Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting with DSGE Models
2. Forecasting

2022

• Dimitris Korobilis & Maximilian Schroder, 2022, "Probabilistic Quantile Factor Analysis," Papers, arXiv.org, number 2212.10301, Dec, revised Aug 2024.
• Seighalani, Shahbod & Jalali-Naini, Seyed Ahmadreza & Khiabani, Nasser, 2022, "External Shocks, Exchange Rate Changes, and Intermediate Goods: Explanation of Stagflation in Iranian Economy (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, volume 27, issue 2, pages 3-50, September.
• Ilkin Huseynov & Nazrin Ramazanova & Hikmat Valirzayev, 2022, "Using National Payment System Data to Nowcast Economic Activity in Azerbaijan," Working Papers, Central Bank of Azerbaijan Republic, number 2201, May.
• Anton A. Gerunov, 2022, "Performance of 109 Machine Learning Algorithms across Five Forecasting Tasks: Employee Behavior Modeling, Online Communication, House Pricing, IT Support and Demand Planning," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 15-43.
• Tsvetomir Tsvetkov & Sonya Georgieva, 2022, "Inflation, Inflation Instability and Nominal Uncertainty in Bulgarian Economy," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 8, pages 41-64.
• Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022, "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 22-04, Jul.
• Luis Antonio Espinosa & Juan José Li Ng, 2022, "Mexico | Did the COVID-19 lockdown reduce air pollution?," Working Papers, BBVA Bank, Economic Research Department, number 22/09, Oct.
• James Younker, 2022, "Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models," Discussion Papers, Bank of Canada, number 2022-19, Sep, DOI: 10.34989/sdp-2022-19.
• Alban Moura & Olivier Pierrard, 2022, "How well do DSGE models with real estate and collateral constraints fit the data?," BCL working papers, Central Bank of Luxembourg, number 168, Oct.
• Giuseppe Cascarino & Mirko Moscatelli & Fabio Parlapiano, 2022, "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 674, Mar.
• Emilia Bonaccorsi Di Patti & Filippo Calabresi & Biagio De Varti & Fabrizio Federico & Massimiliano Affinito & Marco Antolini & Francesco Lorizzo & Sabina Marchetti & Ilaria Masiani & Mirko Moscatelli, 2022, "Artificial intelligence in credit scoring. An analysis of some experiences in the Italian financial system," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 721, Oct.
• Freyaldenhoven Simon & Hansen Christian & Pérez Pérez Jorge & Shapiro Jesse M., 2022, "Visualization, Identification, and Estimation in the Linear Panel Event Study Design," Working Papers, Banco de México, number 2022-07, Aug.
• Stephen G. Hall & George S. Tavlas & Yongli Wang, 2022, "Forecasting Inflation: The Use of Dynamic Factor Analysis and Nonlinear Combinations," Discussion Papers, Department of Economics, University of Birmingham, number 22-12, Oct.
• Stephen G. Hall & George S. Tavlas & Yongli Wang, 2022, "Drivers and Spillover Effects of Inflation: the United States, the Euro Area, and the United Kingdom," Discussion Papers, Department of Economics, University of Birmingham, number 22-13, Oct.
• Aleksei Kipriyanov, 2022, "Comparison of Models for Growth-at-Risk Forecasting," Russian Journal of Money and Finance, Bank of Russia, volume 81, issue 1, pages 23-45, March, DOI: 10.31477/rjmf.202201.23.
• Henry Penikas, 2022, "Pass-Through of the Bank of Russia Key Rate into Deposit Rates Between 2020 and 2022," Russian Journal of Money and Finance, Bank of Russia, volume 81, issue 2, pages 20-48, June.
• Evgeny Moiseev & Denis Zagorodnev & Alexander Berezinskiy & Roman Tikhonov, 2022, "A Method for Assessing the IT Component of Model Risk and the Economic Capital to Cover It," Russian Journal of Money and Finance, Bank of Russia, volume 81, issue 3, pages 107-127, September.
