Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2014

• Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014, "A Multi-Country Approach to Forecasting Output Growth Using PMIs," CESifo Working Paper Series, CESifo, number 5100.
• Robert Lehmann & Michael Weber, 2014, "Der Blick in die Glaskugel wird schärfer: EineEvaluation der Treffsicherheit der ifo DresdenKonjunkturprognosen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, volume 21, issue 03, pages 45-46, June.
• Steffen Henzel & Wolfgang Nierhaus & Timo Wollmershäuser, 2014, "Evaluation der ifo Konjunkturprognosen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, volume 67, issue 17, pages 43-45, September.
• Domenico Giannone & Francesca Monti & Lucrezia Reichlin, 2014, "Exploiting the monthly data-flow in structural forecasting," Discussion Papers, Centre for Macroeconomics (CFM), number 1416, Jun.
• Richard Harrison, 2014, "Estimating the Effects of Forward Guidance in Rational Expectations Models," Discussion Papers, Centre for Macroeconomics (CFM), number 1429, Nov.
• Ioana-Iuliana TOMULEASA, 2014, "The Soundness Of The Banking System During The Global Financial Crisis," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 3, pages 598-608, April.
• Frantisek Brazdik & Zuzana Humplova & Frantisek Kopriva, 2014, "Evaluating a Structural Model Forecast: Decomposition Approach," Research and Policy Notes, Czech National Bank, Research and Statistics Department, number 2014/02, Aug.
• Michal Franta & David Havrlant & Marek Rusnak, 2014, "Forecasting Czech GDP Using Mixed-Frequency Data Models," Working Papers, Czech National Bank, Research and Statistics Department, number 2014/08, Nov.
• Tomas Adam & Miroslav Plasil, 2014, "The Impact of Financial Variables on Czech Macroeconomic Developments: An Empirical Investigation," Working Papers, Czech National Bank, Research and Statistics Department, number 2014/11, Dec.
• Ignacio Lozano & Alexander Guar�n, 2014, "Banking Fragility in Colombia: An Empirical Analysis Based on Balance Sheets," Borradores de Economia, Banco de la Republica, number 11145, Mar.
• Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014, "Pron�sticos para una econom�a menos vol�til: El caso colombiano," Borradores de Economia, Banco de la Republica, number 11252, May.
• Wilmer Osvaldo Mart�nez-Rivera & Manuel Dario Hern�ndez-Bejarano & Juan Manuel Julio-Rom�n, 2014, "On Forecast Evaluation," Borradores de Economia, Banco de la Republica, number 11604, Jun.
• Luis F. Melo Velandia & Rub�n A. Loaiza Maya & Mauricio Villamizar-Villegas, 2014, "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks� Estimates," Borradores de Economia, Banco de la Republica, number 12323, Nov.
• Alexander Guarín & Andr�s Gonz�lez & Daphn� Skandalis & Daniela S�nchez, 2014, "An Early Warning Model for Predicting Credit Booms Using Macroeconomic Aggregates," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, volume 32, issue 73, pages 77-86, DOI: 10.1016/S0120-4483(14)70020-X.
• Ignacio Lozano & Alexander Guar�n, 2014, "Banking fragility in Colombia: An empirical analysis based on balance sheets," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, volume 32, issue 75, pages 48-63, DOI: 10.1016/j.espe.2014.10.001.
• Andrés Ramírez Hassan & Johnatan Cardona Jim�nez, 2014, "Which team will win the 2014 FIFA World Cup? A Bayesian approach for dummies," Documentos de Trabajo de Valor Público, Universidad EAFIT, number 10898, Feb.
• Andrés Ramírez Hassan & Jhonatan Cardona Jim�nez & Raul Pericchi Guerra, 2014, "What is the effect of sample and prior distributions on a Bayesian autoregressive linear model? An application to piped water consumption," Documentos de Trabajo de Valor Público, Universidad EAFIT, number 12434, Jul.
