Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting with DSGE Models
2. Forecasting

2021

• Becker William & Paruolo Paolo & Saltelli Andrea, 2021, "Variable Selection in Regression Models Using Global Sensitivity Analysis," Journal of Time Series Econometrics, De Gruyter, volume 13, issue 2, pages 187-233, July, DOI: 10.1515/jtse-2018-0025.
• Elena Denisa Bala & Stelian Stancu, 2021, "Limiting informal economy in the context of business environment regulations. An analysis of -young- European Union members," Manager Journal, Faculty of Business and Administration, University of Bucharest, volume 33, issue 1, pages 55-66, May.
• Josué Diwambuena & Raquel Fonseca & Stefan Schubert, 2021, "Italian Labour Frictions and Wage Rigidities in an Estimated DSGE," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS88, Sep.
• Maurin Baillif & Matthieu de Lapparent & Evanthia Kazagli, 2021, "A Hybrid Approach to Real Estate Price Definition: A Case Study in Western Switzerland," Revue économique, Presses de Sciences-Po, volume 72, issue 6, pages 1055-1077.
• Palumbo, D., 2021, "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2111, Jan.
• Vesna Karadžić & Nikola Đalović, 2021, "Profitability Determinants of Big European Banks," Journal of Central Banking Theory and Practice, Central bank of Montenegro, volume 10, issue 2, pages 39-56.
• Chou, Jenyu & Easaw, Joshy & Minford, Patrick, 2021, "Does Inattentiveness Matter for DSGE Modelling? An Empirical Investigation," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2021/35, Dec.
• Filip Stanek, 2021, "Optimal Out-of-Sample Forecast Evaluation under Stationarity," CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague, number wp712, Nov.
• Douglas Silveira & Silvinha Vasconcelos & Marcelo Resende & Daniel O. Cajueiro, 2021, "Won't Get Fooled Again: A Supervised Machine Learning Approach for Screening Gasoline Cartels," CESifo Working Paper Series, CESifo, number 8835.
• Christiane Baumeister, 2021, "Measuring Market Expectations," CESifo Working Paper Series, CESifo, number 9305.
• Adam N. Smith & Stephan Seiler & Ishant Aggarwal, 2021, "Optimal Price Targeting," CESifo Working Paper Series, CESifo, number 9439.
• Tsutomu Watanabe & Tomoyoshi Yabu, 2021, "Japan’s Voluntary Lockdown: Further Evidence Based on Age-Specific Mobile Location Data," CARF F-Series, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, number CARF-F-508, Feb.
• 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.
• 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.
• Damir Filipović & Amir Khalilzadeh, 2021, "Machine Learning for Predicting Stock Return Volatility," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-95, Dec.
• Maxime Fajeau, 2021, "Too much finance or too many weak instruments?," International Economics, CEPII research center, issue 165, pages 14-36.
• Josué Diwambuena & Raquel Fonseca & Stefan Schubert, 2021, "Italian Labour Frictions and Wage Rigidities in an Estimated DSGE," CIRANO Working Papers, CIRANO, number 2021s-33, Sep.
• Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021, "Moment tests of independent components," Working Papers, CEMFI, number wp2021_2102, Feb.
• Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021, "Multivariate Hermite polynomials and information matrix tests," Working Papers, CEMFI, number wp2021_2103, May.
• Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2021, "Tests for random coefficient variation in vector autoregressive models," Working Papers, CEMFI, number wp2021_2108, Sep.
• Ricardo Crisóstomo, 2021, "Estimación de probabilidades representativas del mundo real: importancia de los sesgos conductuales," CNMV Documentos de Trabajo, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas, number CNMV Documentos de Trabaj.
• Javier Ojea-Ferreiro, 2021, "Deconstrucción del riesgo sistémico: Un método de prueba de resistencia inversa," CNMV Documentos de Trabajo, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas, number CNMV Documentos de Trabaj.
