Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2018

• Costantini, Mauro & Kunst, Robert M., 2018, "On Using Predictive-ability Tests in the Selection of Time-series Prediction Models: A Monte Carlo Evaluation," Economics Series, Institute for Advanced Studies, number 341, Jul.
• Michael Dotsey & Shigeru Fujita & Tom Stark, 2018, "Do Phillips Curves Conditionally Help to Forecast Inflation?," International Journal of Central Banking, International Journal of Central Banking, volume 14, issue 4, pages 43-92, September.
• Cathal O'Donoghue & Gijs Dekkers, 2018, "Increasing the Impact of Dynamic Microsimulation Modelling," International Journal of Microsimulation, International Microsimulation Association, volume 11, issue 1, pages 61-96.
• Abbygail Jaccard & Lise Retat & Martin Brown & Laura Webber & Zaid Chalabi, 2018, "Global Sensitivity Analysis of a Model Simulating an Individual’s Health State through Their Lifetime," International Journal of Microsimulation, International Microsimulation Association, volume 11, issue 3, pages 100-121.
• Abbygail Jaccard & Lise Retat & Martin Brown & Laura Webber & Zaid Chalabi, 2018, "Global Sensitivity Analysis of a Model Simulating an Individual’s Health State through Their Lifetime APPENDIX," International Journal of Microsimulation, International Microsimulation Association, volume 11, issue 3, pages 122-133.
• Rupendra N Shrestha & Deborah Schofield & Melanie J B Zeppel & Michelle M Cunich & Robert Tanton & Simon J Kelly & Lennert Veerman & Megan E Passey, 2018, "Care&WorkMOD: An Australian Microsimulation Model Projecting the Economic Impacts of Early Retirement in Informal Carers," International Journal of Microsimulation, International Microsimulation Association, volume 11, issue 3, pages 78-99.
• Luis Manuel León Anaya & Víctor Manuel Landassuri Moreno & Héctor Rafael Orozco Aguirre & Maricela Quintana López, 2018, "Predicción del IPC mexicano combinando modelos econométricos e inteligencia artificial," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 13, issue 4, pages 603-629, Octubre-D.
• Achim Zeileis & Christoph Leitner & Kurt Hornik, 2018, "Probabilistic forecasts for the 2018 FIFA World Cup based on the bookmaker consensus model," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2018-09, May.
• Thorsten Simon & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2018, "Lightning Prediction Using Model Output Statistics," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2018-14, Jul.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018, "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201805, Mar, revised Mar 2018.
• Julián Andrada-Félixa & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2018, "“Time connectedness of fear”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201818, Sep, revised Sep 2018.
• Oscar Claveria, 2018, "“A new metric of consensus for Likert scales”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201821, Sep, revised Oct 2018.
• Antonio Cappiello, 2018, "Mediation: economic concepts and some examples of rational framework for legal professionals," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, volume 72, issue 2, pages 149-158, April-Jun.
• Stefania Pozzuoli, 2018, "L'evoluzione del credito alle società non finanziarie e alle famiglie: un'analisi empririca per l'Italia," Working Papers, Department of the Treasury, Ministry of the Economy and of Finance, number 2, Feb.
• Dr. Brijesh Kumar Agarwal & Anamica Bansal, 2018, "An Analytical Study of Marketing Mix of Selected Brands of Vegetable Oil in Northern India," Journal of Commerce and Trade, Society for Advanced Management Studies, volume 13, issue 1, pages 118-123, April.
• Jose Cuesta & Gabriel Lara Ibarra, 2018, "Comparing Cross-Survey Micro Imputation and Macro Projection Techniques: Poverty in Post Revolution Tunisia," Journal of Income Distribution, Ad libros publications inc., volume 25, issue 1, pages 1-30, March.
• Thomas F. Coleman & Alex LaPlante & Alexey Rubtsov, 2018, "Analysis of the SRISK measure and its application to the Canadian banking and insurance industries," Annals of Finance, Springer, volume 14, issue 4, pages 547-570, November, DOI: 10.1007/s10436-018-0326-3.
• David Court & Benjamin Gillen & Jordi McKenzie & Charles R. Plott, 2018, "Two information aggregation mechanisms for predicting the opening weekend box office revenues of films: Boxoffice Prophecy and Guess of Guesses," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), volume 65, issue 1, pages 25-54, January, DOI: 10.1007/s00199-017-1036-1.
• Bo Carlsson & Gunnar Eliasson & Karolin Sjöö, 2018, "The Swedish industrial support program of the 1970s revisited," Journal of Evolutionary Economics, Springer, volume 28, issue 4, pages 805-835, September, DOI: 10.1007/s00191-018-0581-5.