• Silvia Bou Ysas & Magda Cay�n Costa & Albert Hern�ndez, 2014, "Análisis de la heurística en la contratación empresarial a través de una cartera de derivados reales," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, volume 6, issue 1, pages 73-94.
• Wilmer Javier Ríos Pinerez & Carlos Andr�s Yanes Guerra, 2014, "Duration Models to Evaluate First Employment Law’s Impact in Colombia," Documentos de Trabajo, Universidad Católica de Colombia, number 12417, Nov.
• G.A. Meagher & Felicity Pang & R.A. Wilson, 2014, "Interfacing a CGE Labour Market Model with the E3ME Multi-Sector Macroeconomic Model," Centre of Policy Studies/IMPACT Centre Working Papers, Victoria University, Centre of Policy Studies/IMPACT Centre, number g-248, Sep.
• G.A. Meagher & R.A.Wilson & E.Yerushalmi, 2014, "Emerging Structural Pressures in European Labour Markets," Centre of Policy Studies/IMPACT Centre Working Papers, Victoria University, Centre of Policy Studies/IMPACT Centre, number g-249, Sep.
• BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014, "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE), number 2641, Jan.
• Joris de Wind & Luca Gambetti, 2014, "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper, CPB Netherlands Bureau for Economic Policy Analysis, number 270, Mar.
• Joris de Wind, 2014, "Time variation in the dynamic effects of unanticipated changes in tax policy," CPB Discussion Paper, CPB Netherlands Bureau for Economic Policy Analysis, number 271, Mar.
• Kolasa, Marcin & Rubaszek, Michał, 2014, "Forecasting with DSGE models with financial frictions," Dynare Working Papers, CEPREMAP, number 40, Jun.
• Dorota Ewa Grochowina, 2014, "The Influence of Data Imputation Methods on the Classification Efficiency of the Logit Model Used for Forecasting the Bankruptcy of Companies," Acta Universitatis Nicolai Copernici, Ekonomia, Uniwersytet Mikolaja Kopernika, volume 45, issue 2, pages 187-203.
• Taylor, Mark & Hsu, Po-Hsuan, 2014, "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10018, Jun.
• Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2014, "Are there Gains from Pooling Real-Time Oil Price Forecasts?," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10075, Jul.
• Timmermann, Allan & Pettenuzzo, Davide & Valkanov, Rossen, 2014, "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10160, Sep.
• Kilian, Lutz & Baumeister, Christiane, 2014, "A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10162, Sep.
• Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014, "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10168, Sep.
• Ghysels, Eric & Ball, Ryan & Zhou, Huan, 2014, "Can we Automate Earnings Forecasts and Beat Analysts?," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10186, Oct.
• Giacomini, Raffaella, 2014, "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10201, Oct.
• Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014, "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 10272, Nov.
• Marcellino, Massimiliano & Foroni, Claudia, 2014, "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 9815, Feb.
• Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014, "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 9848, Mar.
• Kilian, Lutz & Inoue, Atsushi, 2014, "Joint Confidence Sets for Structural Impulse Responses," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 9892, Mar.
• Giannone, Domenico & Banbura, Marta & Lenza, Michele, 2014, "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 9931, Apr.
• Mario Coccia & Lili Wang, 2014, "Path-breaking directions of nanotechnology-based chemotherapy and molecular cancer therapy," CERIS Working Paper, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY, number 201401, Feb.
• Andrea Monticini & Francesco Ravazzolo, 2014, "Forecasting the intraday market price of money," DISCE - Working Papers del Dipartimento di Economia e Finanza, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE), number def010, Feb.
• Grané Chávez, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014, "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number ws140503, Feb.
• Antonis Michis, 2014, "Time Scale Evaluation of Economic Forecasts," Working Papers, Central Bank of Cyprus, number 2014-1, Feb.
• Konstantin A. Kholodilin & Dirk Ulbricht, 2014, "Mietpreisbremse: Wohnungsmarktregulierung bringt mehr Schaden als Nutzen," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 81, issue 15, pages 319-327.