• Ricardo Crisóstomo, 2021, "Estimating real word probabilities: a forward-looking behavioral framework," CNMV Working Papers, CNMV- Spanish Securities Markets Commission - Research and Statistics Department, number CNMV Working Papers no. 7.
• Javier Ojea-Ferreiro, 2021, "Deconstructing systemic risk: A reverse stress testing approach," CNMV Working Papers, CNMV- Spanish Securities Markets Commission - Research and Statistics Department, number CNMV Working Papers no. 7.
• Nicol√°s Urdaneta Andrade, 2021, "¬øHombres "cracks" y mujeres "amables"? Sesgos de g√©nero en encuestas de profesores," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 19557, Aug.
• Smith, Adam & Seiler, Stephan & Aggarwal, Ishant, 2022, "Optimal Price Targeting," CEPR Discussion Papers, Centre for Economic Policy Research, number 16096, Jul.
• Schorfheide, Frank & Chang, Minsu & Chen, Xiaohong, 2021, "Heterogeneity and Aggregate Fluctuations," CEPR Discussion Papers, Centre for Economic Policy Research, number 16183, May.
• Giacomini, Raffaella & Kitagawa, Toru & Read, Matthew, 2021, "Robust Bayesian Analysis for Econometrics," CEPR Discussion Papers, Centre for Economic Policy Research, number 16488, Aug.
• Baumeister, Christiane, 2021, "Measuring Market Expectations," CEPR Discussion Papers, Centre for Economic Policy Research, number 16520, Sep.
• Kilian, Lutz, 2021, "Comment on Giacomini, Kitagawa and Read’s ‘Narrative Restrictions and Proxies’," CEPR Discussion Papers, Centre for Economic Policy Research, number 16818, Dec.
• Zea Bermúdez, Patricia de & Marín Díazaraque, Juan Miguel & Rue, Havard & Veiga, Helena, 2021, "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 31804, Jan.
• Minsu Chang & Xiaohong Chen & Frank Schorfheide, 2021, "Heterogeneity and Aggregate Fluctuations," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2289, May.
• Тодор Кръстевич, 2021, "Моделиране На Вероятностния Избор При Покупка," Scientific Research Almanac, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, volume 29, issue 1 Year 20, pages 5-47.
• Simplice A. Asongu & Rexon T. Nting, 2021, "The Mobile Phone in Governance for Environmental Sustainability in Sub-Saharan Africa," Journal of Africa SEER Centre(ASC), Africa SEER Centre(ASC), number 21/013, Jan.
• Simplice A. Asongu & Tii N. Nchofoung, 2021, "The terrorism-finance nexus contingent on globalisation and governance dynamics in Africa," Journal of Africa SEER Centre(ASC), Africa SEER Centre(ASC), number 21/022, Mar.
• Jan Philipp Fritsche, 2021, "Labor-Intensive Firms Are a Catalyst for Monetary Policy and Its Distributive Effects," DIW Weekly Report, DIW Berlin, German Institute for Economic Research, volume 11, issue 35/36, pages 261-266.
• Armin Varmaz & Katharina Riebe & Sabrina Hegner, 2021, "Sustainable Financial Literacy and Preferences for Sustainable Investments among Young Adults," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, volume 90, issue 4, pages 43-69, DOI: 10.3790/vjh.90.4.43.
• Jan Philipp Fritsche, 2021, "Arbeitsintensive Unternehmen sind ein Katalysator für Geldpolitik und ihre Verteilungseffekte," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 88, issue 36, pages 587-592.
• Jan Philipp Fritsche & Lea Steininger, 2021, "Zooming in on Monetary Policy - The Labor Share and Production Dynamics of Two Million Firms," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1967.
• Marica Valente, 2021, "Policy Evaluation of Waste Pricing Programs Using Heterogeneous Causal Effect Estimation," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1980.
• Nickel, Christiane & Fröhling, Annette & Álvarez, Luis J. & Willeke, Caroline & Zevi, Giordano & Osbat, Chiara & Ganoulis, Ioannis & Koester, Gerrit & Lis, Eliza & Peronaci, Romana & Hahn, Elke & Beka, 2021, "Inflation measurement and its assessment in the ECB’s monetary policy strategy review," Occasional Paper Series, European Central Bank, number 265, Sep.
