Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2019

• Korobilis, Dimitris, 2019, "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper, University Library of Munich, Germany, number 96079, Sep.
• Chatziantoniou, Ioannis & Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2019, "Can spillover effects provide forecasting gains? The case of oil price volatility," MPRA Paper, University Library of Munich, Germany, number 96266.
• Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2019, "Forecasting Realized Volatility of Agricultural Commodities," MPRA Paper, University Library of Munich, Germany, number 96267.
• Degiannakis, Stavros & Filis, George, 2019, "Forecasting European Economic Policy Uncertainty," MPRA Paper, University Library of Munich, Germany, number 96268.
• Maas, Benedikt, 2019, "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper, University Library of Munich, Germany, number 96408, Sep.
• Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019, "Futures-based forecasts: How useful are they for oil price volatility forecasting?," MPRA Paper, University Library of Munich, Germany, number 96446.
• Valdivia Coria, Joab Dan & Valdivia Coria, Daney David, 2019, "Construcción de una Bolivia artificial: Efectos de la Política Económica desde 2006
  [Construction of an artificial Bolivia: Effects of the Economic Policy since 2006]," MPRA Paper, University Library of Munich, Germany, number 96626, Oct.
• Lorde, Troy & Alleyne, Antonio & Hosein, Roger & Yifei, Mu, 2019, "Should the Caribbean Look to the East? An Assessment of Caribbean Export Potential," MPRA Paper, University Library of Munich, Germany, number 96641, Jun.
• Jackson, Emerson Abraham & Tamuke, Edmund & Jabbie, Mohamed, 2019, "Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone," MPRA Paper, University Library of Munich, Germany, number 96735, Sep, revised 26 Nov 2019.
• Nyoni, Thabani, 2019, "The population question in Zimbabwe: reliable projections from the Box – Jenkins ARIMA approach," MPRA Paper, University Library of Munich, Germany, number 96791, Sep.
• Jackson, Emerson Abraham & Tamuke, Edmund, 2019, "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," MPRA Paper, University Library of Munich, Germany, number 96845, Sep, revised 23 Dec 2019.
• Gharsallah, Sofian & Sucarrat, Genaro, 2019, "Hvor presise er prognosene i Nasjonalbudsjettet?
  [How precise are the forecasts of the Norwegian national budget?]," MPRA Paper, University Library of Munich, Germany, number 96850, Oct.
• Mullat, Joseph, 2019, "The Financing Dilemma Supporting a Project," MPRA Paper, University Library of Munich, Germany, number 96879, Nov.
• Nyoni, Thabani, 2019, "An ARIMA analysis of the Indian Rupee/USD exchange rate in India," MPRA Paper, University Library of Munich, Germany, number 96908, Nov.
• Pincheira, Pablo & Hardy, Nicolás, 2019, "Forecasting Aluminum Prices with Commodity Currencies," MPRA Paper, University Library of Munich, Germany, number 97005, Nov.
• Aknouche, Abdelhakim & Francq, Christian, 2019, "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," MPRA Paper, University Library of Munich, Germany, number 97382, Dec.
• Bovi, Maurizio, 2019, "A Time-Varying Expectations Formation Mechanism," MPRA Paper, University Library of Munich, Germany, number 97624, Dec.
• Pincheira, Pablo & Hernández, Ana María, 2019, "Forecasting Unemployment Rates with International Factors," MPRA Paper, University Library of Munich, Germany, number 97855, Dec.
• Emara, Noha & Ma, Jinpeng, 2019, "An Analysis of the Seasonal Cycle and the Business Cycle," MPRA Paper, University Library of Munich, Germany, number 99310.
• Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2019, "Time-Varying Risk Aversion and the Predictability of Bond Premia," Working Papers, University of Pretoria, Department of Economics, number 201906, Jan.
• Joao F. Caldeira & Rangan Gupta & Tahir Suleman & Hudson S. Torrent, 2019, "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Working Papers, University of Pretoria, Department of Economics, number 201911, Feb.
• Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019, "Variants of Consumption-Wealth Ratios and Predictability of U.S. Government Bond Risk Premia: Old is still Gold," Working Papers, University of Pretoria, Department of Economics, number 201912, Feb.
• Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019, "The Role of Real Estate Uncertainty in Predicting US Home Sales Growth: Evidence from a Quantiles-Based Bayesian Model Averaging Approach," Working Papers, University of Pretoria, Department of Economics, number 201936, May.
• Elie Bouri & Riza Demirer & Rangan Gupta & Xiaojin Sun, 2019, "The Predictability of Stock Market Volatility in Emerging Economies: Relative Roles of Local, Regional and Global Business Cycles," Working Papers, University of Pretoria, Department of Economics, number 201938, May.
