prediction," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 8/21.
• Theis Ingerslev Jensen & Bryan T. Kelly & Lasse Heje Pedersen, 2021, "Is There A Replication Crisis In Finance?," NBER Working Papers, National Bureau of Economic Research, Inc, number 28432, Feb.
• S. Borağan Aruoba & Marko Mlikota & Frank Schorfheide & Sergio Villalvazo, 2021, "SVARs With Occasionally-Binding Constraints," NBER Working Papers, National Bureau of Economic Research, Inc, number 28571, Mar.
• Minsu Chang & Xiaohong Chen & Frank Schorfheide, 2021, "Heterogeneity and Aggregate Fluctuations," NBER Working Papers, National Bureau of Economic Research, Inc, number 28853, May.
• Nan Li & Chris Papageorgiou & Tong Xu & Tao Zha, 2021, "Policy Contagion: What Do We Learn from Financial Reforms?," NBER Working Papers, National Bureau of Economic Research, Inc, number 28994, Jul.
• Patrick M. Kline & Evan K. Rose & Christopher R. Walters, 2021, "Systemic Discrimination Among Large U.S. Employers," NBER Working Papers, National Bureau of Economic Research, Inc, number 29053, Jul.
• Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021, "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," NBER Working Papers, National Bureau of Economic Research, Inc, number 29508, Nov.
• Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021, "Demand Estimation with Infrequent Purchases and Small Market Sizes," NBER Working Papers, National Bureau of Economic Research, Inc, number 29530, Dec.
• Frank Schorfheide & Dongho Song, 2021, "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," NBER Working Papers, National Bureau of Economic Research, Inc, number 29535, Dec.
• King Yoong Lim & Chunping Liu & Shuonan Zhang, 2021, "Optimal Central Banking Policies: Envisioning the Post-Digital Yuan Economy with Loan Prime Rate-setting," NBS Discussion Papers in Economics, Economics, Nottingham Business School, Nottingham Trent University, number 2021/02, Jun.
• Sanyal, Anirban & Singh, Nirvikar, 2021, "Structural Change and Economic Growth: Patterns and Heterogeneity among Indian States and Implications for a Post-COVID Recovery," India Policy Forum, National Council of Applied Economic Research, volume 17, issue 1, pages 143-198.
• Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021, "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Working Papers, NET Institute, number 21-09, Oct.
• Andrew Y. Chen & Fabian Winkler & Rebecca Wasyk, 2021, "In Full-Information Estimates, Long-Run Risks Explain at Most a Quarter of P/D Variance, and Habit Explains Even Less," Critical Finance Review, now publishers, volume 10, issue 3, pages 329-381, August, DOI: 10.1561/104.00000092.
• Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021, "Modelling and Estimating Large Macroeconomic Shocks During the Pandemic," National Institute of Economic and Social Research (NIESR) Discussion Papers, National Institute of Economic and Social Research, number 530, Jun.
• Kenji Hatakenaka & Kosuke Oya, 2021, "Bayesian inference for time varying partial adjustment model with application to intraday price discovery," Discussion Papers in Economics and Business, Osaka University, Graduate School of Economics, number 21-19, Nov.
• Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021, "Online estimation of DSGE models," The Econometrics Journal, Royal Economic Society, volume 24, issue 1, pages 33-58.
• John M Maheu & Azam Shamsi Zamenjani, 2021, "Nonparametric Dynamic Conditional Beta," Journal of Financial Econometrics, Oxford University Press, volume 19, issue 4, pages 583-613.
• Jim Griffin & Jia Liu & John M. Maheu, 2021, "Bayesian Nonparametric Estimation of Ex Post Variance
  [Out of Sample Forecasts of Quadratic Variation]," Journal of Financial Econometrics, Oxford University Press, volume 19, issue 5, pages 823-859.
• Christopher C Geczy & Robert F Stambaugh & David Levin, 2021, "Investing in Socially Responsible Mutual Funds
  [Should investors avoid all actively managed mutual funds? A study in Bayesian performance evaluation]," The Review of Asset Pricing Studies, Society for Financial Studies, volume 11, issue 2, pages 309-351.
• Simon C Smith & Allan Timmermann & Stijn Van Nieuwerburgh, 2021, "Break Risk
  [Maximum likelihood estimation of the equity premium]," The Review of Financial Studies, Society for Financial Studies, volume 34, issue 4, pages 2045-2100.
• Carlos A. Abanto-Valle & Gabriel Rodríguez & Luis M. Castro Cepero & Hernán B. Garrafa-Aragón, 2021, "Approximate Bayesian Estimation of Stochastic Volatility in Mean Models using Hidden Markov Models: Empirical Evidence from Stock Latin American Markets," Documentos de Trabajo / Working Papers, Departamento de Economía - Pontificia Universidad Católica del Perú, number 2021-502, DOI: 10.18800/2079-8474.0502.
