Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2022

• Mohajan, Devajit & Mohajan, Haradhan, 2022, "Sensitivity Analysis between Lagrange Multipliers and Consumer Coupon: Utility Maximization Perspective," MPRA Paper, University Library of Munich, Germany, number 116022, Sep, revised 16 Sep 2022.
• Jadidzadeh, Ali, 2022, "An Application of Smooth Transition Regression Models to Homeless Research," MPRA Paper, University Library of Munich, Germany, number 116356, Dec.
• Mohajan, Devajit & Mohajan, Haradhan, 2022, "Sensitivity Analysis between Commodity and Budget: Utility Maximization Case," MPRA Paper, University Library of Munich, Germany, number 116495, Dec, revised 20 Dec 2022.
• Fantazzini, Dean & Kurbatskii, Alexey & Mironenkov, Alexey & Lycheva, Maria, 2022, "Forecasting oil prices with penalized regressions, variance risk premia and Google data," MPRA Paper, University Library of Munich, Germany, number 118239.
• Brahmana, Rayenda Khresna, 2022, "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper, University Library of Munich, Germany, number 119598, Dec.
• Majumder, Rajarshi & Ghosh, Subhadip & Chatterjee, Bidisha, 2022, "Energy infrastructure in India: challenges and opportunities," MPRA Paper, University Library of Munich, Germany, number 120106.
• Ubilava, David & Valera, Harold Glenn & Pede, Valerien, 2022, "The Rice Market Reaction to El Nino Southern Oscillation Shocks," MPRA Paper, University Library of Munich, Germany, number 123384, Feb.
• Mawuli Segnon & Rangan Gupta & Bernd Wilfling, 2022, "Forecasting Stock Market Volatility with Regime-Switching GARCH-MIDAS: The Role of Geopolitical Risks," Working Papers, University of Pretoria, Department of Economics, number 202203, Jan.
• Oguzhan Cepni & Rangan Gupta & Daniel Pienaar & Christian Pierdzioch, 2022, "Forecasting the Realized Variance of Oil-Price Returns Using Machine-Learning: Is there a Role for U.S. State-Level Uncertainty?," Working Papers, University of Pretoria, Department of Economics, number 202205, Jan.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022, "Climate Risks and Realized Volatility of Major Commodity Currency Exchange Rates," Working Papers, University of Pretoria, Department of Economics, number 202210, Feb.
• Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022, "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers, University of Pretoria, Department of Economics, number 202211, Feb.
• Elie Bouri & Christina Christou & Rangan Gupta, 2022, "Forecasting Returns of Major Cryptocurrencies: Evidence from Regime-Switching Factor Models," Working Papers, University of Pretoria, Department of Economics, number 202213, Feb.
• Rangan Gupta & Christian Pierdzioch, 2022, "Do Economic Conditions of U.S. States Predict the Realized Volatility of Oil-Price Returns? A Quantile Machine-Learning Approach," Working Papers, University of Pretoria, Department of Economics, number 202216, Mar.
• 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," Working Papers, University of Pretoria, Department of Economics, number 202217, Mar.
• David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022, "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers, University of Pretoria, Department of Economics, number 202228, Jun.
• Elie Bouri & Rangan Gupta & Luca Rossini, 2022, "The Role of the Monthly ENSO in Forecasting the Daily Baltic Dry Index," Working Papers, University of Pretoria, Department of Economics, number 202229, Jun.
• Afees A. Salisu & Riza Demirer & Rangan Gupta, 2022, "Policy Uncertainty and Stock Market Volatility Revisited: The Predictive Role of Signal Quality," Working Papers, University of Pretoria, Department of Economics, number 202232, Jun.
• Rangan Gupta & Xiaojin Sun, 2022, "Time-Varying Parameter Four-Equation DSGE Model," Working Papers, University of Pretoria, Department of Economics, number 202234, Aug.
• Rangan Gupta & Jacobus Nel & Afees A. Salisu & Qiang Ji, 2022, "Predictability of Economic Slowdowns in Advanced Countries over Eight Centuries: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202237, Aug.
• Hardik A. Marfatia & Rangan Gupta & Goodness C. Aye & Christian Pierdzioch, 2022, "Forecasting More than Three Centuries of Economic Growth of the United Kingdom: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202238, Aug.
• Sayar Karmakar & Rangan Gupta & Oguzhan Cepni & Lavinia Rognone, 2022, "Climate Risks and Predictability of the Trading Volume of Gold: Evidence from an INGARCH Model," Working Papers, University of Pretoria, Department of Economics, number 202241, Sep.
• Jacobus Nel & Rangan Gupta & Mark E. Wohar & Christian Pierdzioch, 2022, "Climate Risks and Predictability of Commodity Returns and Volatility: Evidence from Over 750 Years of Data," Working Papers, University of Pretoria, Department of Economics, number 202242, Sep.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022, "Climate Risks and State-Level Stock-Market Realized Volatility," Working Papers, University of Pretoria, Department of Economics, number 202246, Sep.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022, "Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment," Working Papers, University of Pretoria, Department of Economics, number 202247, Oct.