• Oguzhan Cepni & Rangan Gupta & I. Ethem Guney & M. Hasan Yilmaz, 2019, "Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages," Working Papers, University of Pretoria, Department of Economics, number 201957, Jul.
• Elie Bouri & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2019, "Gold, Platinum and the Predictability of Bond Risk Premia," Working Papers, University of Pretoria, Department of Economics, number 201967, Aug.
• Oguzhan Cepni & I. Ethem Guney & Rangan Gupta & Mark E. Wohar, 2019, "The Role of an Aligned Investor Sentiment Index in Predicting Bond Risk Premia of the United States," Working Papers, University of Pretoria, Department of Economics, number 201973, Sep.
• Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019, "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers, University of Pretoria, Department of Economics, number 201977, Oct.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2019, "A Moving Average Heterogeneous Autoregressive Model for Forecasting the Realized Volatility of the US Stock Market: Evidence from Over a Century of Data," Working Papers, University of Pretoria, Department of Economics, number 201978, Nov.
• Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2019, "Forecasting Bitcoin Returns: Is there a Role for the U.S. – China Trade War?," Working Papers, University of Pretoria, Department of Economics, number 201980, Nov.
• Mehmet Balcilar & Edmond Berisha & Oguzhan Cepni & Rangan Gupta, 2019, "The Predictive Power of the Term Spread on Inequality in the United Kingdom: An Empirical Analysis," Working Papers, University of Pretoria, Department of Economics, number 201981, Nov.
• Miroslav Navratil & Andrea Kolkova, 2019, "Decomposition and Forecasting Time Series in the Business Economy Using Prophet Forecasting Model," Central European Business Review, Prague University of Economics and Business, volume 2019, issue 4, pages 26-39, DOI: 10.18267/j.cebr.221.
• Pavel Jasek & Lenka Vrana & Lucie Sperkova & Zdenek Smutny & Marek Kobulsky, 2019, "Predictive Performance of Customer Lifetime Value Models in E-Commerce and the Use of Non-Financial Data," Prague Economic Papers, Prague University of Economics and Business, volume 2019, issue 6, pages 648-669, DOI: 10.18267/j.pep.714.
• Maciej Kostrzewski, 2019, "The Bayesian Methods of Jump Detection: The Example of Gas and EUA Contract Prices," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, volume 11, issue 2, pages 107-131, June.
• António Rua & Hossein Hassani, 2019, "Monthly Forecasting of GDP with Mixed Frequency Multivariate Singular Spectrum Analysis," Working Papers, Banco de Portugal, Economics and Research Department, number w201913.
• Alessio Volpicella, 2019, "SVARs Identification through Bounds on the Forecast Error Variance," Working Papers, Queen Mary University of London, School of Economics and Finance, number 890, Jul.
• A Clements & D Preve, 2019, "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series, National Centre for Econometric Research, number 120, Apr.
• Alexander Ballantyne & Tom Cusbert & Richard Evans & Rochelle Guttmann & Jonathan Hambur & Adam Hamilton & Elizabeth Kendall & Rachael McCririck & Gabriela Nodari & Daniel Rees, 2019, "MARTIN Has Its Place: A Macroeconometric Model of the Australian Economy," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2019-07, Aug.
• Carl Singleton & J. James Reade & Alasdair Brown, 2019, "Going with your gut: the (in)accuracy of forecast revisions in a football score prediction game," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2019-05, Apr, revised 01 Nov 2019.
• Guy Elaad & J. James Reade & Carl Singleton, 2019, "Information, prices and efficiency in an online betting market," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2019-10, Apr.
• J. James Reade & Carl Singleton & Alasdair Brown, 2019, "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2019-18, Jun, revised 01 Aug 2020.
• Sacha Gelfer, 2019, "Code and data files for "Data-Rich DSGE Model Forecasts of the Great Recession and its Recovery"," Computer Codes, Review of Economic Dynamics, number 18-269, revised .
• Sacha Gelfer, 2019, "Data-Rich DSGE Model Forecasts of the Great Recession and its Recovery," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, volume 32, pages 18-41, April, DOI: 10.1016/j.red.2018.12.005.
• Alexandre Kohlhas & Tobias Broer, 2019, "Forecaster (Mis-)Behavior," 2019 Meeting Papers, Society for Economic Dynamics, number 1171.
• Thomas Cook, 2019, "Macroeconomic Indicator Forecasting with Deep Neural Networks," 2019 Meeting Papers, Society for Economic Dynamics, number 402.
• Melo-Velandia, Luis Fernando & Loaiza, Rubén & Villamizar-Villegas, Mauricio, 2019, "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks’ Estimates," Working papers, Red Investigadores de Economía, number 8, Jun.