• 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.
• Anton Lisin & Tomonobu Senjyu, 2021, "Renewable Energy Transition: Evidence from Spillover Effects in Exchange-Traded Funds," International Journal of Energy Economics and Policy, Econjournals, volume 11, issue 3, pages 184-190.
• Chaido Dritsaki & Dimitrios Niklis & Pavlos Stamatiou, 2021, "Oil Consumption Forecasting using ARIMA Models: An Empirical Study for Greece," International Journal of Energy Economics and Policy, Econjournals, volume 11, issue 4, pages 214-224.
• Bosede Ngozi Adeleye & Darlington Akam & Nasiru Inuwa & Muftau Olarinde & Victoria Okafor & Ifeoluwa Ogunrinola & Paul Adekola, 2021, "Investigating Growth-Energy-Emissions Trilemma in South Asia," International Journal of Energy Economics and Policy, Econjournals, volume 11, issue 5, pages 112-120.
• Chung, Hess & Fuentes-Albero, Cristina & Paustian, Matthias & Pfajfar, Damjan, 2021, "Latent variables analysis in structural models: A New decomposition of the kalman smoother," Journal of Economic Dynamics and Control, Elsevier, volume 125, issue C, DOI: 10.1016/j.jedc.2021.104097.
• Berger, Tino & Everaert, Gerdie & Pozzi, Lorenzo, 2021, "Testing for international business cycles: A multilevel factor model with stochastic factor selection," Journal of Economic Dynamics and Control, Elsevier, volume 128, issue C, DOI: 10.1016/j.jedc.2021.104134.
• Castle, Jennifer L. & Kurita, Takamitsu, 2021, "A dynamic econometric analysis of the dollar-pound exchange rate in an era of structural breaks and policy regime shifts," Journal of Economic Dynamics and Control, Elsevier, volume 128, issue C, DOI: 10.1016/j.jedc.2021.104139.
• Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021, "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, volume 101, issue C, DOI: 10.1016/j.econmod.2021.105531.
• Lehrer, Steven & Xie, Tian & Zhang, Xinyu, 2021, "Social media sentiment, model uncertainty, and volatility forecasting," Economic Modelling, Elsevier, volume 102, issue C, DOI: 10.1016/j.econmod.2021.105556.
• Lagomarsino, Elena, 2021, "Which nesting structure for the CES? A new selection approach based on input separability," Economic Modelling, Elsevier, volume 102, issue C, DOI: 10.1016/j.econmod.2021.105562.
• Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021, "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, volume 104, issue C, DOI: 10.1016/j.econmod.2021.105643.
• Liu, Ding & Sun, Weihong & Chang, Long, 2021, "Monetary–fiscal policy regime and macroeconomic dynamics in China," Economic Modelling, Elsevier, volume 95, issue C, pages 121-135, DOI: 10.1016/j.econmod.2020.12.007.
• Ouyang, Zi-sheng & Yang, Xi-te & Lai, Yongzeng, 2021, "Systemic financial risk early warning of financial market in China using Attention-LSTM model," The North American Journal of Economics and Finance, Elsevier, volume 56, issue C, DOI: 10.1016/j.najef.2021.101383.
• Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021, "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, volume 57, issue C, DOI: 10.1016/j.najef.2021.101425.
• 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.
• Qiu, Yue, 2021, "Complete subset least squares support vector regression," Economics Letters, Elsevier, volume 200, issue C, DOI: 10.1016/j.econlet.2021.109737.
• Ciccarelli, Matteo & García, Juan Angel, 2021, "Expectation spillovers and the return of inflation," Economics Letters, Elsevier, volume 209, issue C, DOI: 10.1016/j.econlet.2021.110119.
• Lee, Sokbae & Liao, Yuan & Seo, Myung Hwan & Shin, Youngki, 2021, "Sparse HP filter: Finding kinks in the COVID-19 contact rate," Journal of Econometrics, Elsevier, volume 220, issue 1, pages 158-180, DOI: 10.1016/j.jeconom.2020.08.008.