• Oguzhan Cepni & Rangan Gupta & Wenting Liao & Jun Ma, 2022, "Climate Risks and Forecastability of the Weekly State-Level Economic Conditions of the United States," Working Papers, University of Pretoria, Department of Economics, number 202251, Oct.
• Oguzhan Cepni & Christina Christou & Rangan Gupta, 2022, "Forecasting National Recessions of the United States with State-Level Climate Risks: Evidence from Model Averaging in Markov-Switching Models," Working Papers, University of Pretoria, Department of Economics, number 202252, Oct.
• Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022, "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers, University of Pretoria, Department of Economics, number 202258, Dec.
• Muhammad Usman, 2022, "Price Efficiency, Bubbles, Crashes and Crash Risk: Evidence from Chinese Stock Market," Prague Economic Papers, Prague University of Economics and Business, volume 2022, issue 3-4, pages 236-258, DOI: 10.18267/j.pep.804.
• Duarte Maia & Ivan De Lorenzo Buratta, 2022, "How Bad Can Financial Crises Be? A GDP Tail Risk Assessment for Portugal," Working Papers, Banco de Portugal, Economics and Research Department, number w202204.
• Paulo M.M. Rodrigues & Robert Hill, 2022, "Forgetting Approaches to Improve Forecasting," Working Papers, Banco de Portugal, Economics and Research Department, number w202208.
• Kaelo Ntwaepelo & Grivas Chiyaba, 2022, "Financial Stability Surveillance Tools: Evaluating the Performance of Stress Indices," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2022-06, Aug.
• Biwei Chen, 2022, "Shape Evolution of the Interest Rate Term Structure," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, volume 13, issue 4, pages 427-457, January, DOI: https://doi.org/10.15353/rea.v13i3..
• Kulvik, Martti & Lintunen, Jussi & Kunttu, Janni & Orfanidou, Timokleia, 2022, "Management Practices and Use of Finnish Forests: Conclusions and Recommendations of the FutureForest2040 Project I," ETLA Brief, The Research Institute of the Finnish Economy, number 114, Nov.
• Kulvik, Martti & Lintunen, Jussi & Kunttu, Janni & Orfanidou, Timokleia, 2022, "Forest-based Production in Finland: Conclusions and Recommendations of the FutureForest2040 Project II," ETLA Brief, The Research Institute of the Finnish Economy, number 115, Nov.
• Berg-Andersson, Birgitta & Kulvik, Martti & Lintunen, Jussi & Kunttu, Janni & Orfanidou, Timokleia, 2022, "Structural Changes in the Finnish Forest-based Sector, and Market and Employment Impacts in 2040," ETLA Reports, The Research Institute of the Finnish Economy, number 131, Sep.
• Reza Gharoie Ahangar & Myungsup Kim, 2022, "The Impact of COVID-19 Shocks on Business and GDP of Global Economy," American Business Review, Pompea College of Business, University of New Haven, volume 25, issue 2, pages 328-354.
• Raphael Amaro & Carlos Pinho & Mara Madaleno, 2022, "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 65, pages 77-101.
• Andrei Zubarev & Maria Kirillova, 2022, "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 65, pages 117-138.
• Yakup Arı, 2022, "USD/TRY and foreign banks in Turkey: Evidence by TVP-VAR," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 67, pages 5-26.
• Raphael Amaro & Carlos Pinho, 2022, "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 68, pages 5-27.
• Maria Lycheva & Alexey Mironenkov & Alexey Kurbatskii & Dean Fantazzini, 2022, "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 68, pages 28-49.
• Cédric Poutré & Georges Dionne & Gabriel Yergeau, 2022, "The Profitability of Lead-Lag Arbitrage at High-Frequency," Working Papers, HEC Montreal, Canada Research Chair in Risk Management, number 22-5, Sep.
• Ina Hajdini & Andre Kurmann, 2022, "Predictable Forecast Errors in Full-Information Rational Expectations Models with Regime Shifts," School of Economics Working Paper Series, LeBow College of Business, Drexel University, number 2022-5, May.
• Fabiano Guasti Lima & Carolina Trinca Paulino & Rodrigo Lanna Franco Silveira & Rafael Confetti Gatsios & Alexandre Assaf Neto, 2022, "Determining Factors and their Impacts on the Ratings of Companies and Countries," EkBis: Jurnal Ekonomi dan Bisnis, UIN Sunan Kalijaga Yogyakarta, volume 6, issue 1, pages 16-29.
• Cordelia Frings & Broghan Helgeson, 2022, "Developing a Model for Consumer Management of Decentralized Options," EWI Working Papers, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI), number 2022-5, Dec.
• José M. Belbute & Alfredo M. Pereira, 2022, "ARFIMA Reference Forecasts for Worldwide CO2 Emissions and the National Dimension of the Policy Efforts to Meet IPCC Targets," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, volume 47, issue 1, pages 1-27.