• Echavarría, Juan José & Giraldo, Iader & Jaramillo, Fernando, 2019, "Cadenas globales de valor, crecimiento y protección arancelaria en Colombia," Working papers, Red Investigadores de Economía, number 9, Jun.
• Abhijit Sen Gupta & Tara Iyer, 2019, "Quarterly Forecasting Model for India’s Economic Growth: Bayesian Vector Autoregression Approach," ADB Economics Working Paper Series, Asian Development Bank, number 573, Mar.
• Tara Iyer & Abhijit Sen Gupta, 2019, "Nowcasting Economic Growth in India: The Role of Rainfall," ADB Economics Working Paper Series, Asian Development Bank, number 593, Oct.
• Nikita Moiseev & Andrei Volodin, 2019, "Increasing the accuracy of macroeconomic time series forecast by incorporating functional and correlational dependencies between them," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 53, pages 119-137.
• Yury Gorlin & Marina Kartseva & Victor Lyashok, 2019, "The impact of the retirement age increase on the poverty level of the Russian population: Microsimulation analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 54, pages 26-50.
• Dean Fantazzini & Tamara Shangina, 2019, "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 55, pages 5-31.
• Georges Dionne & Xiaozhou Zhou, 2019, "Information Environments and High Price Impact Trades: Implication for Volatility and Price Efficiency," Working Papers, HEC Montreal, Canada Research Chair in Risk Management, number 19-3, Jun.
• Nikolaos DRITSAKIS & Paraskevi KLAZOGLOU, 2019, "Time Series Analysis using ARIMA Models: An Approach to Forecasting Health Expenditure in USA," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, volume 72, issue 1, pages 77-106.
• Chaido Dritsaki, 2019, "Modeling the Volatility of Exchange Rate Currency using GARCH Model," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, volume 72, issue 2, pages 209-230.
• Narges Javidi Abdollahzadeh Aval & Ahmad Assad Zadeh & Sedaghat Shahmorad, 2019, "A Comparative Study of the Efficiency of Ponzi Vs. No-Ponzi Economic System Based on Agent-Based Modeling," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 6, issue 3, pages 73-102.
• Blagica Novkovska & Ksenija Dumicic, 2019, "Ordering Goods And Services Online In South East European Countries: Comparison By Cluster Analysis," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, volume 10, issue 2, pages 163-173.
• A. ISLAS & Víctor M. GUERRERO & Eliud SILVA, 2019, "Forecasting Remittances to Mexico with a Multi-State Markov-Switching Model Applied to the Trend with Controlled Smoothness," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 1, pages 38-56, March.
• Wojciech CHAREMZA & Carlos DÍAZ & Svetlana MAKAROVA, 2019, "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 1, pages 5-18, March.
• Dimitar EFTIMOSKI, 2019, "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 32-53, June.
• Xianning WANG & Jingrong DONG & Zhi XIAO & Guanjie HE, 2019, "A novel spatial mixed frequency forecasting model with application to Chinese regional GDP," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 54-77, June.
• Gheorghe RUXANDA & Sorin OPINCARIU & Stefan IONESCU, 2019, "Modelling Non-Stationary Financial Time Series with Input Warped Student T-Processes," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 3, pages 51-61, September.
• Yuchen PAN & Zhi XIAO & Xianning WANG & Daoli YANG, 2019, "A Multi-Indicator Multi-Output Mixed Frequency Sampling Approach for Stock Index Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 4, pages 100-123, December.
• Wali ULLAH, 2019, "The Role of No-Arbitrage Restriction in Term Structure Model in the Context of an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 4, pages 44-66, December.
• Ansgar Belke & Jens Klose, 2019, "Forecasting ECB Policy Rates with Different Monetary Policy Rules," ROME Working Papers, ROME Network, number 201906, Jun.
• Julia Mortera & A. Philip Dawid, 2019, "Probability Forecasts and Prediction Markets," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0250, Nov.
• Paolo Andreini & Donato Ceci, 2019, "A Horse Race in High Dimensional Space," CEIS Research Paper, Tor Vergata University, CEIS, number 452, Feb, revised 14 Feb 2019.
• Tommaso Proietti, 2019, "Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models," CEIS Research Paper, Tor Vergata University, CEIS, number 455, Mar, revised 22 Mar 2019.
• Emilio Zanetti Chini, 2019, "Strategic judgment: its game-theoretic foundations,its econometric elicitation," Working Papers in Public Economics, Department of Economics and Law, Sapienza University of Rome, number 190, Oct.
• Muhammad Ejaz & Javed Iqbal, 2019, "Estimation and Forecasting of Industrial Production Index," SBP Working Paper Series, State Bank of Pakistan, Research Department, number 103, Apr.
