Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2017

• Sami Oinonen & Maritta Paloviita, 2017, "How Informative are Aggregated Inflation Expectations? Evidence from the ECB Survey of Professional Forecasters," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 13, issue 2, pages 139-163, November, DOI: 10.1007/s41549-017-0017-6.
• Amit K. Sinha & Philip A. Horvath & Robert C. Scott, 2017, "The real miss-specification in the forward rate premium puzzle," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 41, issue 3, pages 463-473, July, DOI: 10.1007/s12197-016-9363-9.
• Beatriz Vaz de Melo Mendes & Victor Bello Accioly, 2017, "Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 41, issue 4, pages 631-658, October, DOI: 10.1007/s12197-017-9386-x.
• Naoya Sueishi & Arihiro Yoshimura, 2017, "Focused Information Criterion for Series Estimation in Partially Linear Models," The Japanese Economic Review, Springer, volume 68, issue 3, pages 352-363, September, DOI: 10.1111/jere.12139.
• 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.
• Mckenzie,David J. & Sansone,Dario & Mckenzie,David J. & Sansone,Dario, 2017, "Man vs. machine in predicting successful entrepreneurs : evidence from a business plan competition in Nigeria," Policy Research Working Paper Series, The World Bank, number 8271, Dec.
• Christian Glocker & Philipp Wegmüller, 2017, "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers, WIFO, number 542, Oct.
• Florian Huber & Thomas Zörner, 2017, "Threshold cointegration and adaptive shrinkage," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp250, Jun.
• Huber, Florian & Zörner, Thomas, 2017, "Threshold cointegration and adaptive shrinkage," Department of Economics Working Paper Series, WU Vienna University of Economics and Business, number 250, Jun.
• Bruno Lanz & Simon Dietz & Timothy Swanson, 2017, "Global Population Growth, Technology, And Malthusian Constraints: A Quantitative Growth Theoretic Perspective," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 58, issue 3, pages 973-1006, August, DOI: 10.1111/iere.12242.
• Anders Warne & Günter Coenen & Kai Christoffel, 2017, "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 1, pages 103-119, January.
• Erik Kole & Dick Dijk, 2017, "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 1, pages 120-139, January.
• Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2017, "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 2, pages 275-295, March, DOI: 10.1002/jae.2510.
• Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2017, "Euromind‐ D : A Density Estimate of Monthly Gross Domestic Product for the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 3, pages 683-703, April.
• Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017, "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 4, pages 783-801, June.
• Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2017, "Have Standard VARS Remained Stable Since the Crisis?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 5, pages 931-951, August.
• Jack Fosten, 2017, "Model selection with estimated factors and idiosyncratic components," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 6, pages 1087-1106, September.
• Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017, "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 2, pages 109-121, March.
• Dirk Ulbricht & Konstantin A. Kholodilin & Tobias Thomas, 2017, "Do Media Data Help to Predict German Industrial Production?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 5, pages 483-496, August.
• Kirstin Hubrich & Frauke Skudelny, 2017, "Forecast Combination for Euro Area Inflation: A Cure in Times of Crisis?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 5, pages 515-540, August.
• Rangan Gupta & Eric Olson & Mark E. Wohar, 2017, "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 6, pages 640-650, September.
• Michael K Andersson & Ted Aranki & André Reslow, 2017, "Adjusting for information content when comparing forecast performance," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 7, pages 784-794, November.
• Manabu Asai & Michael McAleer, 2017, "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., volume 37, issue 11, pages 1141-1152, November.
• Edward S. Knotek & Saeed Zaman, 2017, "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, volume 49, issue 5, pages 931-968, August, DOI: 10.1111/jmcb.12401.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017, "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS), University of Warwick, Department of Economics, number 1145.
• Bartosz Uniejewski & Rafal Weron & Florian Ziel, 2017, "Variance stabilizing transformations for electricity spot price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/17/01, Feb.
• Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2017, "On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/17/02, May.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2017, "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/17/03, Jul.
