Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2022

• 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.
• Mei, Dexiang & Xie, Yutang, 2022, "U.S. grain commodity futures price volatility: Does trade policy uncertainty matter?," Finance Research Letters, Elsevier, volume 48, issue C, DOI: 10.1016/j.frl.2022.103028.
• Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022, "Has the interaction between skewness and kurtosis of asset returns information content for risk forecasting?," Finance Research Letters, Elsevier, volume 49, issue C, DOI: 10.1016/j.frl.2022.103105.
• Bouri, Elie & Christou, Christina & Gupta, Rangan, 2022, "Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models," Finance Research Letters, Elsevier, volume 49, issue C, DOI: 10.1016/j.frl.2022.103193.
• Papík, Mário & Papíková, Lenka, 2022, "Detecting accounting fraud in companies reporting under US GAAP through data mining," International Journal of Accounting Information Systems, Elsevier, volume 45, issue C, DOI: 10.1016/j.accinf.2022.100559.
• Al-Mudafer, Muhammed Taher & Avanzi, Benjamin & Taylor, Greg & Wong, Bernard, 2022, "Stochastic loss reserving with mixture density neural networks," Insurance: Mathematics and Economics, Elsevier, volume 105, issue C, pages 144-174, DOI: 10.1016/j.insmatheco.2022.03.010.
• Ang, Zi Qing & Lee, See Keong, 2022, "Hierarchical Bayesian Gaussian process regression model for loss reserving using combinations of squared exponential kernels," Insurance: Mathematics and Economics, Elsevier, volume 105, issue C, pages 54-63, DOI: 10.1016/j.insmatheco.2022.03.008.
• 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.
• Meng, Shengwang & Gao, Yaqian & Huang, Yifan, 2022, "Actuarial intelligence in auto insurance: Claim frequency modeling with driving behavior features and improved boosted trees," Insurance: Mathematics and Economics, Elsevier, volume 106, issue C, pages 115-127, DOI: 10.1016/j.insmatheco.2022.06.001.
• 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.
• Steinmetz, Julia & Jentsch, Carsten, 2022, "Asymptotic theory for Mack's model," Insurance: Mathematics and Economics, Elsevier, volume 107, issue C, pages 223-268, DOI: 10.1016/j.insmatheco.2022.08.007.
• Verschuren, Robert Matthijs, 2022, "Frequency-severity experience rating based on latent Markovian risk profiles," Insurance: Mathematics and Economics, Elsevier, volume 107, issue C, pages 379-392, DOI: 10.1016/j.insmatheco.2022.09.007.
• Xu, Shuzhe & Zhang, Chuanlong & Hong, Don, 2022, "BERT-based NLP techniques for classification and severity modeling in basic warranty data study," Insurance: Mathematics and Economics, Elsevier, volume 107, issue C, pages 57-67, DOI: 10.1016/j.insmatheco.2022.07.013.
• Zhang, Dan & Farnoosh, Arash & Lantz, Frédéric, 2022, "Does something change in the oil market with the COVID-19 crisis?," International Economics, Elsevier, volume 169, issue C, pages 252-268, DOI: 10.1016/j.inteco.2022.01.008.
• Ferrara, Laurent & Yapi, Joseph, 2022, "Measuring exchange rate risks during periods of uncertainty," International Economics, Elsevier, volume 170, issue C, pages 202-212, DOI: 10.1016/j.inteco.2022.04.001.
• He, Mengxi & Zhang, Yaojie, 2022, "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 81, issue C, DOI: 10.1016/j.intfin.2022.101675.
• Martin, Gael M. & Loaiza-Maya, Rubén & Maneesoonthorn, Worapree & Frazier, David T. & Ramírez-Hassan, Andrés, 2022, "Optimal probabilistic forecasts: When do they work?," International Journal of Forecasting, Elsevier, volume 38, issue 1, pages 384-406, DOI: 10.1016/j.ijforecast.2021.05.008.
• Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2022, "Forecasting realized volatility of agricultural commodities," International Journal of Forecasting, Elsevier, volume 38, issue 1, pages 74-96, DOI: 10.1016/j.ijforecast.2019.08.011.
• Lahiri, Kajal & Yang, Cheng, 2022, "Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York," International Journal of Forecasting, Elsevier, volume 38, issue 2, pages 545-566, DOI: 10.1016/j.ijforecast.2021.10.005.