• Sangeeta Das & Dipankor Coondoo, 2018, "Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 16, issue 1, pages 199-207, December, DOI: 10.1007/s40953-017-0116-1.
• Dilip Kumar, 2018, "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 16, issue 2, pages 313-335, June, DOI: 10.1007/s40953-017-0085-4.
• Zouheir Mighri, 2018, "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 16, issue 2, pages 427-473, June, DOI: 10.1007/s40953-017-0088-1.
• Carlos Cuerpo & Ángel Cuevas & Enrique M. Quilis, 2018, "Estimating output gap: a beauty contest approach," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, volume 9, issue 3, pages 275-304, August, DOI: 10.1007/s13209-018-0181-5.
• Leif Jacobs & Lara Quack, 2018, "Das Ende der Dieselsubvention: Verteilungseffekte einer CO2-basierten Energiesteuerreform
  [The End of the Diesel Subsidy: Distributional Effects of a CO2-based Energy Tax Reform]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, volume 98, issue 8, pages 578-586, August, DOI: 10.1007/s10273-018-2334-3.
• Djahoué Mangblé Gérald, 2018, "Estimating and Forecasting West Africa Stock Market Volatility Using Asymmetric GARCH Models," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 8, issue 6, pages 1-4.
• Emeka Nkoro & Aham Kelvin Uko, 2018, "A Small-Size Macroeconometric Model for Nigerian Economy," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, volume 7, issue 2, pages 1-4.
• Dunne, Peter G., 2018, "Positive liquidity spillovers from sovereign bond-backed securities," ESRB Working Paper Series, European Systemic Risk Board, number 67, Jan.
• Nick Jagger, 2018, "A Co-Evolutionary, Long-Term, MacroEconomic Forecast for the UK Using Demographic Projections," SPRU Working Paper Series, SPRU - Science Policy Research Unit, University of Sussex Business School, number 2018-20, Oct.
• Håvard Hungnes, 2018, "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers, Statistics Norway, Research Department, number 871, Jan.
• Nico Keilman & Dinh Q. Pham & Astri Syse, 2018, "Mortality shifts and mortality compression. The case of Norway, 1900-2060," Discussion Papers, Statistics Norway, Research Department, number 884, Sep.
• Rahul Deb & Mallesh M. Pai & Maher Said, 2018, "Evaluating Strategic Forecasters," Working Papers, New York University, Leonard N. Stern School of Business, Department of Economics, number 18-23.
• Gary Koop & Stuart McIntyre & James Mitchell, 2018, "UK regional nowcasting using a mixed frequency vector autoregressive model," Working Papers, University of Strathclyde Business School, Department of Economics, number 1805, Jul.
• Marian Vavra, 2018, "Assessing Distributional Properties of Forecast Errors," Working and Discussion Papers, Research Department, National Bank of Slovakia, number WP 3/2018, Mar.
• Yuzhi Cai & Guodong Li, 2018, "A novel approach to modelling the distribution of financial returns," Working Papers, Swansea University, School of Management, number 2018-22, Feb.
• Stephen Bazen & Jean-Marie Cardebat, 2018, "Forecasting Bordeaux wine prices using state-space methods," Applied Economics, Taylor & Francis Journals, volume 50, issue 47, pages 5110-5121, October, DOI: 10.1080/00036846.2018.1472740.
• Tomasz Woźniak, 2018, "Granger-causal analysis of GARCH models: A Bayesian approach," Econometric Reviews, Taylor & Francis Journals, volume 37, issue 4, pages 325-346, April, DOI: 10.1080/07474938.2015.1092839.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch & Mark E. Wohar, 2018, "Terror attacks and stock-market fluctuations: evidence based on a nonparametric causality-in-quantiles test for the G7 countries," The European Journal of Finance, Taylor & Francis Journals, volume 24, issue 4, pages 333-346, March, DOI: 10.1080/1351847X.2016.1239586.
• Carlos A. Medel, 2018, "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, volume 32, issue 3, pages 331-371, July, DOI: 10.1080/10168737.2018.1501589.
• Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2018, "On the directional accuracy of inflation forecasts: evidence from South African survey data," Journal of Applied Statistics, Taylor & Francis Journals, volume 45, issue 5, pages 884-900, April, DOI: 10.1080/02664763.2017.1322556.
• Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2018, "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Journal of the American Statistical Association, Taylor & Francis Journals, volume 113, issue 522, pages 675-685, April, DOI: 10.1080/01621459.2016.1273117.
• Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018, "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 36, issue 1, pages 131-145, January, DOI: 10.1080/07350015.2015.1137760.
• Rasmus T. Varneskov & Pierre Perron, 2018, "Combining long memory and level shifts in modelling and forecasting the volatility of asset returns," Quantitative Finance, Taylor & Francis Journals, volume 18, issue 3, pages 371-393, March, DOI: 10.1080/14697688.2017.1329591.