• Dreher, Sandra & Eichfelder, Sebastian & Noth, Felix, 2017, "Predicting earnings and cash flows: The information content of losses and tax loss carryforwards," arqus Discussion Papers in Quantitative Tax Research, arqus - Arbeitskreis Quantitative Steuerlehre, number 224.
• Menden, Christian & Proaño, Christian R., 2017, "Dissecting the financial cycle with dynamic factor models," BERG Working Paper Series, Bamberg University, Bamberg Economic Research Group, number 126.
• Itkonen, Juha & Juvonen, Petteri, 2017, "Nowcasting the Finnish economy with a large Bayesian vector autoregressive model," BoF Economics Review, Bank of Finland, number 6/2017.
• Funke, Michael & Loermann, Julius & Tsang, Andrew, 2017, "The information content in the offshore Renminbi foreign-exchange option market: Analytics and implied USD/CNH densities," BOFIT Discussion Papers, Bank of Finland Institute for Emerging Economies (BOFIT), number 15/2017.
• Mikosch, Heiner & Solanko, Laura, 2017, "Should one follow movements in the oil price or in money supply? Forecasting quarterly GDP growth in Russia with higher-frequency indicators," BOFIT Discussion Papers, Bank of Finland Institute for Emerging Economies (BOFIT), number 19/2017.
• Bettendorf, Timo & Bursian, Dirk, 2017, "Chow-Lin x N: How adding a panel dimension can improve accuracy," Discussion Papers, Deutsche Bundesbank, number 12/2017.
• Götz, Thomas B. & Knetsch, Thomas A., 2017, "Google data in bridge equation models for German GDP," Discussion Papers, Deutsche Bundesbank, number 18/2017.
• Mokinski, Frieder, 2017, "A severity function approach to scenario selection," Discussion Papers, Deutsche Bundesbank, number 34/2017.
• Jang, Tae-Seok & Sacht, Stephen, 2017, "Modeling consumer confidence and its role for expectation formation: A horse race," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2017-04.
• Simionescu, Mihaela, 2017, "The Influence of Brexit on the Foreign Direct Investment Projects and Inflows in the United Kingdom," GLO Discussion Paper Series, Global Labor Organization (GLO), number 68.
• Simionescu, Mihaela, 2017, "Prediction intervals for inflation and unemployment rate in Romania. A Bayesian approach," GLO Discussion Paper Series, Global Labor Organization (GLO), number 82.
• Doll, Jens & Rosenthal, Beatrice & Volkenand, Jonas & Hamella, Sandra, 2017, "Nowcasting des deutschen BIP," Weidener Diskussionspapiere, University of Applied Sciences Amberg-Weiden (OTH), number 59.
• Coupé, Tom, 2017, "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics Discussion Papers, Kiel Institute for the World Economy, number 2017-76.
• Dreher, Sandra & Eichfelder, Sebastian & Noth, Felix, 2017, "Predicting earnings and cash flows: The information content of losses and tax loss carryforwards," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 30/2017.
• Heinisch, Katja & Scheufele, Rolf, 2017, "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 5/2017.
• Bershadskyy, Dmitri & Brautzsch, Hans-Ulrich & Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2017, "Die mittelfristige wirtschaftliche Entwicklung in Deutschland für die Jahre 2017 bis 2022 und finanzpolitische Optionen einer neuen Bundesregierung," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 5, issue 5, pages 138-145.
• Deschermeier, Philipp, 2017, "Bevölkerungsentwicklung in den deutschen Bundesländern bis 2035
  [Regional population development in Germany to 2035]," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 44, issue 3, pages 63-80, DOI: 10.2373/1864-810X.17-03-04.
• Haskamp, Ulrich, 2017, "Forecasting exchange rates: The time-varying relationship between exchange rates and Taylor rule fundamentals," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 704, DOI: 10.4419/86788818.
• Haskamp, Ulrich, 2017, "Improving the forecasts of European regional banks' profitability with machine learning algorithms," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 705, DOI: 10.4419/86788819.
• Prüser, Jan, 2017, "Forecasting US inflation using Markov dimension switching," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 710, DOI: 10.4419/86788828.