• Foroni, Claudia & Marcellino, Massimiliano & Stevanovic, Dalibor, 2022, "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," International Journal of Forecasting, Elsevier, volume 38, issue 2, pages 596-612, DOI: 10.1016/j.ijforecast.2020.12.005.
• Larson, William D. & Sinclair, Tara M., 2022, "Nowcasting unemployment insurance claims in the time of COVID-19," International Journal of Forecasting, Elsevier, volume 38, issue 2, pages 635-647, DOI: 10.1016/j.ijforecast.2021.01.001.
• Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2022, "The illusion of oil return predictability: The choice of data matters!," Journal of Banking & Finance, Elsevier, volume 134, issue C, DOI: 10.1016/j.jbankfin.2021.106331.
• Caporin, Massimiliano & Costola, Michele & Garibal, Jean-Charles & Maillet, Bertrand, 2022, "Systemic risk and severe economic downturns: A targeted and sparse analysis," Journal of Banking & Finance, Elsevier, volume 134, issue C, DOI: 10.1016/j.jbankfin.2021.106339.
• 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.
• Huang, Rong & Pilbeam, Keith & Pouliot, William, 2022, "Are macroeconomic forecasters optimists or pessimists? A reassessment of survey based forecasts," Journal of Economic Behavior & Organization, Elsevier, volume 197, issue C, pages 706-724, DOI: 10.1016/j.jebo.2022.03.012.
• Benchimol, Jonathan & El-Shagi, Makram & Saadon, Yossi, 2022, "Do expert experience and characteristics affect inflation forecasts?," Journal of Economic Behavior & Organization, Elsevier, volume 201, issue C, pages 205-226, DOI: 10.1016/j.jebo.2022.06.025.
• Obaid, Khaled & Pukthuanthong, Kuntara, 2022, "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, volume 144, issue 1, pages 273-297, DOI: 10.1016/j.jfineco.2021.06.002.
• Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2022, "Predicting agri-food quality across space: A Machine Learning model for the acknowledgment of Geographical Indications," Food Policy, Elsevier, volume 112, issue C, DOI: 10.1016/j.foodpol.2022.102345.
• Kishor, N. Kundan & Marfatia, Hardik A. & Nam, Gooan & Rizi, Majid Haghani, 2022, "The local employment effect of house prices: Evidence from U.S. States," Journal of Housing Economics, Elsevier, volume 55, issue C, DOI: 10.1016/j.jhe.2021.101805.
• Degiannakis, Stavros & Filis, George, 2022, "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, volume 123, issue C, DOI: 10.1016/j.jimonfin.2021.102594.
• Casabianca, Elizabeth Jane & Catalano, Michele & Forni, Lorenzo & Giarda, Elena & Passeri, Simone, 2022, "A machine learning approach to rank the determinants of banking crises over time and across countries," Journal of International Money and Finance, Elsevier, volume 129, issue C, DOI: 10.1016/j.jimonfin.2022.102739.
• Dai, Peng-Fei & Xiong, Xiong & Duc Huynh, Toan Luu & Wang, Jiqiang, 2022, "The impact of economic policy uncertainties on the volatility of European carbon market," Journal of Commodity Markets, Elsevier, volume 26, issue C, DOI: 10.1016/j.jcomm.2021.100208.
• Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2022, "Common factors and the dynamics of cereal prices. A forecasting perspective," Journal of Commodity Markets, Elsevier, volume 28, issue C, DOI: 10.1016/j.jcomm.2021.100240.
• Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022, "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, volume 28, issue C, DOI: 10.1016/j.jcomm.2022.100248.
• Stolbov, Mikhail & Shchepeleva, Maria, 2022, "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, volume 25, issue C, DOI: 10.1016/j.jeca.2021.e00238.
• Liu, Guangqiang & Guo, Xiaozhu, 2022, "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, volume 75, issue C, DOI: 10.1016/j.resourpol.2021.102481.
• Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022, "Forecasting oil prices over 150 years: The role of tail risks," Resources Policy, Elsevier, volume 75, issue C, DOI: 10.1016/j.resourpol.2021.102508.
• Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022, "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, volume 75, issue C, DOI: 10.1016/j.resourpol.2021.102521.
• Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022, "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, volume 75, issue C, DOI: 10.1016/j.resourpol.2021.102527.
• Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022, "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, volume 76, issue C, DOI: 10.1016/j.resourpol.2022.102570.