• Perevyshin, Yury (Перевышин, Юрий) & Drobyshevsky, Sergey (Дробышевский, Сергей) & Trunin, Pavel (Трунин, Павел), 2022, "Analysis Of Alternative Approaches To Determining The Target Level Of Inflation In Russia
  [Анализ Альтернативных Подходов К Определению Целевого Уровня Инфляции Банком России]," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w20220204, Nov.
• Vedev, Aleksey (Ведев, Алексей) & Silchuk, Anastasia (Сильчук, Анастасия) & Tuzov, Konstantin (Тузов, Константин) & Kovaleva, Marina (Ковалева, Марина) & Eremkin, Vladimir (Ерёмкин, Владимир), 2022, "Organization Of The System Of Macroeconomic Analysis And Forecasting In The Republic Of Uzbekistan
  [Организация Системы Макроэкономического Анализа И Прогнозирования В Республике Узбекистан]," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w20220210, Nov.
• Vedev, Aleksey (Ведев, Алексей) & Silchuk, Anastasia (Сильчук, Анастасия) & Tuzov, Konstantin (Тузов, Константин) & Kovaleva, Marina (Ковалева, Марина) & Eremkin, Vladimir (Ерёмкин, Владимир), 2022, "Assessment Of The Prospects For Russia To Enter The Path Of Sustainable Growth After 2021: Analysis Of Possible Development Risks And Development Of Proposals For Risk Management
  [Оценка Перспектив," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w20220211, Nov.
• Vedev, Alexey (Ведев, Алексей) & Silchuk, Aleksandra (Сильчук, Александра) & Tuzov, Konstantin (Тузов, Константин) & Kovaleva, Marina (Ковалева, Марина) & Eremkin, Vladimir (Ерёмкин, Владимир), 2022, "Analysis Of The Efficiency Of Industry Support Measures During The Coronavirus Pandemic And Their Contribution To The Recovery Of Economic Activity In Russia
  [Анализ Эффективности Отраслевых Мер По," Working Papers, Russian Presidential Academy of National Economy and Public Administration, number w20220298, Nov.
• Miriam Breitenstein & Carl-Philipp Anke & Duc Khuong Nguyen & Thomas Walther, 2022, "Stranded Asset Risk and Political Uncertainty: The Impact of the Coal Phase-Out on the German Coal Industry," The Energy Journal, , volume 43, issue 5, pages 27-50, September, DOI: 10.5547/01956574.43.5.mbre.
• Mihaela Simionescu & Mihaela-Daniela Vornicescu (Niculescu), 2022, "The Impact of the European Economic Integration on Sustainable Development in the EU New Member States," Bulgarian Economic Papers, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, number bep-2022-02, Jan, revised Jan 2022.
• Mihaela Simionescu, 2022, "Non-life Insurance Market and Macroeconomic Indicators in Baltic States," Bulgarian Economic Papers, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, number bep-2022-05, Jun, revised Jun 2022.
• Christian Hepenstrick & Jason Blunier, 2022, "What were they thinking? Estimating the quarterly forecasts underlying annual growth projections," Working Papers, Swiss National Bank, number 2022-05.
• Gabriel Lyrio de Oliveira & Andre Luis Squarize Chagas & Denise Leyi Li, 2022, "Public Sector Procurements and Reference Prices Estimation with Small Samples in Brazil," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2022_02, Jan.
• Yuting Chen & Don Bredin & Valerio Potì & Roman Matkovskyy, 2022, "COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic," Digital Finance, Springer, volume 4, issue 1, pages 17-61, March, DOI: 10.1007/s42521-021-00045-3.
• Helmut Wasserbacher & Martin Spindler, 2022, "Machine learning for financial forecasting, planning and analysis: recent developments and pitfalls," Digital Finance, Springer, volume 4, issue 1, pages 63-88, March, DOI: 10.1007/s42521-021-00046-2.
• Charl Maree & Christian W. Omlin, 2022, "Reinforcement learning with intrinsic affinity for personalized prosperity management," Digital Finance, Springer, volume 4, issue 2, pages 241-262, September, DOI: 10.1007/s42521-022-00068-4.
• Lixiong Yang, 2022, "Threshold mixed data sampling (TMIDAS) regression models with an application to GDP forecast errors," Empirical Economics, Springer, volume 62, issue 2, pages 533-551, February, DOI: 10.1007/s00181-021-02028-0.
• Julián Andrada-Félix & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2022, "Time connectedness of fear," Empirical Economics, Springer, volume 62, issue 3, pages 905-931, March, DOI: 10.1007/s00181-021-02056-w.
• Julia Kielmann & Hans Manner & Aleksey Min, 2022, "Stock market returns and oil price shocks: A CoVaR analysis based on dynamic vine copula models," Empirical Economics, Springer, volume 62, issue 4, pages 1543-1574, April, DOI: 10.1007/s00181-021-02073-9.
• Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022, "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, volume 62, issue 5, pages 2239-2262, May, DOI: 10.1007/s00181-021-02093-5.
• Christian Glocker & Serguei Kaniovski, 2022, "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, volume 63, issue 1, pages 43-91, July, DOI: 10.1007/s00181-021-02129-w.
