Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting with DSGE Models
2. Forecasting

2021

• 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.
• Chang, Bi-Juan & Hung, Mao-Wei, 2021, "Corporate debt and cash decisions: A nonlinear panel data analysis," The Quarterly Review of Economics and Finance, Elsevier, volume 81, issue C, pages 15-37, DOI: 10.1016/j.qref.2021.04.007.
• du Sart, Colin F. & van Vuuren, Gary W., 2021, "Comparing the performance and composition of tracking error constrained and unconstrained portfolios," The Quarterly Review of Economics and Finance, Elsevier, volume 81, issue C, pages 276-287, DOI: 10.1016/j.qref.2021.06.019.
• 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.
• Bo, Hao & Galiani, Sebastian, 2021, "Assessing external validity," Research in Economics, Elsevier, volume 75, issue 3, pages 274-285, DOI: 10.1016/j.rie.2021.06.005.
• Pradhan, Ashis Kumar & Tiwari, Aviral Kumar, 2021, "Estimating the market risk of clean energy technologies companies using the expected shortfall approach," Renewable Energy, Elsevier, volume 177, issue C, pages 95-100, DOI: 10.1016/j.renene.2021.05.134.
• Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2021, "Systemic-systematic risk in financial system: A dynamic ranking based on expectiles," International Review of Economics & Finance, Elsevier, volume 75, issue C, pages 330-365, DOI: 10.1016/j.iref.2021.04.001.
• Abakah, Emmanuel Joel Aikins & Caporale, Guglielmo Maria & Gil-Alana, Luis Alberiko, 2021, "Economic policy uncertainty: Persistence and cross-country linkages," Research in International Business and Finance, Elsevier, volume 58, issue C, DOI: 10.1016/j.ribaf.2021.101442.
• Bernt P. Stigum, 2021, "Consumer Choice under Certainty and Uncertainty in Applied Econometrics," EERI Research Paper Series, Economics and Econometrics Research Institute (EERI), Brussels, number EERI RP 2021/08, Oct.