• Roesel, Felix, 2017, "The causal effect of wrong-hand drive vehicles on road safety," CEPIE Working Papers, Technische Universität Dresden, Center of Public and International Economics (CEPIE), number 15/17.
• Conrad, Christian, 2017, "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168200.
• Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017, "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168206.
• Knüppel, Malte & Krüger, Fabian, 2017, "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168294.
• Ksenija Dumicic & Berislav Zmuk & Anita Ceh Casni, 2017, "Evaluating forecasting models for unemployment rates by gender in selected european countries," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 15, issue 1, pages 16-35.
• William A. Barnett & Liting Su, 2017, "Financial Firm Production Of Inside Monetary And Credit Card Services: An Aggregation Theoretic Approach1," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 201707, Oct, revised Oct 2017.
• Mihály Ormos & Dusán Timotity, 2017, "Expected downside risk and asset prices: characteristics of emerging and developed European markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, volume 44, issue 3, pages 529-546, August, DOI: 10.1007/s10663-016-9329-3.
• Francesca Rondina, 2017, "An Econometric Learning Approach to Approximate Expectations in Empirical Macro Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, volume 23, issue 4, pages 437-438, November, DOI: 10.1007/s11294-017-9662-8.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2017, "On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test," International Economics and Economic Policy, Springer, volume 14, issue 4, pages 691-700, October, DOI: 10.1007/s10368-016-0357-z.
• Esteban Fernández-Vázquez & Blanca Moreno, 2017, "Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator," Journal of Geographical Systems, Springer, volume 19, issue 4, pages 349-370, October, DOI: 10.1007/s10109-017-0259-9.
• Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017, "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, volume 28, issue 1, pages 47-59, February, DOI: 10.1007/s11079-016-9408-x.
• Niels D. Gilbert & Jasper F.M. Jong, 2017, "Do European fiscal rules induce a bias in fiscal forecasts? Evidence from the Stability and Growth Pact," Public Choice, Springer, volume 170, issue 1, pages 1-32, January, DOI: 10.1007/s11127-016-0372-1.
• Jing Xu & Michelle Hallack & Miguel Vazquez, 2017, "Applying a third party access model for China’s gas pipeline network: an independent pipeline operator and congestion rent transfer," Journal of Regulatory Economics, Springer, volume 51, issue 1, pages 72-97, February, DOI: 10.1007/s11149-017-9316-z.
• Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017, "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, volume 49, issue 4, pages 949-971, November, DOI: 10.1007/s11156-016-0613-x.
• Chulwoo Han & Frank C. Park & Jangkoo Kang, 2017, "A geometric treatment of time-varying volatilities," Review of Quantitative Finance and Accounting, Springer, volume 49, issue 4, pages 1121-1141, November, DOI: 10.1007/s11156-017-0618-0.
• Byeongdeuk Jang & Young Se Kim, 2017, "Driving Forces of Inflation Expectations," Korean Economic Review, Korean Economic Association, volume 33, pages 207-237.
• Mihaela Simionescu, 2017, "The Impact Of Immigrants On The UK Economy," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 9, issue 2, pages 31-46, June.
• Mirel-Daniel Simionescu, 2017, "Determinants of Foreign Direct Investments in Bulgaria and Romania in the Context of Recent Economic Crisis," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 3, issue 1, pages 68-72, March.
• Iulian Lolea, 2017, "Where did the GARCH Models Perform Best in Terms of Volatility Forecasting? Equity vs. Commodities Markets," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 3, issue 3, pages 79-86, September.
• Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet Ali Soytas, 2017, "Exploring the Nexus between Inflation and Globalization under Inflation Targeting through the Lens of New Zealand’s Experience," Koç University-TUSIAD Economic Research Forum Working Papers, Koc University-TUSIAD Economic Research Forum, number 1709, Apr.
• Florian Chatagny & Christian Stettler, 2017, "Fiscal Fore casting in a Federal Country: Does Space Matter?," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, volume 11, issue 4, pages 51-60, December, DOI: 10.3929/ethz-a-005427569.