• Thomas Brenner & Marco Capasso & Matthias Duschl & Koen Frenken & Tania Treibich, 2018, "Causal relations between knowledge-intensive business services and regional employment growth," Regional Studies, Taylor & Francis Journals, volume 52, issue 2, pages 172-183, February, DOI: 10.1080/00343404.2016.1265104.
• Tian, Jing & Goodwin, Thomas, 2018, "An unobserved component modeling approach to evaluate multi-horizon forecasts," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2018-04.
• Mahmut Gunay, 2018, "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, volume 18, issue 4, pages 149-161.
• Mahmut Gunay, 2018, "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1805.
• Nikolaos Arnis, 2018, "Predicting Corporate Bankruptcy: A Cross-Sectoral Empirical Study - The Case of Greece," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, volume 11, issue 3, pages 31-56, December.
• P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018, "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 18-009/III, Jan.
• Marta Banbura & Andries van Vlodrop, 2018, "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 18-025/IV, Mar.
• Mengheng Li & Siem Jan (S.J.) Koopman, 2018, "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 18-027/III, Mar.
• Florian Peters & Simas Kucinskas, 2018, "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 18-058/IV, Jun.
• Prüfer, Jens & Prüfer, Patricia, 2018, "Data Science for Institutional and Organizational Economics," Discussion Paper, Tilburg University, Center for Economic Research, number 2018-016.
• Prüfer, Jens & Prüfer, Patricia, 2018, "Data Science for Institutional and Organizational Economics," Discussion Paper, Tilburg University, Tilburg Law and Economic Center, number 2018-011.
• Prüfer, Jens & Prüfer, Patricia, 2018, "Data Science for Institutional and Organizational Economics," Other publications TiSEM, Tilburg University, School of Economics and Management, number 4392ac65-4fb6-4e9a-a92d-5.
• Prüfer, Jens & Prüfer, Patricia, 2018, "Data Science for Institutional and Organizational Economics," Other publications TiSEM, Tilburg University, School of Economics and Management, number 6d04f0fe-0bcd-4cf4-86f6-f.
• Heikki Kauppi & Timo Virtanen, 2018, "Boosting Non-linear Predictabilityof Macroeconomic Time Series," Discussion Papers, Aboa Centre for Economics, number 124, Dec.
• Giacomo Caterini, 2018, "Classifying Firms with Text Mining," DEM Working Papers, Department of Economics and Management, number 2018/09.
• Carlo Fezzi & Luca Mosetti, 2018, "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers, Department of Economics and Management, number 2018/10.
• Carolina Fugazza, 2018, "Anatomy of Unemployment Risk," Working papers, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino, number 048, Feb.
• Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2018, "Prediction Regions for Interval-valued Time Series," Working Papers, University of California at Riverside, Department of Economics, number 201817, Oct.
• Tae-Hwy Lee & Jianghao Chu & Aman Ullah, 2018, "Variable Selection in Sparse Semiparametric Single Index Models," Working Papers, University of California at Riverside, Department of Economics, number 201908, Sep.
• Tae-Hwy Lee & Yundong Tu, 2018, "Forecasting Using Supervised Factor Models," Working Papers, University of California at Riverside, Department of Economics, number 201909, Dec.
• Alula Nerea, 2018, "The Impact of Illicit Financial Flow on Economic Growth of Ethiopia," Working Papers, University of Ferrara, Department of Economics, number 2018107, Dec.
• Francis Bismans, 2018, "Is the South African economy likely to fall back into recession in 2018-2019?," Working Papers of BETA, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2018-33.
• J. Isaac Miller & Kyungsik Nam, 2019, "Dating Hiatuses: A Statistical Model of the Recent Slowdown in Global Warming – and the Next One," Working Papers, Department of Economics, University of Missouri, number 1903.
• Atsushi Inoue & Barbara Rossi, 2018, "The effects of conventional and unconventional monetary policy on exchange rates," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1639, Dec.
• Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018, "Confidence intervals for bias and size distortion in IV and local projections–IV models," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1640, Sep.
• Galina A. Timofeeva & Yana A. Bozhalkina, 2018, "Dependence of a Loan Portfolio Structure on a Cut-Off Level in a Scoring Model," Journal of New Economy, Ural State University of Economics, volume 19, issue 2, pages 24-35, April, DOI: 10.29141/2073-1019-2018-19-2-2.
• Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018, "Predicting Bond Betas using Macro-Finance Variables," Working Papers, Universitat Rovira i Virgili, Department of Economics, number 2072/306546.