• Raisul Islam & Vladimir Volkov, 2022, "Contagion or interdependence? Comparing spillover indices," Empirical Economics, Springer, volume 63, issue 3, pages 1403-1455, September, DOI: 10.1007/s00181-021-02169-2.
• Simon Blöthner & Mario Larch, 2022, "Economic determinants of regional trade agreements revisited using machine learning," Empirical Economics, Springer, volume 63, issue 4, pages 1771-1807, October, DOI: 10.1007/s00181-022-02203-x.
• Masato Ubukata, 2022, "A time-varying jump tail risk measure using high-frequency options data," Empirical Economics, Springer, volume 63, issue 5, pages 2633-2653, November, DOI: 10.1007/s00181-022-02209-5.
• Gaetano Perone, 2022, "Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 23, issue 6, pages 917-940, August, DOI: 10.1007/s10198-021-01347-4.
• Anna Pajor & Justyna Wróblewska, 2022, "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, volume 12, issue 3, pages 427-448, September, DOI: 10.1007/s40822-022-00203-x.
• Şirin Özlem & Omer Faruk Tan, 2022, "Predicting cash holdings using supervised machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 8, issue 1, pages 1-19, December, DOI: 10.1186/s40854-022-00351-8.
• Charles O. Manasseh & Nnah M. Iroha & Kingsley I. Okere & Ifeoma C. Nwakoby & Ogochukwu C. Okanya & Nnenna Nwonye & Onuselogu Odidi & Oliver I. Inyiama, 2022, "Application of Markov chain to share price movement in Nigeria (1985–2019)," Future Business Journal, Springer, volume 8, issue 1, pages 1-14, December, DOI: 10.1186/s43093-022-00168-y.
• Daniel Baier & Björn Stöcker, 2022, "Profit uplift modeling for direct marketing campaigns: approaches and applications for online shops," Journal of Business Economics, Springer, volume 92, issue 4, pages 645-673, May, DOI: 10.1007/s11573-021-01068-3.
• Theresa Maria Rausch & Tobias Albrecht & Daniel Baier, 2022, "Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables," Journal of Business Economics, Springer, volume 92, issue 4, pages 675-706, May, DOI: 10.1007/s11573-021-01075-4.
• Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022, "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 18, issue 2, pages 129-157, July, DOI: 10.1007/s41549-022-00066-w.
• Tae-Seok Jang & Stephen Sacht, 2022, "Macroeconomic dynamics under bounded rationality: on the impact of consumers’ forecast heuristics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, volume 17, issue 3, pages 849-873, July, DOI: 10.1007/s11403-022-00348-7.
• Eva O. Arceo-Gomez & Raymundo M. Campos-Vazquez & Raquel Y. Badillo & Sergio Lopez-Araiza, 2022, "Gender stereotypes in job advertisements: What do they imply for the gender salary gap?," Journal of Labor Research, Springer, volume 43, issue 1, pages 65-102, March, DOI: 10.1007/s12122-022-09331-4.
• Richard J. Arend, 2022, "Balancing the perceptions of NK modelling with critical insights," Journal of Innovation and Entrepreneurship, Springer, volume 11, issue 1, pages 1-15, December, DOI: 10.1186/s13731-022-00212-9.
• Stephanie Glaser & Robert C. Jung & Karsten Schweikert, 2022, "Spatial panel count data: modeling and forecasting of urban crimes," Journal of Spatial Econometrics, Springer, volume 3, issue 1, pages 1-29, December, DOI: 10.1007/s43071-021-00019-y.
• Oleksandr Bartkoviak & Viktor Shpyrko & Oleksandr Chernyak & Yevgen Chernyak, 2022, "Statistical Arbitrage Using Cointegration and Principal Component Analysis Approach," Springer Proceedings in Business and Economics, Springer, in: Pantelis Sklias & Persefoni Polychronidou & Anastasios Karasavvoglou & Victoria Pistikou & Nikolaos , "Business Development and Economic Governance in Southeastern Europe", DOI: 10.1007/978-3-031-05351-1_9.
• Pawan Kumar Singh & Anushka Chouhan & Rajiv Kumar Bhatt & Ravi Kiran & Ansari Saleh Ahmar, 2022, "Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA," Quality & Quantity: International Journal of Methodology, Springer, volume 56, issue 4, pages 2023-2033, August, DOI: 10.1007/s11135-021-01207-6.
• Afees A. Salisu & Abeeb Olaniran, 2022, "The U.S. Nonfarm Payroll and the out-of-sample predictability of output growth for over six decades," Quality & Quantity: International Journal of Methodology, Springer, volume 56, issue 6, pages 4663-4673, December, DOI: 10.1007/s11135-022-01342-8.
• Jakob A. Dambon & Stefan S. Fahrländer & Saira Karlen & Manuel Lehner & Jaron Schlesinger & Fabio Sigrist & Anna Zimmermann, 2022, "Examining the vintage effect in hedonic pricing using spatially varying coefficients models: a case study of single-family houses in the Canton of Zurich," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, volume 158, issue 1, pages 1-14, December, DOI: 10.1186/s41937-021-00080-2.