• Nájera Salmerón, Jorge Alberto, 2019, "Relaciones en el comportamiento de los precios de las criptomonedas: un análisis econométrico a través de modelos VAR y VEC / Relationship in the Cryptocurrencies Price Behavior: An Econometric Analys," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, volume 9, issue 1, pages 33-61, enero-jun.
• Cristófoli, María Elizabeth & García Fronti, Javier, 2019, "Macroeconomic Reverse Stress Testing: An Early-Warning System for Spanish Banking Regulators. Analysis Based on the 2008 Global Financial Crisis / Prueba de resistencia inversa Macroeconómica: una pru," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, volume 9, issue 2, pages 181-204, julio-dic.
• Zeineb Affes & Rania Hentati-Kaffel, 2019, "Forecast bankruptcy using a blend of clustering and MARS model: case of US banks," Annals of Operations Research, Springer, volume 281, issue 1, pages 27-64, October, DOI: 10.1007/s10479-018-2845-8.
• James P. LeSage & Daniel Hendrikz, 2019, "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, volume 62, issue 3, pages 563-599, June, DOI: 10.1007/s00168-019-00908-z.
• Henryk Gurgul & Łukasz Lach, 2019, "On approximating the accelerator part in dynamic input–output models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, volume 27, issue 1, pages 219-239, March, DOI: 10.1007/s10100-017-0502-y.
• Asmerilda Hitaj & Lorenzo Mercuri & Edit Rroji, 2019, "Lévy CARMA models for shocks in mortality," Decisions in Economics and Finance, Springer;Associazione per la Matematica, volume 42, issue 1, pages 205-227, June, DOI: 10.1007/s10203-019-00248-9.
• Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019, "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, volume 42, issue 2, pages 449-469, December, DOI: 10.1007/s10203-019-00261-y.
• Bahar Şen Doğan & Murat Midiliç, 2019, "Forecasting Turkish real GDP growth in a data-rich environment," Empirical Economics, Springer, volume 56, issue 1, pages 367-395, January, DOI: 10.1007/s00181-017-1357-8.
• Silvija Vlah Jerić & Mihovil Anđelinović, 2019, "Evaluating Croatian stock index forecasts," Empirical Economics, Springer, volume 56, issue 4, pages 1325-1339, April, DOI: 10.1007/s00181-017-1393-4.
• Natalia Ponomareva & Jeffrey Sheen & Ben Zhe Wang, 2019, "The common component of bilateral US exchange rates: to what is it related?," Empirical Economics, Springer, volume 56, issue 4, pages 1251-1268, April, DOI: 10.1007/s00181-017-1395-2.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019, "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, volume 57, issue 3, pages 923-955, September, DOI: 10.1007/s00181-018-1475-y.
• Ard Reijer & Andreas Johansson, 2019, "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, volume 57, issue 4, pages 1351-1373, October, DOI: 10.1007/s00181-018-1500-1.
• Cees Diks & Cars Hommes & Juanxi Wang, 2019, "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, volume 57, issue 4, pages 1201-1228, October, DOI: 10.1007/s00181-018-1527-3.
• Paul Lehmann & Jos Sijm & Erik Gawel & Sebastian Strunz & Unnada Chewpreecha & Jean-Francois Mercure & Hector Pollitt, 2019, "Addressing multiple externalities from electricity generation: a case for EU renewable energy policy beyond 2020?," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, volume 21, issue 2, pages 255-283, April, DOI: 10.1007/s10018-018-0229-6.
• Antonio Fabio Forgione & Carlo Migliardo, 2019, "An empirical analysis of the impact of trade credit on bank debt restructuring," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, volume 36, issue 2, pages 415-438, July, DOI: 10.1007/s40888-018-0110-x.
• Carlos Uribe-Teran & Santiago Mosquera, 2019, "Structural factors, global shocks and sovereign debt credit ratings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 43, issue 1, pages 104-126, January, DOI: 10.1007/s12197-018-9435-0.
• Oscar Claveria, 2019, "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), volume 53, issue 1, pages 1-10, December, DOI: 10.1186/s12651-019-0253-4.
• Roman Matkovskyy & Taoufik Bouraoui, 2019, "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 17, issue 2, pages 433-446, June, DOI: 10.1007/s40953-018-0133-8.
• Balasubramaniam Meghanadh & Lagesh Aravalath & Bhupesh Joshi & Raghunathan Sathiamoorthy & Manish Kumar, 2019, "Imputation of Missing Values in the Fundamental Data: Using MICE Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 17, issue 3, pages 459-475, September, DOI: 10.1007/s40953-018-0142-7.