• Henry Penikas, 2022, "Model Risk for Acceptable, but Imperfect, Discrimination and Calibration in Basel PD and LGD Models," Bank of Russia Working Paper Series, Bank of Russia, number wps92, Apr.
• Mauricio Villamizar‐Villegas & Freddy A. Pinzon‐Puerto & Maria Alejandra Ruiz‐Sanchez, 2022, "A comprehensive history of regression discontinuity designs: An empirical survey of the last 60 years," Journal of Economic Surveys, Wiley Blackwell, volume 36, issue 4, pages 1130-1178, September, DOI: 10.1111/joes.12461.
• Martin Huber & David Imhof & Rieko Ishii, 2022, "Transnational machine learning with screens for flagging bid‐rigging cartels," Journal of the Royal Statistical Society Series A, Royal Statistical Society, volume 185, issue 3, pages 1074-1114, July, DOI: 10.1111/rssa.12811.
• Siddhartha Chib & Minchul Shin & Anna Simoni, 2022, "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, volume 84, issue 3, pages 740-764, July, DOI: 10.1111/rssb.12484.
• Jorge Eduardo Pérez, 2022, "Visualization, identification, and estimation in linear panel event-study design," Colombian Stata Users' Group Meetings 2022, Stata Users Group, number 05, Sep.
• Marcus Buckmann & Andreas Joseph, 2022, "An interpretable machine learning workflow with an application to economic forecasting," Bank of England Staff Working Paper series, Bank of England, number 984, Jun.
• Sophocles N. Brissimis & Michalis-Panayiotis Papafilis, 2022, "The credit channel of monetary transmission in the US: Is it a bank lending channel, a balance sheet channel, or both, or neither?," Working Papers, Bank of Greece, number 300, Jul, DOI: 10.52903/wp2022300.
• Stephen G. Hall & George S. Tavlas & Yongli Wang, 2022, "Drivers and spillover effects of inflation: the United States, the euro area, and the United Kingdom," Working Papers, Bank of Greece, number 309, Dec, DOI: 10.52903/wp2022309.
• Takushi Kurozumi & Ryohei Oishi, 2022, "A Comparison of Japanese and US New Keynesian Phillips Curves with Bayesian VAR-GMM," Bank of Japan Working Paper Series, Bank of Japan, number 22-E-3, Mar.
• Takashi Nakazawa, 2022, "Constructing GDP Nowcasting Models Using Alternative Data," Bank of Japan Working Paper Series, Bank of Japan, number 22-E-9, Jul.
• Segnon Mawuli & Lau Chi Keung & Wilfling Bernd & Gupta Rangan, 2022, "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 26, issue 1, pages 73-98, February, DOI: 10.1515/snde-2019-0009.
• Schmidt Alexander & Schweikert Karsten, 2022, "Multiple structural breaks in cointegrating regressions: a model selection approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 26, issue 2, pages 219-254, April, DOI: 10.1515/snde-2020-0063.
• Victor H. Aguiar & Roberto Serrano, 2022, "Slutsky Matrix Symmetry: A New Behavioral Condition," Working Papers, Brown University, Department of Economics, number 2022-004.
• Alves, C., 2022, "Joan Robinson in 1942, an encounter between Marxian Economics and Macroeconomics," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2226, Apr.
• Ashby, M. & Linton, O. B., 2022, "Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns?," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2259, Oct.
• W. Saart, Patrick & Kim, Namhyun & Bateman, Ian, 2021, "Understanding spatial heterogeneity in GB agricultural land-use for improved policy targeting," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2021/8, May.
• W. Saart, Patrick & Kim, Namhyun & Moscone, Francesco & Xia, Yingcun, 2022, "Varying Coefficient Model with Correlated Error Components and Application to Disparities Between Mental Health Service by Councils in England," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2022/1, Jan.