• Mehmet Sahiner, 2022, "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, volume 2, issue 10, pages 1-74, October, DOI: 10.1007/s43546-022-00329-9.
• Siddhartha Pradeep, 2022, "Role of monetary policy on CO2 emissions in India," SN Business & Economics, Springer, volume 2, issue 1, pages 1-33, January, DOI: 10.1007/s43546-021-00175-1.
• Anja Rossen, 2022, "Rückkehr zu stärkerem Beschäftigungswachstum in den Städten erwartet
  [Return to Stronger Employment Growth Expected in Cities]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, volume 102, issue 7, pages 568-570, July, DOI: 10.1007/s10273-022-3232-2.
• Yu-Min Lian & Jia-Ling Chen & Hsueh-Chien Cheng, 2022, "Predicting Bitcoin Prices via Machine Learning and Time Series Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 12, issue 5, pages 1-2.
• Andrea Carriero & Lorenzo Ricci & Elisabetta Vangelista, 2022, "Expectations and term premia in EFSF bond yields," Working Papers, European Stability Mechanism, number 54, Jul.
• Alexander Foltas & Christian Pierdzioch, 2022, "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Applied Economics Letters, Taylor & Francis Journals, volume 29, issue 10, pages 867-872, June, DOI: 10.1080/13504851.2021.1896668.
• Xin Sheng & Rangan Gupta & Qiang Ji, 2022, "Forecasting charge-off rates with a panel Tobit model: the role of uncertainty," Applied Economics Letters, Taylor & Francis Journals, volume 29, issue 10, pages 927-931, June, DOI: 10.1080/13504851.2021.1898532.
• Peter Fuleky, 2022, "Nowcasting the trajectory of the COVID-19 recovery," Applied Economics Letters, Taylor & Francis Journals, volume 29, issue 11, pages 1037-1041, June, DOI: 10.1080/13504851.2021.1907278.
• Mar Delgado-Téllez & Esther Gordo & Iván Kataryniuk & Javier J. Pérez, 2022, "The decline in public investment: ``social dominance’’ or too-rigid fiscal rules?," Applied Economics, Taylor & Francis Journals, volume 54, issue 10, pages 1123-1136, February, DOI: 10.1080/00036846.2021.1990841.
• Reza Bradrania & Davood Pirayesh Neghab, 2022, "State-dependent asset allocation using neural networks," The European Journal of Finance, Taylor & Francis Journals, volume 28, issue 11, pages 1130-1156, July, DOI: 10.1080/1351847X.2021.1960404.
• Hannes Mueller & Christopher Rauh, 2022, "Using past violence and current news to predict changes in violence," International Interactions, Taylor & Francis Journals, volume 48, issue 4, pages 579-596, July, DOI: 10.1080/03050629.2022.2063853.
• Hardik A. Marfatia & Christophe André & Rangan Gupta, 2022, "Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties," Journal of Behavioral Finance, Taylor & Francis Journals, volume 23, issue 2, pages 189-209, May, DOI: 10.1080/15427560.2020.1865354.
• Daniel Borup & Erik Christian Montes Schütte, 2022, "In Search of a Job: Forecasting Employment Growth Using Google Trends," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 1, pages 186-200, January, DOI: 10.1080/07350015.2020.1791133.
• Mengheng Li & Marcel Scharth, 2022, "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 1, pages 285-301, January, DOI: 10.1080/07350015.2020.1806853.
• Sander Barendse & Andrew J. Patton, 2022, "Comparing Predictive Accuracy in the Presence of a Loss Function Shape Parameter," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 3, pages 1057-1069, June, DOI: 10.1080/07350015.2021.1896527.
• Michael W. McCracken & Joseph T. McGillicuddy & Michael T. Owyang, 2022, "Binary Conditional Forecasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 3, pages 1246-1258, June, DOI: 10.1080/07350015.2021.1920960.
• Alessio Volpicella, 2022, "SVARs Identification Through Bounds on the Forecast Error Variance," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 40, issue 3, pages 1291-1301, June, DOI: 10.1080/07350015.2021.1927742.
• Wei Li & Florentina Paraschiv & Georgios Sermpinis, 2022, "A data-driven explainable case-based reasoning approach for financial risk detection," Quantitative Finance, Taylor & Francis Journals, volume 22, issue 12, pages 2257-2274, December, DOI: 10.1080/14697688.2022.2118071.
• Young Min Kim & Seojin Lee, 2022, "Korean exchange rate forecasts using Bayesian variable selection," Asia-Pacific Journal of Accounting & Economics, Taylor & Francis Journals, volume 29, issue 4, pages 1045-1062, July, DOI: 10.1080/16081625.2019.1653777.
• Gergő Tóth & Zoltán Elekes & Adam Whittle & Changjun Lee & Dieter F. Kogler, 2022, "Technology Network Structure Conditions the Economic Resilience of Regions," Economic Geography, Taylor & Francis Journals, volume 98, issue 4, pages 355-378, August, DOI: 10.1080/00130095.2022.2035715.