• Rómulo A. Chumacero, 2019, "Skills versus Luck: Bolivia and its recent Bonanza," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), volume 28, issue 1, pages 1-27, December, DOI: 10.1186/s40503-019-0069-1.
• Grant Allan & Gary Koop & Stuart McIntyre & Paul Smith, 2019, "Nowcasting Using Mixed Frequency Methods: An Application to the Scottish Economy," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, volume 81, issue 1, pages 12-45, September, DOI: 10.1007/s13571-018-0181-2.
• Aloisio Campelo & Ataman Ozyildirim & Jing Sima-Friedman & Paulo Picchetti & Sarah Piassi Machado Lima, 2019, "Coincident and Leading Indicators for Brazilian Cycles," Societies and Political Orders in Transition, Springer, in: Sergey Smirnov & Ataman Ozyildirim & Paulo Picchetti, "Business Cycles in BRICS", DOI: 10.1007/978-3-319-90017-9_18.
• Paulo Picchetti, 2019, "A Bayesian Approach to Predicting Cycles Using Composite Indicators," Societies and Political Orders in Transition, Springer, in: Sergey Smirnov & Ataman Ozyildirim & Paulo Picchetti, "Business Cycles in BRICS", DOI: 10.1007/978-3-319-90017-9_20.
• Atish Kumar Dash & Ataman Ozyildirim & Jing Sima-Friedman, 2019, "An Application of the Indicator Approach to Developing Coincident and Leading Economic Indexes for India," Societies and Political Orders in Transition, Springer, in: Sergey Smirnov & Ataman Ozyildirim & Paulo Picchetti, "Business Cycles in BRICS", DOI: 10.1007/978-3-319-90017-9_23.
• João A. Bastos, 2019, "Forecasting the capacity of mobile networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, volume 72, issue 2, pages 231-242, October, DOI: 10.1007/s11235-019-00556-w.
• Moussa Wajdi, 2019, "The dynamic relationship between stock index and exchange rate: Evidence for Tunis," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, volume 8, issue 1, pages 1-4.
• Moussa Wajdi, 2019, "On the co-movements among Stock prices and exchange rates cointegration: a VAR/VECM approach," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, volume 8, issue 1, pages 1-5.
• Emerson JACKSON & Edmund TAMUKE, 2019, "Predicting Disaggregated Tourist Arrivals In Sierra Leone Using Arima Model," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, volume 10, issue 2, pages 132-142.
• Jaka Sriyana, 2019, "What drives economic growth sustainability? Evidence from Indonesia," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 7, issue 2, pages 906-918, December, DOI: 10.9770/jesi.2019.7.2(8).
• Milan Vyskrabka & Stanislav Tvrz & Martin Zeleznik, 2019, "PreMISE: DSGE Model of the Slovak Economy Integrated in a Monetary Union," Working and Discussion Papers, Research Department, National Bank of Slovakia, number WP 8/2019, Nov.
• Rachida Ouysse, 2019, "Constrained principal components estimation of large approximate factor models," Discussion Papers, School of Economics, The University of New South Wales, number 2017-12a, Dec.
• Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019, "Higher Moment Constraints for Predictive Density Combinations," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2019-01, Mar.
• Lisa-Cheree Martin, 2019, "Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP," Working Papers, Stellenbosch University, Department of Economics, number 12/2019.
• Katja Heinisch & Axel Lindner, 2019, "For how long do IMF forecasts of world economic growth stay up-to-date?," Applied Economics Letters, Taylor & Francis Journals, volume 26, issue 3, pages 255-260, February, DOI: 10.1080/13504851.2018.1459035.
• Diego Winkelried & Javier Torres, 2019, "Economic mobility along the business cycle. The case of Peru," Applied Economics, Taylor & Francis Journals, volume 51, issue 18, pages 1894-1906, April, DOI: 10.1080/00036846.2018.1529401.
• Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2019, "Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model," Applied Economics, Taylor & Francis Journals, volume 51, issue 33, pages 3624-3631, July, DOI: 10.1080/00036846.2019.1584373.
• Florian Huber & Martin Feldkircher, 2019, "Adaptive Shrinkage in Bayesian Vector Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 37, issue 1, pages 27-39, January, DOI: 10.1080/07350015.2016.1256217.
• James Mitchell & Donald Robertson & Stephen Wright, 2019, "R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 37, issue 4, pages 681-695, October, DOI: 10.1080/07350015.2017.1415909.
• Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019, "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, volume 19, issue 9, pages 1473-1489, September, DOI: 10.1080/14697688.2019.1622290.
• Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019, "Crisis transmission: visualizing vulnerability," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2019-07.
• Eda Gulsen & Hakan Kara, 2019, "Measuring inflation uncertainty in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, volume 19, issue 2, pages 33-43.
