Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2017

• 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.
• 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.
• Evzen Kocenda & Karen Poghosyan, 2017, "Export sophistication: A dynamic panel data approach," KIER Working Papers, Kyoto University, Institute of Economic Research, number 980 Classification-C52; C, Nov.
• 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.
• 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.
• 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.
• Nithi Sopitpongstorn & Param Silvapulle & Jiti Gao, 2017, "Local logit regression for recovery rate," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 19/17.
• 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.
• Alessia Paccagnini, 2017, "Forecasting with FAVAR: macroeconomic versus financial factors," NBP Working Papers, Narodowy Bank Polski, number 256.
• Karol Szafranek, 2017, "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers, Narodowy Bank Polski, number 262.
• Hunt Allcott & Matthew Gentzkow, 2017, "Social Media and Fake News in the 2016 Election," NBER Working Papers, National Bureau of Economic Research, Inc, number 23089, Jan.
• Ulrich K. Müller & Mark W. Watson, 2017, "Long-Run Covariability," NBER Working Papers, National Bureau of Economic Research, Inc, number 23186, Feb.
• Jonathan M.V. Davis & Sara B. Heller, 2017, "Rethinking the Benefits of Youth Employment Programs: The Heterogeneous Effects of Summer Jobs," NBER Working Papers, National Bureau of Economic Research, Inc, number 23443, May.
• 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.
• Yuriy Gorodnichenko & Byoungchan Lee, 2017, "A Note on Variance Decomposition with Local Projections," NBER Working Papers, National Bureau of Economic Research, Inc, number 23998, Nov.
• Hom Nath Gaire, 2017, "Forecasting NEPSE Index: An ARIMA And GARCH Approach," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, volume 29, issue 1, pages 53-68, April.
• 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.
• Maria Chiara Cavalleri & Yvan Guillemette, 2017, "A revised approach to trend employment projections in long-term scenarios," OECD Economics Department Working Papers, OECD Publishing, number 1384, May, DOI: 10.1787/075f0153-en.
• Yvan Guillemette & Alexandre Kopoin & David Turner & Andrea De Mauro, 2017, "A revised approach to productivity convergence in long-term scenarios," OECD Economics Department Working Papers, OECD Publishing, number 1385, May, DOI: 10.1787/0b8947e3-en.
• Alberto Marino & David Morgan & Luca Lorenzoni & Chris James, 2017, "Future trends in health care expenditure: A modelling framework for cross-country forecasts," OECD Health Working Papers, OECD Publishing, number 95, Jun, DOI: 10.1787/247995bb-en.
• Niematallah Elamin & Mototsugu Fukushige, 2017, "Integrating judgment in statistical demand forecasting: An approach to confront uncertainty," Discussion Papers in Economics and Business, Osaka University, Graduate School of Economics, number 17-20, Jul.
• Niematallah Elamin & Mototsugu Fukushige, 2017, "Modeling and Forecasting Hourly Electricity Demand by SARIMAX with Interactions," Discussion Papers in Economics and Business, Osaka University, Graduate School of Economics, number 17-28, Sep.
• Robert A. Cord, 2017, "The London and Cambridge Economic Service: history and contributions," Cambridge Journal of Economics, Cambridge Political Economy Society, volume 41, issue 1, pages 307-326.
• João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017, "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, volume 15, issue 2, pages 247-285.
• Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017, "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, volume 15, issue 4, pages 649-677.
• Michael S. O’Doherty & N. E. Savin & Ashish Tiwari, 2017, "Hedge Fund Replication: A Model Combination Approach," Review of Finance, European Finance Association, volume 21, issue 4, pages 1767-1804.
• Frank J. Fabozzi & Ahmet K. Karagozoglu & Na Wang, 2017, "Effects of Spot Market Short-Sale Constraints on Index Futures Trading," Review of Finance, European Finance Association, volume 21, issue 5, pages 1975-2005.
• Christian Brownlees & Robert F. Engle, 2017, "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," The Review of Financial Studies, Society for Financial Studies, volume 30, issue 1, pages 48-79.
• Aivaz Kamer Ainur & Jugănaru Mariana & Jugănaru Ion Dănut, 2017, "The Seasonality in the Number of Overnight Stays by Residents in Romania and Bulgaria and Its Ranking in Connection to the EU Average Level," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 2, pages 355-360, December.
• Jugănaru Ion DănuÈ› & Aivaz Kamer Ainur & Jugănaru Mariana, 2017, "Comparative Assessments of the Seasonality in "The Total Number of Overnight Stays" in Romania, Bulgaria and the European Union," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 2, pages 95-100, December.