2020

• 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 & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2020, "Predicting bond return predictability," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2020-09, Aug.
• 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.
• Simplice A. Asongu & Sara Le Roux & Pritam Singh, 2020, "Fighting terrorism in Africa: complementarity between inclusive development, military expenditure and political stability," Research Africa Network Working Papers, Research Africa Network (RAN), number 20/004, Jan.
• Simplice A. Asongu & Nicholas M. Odhiambo, 2020, "The role of Globalization in Modulating the Effect of Environmental Degradation on Inclusive Human Development," Research Africa Network Working Papers, Research Africa Network (RAN), number 20/015, Jan.
• Simplice A. Asongu & Nicholas M. Odhiambo, 2020, "Trade and FDI Thresholds of CO2 emissions for a Green Economy in Sub-Saharan Africa," Research Africa Network Working Papers, Research Africa Network (RAN), number 20/072, Jan.
• Abel Brodeur & Nikolai Cook & Anthony Heyes, 2020, "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics," American Economic Review, American Economic Association, volume 110, issue 11, pages 3634-3660, November, DOI: 10.1257/aer.20190687.
• Mark F. J. Steel, 2020, "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, volume 58, issue 3, pages 644-719, September, DOI: 10.1257/jel.20191385.
• Mhamed-Ali El-Aroui & Wafa Snoussi, 2020, "Value-at-Risk in Frontier Markets: Adapted Models and Evidences from Two North-African Stock Exchanges," The African Finance Journal, Africagrowth Institute, volume 22, issue 1, pages 1-20.
• Simplice A. Asongu & Sara Le Roux & Pritam Singh, 2020, "Fighting terrorism in Africa: complementarity between inclusive development, military expenditure and political stability," Working Papers of the African Governance and Development Institute., African Governance and Development Institute., number 20/004, Jan.
• Simplice A. Asongu & Nicholas M. Odhiambo, 2020, "The role of Globalization in Modulating the Effect of Environmental Degradation on Inclusive Human Development," Working Papers of the African Governance and Development Institute., African Governance and Development Institute., number 20/015, Jan.
• Simplice A. Asongu & Nicholas M. Odhiambo, 2020, "Trade and FDI Thresholds of CO2 emissions for a Green Economy in Sub-Saharan Africa," Working Papers of the African Governance and Development Institute., African Governance and Development Institute., number 20/072, Jan.
• 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.
• Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2020, "Local mortality estimates during the COVID-19 pandemic in Italy," Discussion Paper series in Regional Science & Economic Geography, Gran Sasso Science Institute, Social Sciences, number 2020-06, Oct, revised Oct 2020.
• Lodewikus Jacobus Basson & Gary van Vuuren, 2020, "Exploring Hedging Strategies Identified by Fractal Dimensions," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, volume 67, issue 1, pages 1-13, March.
• Ch. Assist. Julian Dimitrov Ph. D, 2020, "Evaluation Of Trading Models On Foreign Exchange Market," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, volume 1, issue 34, pages 75-87, April.
• Candelon, Bertrand & Luisi, Angelo, 2020, "Testing for the Validity of W in GVAR models," LIDAM Discussion Papers LFIN, Université catholique de Louvain, Louvain Finance (LFIN), number 2020009, Jan.
• Hakan Eryüzlü & Sertaç Hopoğlu, 2020, "A Comparison of Economic Expectations In Germany and Turkey: An Analysis of ZEW and Economic Trust Index Sentiment Indicators," Alphanumeric Journal, Bahadir Fatih Yildirim, volume 8, issue 1, pages 131-142, June, DOI: https://doi.org/10.17093/alphanumer.
• Gregory Howard & John C. Whitehead & Jacob Hochard, 2020, "Estimating Discount Rates Using Referendum-style Choice Experiments: An Analysis of Multiple Methods," Working Papers, Department of Economics, Appalachian State University, number 20-01.
• Davide La Vecchia & Alban Moor & Olivier Scaillet, 2020, "A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data," Papers, arXiv.org, number 2001.04867, Jan, revised Jan 2022.
• Chaonan Jiang & Davide La Vecchia & Elvezio Ronchetti & Olivier Scaillet, 2020, "Saddlepoint approximations for spatial panel data models," Papers, arXiv.org, number 2001.10377, Jan, revised Jul 2021.
• Ji Hyung Lee & Youngki Shin, 2020, "Complete Subset Averaging for Quantile Regressions," Papers, arXiv.org, number 2003.03299, Mar, revised Jul 2021.
• Hannes Wallimann & David Imhof & Martin Huber, 2020, "A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels," Papers, arXiv.org, number 2004.05629, Apr.
• Dimitris Korobilis, 2020, "High-dimensional macroeconomic forecasting using message passing algorithms," Papers, arXiv.org, number 2004.11485, Apr.
• Thomas H. J{o}rgensen, 2020, "Sensitivity to Calibrated Parameters," Papers, arXiv.org, number 2004.12100, Apr, revised Mar 2021.
• Philipp F. M. Baumann & Enzo Rossi & Alexander Volkmann, 2020, "What Drives Inflation and How: Evidence from Additive Mixed Models Selected by cAIC," Papers, arXiv.org, number 2006.06274, Jun, revised Aug 2022.
• Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2020, "Sparse HP Filter: Finding Kinks in the COVID-19 Contact Rate," Papers, arXiv.org, number 2006.10555, Jun, revised Jul 2020.
• Le-Yu Chen & Sokbae Lee, 2020, "Sparse Quantile Regression," Papers, arXiv.org, number 2006.11201, Jun, revised Mar 2023.
• Mirco Rubin & Dario Ruzzi, 2020, "Equity Tail Risk in the Treasury Bond Market," Papers, arXiv.org, number 2007.05933, Jul.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020, "Deep Dynamic Factor Models," Papers, arXiv.org, number 2007.11887, Jul, revised May 2023.
• Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020, "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers, arXiv.org, number 2009.07341, Sep.
• Simon Trimborn & Wolfgang Karl Hardle, 2020, "CRIX an index for cryptocurrencies," Papers, arXiv.org, number 2009.09782, Sep.
• Ai Jun Hou & Weining Wang & Cathy Y. H. Chen & Wolfgang Karl Hardle, 2020, "Pricing Cryptocurrency Options," Papers, arXiv.org, number 2009.11007, Sep.
• Marica Valente, 2020, "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Papers, arXiv.org, number 2010.01105, Oct, revised Nov 2022.
• Ricardo Cris'ostomo, 2020, "Estimating real-world probabilities: A forward-looking behavioral framework," Papers, arXiv.org, number 2012.09041, Dec, revised Jan 2021.
• Larysa Yakymova, 2020, "Developmental Patterns of Voluntary Pensions in CEE Countries: Analysis through the Bass Diffusion Model Reflecting the Observational Learning Mechanism," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 166-192.
• 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.
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