• Ciftci, Muhsin, 2021, "Uneven Consequences of Coronavirus Pandemic: Evidence from a Real Time Survey," MPRA Paper, University Library of Munich, Germany, number 107842, Mar.
• Rikhotso, Prayer & Bonga-Bonga, Lumengo, 2021, "Exchange rate misalignments and current accounts in BRICS countries," MPRA Paper, University Library of Munich, Germany, number 107973, May.
• Koffi, Siméon, 2021, "Analyse de la politique budgétaire en Côte d’ivoire à partir d’une estimation Bayésienne d’un modèle d'Equilibre Général Dynamique Stochastique (DSGE)
  [Analysis of fiscal policy in Côte d’Ivoire using Bayesian estimation of a Dynamic Stochastic Ge," MPRA Paper, University Library of Munich, Germany, number 108751, Jul.
• Abreha, Fasika Molla & Salmasi, Luca & Ianuale, Nicola & Pegoraro, Enrico, 2021, "A Bayesian Cost-effectiveness analysis of Holobalance, Holograms for personalized virtual coaching and motivation in an ageing population with balance disorders," MPRA Paper, University Library of Munich, Germany, number 109301, Aug.
• Doojav, Gan-Ochir, 2021, "Macroeconomic modeling for optimal stabilization policy in Mongolia," MPRA Paper, University Library of Munich, Germany, number 111206, Sep.
• Korobilis, Dimitris & Shimizu, Kenichi, 2021, "Bayesian Approaches to Shrinkage and Sparse Estimation," MPRA Paper, University Library of Munich, Germany, number 111631, Dec.
• Fasano, Augusto & Rebaudo, Giovanni & Durante, Daniele & Petrone, Sonia, 2021, "A closed-form filter for binary time series," MPRA Paper, University Library of Munich, Germany, number 122349.
• Matteo Ciccarelli & Fulvia Marotta, 2021, "Demand or Supply? An empirical exploration of the effects of climate change on the macroeconomy," Working Papers, Queen Mary University of London, School of Economics and Finance, number 933, Dec.
• Pérez Forero, Fernando, 2021, "Predicción de variables macroeconómicas en el Perú a través un modelo BVAR con media cambiante en el tiempo," Working Papers, Banco Central de Reserva del Perú, number 2021-001, Mar.
• Brown, Alexander L. & Imai, Taisuke & Vieider, Ferdinand M. & Camerer, Colin F., 2021, "Meta-Analysis of Empirical Estimates of Loss-Aversion," Rationality and Competition Discussion Paper Series, CRC TRR 190 Rationality and Competition, number 275, Jan.
• Anastasia Dimiski, 2021, "Factors that affect Students’ performance in Science: An application using Gini-BMA methodology in PISA 2015 dataset," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, volume 13, issue 2, pages 157-211, June, DOI: https://doi.org/10.15353/rea.v13i2..
• Eric Martial Etoundi Atenga & Maman Hassan Abdo & Mbodja Mougoué, 2021, "Financial Frictions and Macroeconomy During Financial Crises: A Bayesian DSGE Assessment," American Business Review, Pompea College of Business, University of New Haven, volume 24, issue 2, pages 62-99.
• Karen Poghosyan & Ruben Poghosyan, 2021, "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 61, pages 28-46.
• Seewon Kim, 2021, "Evolution of China’s Economy and Monetary Policy: An Empirical Evaluation Using a TVP-VAR Model," East Asian Economic Review, Korea Institute for International Economic Policy, volume 25, issue 1, pages 73-97, DOI: 10.11644/KIEP.EAER.2021.25.1.391.
• Alina BOBAŞU & Bogdan MURARAȘU, 2021, "Fiscal and Monetary Policy Interactions in a DSGE Model for the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 5-21, June.
• Luisa Corrado & Stefano Grassi & Aldo Paolillo, 2021, "Identifying Economic Shocks in a Rare Disaster Environment," CEIS Research Paper, Tor Vergata University, CEIS, number 517, Oct, revised 18 Jul 2024.
• Shesadri Banerjee & Jayanthi K. Anand & Shashanka Bhide, 2021, "Estimation of Macro-financial Linkages for the Indian Economy," Journal of Emerging Market Finance, Institute for Financial Management and Research, volume 20, issue 1, pages 7-47, April, DOI: 10.1177/0972652720927856.