• Eda Gulsen & Hakan Kara, 2019, "Measuring Inflation Uncertainty in Turkey," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1912.
• Mehmet Selman Colak & Ibrahim Ethem Guney & Ahmet Senol & Muhammed Hasan Yilmaz, 2019, "Monitoring and Forecasting Cyclical Dynamics in Bank Credits: Evidence from Turkish Banking Sector," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1929.
• Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019, "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 19-057/III, Aug.
• Sander Barendse & Erik Kole & Dick van Dijk, 2019, "Backtesting Value-at-Risk and Expected Shortfall in the Presence of Estimation Error," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 19-058/III, Aug.
• Heikki Kauppi, 2019, "Recession Prediction with OptimalUse of Leading Indicators," Discussion Papers, Aboa Centre for Economics, number 125, Apr.
• Regis Barnichon & Christian Brownlees, 2019, "Impulse Response Estimation by Smooth Local Projections," The Review of Economics and Statistics, MIT Press, volume 101, issue 3, pages 522-530, July.
• Barbara Rossi & Yiru Wang, 2019, "Vector autoregressive-based Granger causality test in the presence of instabilities," Stata Journal, StataCorp LLC, volume 19, issue 4, pages 883-899, December, DOI: 10.1177/1536867X19893631.
• Nataliia Marynenko & Iryna Fedyshyn & Natalia Garmatiy & Iryna Kramar, 2019, "Financing Innovation Activity In Ukraine: Realities And Perspectives," Economic Review: Journal of Economics and Business, University of Tuzla, Faculty of Economics, volume 17, issue 1, pages 33-46, May.
• Audrone Virbickaite & Christoph Frey & Demian N. Macedo, 2019, "Sequential Stock Return Prediction Through Copulas," DEA Working Papers, Universitat de les Illes Balears, Departament d'Economía Aplicada, number 91.
• Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019, "Prediction Regions for Interval-valued Time Series," Working Papers, University of California at Riverside, Department of Economics, number 201921, Sep.
• Eva Boj & M. Mercè Claramunt & Anna Castañer & Teresa Costa & Oriol Roch, 2019, "Economic Indicators for automobile claim frequencies," Estudios de Economia, University of Chile, Department of Economics, volume 46, issue 2, pages 245-271, December.
• Dmytro Krukovets & Olesia Verchenko, 2019, "Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 248, pages 11-20, DOI: 10.26531/vnbu2019.248.02.
• Anton Grui & Artem Vdovychenko, 2019, "Quarterly Projection Model for Ukraine," Working Papers, National Bank of Ukraine, number 03/2019, Sep.
• Mohammad Ghaderi & Milosz Kadzinsky, 2019, "Accounting for structural patterns in construction of value functions: a convex optimization approach," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1634, Jan.
• Yiru Wang & Barbara Rossi, 2019, "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1642, Jan.
• Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019, "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1689, Dec.
• Do Van Thanh, 2019, "Macro-Econometric Model For Medium-Term Socio-Economic Development Planning In Vietnam. Part 1: Structure Of The Model," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, volume 1, issue 1, pages 121-136.
• Valery Zh. Dubrovsky & Ekaterina M. Ivanova & Natalia V. Chuprakova, 2019, "Problems of assessing defence contractors’ efficiency," Journal of New Economy, Ural State University of Economics, volume 20, issue 5, pages 92-107, December, DOI: 10.29141/2073-1019-2019-20-5-6.
• Roland Füss & Massimo Guidolin & Christian Koeppel, 2019, "Sentiment Risk Premia In The Cross-Section of Global Equity," Working Papers on Finance, University of St. Gallen, School of Finance, number 1913, Aug, revised May 2020.
• Marco Corazza & Giovanni Fasano & Riccardo Gusso & Raffaele Pesenti, 2019, "A comparison among Reinforcement Learning algorithms in financial trading systems," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2019:33.
• Mariana Kaneva, 2019, "Broadband and e-Commerce in the Balkans - Econometric Analysis," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, volume 8, issue 2, pages 100-109, August, DOI: 10.36997/IJUSV-ESS/2019.8.2.100.
• Szubzda Filip & Chlebus Marcin, 2019, "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, volume 6, issue 53, pages 70-85, January, DOI: 10.2478/ceej-2019-0005.
• Szubzda Filip & Chlebus Marcin, 2019, "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, volume 6, issue 53, pages 70-85, January, DOI: 10.2478/ceej-2019-0005.
• Čižmešija Mirjana & Lukač Zrinka & Novoselec Tomislav, 2019, "Nonlinear optimisation approach to proposing novel Croatian Industrial Confidence Indicator," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 5, issue 2, pages 17-26, December, DOI: 10.2478/crebss-2019-0008.