• Mar Delgado-Téllez & José Federico Geli & Enrique Moral-Benito & Javier J. Pérez, 2022, "Outsourcing and public expenditure: an aggregate perspective with regional data," Regional Studies, Taylor & Francis Journals, volume 56, issue 8, pages 1347-1358, August, DOI: 10.1080/00343404.2021.1968364.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman van Dijk, 2022, "A Flexible Predictive Density Combination Model for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 22-013/III, Feb.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2022, "A Flexible Predictive Density Combination for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 22-053/III, Aug.
• Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022, "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, volume 104, issue 4, pages 686-704, October, DOI: 10.1162/rest_a_00974.
• Samuel Bazzi & Robert A. Blair & Christopher Blattman & Oeindrila Dube & Matthew Gudgeon & Richard Peck, 2022, "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," The Review of Economics and Statistics, MIT Press, volume 104, issue 4, pages 764-779, October, DOI: 10.1162/rest_a_01016.
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• Diana Balioz, 2022, "Short-Term Forecasting of Global Energy and Metal Prices: VAR and VECM Approaches," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 254, pages 15-28, DOI: 10.26531/vnbu2022.254.02.
• Yuriy Kleban & Tetiana Stasiuk, 2022, "Crypto Currency Price Forecast: Neural Network Perspectives," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 254, pages 29-42, DOI: 10.26531/vnbu2022.254.03.
• Kaan Arik & Murat Gezer & Seda Tolun Tayali, 2022, "The study of indicators affecting customer churn in MMORPG games with machine learning models," Upravlenets, Ural State University of Economics, volume 13, issue 6, pages 70-85, January, DOI: 10.29141/2218-5003-2022-13-6-6.
• Goller, Daniel & Heiniger, Sandro, 2022, "A general framework to quantify the event importance in multi-event contests," Economics Working Paper Series, University of St. Gallen, School of Economics and Political Science, number 2204, Jul.
• Todd H. Kuethe & Brady Brewer & Chad Fiechter, 2022, "Loss Aversion in Farmland Price Expectations," Land Economics, University of Wisconsin Press, volume 98, issue 1, pages 98-114.
• Matthew C. TRIMBLE, 2022, "Regression Promises And Aggregation Bias Illusions The Application Of Market Delineation To Land Valuation Models," The Valuation Journal, The National Association of Authorized Romanian Valuers, volume 18, issue 1, pages 56-95.
• Sroka Łukasz, 2022, "Applying Block Bootstrap Methods in Silver Prices Forecasting," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 26, issue 2, pages 15-29, June, DOI: 10.15611/eada.2022.2.02.
• Fatih Chellai, 2022, "Forecasting Models Based on Fuzzy Logic: An Application on International Coffee Prices," Econometrics. Advances in Applied Data Analysis, Sciendo, volume 26, issue 4, pages 1-16, December, DOI: 10.15611/eada.2022.4.01.
• Srhoj Stjepan, 2022, "Can we predict high growth firms with financial ratios?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, volume 18, issue 1, pages 66-73, March, DOI: 10.2478/fiqf-2022-0006.
• Płaza Natalia & Žilinskienė Deimantė, 2022, "The Role of Customs Procedures in Reduction of Maintenance, Repair and Overhaul Costs in the Aviation Industry," Financial Internet Quarterly (formerly e-Finanse), Sciendo, volume 18, issue 2, pages 67-82, June, DOI: 10.2478/fiqf-2022-0013.
• Koloane Cathrine Thato & Bodhlyera Oliver, 2022, "A statistical approach to modeling the underground economy in South Africa," Journal of Economics and Management, Sciendo, volume 44, issue 1, pages 64-95, January, DOI: 10.22367/jem.2022.44.04.
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• Maciej Wysocki & Paweł Sakowski, 2022, "Investment Portfolio Optimization Based on Modern Portfolio Theory and Deep Learning Models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-12.
• Illia Baranochnikov & Robert Ślepaczuk, 2022, "A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-21.
• Katarzyna Kryńska & Robert Ślepaczuk, 2022, "Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-25.
• Thi Thu Giang Nguyen & Robert Ślepaczuk, 2022, "The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-29.
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• Abay,Kibrom A. & Yonzan,Nishant & Kurdi,Sikandra Smith & Hirfrfot,Kibrom Tafere, 2022, "Revisiting Poverty Trends and the Role of Social Protection Systems in Africa during theCOVID-19 Pandemic," Policy Research Working Paper Series, The World Bank, number 10172, Sep.
• Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022, "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, volume 55, issue S1, pages 379-405, February, DOI: 10.1111/caje.12551.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2022, "A moving average heterogeneous autoregressive model for forecasting the realized volatility of the US stock market: Evidence from over a century of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., volume 27, issue 1, pages 384-400, January, DOI: 10.1002/ijfe.2158.
• Mehmet Balcilar & Edmond Berisha & Oğuzhan Çepni & Rangan Gupta, 2022, "The predictive power of the term spread on inequality in the United Kingdom: An empirical analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., volume 27, issue 2, pages 1979-1988, April, DOI: 10.1002/ijfe.2254.