• Gupta, Rangan & Pierdzioch, Christian & Salisu, Afees A., 2022, "Oil-price uncertainty and the U.K. unemployment rate: A forecasting experiment with random forests using 150 years of data," Resources Policy, Elsevier, volume 77, issue C, DOI: 10.1016/j.resourpol.2022.102662.
• Hong, Yanran & Wang, Lu & Liang, Chao & Umar, Muhammad, 2022, "Impact of financial instability on international crude oil volatility: New sight from a regime-switching framework," Resources Policy, Elsevier, volume 77, issue C, DOI: 10.1016/j.resourpol.2022.102667.
• Gupta, Rangan & Pierdzioch, Christian, 2022, "Climate risks and forecastability of the realized volatility of gold and other metal prices," Resources Policy, Elsevier, volume 77, issue C, DOI: 10.1016/j.resourpol.2022.102681.
• Mei, Dexiang & Zhao, Chenchen & Luo, Qin & Li, Yan, 2022, "Forecasting the Chinese low-carbon index volatility," Resources Policy, Elsevier, volume 77, issue C, DOI: 10.1016/j.resourpol.2022.102732.
• Lin, Yu & Liao, Qidong & Lin, Zixiao & Tan, Bin & Yu, Yuanyuan, 2022, "A novel hybrid model integrating modified ensemble empirical mode decomposition and LSTM neural network for multi-step precious metal prices prediction," Resources Policy, Elsevier, volume 78, issue C, DOI: 10.1016/j.resourpol.2022.102884.
• Kakade, Kshitij & Jain, Ishan & Mishra, Aswini Kumar, 2022, "Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach," Resources Policy, Elsevier, volume 78, issue C, DOI: 10.1016/j.resourpol.2022.102903.
• Liu, Guangqiang & Zeng, Qing & Lei, Juan, 2022, "Dynamic risks from climate policy uncertainty: A case study for the natural gas market," Resources Policy, Elsevier, volume 79, issue C, DOI: 10.1016/j.resourpol.2022.103014.
• Zhao, Jing, 2022, "Exploring the influence of the main factors on the crude oil price volatility: An analysis based on GARCH-MIDAS model with Lasso approach," Resources Policy, Elsevier, volume 79, issue C, DOI: 10.1016/j.resourpol.2022.103031.
• Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022, "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, volume 79, issue C, DOI: 10.1016/j.resourpol.2022.103093.
• Khezri, Mohsen & Heshmati, Almas & Ghazal, Reza & Khodaei, Mehdi, 2022, "Non-resource revenues and the resource curse in different institutional structures: The DIGNAR-MTFF model," Resources Policy, Elsevier, volume 79, issue C, DOI: 10.1016/j.resourpol.2022.103120.
• Xu, Yongan & Li, Ming & Yan, Wen & Bai, Jiancheng, 2022, "Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty," Resources Policy, Elsevier, volume 79, issue C, DOI: 10.1016/j.resourpol.2022.103141.
• Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022, "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, volume 74, issue C, DOI: 10.1016/j.labeco.2021.102097.
• Restrepo-Ángel, Sergio & Rincón-Castro, Hernán & Ospina-Tejeiro, Juan J., 2022, "Multipliers of taxes and public spending in Colombia: SVAR and local projections approaches," Latin American Journal of Central Banking (previously Monetaria), Elsevier, volume 3, issue 3, DOI: 10.1016/j.latcb.2022.100070.
• Maples, Chellie H. & Hagerman, Amy D. & Lambert, Dayton M., 2022, "Ex-ante effects of the 2018 Agricultural Improvement Act’s grassland initiative," Land Use Policy, Elsevier, volume 116, issue C, DOI: 10.1016/j.landusepol.2022.106055.
• Umar, Zaghum & Yousaf, Imran & Gubareva, Mariya & Vo, Xuan Vinh, 2022, "Spillover and risk transmission between the term structure of the US interest rates and Islamic equities," Pacific-Basin Finance Journal, Elsevier, volume 72, issue C, DOI: 10.1016/j.pacfin.2022.101712.
• Yao, Haixiang & Xia, Shenghao & Liu, Hao, 2022, "Six-factor asset pricing and portfolio investment via deep learning: Evidence from Chinese stock market," Pacific-Basin Finance Journal, Elsevier, volume 76, issue C, DOI: 10.1016/j.pacfin.2022.101886.
• Bui, Quynh & Ślepaczuk, Robert, 2022, "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 592, issue C, DOI: 10.1016/j.physa.2021.126784.