• 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.
• Rania Jammazi & Duc Khuong Nguyen, 2017, "Estimating and forecasting portfolio’s Value-at-Risk with wavelet-based extreme value theory: Evidence from crude oil prices and US exchange rates," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, volume 68, issue 11, pages 1352-1362, November, DOI: 10.1057/s41274-016-0133-z.
• Miguel Ataurima Arellano & Erika Collantes & Gabriel Rodriguez, 2017, "Empirical Modeling of Latin American Stock and Forex Markets Returns and Volatility using Markov-Switching GARCH Models," Documentos de Trabajo / Working Papers, Departamento de Economía - Pontificia Universidad Católica del Perú, number 2017-436.
• 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.
• Francis X. Diebold & Minchul Shin, 2017, "Beating the Simple Average: Egalitarian LASSO for Combining Economic Forecasts," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 17-017, Aug, revised 20 Aug 2017.
• 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.
• Tomasz Berent & Boguslaw Blawat & Marek Dietl & Przemyslaw Krzyk & Radoslaw Rejman, 2017, "Firm's default — new methodological approach and preliminary evidence from Poland," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, volume 12, issue 4, pages 753-773, December, DOI: 10.24136/eq.v12i4.39.
• 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.
• Fajar, Muhammad & Hartini, Sri, 2017, "Inflation forecasting by hybrid singular spectrum analysis – multilayer perceptrons neural network method, case of Indonesia," MPRA Paper, University Library of Munich, Germany, number 105100, Oct, revised 11 May 2018.
• Ngomba Bodi, Francis Ghislain & Bikai, Landry, 2017, "Prévisions de l’inflation et de la croissance en zone CEMAC
  [Inflation and real growth forecasts in CEMAC zone]," MPRA Paper, University Library of Munich, Germany, number 116433, Dec.
• Coble, David & Pincheira, Pablo, 2017, "Nowcasting Building Permits with Google Trends," MPRA Paper, University Library of Munich, Germany, number 76514, Feb.
• Cobb, Marcus P A, 2017, "Joint Forecast Combination of Macroeconomic Aggregates and Their Components," MPRA Paper, University Library of Munich, Germany, number 76556, Feb.
• Cobb, Marcus P A, 2017, "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper, University Library of Munich, Germany, number 76849, Feb.
• Pincheira, Pablo, 2017, "A Power Booster Factor for Out-of-Sample Tests of Predictability," MPRA Paper, University Library of Munich, Germany, number 77027, Feb.
• Tóth, Peter, 2017, "Nowcasting Slovak GDP by a Small Dynamic Factor Model," MPRA Paper, University Library of Munich, Germany, number 77245, Feb.
• BLINOV, Sergey, 2017, "Использование Взаимосвязи Между Ввп И Денежной Массой Для Экономического Прогнозирования
  [Economic Forecasting Based on the Relationship between GDP and Real Money Supply]," MPRA Paper, University Library of Munich, Germany, number 77475, Mar.
• Degiannakis, Stavros & Filis, George, 2017, "Forecasting oil prices," MPRA Paper, University Library of Munich, Germany, number 77531, Mar.
• Medel, Carlos A., 2017, "Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy," MPRA Paper, University Library of Munich, Germany, number 78439, Apr.
• BLINOV, Sergey, 2017, "Economic Forecasting Based on the Relationship between GDP and Real Money Supply," MPRA Paper, University Library of Munich, Germany, number 78717, Apr.
• Maheu, John M & Song, Yong, 2017, "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper, University Library of Munich, Germany, number 79211, May.
• Pyzhov, Vladislav & Pyzhov, Stanislav, 2017, "Comparison of methods of data mining techniques for the predictive accuracy," MPRA Paper, University Library of Munich, Germany, number 79326, May.
• Polman, Fabian M. & Krijgsman, Cees & Dajani, Karma & Hemminga, Marcus A., 2017, "Modelling a Dutch Pension Fund’s Capital Requirement for Longevity Risk," MPRA Paper, University Library of Munich, Germany, number 79438, May.
• Davis, Brent, 2017, "“Negative Political Advertising: It’s All in the Timing”," MPRA Paper, University Library of Munich, Germany, number 79449, May.
• Bhatt, Vipul & Kishor, Kundan & Marfatia, Hardik, 2017, "Estimating excess sensitivity and habit persistence in consumption using Greenbook forecast as an instrument," MPRA Paper, University Library of Munich, Germany, number 79748, Jun.