• Goller, Daniel & Knaus, Michael C. & Lechner, Michael & Okasa, Gabriel, 2018, "Predicting Match Outcomes in Football by an Ordered Forest Estimator," Economics Working Paper Series, University of St. Gallen, School of Economics and Political Science, number 1811, Nov.
• Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018, "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series, Economics Discipline Group, UTS Business School, University of Technology, Sydney, number 44, May.
• Mengheng Li & Marcel Scharth, 2018, "Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model," Working Paper Series, Economics Discipline Group, UTS Business School, University of Technology, Sydney, number 49, Aug.
• Monica Billio & Roberto Casarin & Sylvia Kaufmann & Matteo Iacopini, 2018, "Bayesian Dynamic Tensor Regression," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2018:13.
• Monica Billio & Roberto Casarin & Matteo Iacopini, 2018, "Bayesian Markov Switching Tensor Regression for Time-varying Networks," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2018:14.
• Matteo Iacopini & Dominique Guégan, 2018, "Nonparametric Forecasting of Multivariate Probability Density Functions," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2018:15.
• Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Domenico Sartore, 2018, "A scoring rule for factor and autoregressive models under misspecification," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2018:18.
• Boriss Siliverstovs, 2018, "Dissecting the Purchasing Managers’ Index: Are All Relevant Components Included? Are All Included Components Relevant?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, volume 65, issue 4, pages 381-394.
• Mariana Kaneva, 2018, "Telecommunications in the Balkans - Retrospective Statistical Analysis," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, volume 7, issue 2, pages 163-174, November.
• Gulay Emrah, 2018, "Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition," Scientific Annals of Economics and Business, Sciendo, volume 65, issue 2, pages 159-169, June, DOI: 10.2478/saeb-2018-0010.
• Ginanneschi Marco & Piu Pietro, 2018, "The Role of e-Commerce in the Success of Low-cost Carriers," Scientific Annals of Economics and Business, Sciendo, volume 65, issue 4, pages 407-425, December, DOI: 10.2478/saeb-2018-0029.
• Husáková Martina, 2018, "Use of the Multi-Agent Paradigm in Sustainable Tourism," Czech Journal of Tourism, Sciendo, volume 7, issue 1, pages 5-24, June, DOI: 10.1515/cjot-2018-0001.
• Zekić-Sušac Marijana & Scitovski Rudolf & Has Adela, 2018, "Cluster analysis and artificial neural networks in predicting energy efficiency of public buildings as a cost-saving approach," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 4, issue 2, pages 57-66, November, DOI: 10.2478/crebss-2018-0013.
• Siekelova Anna & Kliestik Tomas & Adamko Peter, 2018, "Predictive Ability of Chosen Bankruptcy Models: A Case Study of Slovak Republic," Economics and Culture, Sciendo, volume 15, issue 1, pages 105-114, June, DOI: 10.2478/jec-2018-0012.
• Zawada Marcin & Szajt Marek, 2018, "Application of Statistical and Econometric Tools in The Analysis of Air Pollution Level on The Example of Czestochowa," Folia Oeconomica Stetinensia, Sciendo, volume 18, issue 2, pages 144-158, December, DOI: 10.2478/foli-2018-0024.
• Kaczmarczyk Paweł, 2018, "Neural Network Application to Support Regression Model in Forecasting Single-Sectional Demand for Telecommunications Services," Folia Oeconomica Stetinensia, Sciendo, volume 18, issue 2, pages 159-177, December, DOI: 10.2478/foli-2018-0025.
• Simionescu Mihaela, 2018, "The Impact of European Economic Integration on Migration in the European Union," HOLISTICA – Journal of Business and Public Administration, Sciendo, volume 9, issue 1, pages 23-34, May, DOI: 10.1515/hjbpa-2018-0002.
• Ene Andreea Bianca, 2018, "Distance Education in Romanian Higher Education," HOLISTICA – Journal of Business and Public Administration, Sciendo, volume 9, issue 1, pages 65-70, May, DOI: 10.1515/hjbpa-2018-0005.
• Devjak Srečko, 2018, "Modeling of Cash Flows from Nonperforming Loans in a Commercial Bank," Naše gospodarstvo/Our economy, Sciendo, volume 64, issue 4, pages 3-9, December, DOI: 10.2478/ngoe-2018-0018.
• Weigand Roland & Wanger Susanne & Zapf Ines, 2018, "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, volume 34, issue 1, pages 265-301, March, DOI: 10.1515/jos-2018-0012.
• Simionescu Mihaela, 2018, "What Drives Economic Growth in Some CEE Countries?," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, volume 28, issue 1, pages 46-56, March, DOI: 10.2478/sues-2018-0004.