• Meenagh, David & Minford, Patrick & Xu, Yongdeng, 2022, "Why does Indirect Inference estimation produce less small sample bias than maximum likelihood? A note," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2022/10, May.
• Meenagh, David & Minford, Patrick & Xu, Yongdeng, 2022, "Targeting moments for calibration compared with indirect inference," Cardiff Economics Working Papers, Cardiff University, Cardiff Business School, Economics Section, number E2022/12, Jul.
• Tsutomu Watanabe & Tomoyoshi Yabu, 2022, "The Demand for Money at the Zero Interest Rate Bound," CARF F-Series, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, number CARF-F-552, Dec.
• Rodrigo Alfaro & Alejandra Inzunza, 2022, "Modeling S&P500 returns with GARCH models," Working Papers Central Bank of Chile, Central Bank of Chile, number 955, May.
• Walter Farkas & Francesco Ferrari & Urban Ulrych, 2022, "Pricing Autocallables under Local-Stochastic Volatility," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 22-71, Sep.
• Damir Filipović & Puneet Pasricha, 2022, "Empirical Asset Pricing via Ensemble Gaussian Process Regression," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 22-95, Dec.
• Christophe Gouel & Nicolas Legrand, 2022, "The Role of Storage in Commodity Markets: Indirect Inference Based on Grains Data," Working Papers, CEPII research center, number 2022-04, Jul.
• Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022, "Specification tests for non-Gaussian structural vector autoregressions," Working Papers, CEMFI, number wp2022_2212, Dec.
• Laura Vanessa Hern√°ndez Cruz, 2022, "Crisis empresarial en Colombia: probabilidad de entrar en proceso de insolvencia 2016-2019," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 20126, May.
• Alexander Arévalo S & V�ctor Gim�nez G & Diego Prior J, 2022, "Análisis de eficiencia en educación: una aplicación del método StoNED," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, volume 92, issue 2, pages 45-91.
• Eduardo Loría & Ra�l Tirado, 2022, "Sacrifice rate and labour precariousness in Mexico, 2005Q1-2019Q4," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, volume 41, issue 87, pages 427-456, DOI: 10.15446/cuad.econ.v41n87.92783.
• Jairo Núnez Méndez & Carlos Casta�eda & Juan Felipe Castillo & David Forero & Nicol�s Mart�nez & Olga T�llez & Fedesarrollo, 2022, "Evaluación de impacto de la política de formación de capital humano de alto nivel : programa de créditos condonables de doctorado 1992-2018. Producto 6 : Informe Final y de Recomendaciones," Informes de Investigación, Fedesarrollo, number 20228, Feb.
• Julián Camilo Galvis Niño & Juan Felipe Acevedo Estrella, 2022, "Determinantes de las brechas de género para Colombia 2016-2020," Econógrafos, Escuela de Economía, Universidad Nacional de Colombia, FCE, CID, number 022648, Sep.
• Carlos Andrés Zapata Quimbayo & Ra�l Alberto Chamorro Narv�ez, 2022, "Deuda pública y sostenibilidad fiscal en Colombia: análisis mediante funciones de reacción fiscal," Ensayos de Economía, Universidad Nacional de Colombia Sede Medellín, number 20647, Aug.
• Chang, Minsu & Schorfheide, Frank, 2022, "On the Effects of Monetary Policy Shocks on Earnings and Consumption Heterogeneity," CEPR Discussion Papers, Centre for Economic Policy Research, number 17049, Feb.
• Christophe Bellégo & David Benatia & Louis-Daniel Pape, 2022, "Dealing with Logs and Zeros in Regression Models," Working Papers, Center for Research in Economics and Statistics, number 2022-08, Mar.
• Blazsek, Szabolcs & Escribano, Álvaro, 2022, "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics, Universidad Carlos III de Madrid. Departamento de Economía, number 34757, May.
• Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022, "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series, School of Economics, University of Cape Town, number 2022-03.