• Corporate author, 2014, "Von einer Explosion der Mieten kann keine Rede sein: Sechs Fragen an Konstantin Kholodilin," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 81, issue 15, pages 328-328.
• Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2014, "Stark steigende Immobilienpreise in Deutschland: aber keine gesamtwirtschaftlich riskante Spekulationsblase," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 81, issue 47, pages 1231-1240.
• Konstantin A. Kholodilin & Boriss Siliverstovs, 2014, "Business Confidence and Forecasting of Housing Prices and Rents in Large German Cities," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1360.
• Konstantin A. Kholodilin & Tobias Thomas & Dirk Ulbricht, 2014, "Do Media Data Help to Predict German Industrial Production?," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1393.
• Guglielmo Maria Caporale & Marinko Skare, 2014, "Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1395.
• Johannes Mayr & Dirk Ulbricht, 2014, "Log versus Level in VAR Forecasting: 42 Million Empirical Answers - Expect the Unexpected," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1412.
• Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2014, "Speculative Price Bubbles in Urban Housing Markets in Germany," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1417.
• Michalski , Tomasz & Amat , Christophe, 2014, "Fundamentals and Exchange Rate Forecastability with Machine Learning Methods," HEC Research Papers Series, HEC Paris, number 1049, Aug.
• Marta Bañbura & Domenico Giannone & Michèle Lenza, 2014, "Conditional Forecasts and Scenario Analysis with Vector Autoregressions for Large Cross-Sections," Working Papers ECARES, ULB -- Universite Libre de Bruxelles, number ECARES 2014-15, Mar.
• Krylova, Elizaveta & Darracq Pariès, Matthieu & Moccero, Diego & Marchini, Claudia, 2014, "The retail bank interest rate pass-through: The case of the euro area during the financial and sovereign debt crisis," Occasional Paper Series, European Central Bank, number 155, Sep.
• Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2014, "Does the federal reserve staff still beat private forecasters?," Working Paper Series, European Central Bank, number 1635, Feb.
• Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2014, "Density characteristics and density forecast performance: a panel analysis," Working Paper Series, European Central Bank, number 1679, May.
• Onorante, Luca & Alessi, Lucia & Ghysels, Eric & Potter, Simon & Peach, Richard, 2014, "Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences," Working Paper Series, European Central Bank, number 1688, Jul.
• Dées, Stéphane & Güntner, Jochen, 2014, "Analysing and forecasting price dynamics across euro area countries and sectors: a panel VAR approach," Working Paper Series, European Central Bank, number 1724, Aug.
• Giannone, Domenico & Bańbura, Marta & Lenza, Michele, 2014, "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," Working Paper Series, European Central Bank, number 1733, Sep.
• Van Robays, Ine & Belu Mănescu, Cristiana, 2014, "Forecasting the Brent oil price: addressing time-variation in forecast performance," Working Paper Series, European Central Bank, number 1735, Sep.
• Girish Godekere Panchakshara Murthy & Vijayalakshmi Sedidi, 2014, "Forecasting Electricity Prices in Deregulated Wholesale Spot Electricity Market: A Review," International Journal of Energy Economics and Policy, Econjournals, volume 4, issue 1, pages 32-42.
• Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2014, "Exchange Rate Predictability in a Changing World," SIRE Discussion Papers, Scottish Institute for Research in Economics (SIRE), number 2014-021, Feb.
• Korobilis, Dimitris, 2014, "Data-based priors for vector autoregressions with drifting coefficients," SIRE Discussion Papers, Scottish Institute for Research in Economics (SIRE), number 2014-022, Jan.
• Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2014, "On the Sources of Uncertainty in Exchange Rate Predictability," SIRE Discussion Papers, Scottish Institute for Research in Economics (SIRE), number 2015-24, Sep.