• Malte Knüppel & Fabian Krüger, 2022, "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 1, pages 23-41, January, DOI: 10.1002/jae.2834.
• Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022, "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 3, pages 461-476, April, DOI: 10.1002/jae.2887.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022, "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 3, pages 583-602, April, DOI: 10.1002/jae.2889.
• Michael P. Clements, 2022, "Individual forecaster perceptions of the persistence of shocks to GDP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 3, pages 640-656, April, DOI: 10.1002/jae.2884.
• Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022, "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 4, pages 700-721, June, DOI: 10.1002/jae.2896.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022, "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 5, pages 843-866, August, DOI: 10.1002/jae.2903.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022, "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 5, pages 920-964, August, DOI: 10.1002/jae.2910.
• Tae‐Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022, "Optimal forecast under structural breaks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 5, pages 965-987, August, DOI: 10.1002/jae.2908.
• Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022, "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 6, pages 1230-1255, September, DOI: 10.1002/jae.2923.
• Ana Beatriz Galvão & Michael Owyang, 2022, "Forecasting low‐frequency macroeconomic events with high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 37, issue 7, pages 1314-1333, November, DOI: 10.1002/jae.2931.
• Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022, "Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 2, pages 303-315, March, DOI: 10.1002/for.2813.
• Barbara Jarmulska, 2022, "Random forest versus logit models: Which offers better early warning of fiscal stress?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 3, pages 455-490, April, DOI: 10.1002/for.2806.
• Yongchen Zhao, 2022, "Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 4, pages 810-828, July, DOI: 10.1002/for.2834.
• Philip Hans Franses & Max Welz, 2022, "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 4, pages 829-839, July, DOI: 10.1002/for.2835.
• Stavros Degiannakis, 2022, "Stock market as a nowcasting indicator for real investment," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 5, pages 911-919, August, DOI: 10.1002/for.2838.
• Caroline Jardet & Baptiste Meunier, 2022, "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 6, pages 1181-1200, September, DOI: 10.1002/for.2858.
• Robert A. Hill & Paulo M. M. Rodrigues, 2022, "Forgetting approaches to improve forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 7, pages 1356-1371, November, DOI: 10.1002/for.2877.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna & Mark E. Wohar, 2022, "Uncertainty and predictability of real housing returns in the United Kingdom: A regional analysis," Journal of Forecasting, John Wiley & Sons, Ltd., volume 41, issue 7, pages 1525-1556, November, DOI: 10.1002/for.2878.
• Alexander Glas & Matthias Hartmann, 2022, "Uncertainty measures from partially rounded probabilistic forecast surveys," Quantitative Economics, Econometric Society, volume 13, issue 3, pages 979-1022, July, DOI: 10.3982/QE1703.
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• Tayyab Raza Fraz & Samreen Fatima, 2022, "Modeling And Forecasting Volatility Of Stock Market Using Family Of Garch Models: Evidence From Cpec Linked Countries," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., volume 22, issue 01, pages 1-15, March, DOI: 10.1142/S219456592250004X.
• Massimo Guidolin & Alexei G. Orlov, 2022, "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., volume 12, issue 03, pages 1-61, September, DOI: 10.1142/S2010139222500070.
• Hua Chen & Domenico Tarzia & Giovanni Vittorino & Andros Gregoriou, 2022, "Volatility Spillovers During the Chinese Stock Market Crisis: A MEM-Based Approach," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., volume 25, issue 04, pages 1-30, December, DOI: 10.1142/S021909152250031X.
• Lucija Benko & Karlo Krstanović & Luka Sovulj, 2022, "Procjena učinaka pandemije koronavirusa na turističke dolaske i noćenja u Republici Hrvatskoj te na vrijednost CROBEXturist indeksa Zagrebačke burze," EFZG Working Papers Series, Faculty of Economics and Business, University of Zagreb, number 2201, Mar.
• Dreher, Sandra & Eichfelder, Sebastian & Noth, Felix, 2022, "Does IFRS information on tax loss carryforwards and negative performance improve predictions of earnings and cash flows?," arqus Discussion Papers in Quantitative Tax Research, arqus - Arbeitskreis Quantitative Steuerlehre, number 276.
• Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022, "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers, Deutsche Bundesbank, number 13/2022.
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• Hartwig, Benny, 2022, "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers, Deutsche Bundesbank, number 52/2022.
• Zadrozny, Peter A., 2022, "Linear identification of linear rational-expectations models by exogenous variables reconciles Lucas and Sims," CFS Working Paper Series, Center for Financial Studies (CFS), number 682.
• Benchimol, Jonathan & El-Shagi, Makram & Saadon, Yossi, 2022, "Do expert experience and characteristics affect inflation forecasts?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 201, pages 205-226.
• Hauber, Philipp, 2022, "Real-time nowcasting with sparse factor models," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 251551.
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• Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Sardone, Alessandro & Zeddies, Götz, 2022, "Wirtschaftswachstum, Staatsfinanzen und Treibhausgas-Emissionen in der mittleren Frist," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 10, issue 4, pages 146-151.