• Virág, Miklós & Nyitrai, Tamás, 2017, "Magyar vállalkozások felszámolásának előrejelzése pénzügyi mutatóik idősorai alapján
  [Predicting the liquidation of Hungarian firms using a time series of their financial ratios]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), volume 0, issue 3, pages 305-324, DOI: 10.18414/KSZ.2017.3.305.
• Ouael EL JEBARI & Abdelati HAKMAOUI, 2017, "Modeling persistence of volatility in the Moroccan exchange market using a fractionally integrated EGARCH," Turkish Economic Review, KSP Journals, volume 4, issue 4, pages 388-399, December.
• Ron W. NIELSEN, 2017, "Application of differential equations in projecting growth trajectories," Journal of Economics Bibliography, KSP Journals, volume 4, issue 3, pages 203-221, September.
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• Marisol Valencia Cárdenas & Juan Gabriel Vanegas López & Juan Carlos Correa Morales & Jorge Aníbal Restrepo Morales, 2017, "Comparing forecasts for tourism dynamics in Medellín, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 199-230, Enero - J, DOI: 10.17533/udea.le.n86a08.
• Anh Dinh Minh Nguyen, 2017, "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series, Bank of Lithuania, number 41, Mar.
• Michael McAleer & Xiao-Guang Yue, 2017, "Prediction of Gas Concentration Based on the Opposite Degree Algorithm," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 154-162.
• Aumnad Phdungsilp, 2017, "Projections of Energy Use and Carbon Emissions for Bangkok,Thailand," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 248-257.
• Narongdech Keeratipranon & Phatcharasak Phawanaphinyo, 2017, "Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 269-278.
• Lehmann, Robert & Wohlrabe, Klaus, 2017, "Boosting and regional economic forecasting: the case of Germany," Munich Reprints in Economics, University of Munich, Department of Economics, number 49919.
• Magdalena Petrovska & Gani Ramadani & Nikola Naumovski & Biljana Jovanovic, 2017, "Forecasting Macedonian Inflation: Evaluation of different models for short-term forecasting," Working Papers, National Bank of the Republic of North Macedonia, number 2017-06.
• Mohammad Reza Farzanegan & Mai Hassan, 2017, "The impact of economic globalization on the shadow economy in Egypt," MAGKS Papers on Economics, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung), number 201718.
• Radim Farana & Ivo Formánek & Cyril Klimeš & Bogdan Walek, 2017, "System Modelling and Decision Making System Based on Fuzzy Expert System," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, volume 3, issue 2, pages 118-122, DOI: 10.11118/ejobsat.v3i2.103.
• Aleksandra Hałka & Jacek Kotłowski, 2017, "Global or Domestic? Which Shocks Drive Inflation in European Small Open Economies?," Emerging Markets Finance and Trade, Taylor & Francis Journals, volume 53, issue 8, pages 1812-1835, August, DOI: 10.1080/1540496X.2016.1193001.
• Christoph Anders & Max Groneck, 2017, "The Optimal Portfolio of PAYG Benefits and Funded Pensions in Germany," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, volume 73, issue 3, pages 255-291, September, DOI: 10.1628/001522117X14915570953903.
• Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017, "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17006, Jan, DOI: 10.1016/j.jedc.2020.103853.
• Armagan Tuna Aktuna-Gunes & Okay Gunes, 2017, "Time Use Elasticity of Substitution Estimates Conditional on Working Time Available," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17016, Feb.
• Antoine Kornprobst, 2017, "Winning Investment Strategies Based on Financial Crisis Indicators," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17039, Sep, DOI: 10.48550/arXiv.1709.02701.
• Jørgen Vitting Andersen & Philippe de Peretti, 2017, "New method to detect convergence in simple multi-period market games," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17058, Dec.
• David T. Frazier & Gael M. Martin & Christian P. Robert & Judith Rousseau, 2017, "Asymptotic properties of approximate Bayesian computation," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 12/17.
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• Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017, "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 2/17.