• Florea Nicoleta Valentina & Tănăsescu Dorina Antoneta & Duică Anişoara, 2018, "Enabling Customer-Centricity and Relationship Management using Net Promoter Score," Valahian Journal of Economic Studies, Sciendo, volume 9, issue 2, pages 115-126, November, DOI: 10.2478/vjes-2018-0023.
• Shehu U.R. Aliyu & Nafiu B. Abdulsalam & Sani Bawa, 2018, "Testing For Financial Spillovers In Calm And Turbulent Periods," West African Journal of Monetary and Economic Integration, West African Monetary Institute, volume 18, issue 2, pages 1-27, December.
• Martin Feldkircher & Florian Huber & Gregor Kastner, 2018, "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp260, Jan.
• Feldkircher, Martin & Kastner, Gregor & Huber, Florian, 2018, "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series, WU Vienna University of Economics and Business, number 260, Jan.
• Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2018, "On The Sources Of Uncertainty In Exchange Rate Predictability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 59, issue 1, pages 329-357, February, DOI: 10.1111/iere.12271.
• John M. Maheu & Yong Song, 2018, "An efficient Bayesian approach to multiple structural change in multivariate time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 33, issue 2, pages 251-270, March, DOI: 10.1002/jae.2606.
• Carlos Díaz, 2018, "Extracting information shocks from the Bank of England inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., volume 37, issue 3, pages 316-326, April, DOI: 10.1002/for.2501.
• Ricardo Crisóstomo & Lorena Couso, 2018, "Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes," Journal of Forecasting, John Wiley & Sons, Ltd., volume 37, issue 5, pages 589-603, August, DOI: 10.1002/for.2521.
• Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018, "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., volume 37, issue 7, pages 705-719, November, DOI: 10.1002/for.2539.
• Marek Jarociński & Michele Lenza, 2018, "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, volume 50, issue 6, pages 1189-1224, September, DOI: 10.1111/jmcb.12496.
• Bartosz Uniejewski & Rafal Weron, 2018, "Efficient forecasting of electricity spot prices with expert and LASSO models," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/02, Jun.
• Katarzyna Hubicka & Grzegorz Marcjasz & Rafal Weron, 2018, "A note on averaging day-ahead electricity price forecasts across calibration windows," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/03, Jul.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018, "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/05, Jul.
• Grzegorz Marcjasz & Tomasz Serafin & Rafal Weron, 2018, "Selection of calibration windows for day-ahead electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/06, Aug.
• Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2018, "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/07, Aug.
• Rafal Weron & Florian Ziel, 2018, "Electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/08, Sep.
• Benchimol, Jonathan & Bounader, Lahcen, 2018, "Optimal monetary policy under bounded rationality," Bank of Finland Research Discussion Papers, Bank of Finland, number 9/2018.
• Granziera, Eleonora & Sekhposyan, Tatevik, 2018, "Predicting relative forecasting performance: An empirical investigation," Bank of Finland Research Discussion Papers, Bank of Finland, number 23/2018.
• Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018, "Mixed frequency models with MA components," Discussion Papers, Deutsche Bundesbank, number 02/2018.
• Breitung, Jörg & Knüppel, Malte, 2018, "How far can we forecast? Statistical tests of the predictive content," Discussion Papers, Deutsche Bundesbank, number 07/2018.
• Kurz-Kim, Jeong-Ryeol, 2018, "A note on the predictive power of survey data in nowcasting euro area GDP," Discussion Papers, Deutsche Bundesbank, number 10/2018.
• Gerke, Rafael & Giesen, Sebastian & Kienzler, Daniel, 2018, "Uncertainty about QE effects when an interest rate peg is anticipated," Discussion Papers, Deutsche Bundesbank, number 12/2018.
• Pinkwart, Nicolas, 2018, "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers, Deutsche Bundesbank, number 36/2018.
• Götz, Thomas B. & Hauzenberger, Klemens, 2018, "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers, Deutsche Bundesbank, number 40/2018.
• Ollech, Daniel, 2018, "Seasonal adjustment of daily time series," Discussion Papers, Deutsche Bundesbank, number 41/2018.
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018, "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers, Deutsche Bundesbank, number 48/2018.
• Knüppel, Malte & Schultefrankenfeld, Guido, 2018, "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers, Deutsche Bundesbank, number 56/2018.
• Jang, Tae-Seok & Sacht, Stephen, 2018, "Forecast heuristics, consumer expectations, and new-Keynesian macroeconomics: A horse race," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2018-09.
• Jang, Tae-Seok & Sacht, Stephen, 2018, "Macroeconomic dynamics under bounded rationality: On the impact of consumers' forecast heuristics," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2018-10.
• Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018, "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2018-11.
• Kašćelan, Ljiljana & Lazović, Vujica & Đuričković, Tamara & Rondović Biljana, 2018, "Analysis of the Diffusion of E-services in Public Sector Using the Decision Tree Method," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2018), Split, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018".