• Takaharu ISHII, 2022, "International uncertainty shocks and central bank quantitative easing under supply shocks," Turkish Economic Review, EconSciences Journals, volume 9, issue 3, pages 162-242, September.
• Lachezar Borisov, 2022, "The Relationship Between Food Production Prices And Inflation In Bulgaria," Economic Archive, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 1 Year 20, pages 34-43.
• Лъчезар Борисов, 2022, "Зависимост Между Цените На Производство И Инфлацията При Хранителните Продукти В България," Economic Archive, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 1 Year 20, pages 36-47.
• Olatunji A. Shobande & Simplice A. Asongu, 2022, "Searching for Sustainable Footprints: Does ICT increase CO2 emissions?," Journal of Africa SEER Centre(ASC), Africa SEER Centre(ASC), number 22/009, Jan.
• Olatunji A. Shobande & Simplice A. Asongu, 2022, "The Critical Role of Education and ICT in Promoting Environmental Sustainability in Eastern and Southern Africa: A Panel VAR Approach," Journal of Africa SEER Centre(ASC), Africa SEER Centre(ASC), number 22/015, Jan.
• Hué, Sullivan & Hurlin, Christophe & Pérignon, Christophe & Saurin, Sébastien, 2022, "Explainable Performance," HEC Research Papers Series, HEC Paris, number 1463, Nov, DOI: 10.2139/ssrn.4280563.
• Foroni, Claudia & Gelain, Paolo & Marcellino, Massimiliano, 2022, "The financial accelerator mechanism: does frequency matter?," Working Paper Series, European Central Bank, number 2637, Feb.
• Hoffreumon, Charles & Labhard, Vincent, 2022, "Cross-country cross-technology digitalisation: a Bayesian hierarchical model perspective," Working Paper Series, European Central Bank, number 2700, Aug.
• Daniel Mburamatare & William K. Gboney & Jean De Dieu Hakizimana & Fidel Mutemberezi, 2022, "Analyzing and Forecasting Electricity Consumption in Energy-intensive Industries in Rwanda," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 12, issue 1, pages 483-493.
• Daniel Mburamatare & William K. Gboney & Jean De Dieu Hakizimana & Fidel Mutemberezi, 2022, "Effects of Industrialization, Technology and Labor efficiency on Electricity Consumption: Panel Data Experience of Rwanda, Tanzania and Kenya," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 12, issue 2, pages 349-359, March.
• Quoc Nghi Nguyen & Thi Hong Loc Hoang & Van Nam Mai, 2022, "Applying the Theory of Planned Behavior to Analyze Household Energy-Saving Behavior," International Journal of Energy Economics and Policy, International Journal of Energy Economics and Policy, volume 12, issue 5, pages 287-293, September.
• Müller, Tobias & Christoffel, Kai & Mazelis, Falk & Montes-Galdón, Carlos, 2022, "Disciplining expectations and the forward guidance puzzle," Journal of Economic Dynamics and Control, Elsevier, volume 137, issue C, DOI: 10.1016/j.jedc.2022.104336.
• Karamysheva, Madina & Skrobotov, Anton, 2022, "Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations," Journal of Economic Dynamics and Control, Elsevier, volume 138, issue C, DOI: 10.1016/j.jedc.2022.104358.
• Fernández-Villaverde, Jesús & Jones, Charles I., 2022, "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, volume 140, issue C, DOI: 10.1016/j.jedc.2022.104318.
• Rathnayaka, Shashika D. & Selvanathan, Eliyathamby A. & Selvanathan, Saroja, 2022, "Modelling the consumption patterns in the Asian countries," Economic Analysis and Policy, Elsevier, volume 74, issue C, pages 277-296, DOI: 10.1016/j.eap.2022.02.004.
• Qu, Hui & Zhang, Yi, 2022, "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, volume 106, issue C, DOI: 10.1016/j.econmod.2021.105699.