• Yang, Bill Huajian, 2017, "Smoothing Algorithms by Constrained Maximum Likelihood," MPRA Paper, University Library of Munich, Germany, number 79911, Jun.
• Yang, Bill Huajian, 2017, "Forward Ordinal Probability Models for Point-in-Time Probability of Default Term Structure," MPRA Paper, University Library of Munich, Germany, number 79934, Sep.
• Bisio, Laura & Moauro, Filippo, 2017, "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper, University Library of Munich, Germany, number 80211, Jul, revised 14 Jul 2017.
• Lindblad, Annika, 2017, "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper, University Library of Munich, Germany, number 80266, Jul.
• Kuusela, Annika & Hännikäinen, Jari, 2017, "What do the shadow rates tell us about future inflation?," MPRA Paper, University Library of Munich, Germany, number 80542, Aug.
• Yang, Bill Huajian, 2017, "Point-in-Time PD Term Structure Models with Loan Credit Quality as a Component," MPRA Paper, University Library of Munich, Germany, number 80641, Aug.
• Nelimarkka, Jaakko, 2017, "Evidence on News Shocks under Information Deficiency," MPRA Paper, University Library of Munich, Germany, number 80850, Aug.
• Fries, Sébastien & Zakoian, Jean-Michel, 2017, "Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles," MPRA Paper, University Library of Munich, Germany, number 81345, Sep.
• Cobb, Marcus P A, 2017, "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper, University Library of Munich, Germany, number 81585, Sep.
• Raihan, Tasneem, 2017, "Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty," MPRA Paper, University Library of Munich, Germany, number 82343, Oct.
• Svetunkov, Ivan & Boylan, John Edward, 2017, "Multiplicative state-space models for intermittent time series," MPRA Paper, University Library of Munich, Germany, number 82487, Nov.
• Hegadekatti, Kartik & S G, Yatish, 2017, "The Programmable Economy: Envisaging an Entire Planned Economic System as a Single Computer through Blockchain Networks," MPRA Paper, University Library of Munich, Germany, number 82831, Mar, revised 16 May 2017.
• Hassett, Kevin & Zhong, Weifeng, 2017, "On the Observational Implications of Knightian Uncertainty," MPRA Paper, University Library of Munich, Germany, number 82998, Oct.
• Brkic, Sabina & Hodzic, Migdat & Dzanic, Enis, 2017, "Fuzzy Logic Model of Soft Data Analysis for Corporate Client Credit Risk Assessment in Commercial Banking," MPRA Paper, University Library of Munich, Germany, number 83028, Nov, revised Nov 2017.
• Bucci, Andrea, 2017, "Forecasting realized volatility: a review," MPRA Paper, University Library of Munich, Germany, number 83232, Dec.
• Zeynalov, Ayaz, 2017, "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper, University Library of Munich, Germany, number 83268, Dec.
• Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017, "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper, University Library of Munich, Germany, number 83282, Feb.
• Lee, Seohyun, 2017, "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper, University Library of Munich, Germany, number 83617, Jul.
• Chhorn, Theara & Chaiboonsri, Chukiat, 2017, "Modelling and Forecasting Tourist Arrivals to Cambodia: An Application of ARIMA-GARCH Approach," MPRA Paper, University Library of Munich, Germany, number 83942, Dec, revised 27 Dec 2017.
• Tonnerre, Antoine, 2017, "Merger Simulations in the American Airline Industry," MPRA Paper, University Library of Munich, Germany, number 84395, Oct.
• Nguyen, Duc Khuong & Walther, Thomas, 2017, "Modeling and forecasting commodity market volatility with long-term economic and financial variables," MPRA Paper, University Library of Munich, Germany, number 84464, May, revised Jan 2018.
• Li, Longqing, 2017, "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper, University Library of Munich, Germany, number 85645, Feb.
• MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017, "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper, University Library of Munich, Germany, number 87545, Sep.
• Degiannakis, Stavros & Filis, George, 2017, "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper, University Library of Munich, Germany, number 96276.
• Christina Christou & Rangan Gupta & Fredj Jawadi, 2017, "Does Inequality Help in Forecasting Equity Premium in a Panel of G7 Countries?," Working Papers, University of Pretoria, Department of Economics, number 201720, Mar.
• Christian Pierdzioch & Rangan Gupta, 2017, "Uncertainty and Forecasts of U.S. Recessions," Working Papers, University of Pretoria, Department of Economics, number 201732, May.
• Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017, "Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data," Working Papers, University of Pretoria, Department of Economics, number 201739, May.