• Opiła, Janusz, 2018, "Visualization in a Knowledge Transfer Process," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2018), Split, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018".
• Jackson, Emerson Abraham & Sillah, Abdulai & Tamuke, Edmund, 2018, "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 7, issue 1, pages 51-56, DOI: 10.18483/ijSci.1479.
• Heinisch, Katja & Lindner, Axel, 2018, "For how long do IMF forecasts of world economic growth stay up-to-date?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest ar, pages 1-6, DOI: 10.1080/13504851.2018.1459035.
• Kholodilin, Konstantin A. & Michelsen, Claus & Ulbricht, Dirk, 2018, "Speculative price bubbles in urban housing markets," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 55, issue 4, pages 1957-1983.
• Dockery, Everton & Efentakis, Miltiadis & Al-Faryan, Mamdouh Abdulaziz Saleh, 2018, "Are range based models good enough? Evidence from seven stock markets," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 8, issue 2, pages 7-40, DOI: 10.22495/rgcv8i2p1.
• Havranek, Tomas & Zeynalov, Ayaz, 2018, "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 187420.
• Jahn, Malte, 2018, "Artificial neural network regression models: Predicting GDP growth," HWWI Research Papers, Hamburg Institute of International Economics (HWWI), number 185.
• Coupé, Tom, 2018, "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, volume 12, pages 1-8, DOI: 10.5018/economics-ejournal.ja.2018-.
• Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018, "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2018-021.
• Chen, Ying & Han, Qian & Niu, Linlin, 2018, "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2018-046.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2018, "Cryptocurrencies, Metcalfe's law and LPPL models," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2018-056.
• Holtemöller, Oliver & Schult, Christoph, 2018, "Expectation formation, financial frictions, and forecasting performance of dynamic stochastic general equilibrium models," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 15/2018.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2018, "Mittelfristprojektion des IWH: Wirtschaftsentwicklung und Öffentliche Finanzen 2018 bis 2025," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 6, issue 4, pages 105-114.
• Duarte, Pablo & Süßmuth, Bernd, 2018, "Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis," Working Papers, University of Leipzig, Faculty of Economics and Management Science, number 152.
• Wei-Bin Zhang, 2018, "A Growth Theory Based on Walrasian General Equilibrium, Solow-Uzawa Growth, and Heckscher-Ohlin Trade Theories," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 16, issue 3-B, pages 452-464.
• Berislav Žmuk & Ksenija Dumièiæ & Irena Paliæ, 2018, "Forecasting Labour Productivity in the European Union Member States: Is Labour Productivity Changing as Expected?," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 16, issue 3-B, pages 504-523.

2017

• Christopher G. Gibbs, 2017, "Forecast combination, non-linear dynamics, and the macroeconomy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), volume 63, issue 3, pages 653-686, March, DOI: 10.1007/s00199-016-0951-x.
• Cars Hommes & Tomasz Makarewicz & Domenico Massaro & Tom Smits, 2017, "Genetic algorithm learning in a New Keynesian macroeconomic setup," Journal of Evolutionary Economics, Springer, volume 27, issue 5, pages 1133-1155, November, DOI: 10.1007/s00191-017-0511-y.
• Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017, "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), volume 26, issue 1, pages 1-35, December, DOI: 10.1007/s40503-017-0044-7.
• Robert Lehmann & Klaus Wohlrabe, 2017, "Boosting and regional economic forecasting: the case of Germany," Letters in Spatial and Resource Sciences, Springer, volume 10, issue 2, pages 161-175, July, DOI: 10.1007/s12076-016-0179-1.
• Mikael Collan & Jyrki Savolainen & Pasi Luukka, 2017, "Investigating the effect of price process selection on the value of a metal mining asset portfolio," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, volume 30, issue 2, pages 107-115, July, DOI: 10.1007/s13563-017-0102-2.
• Iñaki Bildosola & Pilar Gonzalez & Paz Moral, 2017, "An approach for modelling and forecasting research activity related to an emerging technology," Scientometrics, Springer;Akadémiai Kiadó, volume 112, issue 1, pages 557-572, July, DOI: 10.1007/s11192-017-2381-3.
• Wali Ullah, 2017, "Term structure forecasting in affine framework with time-varying volatility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, volume 26, issue 3, pages 453-483, August, DOI: 10.1007/s10260-017-0378-y.
• Bogdan Batrinca & Christian W. Hesse & Philip C. Treleaven, 2017, "Developing a Volume Forecasting Model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 7, issue 1, pages 1-1.
• Bing Li, 2017, "Network Evolution of the Chinese Stock Market: A Study based on the CSI 300 Index," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 7, issue 3, pages 1-5.