• Li, Wei-Zhen & Zhai, Jin-Rui & Jiang, Zhi-Qiang & Wang, Gang-Jin & Zhou, Wei-Xing, 2022, "Predicting tail events in a RIA-EVT-Copula framework," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 600, issue C, DOI: 10.1016/j.physa.2022.127524.
• Ahmed, Walid M.A., 2022, "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, volume 83, issue C, pages 135-151, DOI: 10.1016/j.qref.2021.12.003.
• Su, Zhi & Liu, Peng & Fang, Tong, 2022, "Uncertainty matters in US financial information spillovers: Evidence from a directed acyclic graph approach," The Quarterly Review of Economics and Finance, Elsevier, volume 84, issue C, pages 229-242, DOI: 10.1016/j.qref.2022.01.007.
• Fasanya, Ismail O. & Oyewole, Oluwatomisin J. & Oliyide, Johnson A., 2022, "Investors' sentiments and the dynamic connectedness between cryptocurrency and precious metals markets," The Quarterly Review of Economics and Finance, Elsevier, volume 86, issue C, pages 347-364, DOI: 10.1016/j.qref.2022.08.009.
• Cerqua, Augusto & Letta, Marco, 2022, "Local inequalities of the COVID-19 crisis," Regional Science and Urban Economics, Elsevier, volume 92, issue C, DOI: 10.1016/j.regsciurbeco.2021.103752.
• Islam, Md. Monirul & Irfan, Muhammad & Shahbaz, Muhammad & Vo, Xuan Vinh, 2022, "Renewable and non-renewable energy consumption in Bangladesh: The relative influencing profiles of economic factors, urbanization, physical infrastructure and institutional quality," Renewable Energy, Elsevier, volume 184, issue C, pages 1130-1149, DOI: 10.1016/j.renene.2021.12.020.
• Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022, "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, volume 77, issue C, pages 179-190, DOI: 10.1016/j.iref.2021.09.017.
• Umar, Zaghum & Riaz, Yasir & Aharon, David Y., 2022, "Network connectedness dynamics of the yield curve of G7 countries," International Review of Economics & Finance, Elsevier, volume 79, issue C, pages 275-288, DOI: 10.1016/j.iref.2022.02.052.
• Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je & Gau, Yin-Feng, 2022, "Risk-return trade-off in the Australian Securities Exchange: Accounting for overnight effects, realized higher moments, long-run relations, and fractional cointegration," International Review of Economics & Finance, Elsevier, volume 80, issue C, pages 384-401, DOI: 10.1016/j.iref.2022.02.057.
• Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022, "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, volume 59, issue C, DOI: 10.1016/j.ribaf.2021.101567.
• Kristóf, Tamás & Virág, Miklós, 2022, "EU-27 bank failure prediction with C5.0 decision trees and deep learning neural networks," Research in International Business and Finance, Elsevier, volume 61, issue C, DOI: 10.1016/j.ribaf.2022.101644.
• Wang, Yaqi & Wang, Chunfeng & Sensoy, Ahmet & Yao, Shouyu & Cheng, Feiyang, 2022, "Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning," Research in International Business and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.ribaf.2022.101683.
• Su, Yuandong & Lu, Xinjie & Zeng, Qing & Huang, Dengshi, 2022, "Good air quality and stock market returns," Research in International Business and Finance, Elsevier, volume 62, issue C, DOI: 10.1016/j.ribaf.2022.101723.
• Tripathy, Naliniprava, 2022, "Long memory and volatility persistence across BRICS stock markets," Research in International Business and Finance, Elsevier, volume 63, issue C, DOI: 10.1016/j.ribaf.2022.101782.
• Naimoli, Antonio, 2022, "Modelling the persistence of Covid-19 positivity rate in Italy," Socio-Economic Planning Sciences, Elsevier, volume 82, issue PA, DOI: 10.1016/j.seps.2022.101225.
• Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022, "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, volume 182, issue C, DOI: 10.1016/j.techfore.2022.121810.
• Liu Yang & Kajal Lahiri & Adrian Pagan, 2022, "Getting the ROC into Sync," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2022-01, Jan.
• James Morley & Trung Duc Tran & Benjamin Wong, 2022, "A Simple Correction for Misspecification in Trend-Cycle Decompositions with an Application to Estimating r," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2022-02, Jan, revised Mar 2023.