• Wang, Tianyi & Liang, Fang & Huang, Zhuo & Yan, Hong, 2022, "Do realized higher moments have information content? - VaR forecasting based on the realized GARCH-RSRK model," Economic Modelling, Elsevier, volume 109, issue C, DOI: 10.1016/j.econmod.2022.105781.
• Alanya-Beltran, Willy, 2022, "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, volume 115, issue C, DOI: 10.1016/j.econmod.2022.105984.
• Chalmovianský, Jakub & Němec, Daniel, 2022, "Assessing uncertainty of output gap estimates: Evidence from Visegrad countries," Economic Modelling, Elsevier, volume 116, issue C, DOI: 10.1016/j.econmod.2022.105994.
• Chen, Qi-an & Hu, Qingyu & Yang, Hu & Qi, Kai, 2022, "A kind of new time-weighted nonnegative lasso index-tracking model and its application," The North American Journal of Economics and Finance, Elsevier, volume 59, issue C, DOI: 10.1016/j.najef.2021.101603.
• Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Gil-Alana, Luis Alberiko, 2022, "The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets," The North American Journal of Economics and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.najef.2022.101735.
• Diebold, Francis X. & Göbel, Maximilian, 2022, "A benchmark model for fixed-target Arctic sea ice forecasting," Economics Letters, Elsevier, volume 215, issue C, DOI: 10.1016/j.econlet.2022.110478.
• Zhang, Congshan & Li, Jia & Todorov, Viktor & Tauchen, George, 2022, "Variation and efficiency of high-frequency betas," Journal of Econometrics, Elsevier, volume 228, issue 1, pages 156-175, DOI: 10.1016/j.jeconom.2020.05.022.
• Saart, Patrick W. & Xia, Yingcun, 2022, "Functional time series approach to analyzing asset returns co-movements," Journal of Econometrics, Elsevier, volume 229, issue 1, pages 127-151, DOI: 10.1016/j.jeconom.2020.11.012.
• Freyaldenhoven, Simon, 2022, "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, volume 229, issue 1, pages 80-102, DOI: 10.1016/j.jeconom.2021.04.006.
• Peng, Jingfu & Yang, Yuhong, 2022, "On improvability of model selection by model averaging," Journal of Econometrics, Elsevier, volume 229, issue 2, pages 246-262, DOI: 10.1016/j.jeconom.2020.12.003.
• Todorov, Viktor, 2022, "Nonparametric jump variation measures from options," Journal of Econometrics, Elsevier, volume 230, issue 2, pages 255-280, DOI: 10.1016/j.jeconom.2021.04.005.
• De Luca, Giuseppe & Magnus, Jan R. & Peracchi, Franco, 2022, "Sampling properties of the Bayesian posterior mean with an application to WALS estimation," Journal of Econometrics, Elsevier, volume 230, issue 2, pages 299-317, DOI: 10.1016/j.jeconom.2021.04.008.
• Hansen, Peter Reinhard & Dumitrescu, Elena-Ivona, 2022, "How should parameter estimation be tailored to the objective?," Journal of Econometrics, Elsevier, volume 230, issue 2, pages 535-558, DOI: 10.1016/j.jeconom.2020.12.014.
• Inoue, Atsushi & Kilian, Lutz, 2022, "Joint Bayesian inference about impulse responses in VAR models," Journal of Econometrics, Elsevier, volume 231, issue 2, pages 457-476, DOI: 10.1016/j.jeconom.2021.05.010.
• Diebold, Francis X. & Rudebusch, Glenn D., 2022, "Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections," Journal of Econometrics, Elsevier, volume 231, issue 2, pages 520-534, DOI: 10.1016/j.jeconom.2020.12.007.
• Blackburn, McKinley L., 2022, "Testing for coefficient differences across nested linear regression specifications," Econometrics and Statistics, Elsevier, volume 23, issue C, pages 1-18, DOI: 10.1016/j.ecosta.2021.03.007.