• Caporin, Massimiliano & McAleer, Michael, 2014, "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, volume 76, issue C, pages 172-185, DOI: 10.1016/j.csda.2012.05.012.
• Audrino, Francesco, 2014, "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, volume 76, issue C, pages 43-60, DOI: 10.1016/j.csda.2013.06.002.
• Nyberg, Henri & Saikkonen, Pentti, 2014, "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, volume 76, issue C, pages 536-555, DOI: 10.1016/j.csda.2013.10.014.
• Aielli, Gian Piero & Caporin, Massimiliano, 2014, "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, volume 76, issue C, pages 556-576, DOI: 10.1016/j.csda.2013.01.029.
• Guillén, Osmani Teixeira de Carvalho & Issler, João Victor & Franco-Neto, Afonso Arinos de Mello, 2014, "On the welfare costs of business-cycle fluctuations and economic-growth variation in the 20th century and beyond," Journal of Economic Dynamics and Control, Elsevier, volume 39, issue C, pages 62-78, DOI: 10.1016/j.jedc.2013.11.008.
• Lee, Yongwoong & Poon, Ser-Huang, 2014, "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, volume 41, issue C, pages 69-92, DOI: 10.1016/j.jedc.2014.02.008.
• Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014, "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, volume 48, issue C, pages 79-94, DOI: 10.1016/j.jedc.2014.08.021.
• Claveria, Oscar & Torra, Salvador, 2014, "Forecasting tourism demand to Catalonia: Neural networks vs. time series models," Economic Modelling, Elsevier, volume 36, issue C, pages 220-228, DOI: 10.1016/j.econmod.2013.09.024.
• Todorova, Neda & Souček, Michael, 2014, "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, volume 36, issue C, pages 332-340, DOI: 10.1016/j.econmod.2013.10.003.
• Ferrara, Laurent & Marsilli, Clément & Ortega, Juan-Pablo, 2014, "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Economic Modelling, Elsevier, volume 36, issue C, pages 44-50, DOI: 10.1016/j.econmod.2013.08.042.
• Garratt, Anthony & Mise, Emi, 2014, "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, volume 37, issue C, pages 32-40, DOI: 10.1016/j.econmod.2013.10.017.
• Higgins, Matthew L. & Mishra, Sagarika, 2014, "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Economic Modelling, Elsevier, volume 38, issue C, pages 627-632, DOI: 10.1016/j.econmod.2014.02.016.
• Aubry, Mathilde & Renou-Maissant, Patricia, 2014, "Semiconductor industry cycles: Explanatory factors and forecasting," Economic Modelling, Elsevier, volume 39, issue C, pages 221-231, DOI: 10.1016/j.econmod.2014.02.039.
• Li, Qian & Bao, Liang, 2014, "Enhanced index tracking with multiple time-scale analysis," Economic Modelling, Elsevier, volume 39, issue C, pages 282-292, DOI: 10.1016/j.econmod.2014.03.009.
• Akram, Q. Farooq, 2014, "Macro effects of capital requirements and macroprudential policy," Economic Modelling, Elsevier, volume 42, issue C, pages 77-93, DOI: 10.1016/j.econmod.2014.05.033.
• Gupta, Rangan & Hammoudeh, Shawkat & Kim, Won Joong & Simo-Kengne, Beatrice D., 2014, "Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals, financial stress and economic uncertainty," The North American Journal of Economics and Finance, Elsevier, volume 28, issue C, pages 170-189, DOI: 10.1016/j.najef.2014.02.003.
• Hunzinger, Chadd B. & Labuschagne, Coenraad C.A., 2014, "The Cox, Ross and Rubinstein tree model which includes counterparty credit risk and funding costs," The North American Journal of Economics and Finance, Elsevier, volume 29, issue C, pages 200-217, DOI: 10.1016/j.najef.2014.06.002.
• Demiralay, Sercan & Ulusoy, Veysel, 2014, "Non-linear volatility dynamics and risk management of precious metals," The North American Journal of Economics and Finance, Elsevier, volume 30, issue C, pages 183-202, DOI: 10.1016/j.najef.2014.10.002.