• Fabio Calonaci & George Kapetanios & Simon Price, 2022, "Stock Returns Predictability with Unstable Predictors," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2022-04, Jan.
• Laurent Ferrara & Aikaterini Karadimitropoulou & Athanasios Triantafyllou, 2022, "Commodity Price Uncertainty Comovement: Does It Matter for Global Economic Growth?," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2022-08, Jan.
• Jarvis, Stephen & Deschenes, Olivier & Jha, Akshaya, 2022, "The private and external costs of Germany’s nuclear phase-out," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 113634, Jun.
• Oparina, Ekaterina & Kaiser, Caspar & Gentile, Niccoló & Tkatchenko, Alexandre & Clark, Andrew E. & De Neve, Jan-Emmanuel & D'Ambrosio, Conchita, 2022, "Human wellbeing and machine learning," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 117955, Jul.
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022, "Efficient Combined Estimation under Structural Breaks," Advances in Econometrics, Emerald Group Publishing Limited, "Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling", DOI: 10.1108/S0731-90532021000043A007.
• Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2022, "Smooth Robust Multi-Horizon Forecasts," Advances in Econometrics, Emerald Group Publishing Limited, "Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling", DOI: 10.1108/S0731-90532021000043A008.
• Luca Nocciola, 2022, "Finite Sample Forecast Properties and Window Length Under Breaks in Cointegrated Systems," Advances in Econometrics, Emerald Group Publishing Limited, "Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling", DOI: 10.1108/S0731-90532021000043A009.
• Luis Uzeda, 2022, "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, Emerald Group Publishing Limited, "Essays in Honour of Fabio Canova", DOI: 10.1108/S0731-90532022000044A003.
• Xuan Liu & G. Cornelis van Kooten & Eric Martin Gerbrandt & Jun Duan, 2022, "Prospects for weather-indexed insurance for blueberry growers," Agricultural Finance Review, Emerald Group Publishing Limited, volume 83, issue 2, pages 333-351, December, DOI: 10.1108/AFR-05-2022-0059.
• Peterson K. Ozili & Thankom G. Arun, 2022, "Does economic policy uncertainty affect bank profitability?," International Journal of Managerial Finance, Emerald Group Publishing Limited, volume 19, issue 4, pages 803-830, August, DOI: 10.1108/IJMF-04-2022-0177.
• Davide Fiaschi & Cristina Tealdi, 2022, "Young people between education and the labour market during the COVID-19 pandemic in Italy," International Journal of Manpower, Emerald Group Publishing Limited, volume 43, issue 7, pages 1719-1757, July, DOI: 10.1108/IJM-06-2021-0352.
• Fariq Rahadiyan Chalik & Taufik Faturohman, 2022, "Customer Satisfaction of E-wallet User: An Adoption of Information System Success Model," International Symposia in Economic Theory and Econometrics, Emerald Group Publishing Limited, "Quantitative Analysis of Social and Financial Market Development", DOI: 10.1108/S1571-038620220000030005.
• Thi Thu Ha Nguyen & Salma Ibrahim & George Giannopoulos, 2022, "Detecting earnings management: a comparison of accrual and real earnings manipulation models," Journal of Applied Accounting Research, Emerald Group Publishing Limited, volume 24, issue 2, pages 344-379, August, DOI: 10.1108/JAAR-08-2021-0217.
• Edmond Berisha & David Gabauer & Rangan Gupta & Jacobus Nel, 2022, "Time-varying predictability of financial stress on inequality in United Kingdom," Journal of Economic Studies, Emerald Group Publishing Limited, volume 50, issue 5, pages 987-1007, August, DOI: 10.1108/JES-02-2022-0103.
• Smita Roy Trivedi, 2022, "A volatile mind? Experimental evidence on dealers' biases and market volatility," Review of Behavioral Finance, Emerald Group Publishing Limited, volume 15, issue 4, pages 550-569, March, DOI: 10.1108/RBF-10-2021-0223.
• Ioannis Georgakopoulos & Dimitrios Piromalis & Panagiotis S. Makrygiannis & Vassilis Zakopoulos & Christos Drosos, 2022, "A Robust Risk Model to Identify Factors that Affect Students’ Critical Achievement in Remote Lab Courses," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), volume 0, issue 3, pages 3-22.