• Kvainickas Tomas Sovijus & Stankevičienė Jelena, 2019, "Regional Limitations of Stock Indices Prediction Models Based on Macroeconomic Variables," Economics and Culture, Sciendo, volume 16, issue 2, pages 5-20, December, DOI: 10.2478/jec-2019-0018.
• Pelinescu Elena & Simionescu Mihaela, 2019, "Higher Education Policies and Employability of University Graduates in the EU-28," Journal of Intercultural Management, Sciendo, volume 11, issue 3, pages 105-133, September, DOI: 10.2478/joim-2019-0020.
• Bălan Mariana, 2019, "Particularities of the Recent Evolution of Higher Education in Romania. Analysis and Forecasts," Journal of Intercultural Management, Sciendo, volume 11, issue 3, pages 87-104, September, DOI: 10.2478/joim-2019-0019.
• Simionescu Mihaela & Naroș Maria-Simona, 2019, "The Unemployment of Highly Educated People in Romania. A Panel VAR Approach," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, volume 29, issue 3, pages 20-37, September, DOI: 10.2478/sues-2019-0010.
• Mateusz Buczyński & Marcin Chlebus, 2019, "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2019-12.
• Michael W. McCracken & Joseph T. McGillicuddy, 2019, "An empirical investigation of direct and iterated multistep conditional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 2, pages 181-204, March, DOI: 10.1002/jae.2668.
• Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019, "Real‐time forecast combinations for the oil price," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 3, pages 456-462, April, DOI: 10.1002/jae.2673.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019, "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 7, pages 1027-1049, November, DOI: 10.1002/jae.2722.
• Pablo Cuba‐Borda & Luca Guerrieri & Matteo Iacoviello & Molin Zhong, 2019, "Likelihood evaluation of models with occasionally binding constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 34, issue 7, pages 1073-1085, November, DOI: 10.1002/jae.2729.
• Philip Hans Franses, 2019, "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., volume 38, issue 2, pages 73-80, March, DOI: 10.1002/for.2557.
• Libero Monteforte & Valentina Raponi, 2019, "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 38, issue 3, pages 207-221, April, DOI: 10.1002/for.2565.
• João H. Gonçalves Mazzeu & Helena Veiga & Massimo B. Mariti, 2019, "Modeling and forecasting the oil volatility index," Journal of Forecasting, John Wiley & Sons, Ltd., volume 38, issue 8, pages 773-787, December, DOI: 10.1002/for.2598.
• Willy Alanya & Gabriel Rodríguez, 2019, "Asymmetries in Volatility: An Empirical Study for the Peruvian Stock and Forex Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., volume 22, issue 01, pages 1-18, March, DOI: 10.1142/S0219091519500036.
• Katarzyna Maciejowska & Rafal Weron, 2019, "Electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/01, Feb.
• Bartosz Uniejewski & Rafal Weron, 2019, "Regularized Quantile Regression Averaging for probabilistic electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/04, Nov.
• Christopher Kath & Weronika Nitka & Tomasz Serafin & Tomasz Weron & Przemyslaw Zaleski & Rafal Weron, 2019, "Balancing RES generation: Profitability of an energy trader," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/07, Dec.
• Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019, "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/19/08, Dec.
• Li Chen & Jiti Gao & Farshid Vahid, 2019, "Global temperatures and greenhouse gases - a common features approach," Working Papers, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, number 2019-07-15, Jul.
• Alberto Caruso & Laura Coroneo, 2019, "Predicting interest rates in real-time," Discussion Papers, Department of Economics, University of York, number 19/18, Nov.
• Makarewicz, Tomasz, 2019, "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," BERG Working Paper Series, Bamberg University, Bamberg Economic Research Group, number 141.
• Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2019, "Exploiting ergodicity in forecasts of corporate profitability," BERG Working Paper Series, Bamberg University, Bamberg Economic Research Group, number 147.
• Stanisławska, Ewa & Paloviita, Maritta & Łyziak, Tomasz, 2019, "Assessing reliability of aggregated inflation views in the European Commission consumer survey," Bank of Finland Research Discussion Papers, Bank of Finland, number 10/2019.
• Knüppel, Malte & Krüger, Fabian, 2019, "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers, Deutsche Bundesbank, number 28/2019.
• Eraslan, Sercan & Schröder, Maximilian, 2019, "Nowcasting GDP with a large factor model space," Discussion Papers, Deutsche Bundesbank, number 41/2019.
• Jackson, Emerson Abraham & Tamuke, Edmund, 2019, "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 202547.
• Strohsal, Till & Wolf, Elias, 2019, "Data revisions to German national accounts: Are initial releases good nowcasts?," Discussion Papers, Free University Berlin, School of Business & Economics, number 2019/11.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019, "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers, Kiel Institute for the World Economy (IfW Kiel), number 2019-16.