• Michis, Antonis A., 2014, "Time scale evaluation of economic forecasts," Economics Letters, Elsevier, volume 123, issue 3, pages 279-281, DOI: 10.1016/j.econlet.2014.03.002.
• Berardi, Michele & Galimberti, Jaqueson K., 2014, "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, volume 124, issue 1, pages 104-107, DOI: 10.1016/j.econlet.2014.04.028.
• Cheong, Chongcheul & Lee, Hyunchul, 2014, "Forecasting with a parsimonious subset VAR model," Economics Letters, Elsevier, volume 125, issue 2, pages 167-170, DOI: 10.1016/j.econlet.2014.08.027.
• Matheson, Troy & Stavrev, Emil, 2014, "News and monetary shocks at a high frequency: A simple approach," Economics Letters, Elsevier, volume 125, issue 2, pages 282-286, DOI: 10.1016/j.econlet.2014.09.021.
• Kalli, Maria & Griffin, Jim E., 2014, "Time-varying sparsity in dynamic regression models," Journal of Econometrics, Elsevier, volume 178, issue 2, pages 779-793, DOI: 10.1016/j.jeconom.2013.10.012.
• Jensen, Mark J. & Maheu, John M., 2014, "Estimating a semiparametric asymmetric stochastic volatility model with a Dirichlet process mixture," Journal of Econometrics, Elsevier, volume 178, issue P3, pages 523-538, DOI: 10.1016/j.jeconom.2013.08.018.
• Chen, Ying & Niu, Linlin, 2014, "Adaptive dynamic Nelson–Siegel term structure model with applications," Journal of Econometrics, Elsevier, volume 180, issue 1, pages 98-115, DOI: 10.1016/j.jeconom.2014.02.009.
• Corradi, Valentina & Swanson, Norman R., 2014, "Testing for structural stability of factor augmented forecasting models," Journal of Econometrics, Elsevier, volume 182, issue 1, pages 100-118, DOI: 10.1016/j.jeconom.2014.04.011.
• Giacomini, Raffaella & Ragusa, Giuseppe, 2014, "Theory-coherent forecasting," Journal of Econometrics, Elsevier, volume 182, issue 1, pages 145-155, DOI: 10.1016/j.jeconom.2014.04.014.
• Gonçalves, Sílvia & Perron, Benoit, 2014, "Bootstrapping factor-augmented regression models," Journal of Econometrics, Elsevier, volume 182, issue 1, pages 156-173, DOI: 10.1016/j.jeconom.2014.04.015.
• Granziera, Eleonora & Hubrich, Kirstin & Moon, Hyungsik Roger, 2014, "A predictability test for a small number of nested models," Journal of Econometrics, Elsevier, volume 182, issue 1, pages 174-185, DOI: 10.1016/j.jeconom.2014.04.016.
• Lee, Tae-Hwy & Tu, Yundong & Ullah, Aman, 2014, "Nonparametric and semiparametric regressions subject to monotonicity constraints: Estimation and forecasting," Journal of Econometrics, Elsevier, volume 182, issue 1, pages 196-210, DOI: 10.1016/j.jeconom.2014.04.018.
• Chen, Yu-chin & Turnovsky, Stephen J. & Zivot, Eric, 2014, "Forecasting inflation using commodity price aggregates," Journal of Econometrics, Elsevier, volume 183, issue 1, pages 117-134, DOI: 10.1016/j.jeconom.2014.06.013.
• Koop, Gary & Korobilis, Dimitris, 2014, "A new index of financial conditions," European Economic Review, Elsevier, volume 71, issue C, pages 101-116, DOI: 10.1016/j.euroecorev.2014.07.002.
• Amado, Cristina & Teräsvirta, Timo, 2014, "Modelling changes in the unconditional variance of long stock return series," Journal of Empirical Finance, Elsevier, volume 25, issue C, pages 15-35, DOI: 10.1016/j.jempfin.2013.09.003.
• Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014, "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, volume 29, issue C, pages 113-128, DOI: 10.1016/j.jempfin.2014.08.002.
• Baillie, Richard T. & Kapetanios, George & Papailias, Fotis, 2014, "Bandwidth selection by cross-validation for forecasting long memory financial time series," Journal of Empirical Finance, Elsevier, volume 29, issue C, pages 129-143, DOI: 10.1016/j.jempfin.2014.04.002.
• Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014, "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, volume 29, issue C, pages 207-229, DOI: 10.1016/j.jempfin.2014.06.008.
• Monticini, Andrea & Ravazzolo, Francesco, 2014, "Forecasting the intraday market price of money," Journal of Empirical Finance, Elsevier, volume 29, issue C, pages 304-315, DOI: 10.1016/j.jempfin.2014.08.006.
• Lin, Chu-Hsiung & Changchien, Chang-Cheng & Kao, Tzu-Chuan & Kao, Wei-Shun, 2014, "High-order moments and extreme value approach for value-at-risk," Journal of Empirical Finance, Elsevier, volume 29, issue C, pages 421-434, DOI: 10.1016/j.jempfin.2014.10.001.
• Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014, "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, volume 42, issue C, pages 152-160, DOI: 10.1016/j.eneco.2013.12.014.
• Zolotko, Mikhail & Okhrin, Ostap, 2014, "Modelling the general dependence between commodity forward curves," Energy Economics, Elsevier, volume 43, issue C, pages 284-296, DOI: 10.1016/j.eneco.2014.02.019.
• Lisi, Francesco & Nan, Fany, 2014, "Component estimation for electricity prices: Procedures and comparisons," Energy Economics, Elsevier, volume 44, issue C, pages 143-159, DOI: 10.1016/j.eneco.2014.03.018.
• Hahn, Warren J. & DiLellio, James A. & Dyer, James S., 2014, "What do market-calibrated stochastic processes indicate about the long-term price of crude oil?," Energy Economics, Elsevier, volume 44, issue C, pages 212-221, DOI: 10.1016/j.eneco.2014.04.007.
• Chen, Shiyi & Golley, Jane, 2014, "‘Green’ productivity growth in China's industrial economy," Energy Economics, Elsevier, volume 44, issue C, pages 89-98, DOI: 10.1016/j.eneco.2014.04.002.
• An, Lian & Jin, Xiaoze & Ren, Xiaomei, 2014, "Are the macroeconomic effects of oil price shock symmetric?: A Factor-Augmented Vector Autoregressive approach," Energy Economics, Elsevier, volume 45, issue C, pages 217-228, DOI: 10.1016/j.eneco.2014.06.003.
• Yu, Lean & Zhao, Yang & Tang, Ling, 2014, "A compressed sensing based AI learning paradigm for crude oil price forecasting," Energy Economics, Elsevier, volume 46, issue C, pages 236-245, DOI: 10.1016/j.eneco.2014.09.019.
• Nowotarski, Jakub & Raviv, Eran & Trück, Stefan & Weron, Rafał, 2014, "An empirical comparison of alternative schemes for combining electricity spot price forecasts," Energy Economics, Elsevier, volume 46, issue C, pages 395-412, DOI: 10.1016/j.eneco.2014.07.014.
• Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2014, "Are there gains from pooling real-time oil price forecasts?," Energy Economics, Elsevier, volume 46, issue S1, pages 33-43, DOI: 10.1016/j.eneco.2014.08.008.
• Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014, "Forecasting the oil–gasoline price relationship: Do asymmetries help?," Energy Economics, Elsevier, volume 46, issue S1, pages 44-56, DOI: 10.1016/j.eneco.2014.08.006.
• Simlai, Prodosh, 2014, "Persistence of ex-ante volatility and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, volume 33, issue C, pages 253-261, DOI: 10.1016/j.irfa.2014.03.002.