• Duan, Fang, 2022, "Forecasting risk measures based on structural breaks in the correlation matrix," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 945, DOI: 10.4419/96973106.
• Prüser, Jan & Blagov, Boris, 2022, "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 960, DOI: 10.4419/96973124.
• Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022, "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 964, DOI: 10.4419/96973128.
• du Plessis, Emile & Fritsche, Ulrich, 2022, "New forecasting methods for an old problem: Predicting 147 years of systemic financial crises," WiSo-HH Working Paper Series, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory, number 67.
• Zahner, Johannes & Baumgärtner, Martin, 2022, "Whatever it Takes to Understand a Central Banker – Embedding their Words Using Neural Networks," VfS Annual Conference 2022 (Basel): Big Data in Economics, Verein für Socialpolitik / German Economic Association, number 264019.
• Stamer, Vincent, 2022, "Thinking Outside the Container: A Sparse Partial Least Squares Approach to Forecasting Trade Flows," VfS Annual Conference 2022 (Basel): Big Data in Economics, Verein für Socialpolitik / German Economic Association, number 264096.
• Axenbeck, Janna & Breithaupt, Patrick, 2022, "Measuring the digitalisation of firms: A novel text mining approach," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 22-065.
• Janusz Opi³a, 2022, "On Employing of Extended Characteristic Surface Model for Forecasting of Demand in Tourism," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 20, issue 5, pages 621-639.
• Iqbal Jebril & P. Dhanaraj & Ghaida Muttashar Abdulsahib & SatheeshKumar Palanisamy & T.Prabhu & Osamah Ibrahim Khalaf, 2022, "Analysis of Electrically Couple SRR EBG Structure for Sub 6 GHz Wireless Applications," Advances in Decision Sciences, Asia University, Taiwan, volume 26, issue Special, pages 102-123, December.
• Mikkel Bennedsen & Eric Hillebrand & Sebastian Jensen, 2022, "A Neural Network Approach to the Environmental Kuznets Curve," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2022-09, May.
• Sarthak Behera & Hyeongwoo Kim & Soohyon Kim, 2022, "Superior Predictability of American Factors of the Won/Dollar Real Exchange Rate," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2022-03, Jul.
• Christian Gourieroux & Joann Jasiak, 2022, "Long Run Predictions," Annals of Economics and Statistics, GENES, issue 145, pages 75-90, DOI: https://doi.org/10.2307/48655902.
• Paul Beaudry & Tim Willems, 2022, "On the Macroeconomic Consequences of Over-Optimism," American Economic Journal: Macroeconomics, American Economic Association, volume 14, issue 1, pages 38-59, January, DOI: 10.1257/mac.20190332.
• 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 of the African Governance and Development Institute., African Governance and Development Institute., number 22/061, Jan.
• Bekir Tamer Gökalp, 2022, "Kripto Para Piyasasının Borsa İstanbul Endeksleri Üzerindeki Etkileri," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, volume 7, issue 2, pages 481-499, DOI: 10.30784/epfad.1081705.
• Ilya V. Naumov & Sergey S. Krasnykh & Yulia S. Otmakhova, 2022, "Scenario forecasting of the socio-economic consequences of the COVID-19 pandemic in Russian regions," R-Economy, Ural Federal University, Graduate School of Economics and Management, volume 8, issue 1, pages 5-20, DOI: https://doi.org/10.15826/recon.2022.
• Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022, "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN, Université catholique de Louvain, Louvain Finance (LFIN), number 2022003, May.
• Nuno Goncalves, 2022, "Most probable or more prudent? Analysing CFP's macroeconomic projections, 2015-2019," CFP Occasional Papers, Portuguese Public Finance Council, number 02/2022, Apr.
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• Kaiser, Caspar & Oparina, Ekaterina & Gentile, Niccolò & Tkatchenko, Alexandre & Clark, Andrew E. & De Neve, Jan-Emmanuel & D’Ambrosio, Conchita, 2022, "Human Wellbeing and Machine Learning," INET Oxford Working Papers, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, number 2022-11, Jun.
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• Kerry Loaiza-Marín, 2022, "Nowcasting the Costa Rican Quarterly Output Growth," Documentos de Trabajo, Banco Central de Costa Rica, number 2107, Feb.
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• Davide Fiaschi & Cristina Tealdi, 2022, "The attachment of adult women to the Italian labour market in the shadow of COVID-19," Papers, arXiv.org, number 2202.13317, Feb, revised May 2023.
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• Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022, "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers, arXiv.org, number 2203.04040, Mar, revised May 2023.
• Alain Hecq & Joao Issler & Elisa Voisin, 2022, "A short term credibility index for central banks under inflation targeting: an application to Brazil," Papers, arXiv.org, number 2205.00924, May, revised Jul 2022.
• Ekaterina Oparina & Caspar Kaiser & Niccol`o Gentile & Alexandre Tkatchenko & Andrew E. Clark & Jan-Emmanuel De Neve & Conchita D'Ambrosio, 2022, "Human Wellbeing and Machine Learning," Papers, arXiv.org, number 2206.00574, Jun.
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