• Pagan, Adrian & Robinson, Tim, 2022, "Excess shocks can limit the economic interpretation," European Economic Review, Elsevier, volume 145, issue C, DOI: 10.1016/j.euroecorev.2022.104120.
• Korobilis, Dimitris, 2022, "A new algorithm for structural restrictions in Bayesian vector autoregressions," European Economic Review, Elsevier, volume 148, issue C, DOI: 10.1016/j.euroecorev.2022.104241.
• Nazemi, Abdolreza & Baumann, Friedrich & Fabozzi, Frank J., 2022, "Intertemporal defaulted bond recoveries prediction via machine learning," European Journal of Operational Research, Elsevier, volume 297, issue 3, pages 1162-1177, DOI: 10.1016/j.ejor.2021.06.047.
• Fianu, Emmanuel Senyo & Ahelegbey, Daniel Felix & Grossi, Luigi, 2022, "Modeling risk contagion in the Italian zonal electricity market," European Journal of Operational Research, Elsevier, volume 298, issue 2, pages 656-679, DOI: 10.1016/j.ejor.2021.06.052.
• Bastos, João A. & Matos, Sara M., 2022, "Explainable models of credit losses," European Journal of Operational Research, Elsevier, volume 301, issue 1, pages 386-394, DOI: 10.1016/j.ejor.2021.11.009.
• Silveira, Douglas & Vasconcelos, Silvinha & Resende, Marcelo & Cajueiro, Daniel O., 2022, "Won’t Get Fooled Again: A supervised machine learning approach for screening gasoline cartels," Energy Economics, Elsevier, volume 105, issue C, DOI: 10.1016/j.eneco.2021.105711.
• Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022, "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, volume 106, issue C, DOI: 10.1016/j.eneco.2021.105760.
• Pincheira-Brown, Pablo & Bentancor, Andrea & Hardy, Nicolás & Jarsun, Nabil, 2022, "Forecasting fuel prices with the Chilean exchange rate: Going beyond the commodity currency hypothesis," Energy Economics, Elsevier, volume 106, issue C, DOI: 10.1016/j.eneco.2021.105802.
• Kilian, Lutz, 2022, "Understanding the estimation of oil demand and oil supply elasticities," Energy Economics, Elsevier, volume 107, issue C, DOI: 10.1016/j.eneco.2022.105844.
• Ren, Xiaohang & Duan, Kun & Tao, Lizhu & Shi, Yukun & Yan, Cheng, 2022, "Carbon prices forecasting in quantiles," Energy Economics, Elsevier, volume 108, issue C, DOI: 10.1016/j.eneco.2022.105862.
• Kilian, Lutz, 2022, "Facts and fiction in oil market modeling," Energy Economics, Elsevier, volume 110, issue C, DOI: 10.1016/j.eneco.2022.105973.
• Hitz, Lukas & Mustafi, Ismail H. & Zimmermann, Heinz, 2022, "The pricing of volatility risk in the US equity market," International Review of Financial Analysis, Elsevier, volume 79, issue C, DOI: 10.1016/j.irfa.2021.101951.
• Ellington, Michael & Stamatogiannis, Michalis P. & Zheng, Yawen, 2022, "A study of cross-industry return predictability in the Chinese stock market," International Review of Financial Analysis, Elsevier, volume 83, issue C, DOI: 10.1016/j.irfa.2022.102249.
• Kurosaki, Tetsuo & Kim, Young Shin, 2022, "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Finance Research Letters, Elsevier, volume 45, issue C, DOI: 10.1016/j.frl.2021.102143.
• Kutuk, Yasin & Barokas, Lina, 2022, "Multivariate CDS risk premium prediction with SOTA RNNs on MI[N]T countries," Finance Research Letters, Elsevier, volume 45, issue C, DOI: 10.1016/j.frl.2021.102198.