• Perera, Indeewara & Silvapulle, Mervyn J., 2021, "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, volume 221, issue 1, pages 1-24, DOI: 10.1016/j.jeconom.2020.01.022.
• 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.
• Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021, "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 364-392, DOI: 10.1016/j.jeconom.2020.07.006.
• Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021, "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 451-467, DOI: 10.1016/j.jeconom.2020.07.010.
• Meitz, Mika & Saikkonen, Pentti, 2021, "Testing for observation-dependent regime switching in mixture autoregressive models," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 601-624, DOI: 10.1016/j.jeconom.2020.04.048.
• Delgado, Miguel A. & Arteaga-Molina, Luis A., 2021, "Testing constancy in varying coefficient models," Journal of Econometrics, Elsevier, volume 222, issue 1, pages 625-644, DOI: 10.1016/j.jeconom.2020.07.041.
• Sun, Yuying & Hong, Yongmiao & Lee, Tae-Hwy & Wang, Shouyang & Zhang, Xinyu, 2021, "Time-varying model averaging," Journal of Econometrics, Elsevier, volume 222, issue 2, pages 974-992, DOI: 10.1016/j.jeconom.2020.02.006.
• Heiler, Phillip & Mareckova, Jana, 2021, "Shrinkage for categorical regressors," Journal of Econometrics, Elsevier, volume 223, issue 1, pages 161-189, DOI: 10.1016/j.jeconom.2020.07.051.
• Liao, Jun & Zou, Guohua & Gao, Yan & Zhang, Xinyu, 2021, "Model averaging prediction for time series models with a diverging number of parameters," Journal of Econometrics, Elsevier, volume 223, issue 1, pages 190-221, DOI: 10.1016/j.jeconom.2020.10.004.
• Hansen, Lars Peter & Sargent, Thomas J., 2021, "Macroeconomic uncertainty prices when beliefs are tenuous," Journal of Econometrics, Elsevier, volume 223, issue 1, pages 222-250, DOI: 10.1016/j.jeconom.2019.11.010.
• Su, Jiun-Hua, 2021, "Model selection in utility-maximizing binary prediction," Journal of Econometrics, Elsevier, volume 223, issue 1, pages 96-124, DOI: 10.1016/j.jeconom.2020.07.052.
• Andersen, Torben G. & Varneskov, Rasmus T., 2021, "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, volume 224, issue 1, pages 215-244, DOI: 10.1016/j.jeconom.2020.04.051.
• Voges, Michelle & Sibbertsen, Philipp, 2021, "Cyclical fractional cointegration," Econometrics and Statistics, Elsevier, volume 19, issue C, pages 114-129, DOI: 10.1016/j.ecosta.2020.05.004.
• Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021, "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, volume 60, issue C, pages 56-73, DOI: 10.1016/j.jempfin.2020.11.003.
• Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021, "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, volume 62, issue C, pages 179-201, DOI: 10.1016/j.jempfin.2021.03.003.
• Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021, "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, volume 62, issue C, pages 46-61, DOI: 10.1016/j.jempfin.2021.01.007.
• Olson, Luke M. & Qi, Min & Zhang, Xiaofei & Zhao, Xinlei, 2021, "Machine learning loss given default for corporate debt," Journal of Empirical Finance, Elsevier, volume 64, issue C, pages 144-159, DOI: 10.1016/j.jempfin.2021.08.009.
• Ewald, Christian & Zou, Yihan, 2021, "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, volume 64, issue C, pages 37-52, DOI: 10.1016/j.jempfin.2021.08.006.
• Uniejewski, Bartosz & Weron, Rafał, 2021, "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, volume 95, issue C, DOI: 10.1016/j.eneco.2021.105121.
• 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.
• He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2021, "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Energy Economics, Elsevier, volume 97, issue C, DOI: 10.1016/j.eneco.2021.105171.