• Vassilis Zakopoulos & Ioannis Georgakopoulos & Pelagia Kontaxaki, 2022, "Developing a Risk Model to Control Attrition by Analyzing Students’ Academic and Nonacademic Data," European Research Studies Journal, European Research Studies Journal, volume 0, issue 2, pages 350-366.
• Calonaci, Fabio & Kapetanios, George & Price, Simon, 2022, "Stock returns predictability with unstable predictors," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 32331, Feb.
• Isaac K. Ofori & Camara K. Obeng & Simplice A. Asongu, 2022, "What Really Drives Economic Growth in Sub-Saharan Africa? Evidence from The Lasso Regularization and Inferential Techniques," Working Papers, European Xtramile Centre of African Studies (EXCAS), number 22/061, Jan.
• Jan Sila & Michael Mark & Ladislav Kristoufek, 2022, "On Empirical Challenges in Forecasting Market Betas in Crypto Markets," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2022/19, Aug, revised Aug 2022.
• Lorena Skufi & Adam Gersl, 2022, "Using Macro-Financial Models to Simulate Macroeconomic Developments During the Covid-19 Pandemic: The Case of Albania," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2022/24, Sep, revised Sep 2022.
• Kirstin Hubrich & Daniel F. Waggoner, 2022, "The Transmission of Financial Shocks and Leverage of Financial Institutions: An Endogenous Regime-Switching Framework," FRB Atlanta Working Paper, Federal Reserve Bank of Atlanta, number 2022-5, Jun, DOI: 10.29338/wp2022-05.
• Daniel Borup & Philippe Goulet Coulombe & Erik Christian Montes Schütte & David E. Rapach & Sander Schwenk-Nebbe, 2022, "The Anatomy of Out-of-Sample Forecasting Accuracy," FRB Atlanta Working Paper, Federal Reserve Bank of Atlanta, number 2022-16, Nov, DOI: 10.29338/wp2022-16.
• Ina Hajdini, 2022, "Mis-specified Forecasts and Myopia in an Estimated New Keynesian Model," Working Papers, Federal Reserve Bank of Cleveland, number 22-03R, Feb, revised 06 Mar 2023, DOI: 10.26509/frbc-wp-202203r.
• Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022, "Forecasting US Inflation Using Bayesian Nonparametric Models," Working Papers, Federal Reserve Bank of Cleveland, number 22-05, Mar, DOI: 10.26509/frbc-wp-202205.
• Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022, "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," Working Papers, Federal Reserve Bank of Cleveland, number 22-06, Mar, DOI: 10.26509/frbc-wp-202206.
• James Mitchell & Aubrey Poon & Dan Zhu, 2022, "Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics," Working Papers, Federal Reserve Bank of Cleveland, number 22-12R, May, revised 11 Apr 2023, DOI: 10.26509/frbc-wp-202212r.
• Michael Clements & Robert W. Rich & Joseph Tracy, 2022, "Surveys of Professionals," Working Papers, Federal Reserve Bank of Cleveland, number 22-13, May, DOI: 10.26509/frbc-wp-202213.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022, "Specification Choices in Quantile Regression for Empirical Macroeconomics," Working Papers, Federal Reserve Bank of Cleveland, number 22-25, Aug, DOI: 10.26509/frbc-wp-202225.
• Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022, "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers, Federal Reserve Bank of Cleveland, number 22-36, Nov, DOI: 10.26509/frbc-wp-202236.
• Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022, "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers, Federal Reserve Bank of Cleveland, number 22-37, Nov, DOI: 10.26509/frbc-wp-202237.
• Kirstin Hubrich & Daniel F. Waggoner, 2022, "The transmission of financial shocks and leverage of financial institutions: An endogenous regime switching framework," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2022-034, Jun, DOI: 10.17016/FEDS.2022.034.
• Amy Y. Guisinger & Michael W. McCracken & Michael T. Owyang, 2022, "Reconsidering the Fed's Inflation Forecasting Advantage," Working Papers, Federal Reserve Bank of St. Louis, number 2022-001, Jan, revised 23 Oct 2023, DOI: 10.20955/wp.2022.001.
• Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022, "A Bayesian Approach to Inference on Probabilistic Surveys," Staff Reports, Federal Reserve Bank of New York, number 1025, Jul.
• Tobias Adrian & Nina Boyarchenko & Domenico Giannone & Ananthakrishnan Prasad & Dulani Seneviratne & Yanzhe Xiao, 2022, "800,000 Years of Climate Risk," Staff Reports, Federal Reserve Bank of New York, number 1031, Sep.