• Steven F. Koch, 2017, "Does the Equivalence Scale Matter? Equivalence and Out-of-Pocket Payments," Working Papers, University of Pretoria, Department of Economics, number 201746, Jun.
• Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2017, "The Role of Economic Uncertainty in Forecasting Exchange Rate Returns and Realized Volatility: Evidence from Quantile Predictive Regressions," Working Papers, University of Pretoria, Department of Economics, number 201774, Oct.
• Milan Fičura, 2017, "Forecasting Stock Market Realized Variance with Echo State Neural Networks," European Financial and Accounting Journal, Prague University of Economics and Business, volume 2017, issue 3, pages 145-155, DOI: 10.18267/j.efaj.193.
• Nikola Radivojevic & Jelena Jovovic, 2017, "Examining of Determinants of Non-Performing Loans," Prague Economic Papers, Prague University of Economics and Business, volume 2017, issue 3, pages 300-316, DOI: 10.18267/j.pep.615.
• Martina Miskolczi & Jitka Langhamrová, 2017, "Využití metody vícestavové demografie při analýze trhu práce
  [Utilization of Multistate Demography Method at the Labour Market Analysis]," Politická ekonomie, Prague University of Economics and Business, volume 2017, issue 1, pages 82-95, DOI: 10.18267/j.polek.1128.
• Jan Vlachý, 2017, "Analýza daňových systémů středoevropských zemí pomocí statistické simulace
  [An Analysis of Central European Tax Systems Using Statistical Simulation]," Politická ekonomie, Prague University of Economics and Business, volume 2017, issue 4, pages 410-423, DOI: 10.18267/j.polek.1152.
• Angus Deaton & Nancy Cartwright, 2017, "Understanding and misunderstanding randomized controlled trials," Working Papers, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing., number 2017-10, Oct.
• Antoine A. Djogbenou, 2017, "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper, Economics Department, Queen's University, number 1391, Oct.
• David Reifschneider & Peter Tulip, 2017, "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2017-01, Feb.
• Alain Kabundi & Asi Mbelu, 2017, "Estimating a timevarying financial conditions index for South Africa," Working Papers, South African Reserve Bank, number 8008, Sep.
• Michael P Clements & Ana Beatriz Galvao, 2017, "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2017-01, Jan.
• Emese Lazar & Ning Zhang, 2017, "Model Risk of Expected Shortfall," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2017-10, Nov.
• Piergiorgio Alessandri & Haroon Mumtaz, 2017, "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices, Review of Economic Dynamics, number 14-103.
• Piergiorgio Alessandri & Haroon Mumtaz, 2017, "Code and data files for "Financial conditions and density forecasts for US output and inflation"," Computer Codes, Review of Economic Dynamics, number 14-103, revised .
• Piergiorgio Alessandri & Haroon Mumtaz, 2017, "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, volume 24, pages 66-78, March, DOI: 10.1016/j.red.2017.01.003.
• Nina Boyarchenko & Domenico Giannone & Tobias Adrian, 2017, "Vulnerable Growth," 2017 Meeting Papers, Society for Economic Dynamics, number 1317.
• Simon M. Potter & Giorgio Topa & Wilbert van den Klaauv, 2017, "The Advantages of Probabilistic Survey Questions," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, volume 9, issue 1, pages 1-32, June.
• Gustavo Rodriguez & Jorge Davalos, 2017, "El Potencial de Comercio del Acuerdo Trans-Pacifico para el Peru, un enfoque Gravitacional," Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), volume 5, issue 2, pages 93-107, October, DOI: 10.5281/zenodo.7507073.
• Fornaro, Paolo & Luomaranta, Henri & Saarinen, Lauri, 2017, "Nowcasting Finnish Turnover Indexes Using Firm-Level Data," ETLA Working Papers, The Research Institute of the Finnish Economy, number 46, Jan.
• Elettra Agliardi & Thomas Alexopoulos & Christian Cech, 2017, "On the relationship between GHGs and Global Temperature Anomalies: Multi-level rolling analysis and Copula calibration," Working Paper series, Rimini Centre for Economic Analysis, number 17-05, Feb.
• Siddhartha Vadlamudi, 2017, "Stock Market Prediction using Machine Learning: A Systematic Literature Review," American Journal of Trade and Policy, Asian Business Consortium, volume 4, issue 3, pages 123-128.
• Sebastian Fossati, 2017, "Testing for State-Dependent Predictive Ability," Working Papers, University of Alberta, Department of Economics, number 2017-09, Sep.