• Kramer, Anke & Kiesel, Rüdiger, 2021, "Exogenous factors for order arrivals on the intraday electricity market," Energy Economics, Elsevier, volume 97, issue C, DOI: 10.1016/j.eneco.2021.105186.
• Sun, Jie & Zhao, Xiaojun & Xu, Chao, 2021, "Crude oil market autocorrelation: Evidence from multiscale quantile regression analysis," Energy Economics, Elsevier, volume 98, issue C, DOI: 10.1016/j.eneco.2021.105239.
• Yang, Haijun & Han, Xin & Wang, Li, 2021, "Is there a bubble in the shale gas market?," Energy, Elsevier, volume 215, issue PA, DOI: 10.1016/j.energy.2020.119101.
• Nunes, Luis Eduardo & Lima, Marcus Vinicius Andrade de & Davison, Matthew & Leite, André Luis da Silva, 2021, "Switch and defer option in renewable energy projects: Evidences from Brazil," Energy, Elsevier, volume 231, issue C, DOI: 10.1016/j.energy.2021.120972.
• Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021, "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, volume 78, issue C, DOI: 10.1016/j.irfa.2021.101915.
• Silahli, Baykar & Dingec, Kemal Dincer & Cifter, Atilla & Aydin, Nezir, 2021, "Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, volume 38, issue C, DOI: 10.1016/j.frl.2019.101425.
• Huang, Zhuo & Liang, Fang & Wang, Tianyi & Li, Chao, 2021, "Modeling dynamic higher moments of crude oil futures," Finance Research Letters, Elsevier, volume 39, issue C, DOI: 10.1016/j.frl.2020.101570.
• Zhou, Jian & Shen, Yixuan & Pantelous, Athanasios A. & Zhang, Hui, 2021, "The range of uncertainty on the property market pricing: The case of the city of Shanghai," Finance Research Letters, Elsevier, volume 40, issue C, DOI: 10.1016/j.frl.2020.101720.
• Zhao, Yuqian, 2021, "Validating intra-day risk premium in cross-sectional return curves," Finance Research Letters, Elsevier, volume 43, issue C, DOI: 10.1016/j.frl.2021.102020.
• Ferrari, Stijn & Van Roy, Patrick & Vespro, Cristina, 2021, "Sensitivity of credit risk stress test results: Modelling issues with an application to Belgium," Journal of Financial Stability, Elsevier, volume 52, issue C, DOI: 10.1016/j.jfs.2020.100805.
• 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.
• Fajeau, Maxime, 2021, "Too much finance or too many weak instruments?," International Economics, Elsevier, volume 165, issue C, pages 14-36, DOI: 10.1016/j.inteco.2020.10.003.
• Calice, Pietro & Leonida, Leone & Muzzupappa, Eleonora, 2021, "Concentration-stability vs concentration-fragility. New cross-country evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 74, issue C, DOI: 10.1016/j.intfin.2021.101411.
• Costantini, Mauro & Kunst, Robert M., 2021, "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, volume 37, issue 2, pages 445-460, DOI: 10.1016/j.ijforecast.2020.06.010.
• 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.
• Baumeister, Christiane & Guérin, Pierre, 2021, "A comparison of monthly global indicators for forecasting growth," International Journal of Forecasting, Elsevier, volume 37, issue 3, pages 1276-1295, DOI: 10.1016/j.ijforecast.2021.02.008.
• Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021, "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, volume 37, issue 4, pages 1376-1398, DOI: 10.1016/j.ijforecast.2021.04.003.
• Imhof, David & Wallimann, Hannes, 2021, "Detecting bid-rigging coalitions in different countries and auction formats," International Review of Law and Economics, Elsevier, volume 68, issue C, DOI: 10.1016/j.irle.2021.106016.
• Clements, Adam & Preve, Daniel P.A., 2021, "A Practical Guide to harnessing the HAR volatility model," Journal of Banking & Finance, Elsevier, volume 133, issue C, DOI: 10.1016/j.jbankfin.2021.106285.