• Caporin, Massimiliano & Garcia-Jorcano, Laura & Jimenez-Martin, Juan-Angel, 2022, "Measuring systemic risk during the COVID-19 period: A TALIS3 approach," Finance Research Letters, Elsevier, volume 46, issue PA, DOI: 10.1016/j.frl.2021.102304.
• Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022, "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, volume 46, issue PA, DOI: 10.1016/j.frl.2021.102365.
• Tran, Quang Van & Kukal, Jaromir, 2022, "A novel heavy tail distribution of logarithmic returns of cryptocurrencies," Finance Research Letters, Elsevier, volume 47, issue PA, DOI: 10.1016/j.frl.2021.102574.
• Jin, Chenglu & Lu, Xingyu & Zhang, Yihan, 2022, "Market reaction, COVID-19 pandemic and return distribution," Finance Research Letters, Elsevier, volume 47, issue PB, DOI: 10.1016/j.frl.2022.102701.
• Achakzai, Muhammad Atif Khan & Juan, Peng, 2022, "Using machine learning Meta-Classifiers to detect financial frauds," Finance Research Letters, Elsevier, volume 48, issue C, DOI: 10.1016/j.frl.2022.102915.
• González-Pla, Francisco & Lovreta, Lidija, 2022, "Modeling and forecasting firm-specific volatility: The role of asymmetry and long-memory," Finance Research Letters, Elsevier, volume 48, issue C, DOI: 10.1016/j.frl.2022.102931.
• Shang, Yue & Wei, Yu & Chen, Yongfei, 2022, "Cryptocurrency policy uncertainty and gold return forecasting: A dynamic Occam's window approach," Finance Research Letters, Elsevier, volume 50, issue C, DOI: 10.1016/j.frl.2022.103251.
• Gaillard, Aurélie & García-Lorenzo, Borja & Renaud, Thomas & Wittwer, Jérôme, 2022, "Does integrated care mean fewer hospitalizations? An evaluation of a French field experiment," Health Policy, Elsevier, volume 126, issue 8, pages 786-794, DOI: 10.1016/j.healthpol.2022.05.009.
• Meng, Jin & Chan, Kung-Sik, 2022, "Penalized quasi-likelihood estimation of generalized Pareto regression – consistent identification of risk factors for extreme losses," Insurance: Mathematics and Economics, Elsevier, volume 104, issue C, pages 60-75, DOI: 10.1016/j.insmatheco.2022.01.005.
• Henckaerts, Roel & Antonio, Katrien, 2022, "The added value of dynamically updating motor insurance prices with telematics collected driving behavior data," Insurance: Mathematics and Economics, Elsevier, volume 105, issue C, pages 79-95, DOI: 10.1016/j.insmatheco.2022.03.011.
• Hu, Changyue & Quan, Zhiyu & Chong, Wing Fung, 2022, "Imbalanced learning for insurance using modified loss functions in tree-based models," Insurance: Mathematics and Economics, Elsevier, volume 106, issue C, pages 13-32, DOI: 10.1016/j.insmatheco.2022.04.010.
• Malavasi, Matteo & Peters, Gareth W. & Shevchenko, Pavel V. & Trück, Stefan & Jang, Jiwook & Sofronov, Georgy, 2022, "Cyber risk frequency, severity and insurance viability," Insurance: Mathematics and Economics, Elsevier, volume 106, issue C, pages 90-114, DOI: 10.1016/j.insmatheco.2022.05.003.
• Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022, "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, volume 38, issue 1, pages 51-73, DOI: 10.1016/j.ijforecast.2019.08.007.
• Taylor, James W., 2022, "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, volume 140, issue C, DOI: 10.1016/j.jbankfin.2022.106519.
• Hersh, Jonathan & Lang, Bree J. & Lang, Matthew, 2022, "Car accidents, smartphone adoption and 3G coverage," Journal of Economic Behavior & Organization, Elsevier, volume 196, issue C, pages 278-293, DOI: 10.1016/j.jebo.2022.01.033.
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