• Bolgorian, Meysam, 2019, "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers, Kiel Institute for the World Economy (IfW Kiel), number 2019-2.
• Thompson, Erica L. & Smith, Leonard A., 2019, "Escape from model-land," Economics Discussion Papers, Kiel Institute for the World Economy (IfW Kiel), number 2019-23.
• Brighton, Henry, 2019, "Beyond quantified ignorance: Rebuilding rationality without the bias bias," Economics Discussion Papers, Kiel Institute for the World Economy (IfW Kiel), number 2019-25.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019, "Metcalfe's law and log-period power laws in the cryptocurrencies market," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), volume 13, pages 1-26, DOI: 10.5018/economics-ejournal.ja.2019-.
• Thompson, Erica L. & Smith, Leonard A., 2019, "Escape from model-land," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), volume 13, pages 1-17, DOI: 10.5018/economics-ejournal.ja.2019-.
• Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019, "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-003.
• Kostmann, Michael & Härdle, Wolfgang Karl, 2019, "Forecasting in Blockchain-based Local Energy Markets," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-014.
• Pele, Daniel Traian & Wesselhöfft, Niels & Härdle, Wolfgang Karl & Kolossiatis, Michalis & Yatracos, Yannis, 2019, "Phenotypic convergence of cryptocurrencies," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-018.
• Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019, "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-024.
• Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019, "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2019-027.
• Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019, "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 18/2019.
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019, "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 2/2019.
• Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019, "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 24/2019.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Schult, Christoph & Wieschemeyer, Matthias & Zeddies, Götz, 2019, "Sinkendes Potenzialwachstum in Deutschland, beschleunigter Braunkohleausstieg und Klimapaket: Finanzpolitische Konsequenzen für die Jahre bis 2024," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 7, issue 4, pages 109-120.
• Conrad, Christian & Schienle, Melanie, 2019, "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 121, DOI: 10.5445/IR/1000090371.
• Bormann, Carsten & Schienle, Melanie, 2019, "Detecting structural differences in tail dependence of financial time series," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 122, DOI: 10.5445/IR/1000092468.
• Behrens, Christoph, 2019, "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 9, DOI: 10.18452/19832.
• Belke, Ansgar & Klose, Jens, 2019, "Forecasting ECB policy rates with different monetary policy rules," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 815, DOI: 10.4419/86788944.
• Döhrn, Roland, 2019, "Comparing forecast accuracy in small samples," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 833, DOI: 10.4419/86788966.
• Hinterlang, Natascha, 2019, "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy, Verein für Socialpolitik / German Economic Association, number 203503.
• Axenbeck, Janna & Breithaupt, Patrick, 2019, "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 19-063.
• Oliver Merz & Raphael Flepp & Egon Franck, 2020, "Sonic Thunder vs. Brian the Snail : Are people affected by uninformative racehorse names?," Working Papers, University of Zurich, Department of Business Administration (IBW), number 384, Nov.
• Bunjira Makond & Mayuening Eso, 2019, "Predictive Models for Classifying the Outcomes of Violence Case Study for Thailand's Deep South," Advances in Decision Sciences, Asia University, Taiwan, volume 23, issue 3, pages 56-92, September.
• Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019, "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-04, Mar.
• Søren Kjærgaard & Yunus Emre Ergemen & Malene Kallestrup-Lamb & Jim Oeppen & Rune Lindahl-Jacobsen, 2019, "Forecasting Causes of Death using Compositional Data Analysis: the Case of Cancer Deaths," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-07, May.
• Søren Kjærgaard & Yunus Emre Ergemen & Marie-Pier Bergeron Boucher & Jim Oeppen & Malene Kallestrup-Lamb, 2019, "Longevity forecasting by socio-economic groups using compositional data analysis," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-08, May.
• Daniel Borup & Erik Christian Montes Schütte, 2019, "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-13, Aug.
• Kristoffer Pons Bertelsen, 2019, "Comparing Tests for Identification of Bubbles," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-16, Oct.
• Malene Kallestrup-Lamb & Søren Kjærgaard & Carsten P. T. Rosenskjold, 2019, "Insight into Stagnating Life Expectancy: Analysing Cause of Death Patterns across Socio-economic Groups," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-20, Nov.
• Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019, "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2019-21, Nov.
• Andrzej JARYNOWSKI, 2019, "Cost-Effectiveness Analysis For Hpv Mitigation Strategies In The Republic Of Moldova Based On Infectious Disease Modelling," Economy and Sociology, The Journal Economy and Sociology, issue 2, pages 50-64.