• Cole, Stephen J. & Milani, Fabio, 2021, "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, volume 188, issue C, pages 627-650, DOI: 10.1016/j.jebo.2021.05.034.
• Howard, Gregory & Whitehead, John C. & Hochard, Jacob, 2021, "Estimating discount rates using referendum-style choice experiments: An analysis of multiple methodologies," Journal of Environmental Economics and Management, Elsevier, volume 105, issue C, DOI: 10.1016/j.jeem.2020.102399.
• Chinco, Alex & Neuhierl, Andreas & Weber, Michael, 2021, "Estimating the anomaly base rate," Journal of Financial Economics, Elsevier, volume 140, issue 1, pages 101-126, DOI: 10.1016/j.jfineco.2020.12.003.
• Chaieb, Ines & Langlois, Hugues & Scaillet, Olivier, 2021, "Factors and risk premia in individual international stock returns," Journal of Financial Economics, Elsevier, volume 141, issue 2, pages 669-692, DOI: 10.1016/j.jfineco.2021.04.007.
• Biolsi, Christopher, 2021, "Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?," Journal of Macroeconomics, Elsevier, volume 69, issue C, DOI: 10.1016/j.jmacro.2021.103321.
• Li, Bing & Pei, Pei & Tan, Fei, 2021, "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, volume 70, issue C, DOI: 10.1016/j.jmacro.2021.103353.
• Karakotsios, Achillefs & Katrakilidis, Constantinos & Kroupis, Nikolaos, 2021, "The dynamic linkages between food prices and oil prices. Does asymmetry matter?," The Journal of Economic Asymmetries, Elsevier, volume 23, issue C, DOI: 10.1016/j.jeca.2021.e00203.
• Wolters, Jannik & Huchzermeier, Arnd, 2021, "Joint In-Season and Out-of-Season Promotion Demand Forecasting in a Retail Environment," Journal of Retailing, Elsevier, volume 97, issue 4, pages 726-745, DOI: 10.1016/j.jretai.2021.01.003.
• Asongu, Simplice A. & Le Roux, Sara & Singh, Pritam, 2021, "Fighting terrorism in Africa: Complementarity between inclusive development, military expenditure and political stability," Journal of Policy Modeling, Elsevier, volume 43, issue 5, pages 897-922, DOI: 10.1016/j.jpolmod.2020.01.014.
• Pincheira, Pablo & Hardy, Nicolás, 2021, "Forecasting aluminum prices with commodity currencies," Resources Policy, Elsevier, volume 73, issue C, DOI: 10.1016/j.resourpol.2021.102066.
• Vásquez Cordano, Arturo L. & Prialé Zevallos, Rodrigo, 2021, "Country competitiveness and investment allocation in the mining industry: A survey of the literature and new empirical evidence," Resources Policy, Elsevier, volume 73, issue C, DOI: 10.1016/j.resourpol.2021.102136.
• Hung, Ngo Thai, 2021, "Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Resources Policy, Elsevier, volume 73, issue C, DOI: 10.1016/j.resourpol.2021.102236.
• Jena, Sangram Keshari & Lahiani, Amine & Tiwari, Aviral Kumar & Roubaud, David, 2021, "Uncovering the complex asymmetric relationship between trading activity and commodity futures price: Evidenced from QNARDL study," Resources Policy, Elsevier, volume 74, issue C, DOI: 10.1016/j.resourpol.2021.102277.
• Den Haan, Wouter J. & Drechsel, Thomas, 2021, "Agnostic Structural Disturbances (ASDs): Detecting and reducing misspecification in empirical macroeconomic models," Journal of Monetary Economics, Elsevier, volume 117, issue C, pages 258-277, DOI: 10.1016/j.jmoneco.2020.01.005.
• Brownlees, Christian & Souza, André B.M., 2021, "Backtesting global Growth-at-Risk," Journal of Monetary Economics, Elsevier, volume 118, issue C, pages 312-330, DOI: 10.1016/j.jmoneco.2020.11.003.