• Vitaly Meursault & Daniel Moulton & Larry Santucci & Nathan Schor, 2022, "One Threshold Doesn’t Fit All: Tailoring Machine Learning Predictions of Consumer Default for Lower-Income Areas," Working Papers, Federal Reserve Bank of Philadelphia, number 22-39, Nov, DOI: 10.21799/frbp.wp.2022.39.
• Abay, Kibrom A. & Yonzan, Nishant & Kurdi, Sikandra & Tafere, Kibrom, 2022, "Revisiting poverty trends and the role of social protection systems in Africa during the COVID-19 pandemic," IFPRI discussion papers, International Food Policy Research Institute (IFPRI), number 2142.
• Andrey Yu. Nevela & Victor A. Lapshin, 2022, "Model Risk and Basic Approaches to its Estimation on Example of Market Risk Models," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 2, pages 91-112, April, DOI: 10.31107/2075-1990-2022-2-91-112.
• Daria S. Leonteva, 2022, "Using Market Indicators to Refine Estimates of Corporate Bankruptcy Probabilities," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 74-90, December, DOI: 10.31107/2075-1990-2022-6-74-90.
• Tsukhlo Sergey, 2022, "Russian industrial sector in 2021: (based on surveys’ findings)," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2022-1203, revised 2022.
• Barinova Vera & Zemtsov Tsepan & Tsareva Yulia, 2022, "Russian small and medium-sized businesses during coronavirus crisis," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2022-1208, revised 2022.
• Andrey V. Polbin & Andrey V. Shumilov, 2022, "Forecasting Output Growth of Russian Manufacturing Industries Using Panel Data Models
  [Об Использовании Моделей Панельных Данных Для Прогнозирования Темпов Роста Отраслей Российской Обрабатывающей Промышленности]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 2, pages 15-19, February.
• Vadim Ye. Zyamalov, 2022, "Applying the Multi Regime Models to the Modelling the Dynamics of Financial Time Series
  [Использование Многорежимных Моделей Для Моделирования Динамики Финансовых Временных Рядов]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 5, pages 13-19, May.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "IMF and World Bank Downgraded World Economy Growth Forecast for 2022–2023 and Raised Inflation Projection for 2022
  [Мвф И Всемирный Банк Понизили Прогноз Роста Мировой Экономики В 2022–2023 Гг. И Повысили Прогноз Инфляции На 2022 Г]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 6, pages 4-14, June.
• Natalia S. Nikitina, 2022, "Forecasting the Real Estate Price Index in Russia
  [Прогнозирование Индекса Цен На Недвижимость В России]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 6, pages 23-28, June.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "G20 Countries Tightened Their Monetary Policies in May 2022, Global Economic Outlook Revised Downward
  [В Мае 2022 Г. Продолжилось Ужесточение Монетарной Политики В Странах G20, Прогнозы Роста Мировой Экономики Ухудшались]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 7, pages 4-14, July.
• Andrey V. Zubarev & Mariya A. Kirillova, 2022, "Estimating the Decline in Russia's GDP Due to the Trade Restrictions with the EU, the US, Great Britain and Japan
  [Оценка Потерь Ввп Из-За Ограничения Странами Ес, Сша, Великобританией И Японией Торговли С Россией]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 8, pages 21-23, August.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "Global Economic Development: Worsening Forecasts
  [Развитие Мировой Экономики: Ухудшение Прогнозов]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 9, pages 4-14, September.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "Social and Economic Situation in G20 Countries: Outlooks are Getting Worse
  [Социально-Экономическое Положение В Странах G20: Прогнозы Ухудшаются]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 10, pages 4-12, October.
• Andrey V. Polbin & Andrey V. Shumilov, 2022, "Об Использовании Моделей Панельных Данных Для Прогнозирования Темпов Роста Отраслей Российской Обрабатывающей Промышленности," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 2, pages 15-19, February.
• Vadim Ye. Zyamalov, 2022, "Использование Многорежимных Моделей Для Моделирования Динамики Финансовых Временных Рядов," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 5, pages 13-19, May.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "Мвф И Всемирный Банк Понизили Прогноз Роста Мировой Экономики В 2022–2023 Гг. И Повысили Прогноз Инфляции На 2022 Г," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 6, pages 4-14, June.