• Petrus Strydom, 2017, "Macro economic cycle effect on mortgage and personal loan default rates," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 7, issue 6, pages 1-1.
• Brian Stacey, 2017, "A Standardized Treatment of Binary Similarity Measures with an Introduction to k-Vector Percentage Normalized Similarity," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, volume 6, issue 1, pages 1-3.
• Brownlees, Christian & Engle, Robert F., 2017, "SRISK: a conditional capital shortfall measure of systemic risk," ESRB Working Paper Series, European Systemic Risk Board, number 37, Mar.
• Andrea BUCCI, 2017, "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, volume 8, issue 2, pages 94-138.
• Anthony Mouraud, 2017, "Innovative time series forecasting: auto regressive moving average vs deep networks," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 4, issue 3, pages 282-293, March, DOI: 10.9770/jesi.2017.4.3S(4).
• Rahul Deb & Mallesh M. Pai & Maher Said, 2017, "Evaluating Strategic Forecasters," Working Papers, New York University, Leonard N. Stern School of Business, Department of Economics, number 17-02.
• Christopher G. Gibbs & Andrey L. Vasnev, 2017, "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers, School of Economics, The University of New South Wales, number 2017-10, Feb.
• Rachida Ouysse, 2017, "Constrained principal components estimation of large approximate factor models," Discussion Papers, School of Economics, The University of New South Wales, number 2017-12, Apr.
• R. Lehmann & K. Wohlrabe, 2017, "Experts, firms, consumers or even hard data? Forecasting employment in Germany," Applied Economics Letters, Taylor & Francis Journals, volume 24, issue 4, pages 279-283, February, DOI: 10.1080/13504851.2016.1184219.
• Jari Hännikäinen, 2017, "The shadow rate as a predictor of real activity and inflation: evidence from a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, volume 24, issue 8, pages 527-535, May, DOI: 10.1080/13504851.2016.1208347.
• Colin O’hare & Youwei Li, 2017, "Modelling mortality: are we heading in the right direction?," Applied Economics, Taylor & Francis Journals, volume 49, issue 2, pages 170-187, January, DOI: 10.1080/00036846.2016.1192278.
• Stavros Degiannakis & George Filis & George Palaiodimos, 2017, "Investments and uncertainty revisited: the case of the US economy," Applied Economics, Taylor & Francis Journals, volume 49, issue 45, pages 4521-4529, September, DOI: 10.1080/00036846.2017.1284995.
• Mardi Dungey & Jan P.A.M. Jacobs & Jing Tian, 2017, "Forecasting output gaps in the G-7 countries: the role of correlated innovations and structural breaks," Applied Economics, Taylor & Francis Journals, volume 49, issue 45, pages 4554-4566, September, DOI: 10.1080/00036846.2017.1284998.
• Philip Hans Franses & Rianne Legerstee & Richard Paap, 2017, "Estimating loss functions of experts," Applied Economics, Taylor & Francis Journals, volume 49, issue 4, pages 386-396, January, DOI: 10.1080/00036846.2016.1197373.
• Colin O’hare & Youwei Li, 2017, "Models of mortality rates – analysing the residuals," Applied Economics, Taylor & Francis Journals, volume 49, issue 52, pages 5309-5323, November, DOI: 10.1080/00036846.2017.1305092.
• Francis X. Diebold & Minchul Shin, 2017, "Assessing point forecast accuracy by stochastic error distance," Econometric Reviews, Taylor & Francis Journals, volume 36, issue 6-9, pages 588-598, October, DOI: 10.1080/07474938.2017.1307247.
• Manabu Asai & Michael McAleer, 2017, "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, volume 36, issue 6-9, pages 638-650, October, DOI: 10.1080/07474938.2017.1307326.
• Sotirios Bersimis & Stavros Degiannakis & Dimitrios Georgakellos, 2017, "Real-time monitoring of carbon monoxide using value-at-risk measure and control charting," Journal of Applied Statistics, Taylor & Francis Journals, volume 44, issue 1, pages 89-108, January, DOI: 10.1080/02664763.2016.1161738.
• Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2017, "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 1, pages 110-129, January, DOI: 10.1080/07350015.2015.1061436.
• Joshua C. C. Chan, 2017, "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 1, pages 17-28, January, DOI: 10.1080/07350015.2015.1052459.
• Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017, "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 2, pages 162-182, April, DOI: 10.1080/07350015.2015.1123636.
• Davide Pettenuzzo & Allan Timmermann, 2017, "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 2, pages 183-201, April, DOI: 10.1080/07350015.2015.1051183.
• Michael P. Clements, 2017, "Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 3, pages 420-433, July, DOI: 10.1080/07350015.2015.1081596.
• Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017, "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 3, pages 470-485, July, DOI: 10.1080/07350015.2015.1087856.
• Christian Menden & Christian R. Proaño, 2017, "Dissecting the financial cycle with dynamic factor models," Quantitative Finance, Taylor & Francis Journals, volume 17, issue 12, pages 1965-1994, December, DOI: 10.1080/14697688.2017.1357971.
• G. Demos & D. Sornette, 2017, "Birth or burst of financial bubbles: which one is easier to diagnose?," Quantitative Finance, Taylor & Francis Journals, volume 17, issue 5, pages 657-675, May, DOI: 10.1080/14697688.2016.1231417.
• V. Filimonov & G. Demos & D. Sornette, 2017, "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, volume 17, issue 8, pages 1167-1186, August, DOI: 10.1080/14697688.2016.1276298.
• Goodwin, Thomas & Tian, Jing, 2017, "A state space approach to evaluate multi-horizon forecasts," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2017-15.
• Kurmas Akdogan, 2017, "Mean-Reversion in Unprocessed Food Prices," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1703.
• Ferhat Camlica & Didem Gunes & Etkin Ozen, 2017, "A Financial Connectedness Analysis for Turkey," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1719.
• Manabu Asai & Michael McAleer, 2017, "Forecasting the Volatility of Nikkei 225 Futures," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 17-017/III, Jan.
• Tom Boot & Andreas Pick, 2017, "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 17-039/III, Apr.
• León, C. & Moreno, José Fernando & Cely, Jorge, 2017, "Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition," Discussion Paper, Tilburg University, Center for Economic Research, number 2017-009.
• León, C. & Moreno, José Fernando & Cely, Jorge, 2017, "Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition," Other publications TiSEM, Tilburg University, School of Economics and Management, number 75d8648e-9855-4c5c-9aa9-0.
• Steven Lehrer & Tian Xie, 2017, "Box Office Buzz: Does Social Media Data Steal the Show from Model Uncertainty When Forecasting for Hollywood?," The Review of Economics and Statistics, MIT Press, volume 99, issue 5, pages 749-755, December.
• Gianni Amisano & John Geweke, 2017, "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, volume 99, issue 5, pages 912-925, December.
• Manabu Asai & Michael McAleer, 2017, "Forecasting the volatility of Nikkei 225 futures," Documentos de Trabajo del ICAE, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, number 2017-07, Jan.
• Roberta Cardani & Alessia Paccagnini & Stelios D. Bekiros, 2017, "The Effectiveness of Forward Guidance in an Estimated DSGE Model for the Euro Area: the Role of Expectations," Working Papers, School of Economics, University College Dublin, number 201701, Jan.
• Michael Spagat & Neil Johnson & Stijn van Weezel, 2017, "David Versus Goliath: Fundamental Patterns and Predictions in Modern Wars and Terrorist Campaigns," Working Papers, School of Economics, University College Dublin, number 201721, Oct.
• Anton Grui & Roman Lysenko, 2017, "Nowcasting Ukraine's GDP Using a Factor-Augmented VAR (FAVAR) Model," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 242, pages 5-13, DOI: 10.26531/vnbu2017.242.005.
• Teresa de J. Vargas Vega & Zeus S. Hernández Veleros & Eleazar Villegas González, 2017, "Economic growth and financial development: Evidence from three countries in North America," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, volume 42, issue 43, pages 11-50, January-j.
• Lorenzo Ricci, 2017, "Essays on tail risk in macroeconomics and finance: measurement and forecasting," ULB Institutional Repository, ULB -- Universite Libre de Bruxelles, number 2013/242122, Feb.
• Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2017, "A Justification of Conditional Confidence Intervals," Research Memorandum, Maastricht University, Graduate School of Business and Economics (GSBE), number 023, Oct, DOI: 10.26481/umagsb.2017023.
• A. Ason Okoruwa, 2017, "Regression Analysis of Property Productivity Index and Value," The Valuation Journal, The National Association of Authorized Romanian Valuers, volume 12, issue 1, pages 58-93.
• Chlebus Marcin, 2017, "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, volume 3, issue 50, pages 01-25, December, DOI: 10.1515/ceej-2017-0014.
• Popescu Mioara, 2017, "Modelling prediction of unemployment statistics using web technologies," HOLISTICA – Journal of Business and Public Administration, Sciendo, volume 8, issue 3, pages 55-60, December, DOI: 10.1515/hjbpa-2017-0023.
• Gurgul Henryk & Machno Artur, 2017, "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Statistics Poland, volume 18, issue 1, pages 91-114, March, DOI: 10.21307/stattrans-2016-059.
• Mateusz Buczyński & Marcin Chlebus, 2017, "Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(1,1), CAViaR and the historical simulation models ," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2017-29.