• Tamás Krisztin & Philipp Piribauer, 2021, "Modelling European regional FDI flows using a Bayesian spatial Poisson interaction model," The Annals of Regional Science, Springer;Western Regional Science Association, volume 67, issue 3, pages 593-616, December, DOI: 10.1007/s00168-021-01058-x.
• Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021, "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, volume 60, issue 1, pages 227-259, January, DOI: 10.1007/s00181-020-01893-5.
• William W. Chow & Michael K. Fung, 2021, "The effects of macroprudential policy on Hong Kong’s housing market: a multivariate ordered probit-augmented vector autoregressive approach," Empirical Economics, Springer, volume 60, issue 2, pages 633-660, February, DOI: 10.1007/s00181-019-01765-7.
• Yifei Cai & Angeliki Menegaki, 2021, "FDI, growth and trade partisan conflict in the US: TVP-BVAR approach," Empirical Economics, Springer, volume 60, issue 3, pages 1335-1362, March, DOI: 10.1007/s00181-019-01795-1.
• Andrés Ramírez–Hassan & Rosember Guerra–Urzola, 2021, "Bayesian treatment effects due to a subsidized health program: the case of preventive health care utilization in Medellín (Colombia)," Empirical Economics, Springer, volume 60, issue 3, pages 1477-1506, March, DOI: 10.1007/s00181-019-01796-0.
• Yushu Li & Fredrik N. G. Andersson, 2021, "A simple wavelet-based test for serial correlation in panel data models," Empirical Economics, Springer, volume 60, issue 5, pages 2351-2363, May, DOI: 10.1007/s00181-020-01830-6.
• Tamás Krisztin & Philipp Piribauer, 2021, "A Bayesian spatial autoregressive logit model with an empirical application to European regional FDI flows," Empirical Economics, Springer, volume 61, issue 1, pages 231-257, July, DOI: 10.1007/s00181-020-01856-w.
• Nima Nonejad, 2021, "Using the conditional volatility channel to improve the accuracy of aggregate equity return predictions," Empirical Economics, Springer, volume 61, issue 2, pages 973-1009, August, DOI: 10.1007/s00181-020-01882-8.
• Arjun Gupta & Soudeh Mirghasemi & Mohammad Arshad Rahman, 2021, "Heterogeneity in food expenditure among US families: evidence from longitudinal quantile regression," Indian Economic Review, Springer, volume 56, issue 1, pages 25-48, June, DOI: 10.1007/s41775-020-00101-6.
• Olumuyiwa Tolulope Apanisile, 2021, "Remittances, financial development and the effectiveness of monetary policy transmission mechanism in Nigeria: a DSGE approach (1986–2018)," Indian Economic Review, Springer, volume 56, issue 1, pages 91-112, June, DOI: 10.1007/s41775-021-00110-z.
• Nils Bertschinger & Iurii Mozzhorin, 2021, "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, volume 16, issue 1, pages 173-210, January, DOI: 10.1007/s11403-020-00289-z.
• Anoop Chaturvedi & Shalabh & Sandeep Mishra, 2021, "Generalized Bayes Estimator for Spatial Durbin Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 19, issue 1, pages 267-285, December, DOI: 10.1007/s40953-021-00271-x.
• Márcio P. Laurini & Pedro Chaim, 2021, "Brazilian stock market bubble in the 2010s," SN Business & Economics, Springer, volume 1, issue 1, pages 1-19, January, DOI: 10.1007/s43546-020-00005-w.
• Griselda Dávila-Aragón & Salvador Rivas-Aceves & Héctor X. Ramírez-Pérez, 2021, "Survival Likelihood of Micro and Small Businesses Facing a Catastrophe," Springer Books, Springer, in: Griselda Dávila-Aragón & Salvador Rivas-Aceves, "The Future of Companies in the Face of a New Reality", DOI: 10.1007/978-981-16-2613-5_2.
• Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2021, "Is there a euro effect in the drivers of US FDI? New evidence using Bayesian model averaging techniques," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), volume 157, issue 4, pages 881-926, November, DOI: 10.1007/s10290-020-00405-y.
• Simona Hašková & Petr Šuleř & Tomáš Krulický, 2021, "Advantages of fuzzy approach compared to probabilistic approach in project evaluation," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 9, issue 2, pages 446-456, December, DOI: 10.9770/jesi.2021.9.2(29).
• Haroon Mumtaz & Konstantinos Theodoridis, 2021, "Fiscal policy shocks and stock prices in the United States," Working Papers, European Stability Mechanism, number 48, May.
• Martin Iseringhausen, 2021, "A time-varying skewness model for Growth-at-Risk," Working Papers, European Stability Mechanism, number 49, Jun.
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