• Natalia S. Nikitina, 2022, "Прогнозирование Индекса Цен На Недвижимость В России," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 6, pages 23-28, June.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "В Мае 2022 Г. Продолжилось Ужесточение Монетарной Политики В Странах G20, Прогнозы Роста Мировой Экономики Ухудшались," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 7, pages 4-14, July.
• Andrey V. Zubarev & Mariya A. Kirillova, 2022, "Оценка Потерь Ввп Из-За Ограничения Странами Ес, Сша, Великобританией И Японией Торговли С Россией," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 8, pages 21-23, August.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "Развитие Мировой Экономики: Ухудшение Прогнозов," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 9, pages 4-14, September.
• Urmat K. Dzhunkeev & Yury N. Perevyshin & Pavel V. Trunin & Maria I. Chembulatova, 2022, "Социально-Экономическое Положение В Странах G20: Прогнозы Ухудшаются," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 10, pages 4-12, October.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022, "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, volume 15, issue 22, pages 1-26, November.
• William A. Barnett & Kun He & Jingtong He, 2022, "Consumption Loan Augmented Divisia Monetary Index and China Monetary Aggregation," JRFM, MDPI, volume 15, issue 10, pages 1-17, October.
• Dean Fantazzini, 2022, "Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death," JRFM, MDPI, volume 15, issue 7, pages 1-34, July.
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• Miriam Hortas-Rico & Vicente Rios, 2022, "Does women´s political empowerment matter for income inequality?," Working Papers. Collection A: Public economics, governance and decentralization, Universidade de Vigo, GEN - Governance and Economics research Network, number 2206, Nov.
• Dr. Britta Stöver & Dr. Markus Flaute & Saskia Reuschel, 2022, "Forschungsstand und Literatur zu den volkswirtschaftlichen Folgekosten des Klimawandels in Deutschland – Studie im Rahmen des Projektes Kosten durch Klimawandelfolgen in Deutschland," GWS Research Report Series, GWS - Institute of Economic Structures Research, number 22-1.
• Markus Flaute & Saskia Reuschel & Britta Stöver, 2022, "Volkswirtschaftliche Folgekosten durch Klimawandel: Szenarioanalyse bis 2050 – Studie im Rahmen des Projektes Kosten durch Klimawandelfolgen in Deutschland," GWS Research Report Series, GWS - Institute of Economic Structures Research, number 22-2.
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• Tobias Broer & Alexandre Kohlhas & Kurt Mitman & Kathrin Schlafmann, 2022, "On the possibility of Krusell-Smith Equilibria," Post-Print, HAL, number halshs-03758982, Aug, DOI: 10.1016/j.jedc.2022.104391.
• Tobias Broer & Alexandre Kohlhas & Kurt Mitman & Kathrin Schlafmann, 2022, "On the possibility of Krusell-Smith Equilibria," PSE-Ecole d'économie de Paris (Postprint), HAL, number halshs-03758982, Aug, DOI: 10.1016/j.jedc.2022.104391.
• Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022, "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Sciences Po Economics Publications (main), HAL, number hal-03573080, Feb.
• Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022, "Monitoring the Economy in Real Time: Trends and Gaps in Real Activity and Prices," Working Papers, HAL, number hal-03573080, Feb.
• Gergő Tóth & Zoltán Elekes & Adam Whittle & Changjun Lee & Dieter F. Kogler, 2022, "Technology network structure conditions the economic resilience of regions," KRTK-KTI WORKING PAPERS, Institute of Economics, Centre for Economic and Regional Studies, number 2202, Jan.
• Tea Baldigara, 2022, "Primjena Umjetnih Neuronskih Mreža U Modeliranju Domaće Turističke Potražnje," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), volume 73, issue 3, pages 349-370, DOI: 10.32910/ep.73.3.1.
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• Foltas Alexander, 2022, "Testing Investment Forecast Efficiency with Forecasting Narratives," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, volume 242, issue 2, pages 191-222, April, DOI: 10.1515/jbnst-2020-0027.
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• Zongwu Cai & Pixiong Chen, 2022, "New Online Investor Sentiment and Asset Returns," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202216, Nov, revised Nov 2022.
• William Barnett & Kun He & Jingtong He, 2022, "Consumption Loan Augmented Divisia Monetary Index and China Monetary Aggregation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202217, Nov.
• Tsvetan Tsvetanov, 2022, "Tax Holidays and the Heterogeneous Pass-Through of Gasoline Taxes," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202219, Dec.
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