• Omar, Arti & Prasanna, P. Krishna, 2021, "Asymmetric effects of noise in Merton default risk model: Evidence from emerging Asia," Pacific-Basin Finance Journal, Elsevier, volume 65, issue C, DOI: 10.1016/j.pacfin.2021.101497.
• Zakamulin, Valeriy & Hunnes, John A., 2021, "Stock earnings and bond yields in the US 1871–2017: The story of a changing relationship," The Quarterly Review of Economics and Finance, Elsevier, volume 79, issue C, pages 182-197, DOI: 10.1016/j.qref.2020.05.013.
• Hanif, Waqas & Areola Hernandez, Jose & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2021, "Tail dependence risk and spillovers between oil and food prices," The Quarterly Review of Economics and Finance, Elsevier, volume 80, issue C, pages 195-209, DOI: 10.1016/j.qref.2021.01.019.
• Abanto-Valle, Carlos A. & Rodríguez, Gabriel & Garrafa-Aragón, Hernán B., 2021, "Stochastic Volatility in Mean: Empirical evidence from Latin-American stock markets using Hamiltonian Monte Carlo and Riemann Manifold HMC methods," The Quarterly Review of Economics and Finance, Elsevier, volume 80, issue C, pages 272-286, DOI: 10.1016/j.qref.2021.02.005.
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• Yang Zhao & Zhonglu Chen, 2021, "Forecasting stock price movement: new evidence from a novel hybrid deep learning model," Journal of Asian Business and Economic Studies, Emerald Group Publishing Limited, volume 29, issue 2, pages 91-104, August, DOI: 10.1108/JABES-05-2021-0061.
• Simplice Asongu & Rexon Nting, 2021, "The mobile phone in governance for environmental sustainability in Sub-Saharan Africa," Journal of Economic and Administrative Sciences, Emerald Group Publishing Limited, volume 39, issue 1, pages 225-243, June, DOI: 10.1108/JEAS-01-2021-0001.
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• Trakakis Anastasios & Nektarios Miltiadis & Tziaferi Styliani & Prezerakos Panagiotis, 2021, "Measuring Technical Efficiency of Health Centers in Greece: A Data Envelopment Analysis Application for the Primary Health System of Greece," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special 1, pages 1333-1353.
• Natalia Nehrebecka, 2021, "Internal Credit Risk Models and Digital Transformation: What to Prepare for? An Application to Poland," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special 2, pages 719-736.
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• Simplice A. Asongu & Rexon T. Nting, 2021, "The Mobile Phone in Governance for Environmental Sustainability in Sub-Saharan Africa," Working Papers, European Xtramile Centre of African Studies (EXCAS), number 21/035, Jan.
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• Karen Poghosyan & Ruben Poghosyan, 2021, "On the Applicability of Dynamic Factor Models for Forecasting Real GDP Growth in Armenia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 71, issue 1, pages 52-79, June.
• Anna Gloria Billé & Alessio Tomelleri & Francesco Ravazzolo, 2021, "Forecasting Regional GDPs: a Comparison with Spatial Dynamic Panel Data Models," FBK-IRVAPP Working Papers, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation, number 2021-02, Dec.
• Paolo Maranzano & Joao Paulo Cerdeira Bento & Matteo Manera, 2021, "The Role of Education and Income Inequality on Environmental Quality. A Panel Data Analysis of the EKC Hypothesis on OECD," Working Papers, Fondazione Eni Enrico Mattei, number 2021.08, Mar.
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• Katarina Juselius, 2021, "Searching for a Theory That Fits the Data: A Personal Research Odyssey," Econometrics, MDPI, volume 9, issue 1, pages 1-27, February.
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• David H. Bernstein & Andrew B. Martinez, 2021, "Jointly Modeling Male and Female Labor Participation and Unemployment," Econometrics, MDPI, volume 9, issue 4, pages 1-14, December.
• 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.
• Tamás Kiss & Hoang Nguyen & Pär Österholm, 2021, "Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails," JRFM, MDPI, volume 14, issue 11, pages 1-17, October.
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