• Souhaib Ben Taieb & James W. Taylor & Rob J. Hyndman, 2017, "Coherent Probabilistic Forecasts for Hierarchical Time Series," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 3/17.
• David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017, "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 9/17.
• Raïsa Basselier & David de Antonio Liedo & Geert Langenus,, 2017, "Nowcasting real economic activity in the euro area : Assessing the impact of qualitative surveys," Working Paper Research, National Bank of Belgium, number 331, Dec.
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• Andrés F. Barrientos & Alexander Bolton & Tom Balmat & Jerome P. Reiter & John M. de Figueiredo & Ashwin Machanavajjhala & Yan Chen & Charles Kneifel & Mark DeLong, 2017, "A Framework for Sharing Confidential Research Data, Applied to Investigating Differential Pay by Race in the U. S. Government," NBER Working Papers, National Bureau of Economic Research, Inc, number 23534, Jun.
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• Evgenia Vasileva, 2017, "Creating of Something from Nothing. Methodic. Applying the Principles of Chaos and Complex Systems in a Learning Environment," Nauchni trudove, University of National and World Economy, Sofia, Bulgaria, issue 2, pages 169-186, October.
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• Simionescu, Mihaela, 2017, "Forecast Intervals for US/EURO Foreign Exchange Rate || Intervalos de pronóstico para los tipos de cambio US/EURO," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, volume 23, issue 1, pages 257-271, Junio.
• Alonso, Julio César & Rivera, Andrés Felipe, 2017, "Pronosticando la inflación mensual en Colombia un paso hacia delante: una aproximación "de abajo hacia arriba" || Forecasting the Colombian Monthly Inflation One Step Ahead: A "Bottom to Top" Approach," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, volume 23, issue 1, pages 98-118, Junio.
• Caro, Norma Patricia & Arias, Ver—nica & Ortiz, Pablo, 2017, "Predicci—n de fracaso en empresas latinoamericanas utilizando el mŽtodo del vecino más cercano para predecir efectos aleatorios en modelos mixtos || Prediction of Failure in Latin-American Companies Using the Nearest-Neighbor Method to Predict Random," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, volume 24, issue 1, pages 5-24, Diciembre.
• Erdely, Arturo, 2017, "Value at Risk and the Diversification Dogma || Valor en riesgo y el dogma de la diversificación," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, volume 24, issue 1, pages 209-219, Diciembre.
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• Laura Liu, 2017, "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 17-006, Apr, revised 28 Apr 2017.
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• Blazej Mazur, 2017, "Probabilistic predictive analysis of business cycle fluctuations in Polish economy," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, volume 12, issue 3, pages 435-452, September, DOI: 10.24136/eq.v12i3.23.
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• Tomasz Berent & Boguslaw Blawat & Marek Dietl & Radoslaw Rejman, 2017, "Firms’ Default – from Prediction Accuracy to Informational Capacity of Predictors," Working Papers, Institute of Economic Research, number 158/2017, May, revised May 2017.
• Blazej Mazur, 2017, "Density Forecasts of Polish Industrial Production: a Probabilistic Perspective on Business Cycle Fluctuations," Working Papers, Institute of Economic Research, number 75/2017, May, revised May 2017.
• Nuhu Isah & Abdul Talib Bon, 2017, "Application of Markov Model in Crude Oil Price Forecasting," Traektoriâ Nauki = Path of Science, Altezoro, s.r.o. & Dialog, volume 3, issue 8(25), pages 1007-1012, August, DOI: 10.22178/pos.25-3.
• Ganna Gridina, 2017, "Фінансовий Лізинг: Проблеми Та Перспективи Розвитку В Україні
  [Financial Leasing: Problems and Prospects of Development in Ukraine]," Traektoriâ Nauki = Path of Science, Altezoro, s.r.o. & Dialog, volume 3, issue 9(26), pages 3019-3025, September, DOI: 10.22178/pos.26-2.
• Doojav, Gan-Ochir & Luvsannyam, Davaajargal, 2017, "Forecasting inflation in Mongolia: A dynamic model averaging approach," MPRA Paper, University Library of Munich, Germany, number 102602.
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