• Kumar, Dilip & Maheswaran, S., 2014, "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, volume 34, issue C, pages 166-176, DOI: 10.1016/j.irfa.2014.06.002.
• Batten, Jonathan A. & Jacoby, Gady & Liao, Rose C., 2014, "Corporate yield spreads and real interest rates," International Review of Financial Analysis, Elsevier, volume 34, issue C, pages 89-100, DOI: 10.1016/j.irfa.2014.05.009.
• Todorova, Neda & Souček, Michael, 2014, "Overnight information flow and realized volatility forecasting," Finance Research Letters, Elsevier, volume 11, issue 4, pages 420-428, DOI: 10.1016/j.frl.2014.07.001.
• Hong, Han & Huang, Jing-Zhi & Wu, Deming, 2014, "The information content of Basel III liquidity risk measures," Journal of Financial Stability, Elsevier, volume 15, issue C, pages 91-111, DOI: 10.1016/j.jfs.2014.09.003.
• Pešta, Michal & Okhrin, Ostap, 2014, "Conditional least squares and copulae in claims reserving for a single line of business," Insurance: Mathematics and Economics, Elsevier, volume 56, issue C, pages 28-37, DOI: 10.1016/j.insmatheco.2014.02.007.
• Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014, "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 30, issue C, pages 21-54, DOI: 10.1016/j.intfin.2014.01.006.
• Caporin, Massimiliano & Jimenez-Martin, Juan-Angel & Gonzalez-Serrano, Lydia, 2014, "Currency hedging strategies in strategic benchmarks and the global and Euro sovereign financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 31, issue C, pages 159-177, DOI: 10.1016/j.intfin.2014.03.015.
• Ye, George L., 2014, "The interactions between China and US stock markets: New perspectives," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 31, issue C, pages 331-342, DOI: 10.1016/j.intfin.2014.04.008.
• Gupta, Rangan & Hammoudeh, Shawkat & Modise, Mampho P. & Nguyen, Duc Khuong, 2014, "Can economic uncertainty, financial stress and consumer sentiments predict U.S. equity premium?," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 33, issue C, pages 367-378, DOI: 10.1016/j.intfin.2014.09.004.
• Luciani, Matteo, 2014, "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, volume 30, issue 1, pages 20-29, DOI: 10.1016/j.ijforecast.2013.05.001.
• Martinsen, Kjetil & Ravazzolo, Francesco & Wulfsberg, Fredrik, 2014, "Forecasting macroeconomic variables using disaggregate survey data," International Journal of Forecasting, Elsevier, volume 30, issue 1, pages 65-77, DOI: 10.1016/j.ijforecast.2013.02.003.
• Rombouts, Jeroen & Stentoft, Lars & Violante, Franceso, 2014, "The value of multivariate model sophistication: An application to pricing Dow Jones Industrial Average options," International Journal of Forecasting, Elsevier, volume 30, issue 1, pages 78-98, DOI: 10.1016/j.ijforecast.2013.07.006.
• Clements, Michael P., 2014, "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, volume 30, issue 1, pages 99-117, DOI: 10.1016/j.ijforecast.2013.07.010.
• Capistrán, Carlos & López-Moctezuma, Gabriel, 2014, "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, volume 30, issue 2, pages 177-191, DOI: 10.1016/j.ijforecast.2013.07.016.
• Wang, Yiyao & Lee, Tae-Hwy, 2014, "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, volume 30, issue 2, pages 235-245, DOI: 10.1016/j.ijforecast.2013.07.017.
• Knüppel, Malte, 2014, "Efficient estimation of forecast uncertainty based on recent forecast errors," International Journal of Forecasting, Elsevier, volume 30, issue 2, pages 257-267, DOI: 10.1016/j.ijforecast.2013.08.004.
• Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014, "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, volume 30, issue 2, pages 268-279, DOI: 10.1016/j.ijforecast.2013.07.012.
• Bräuning, Falk & Koopman, Siem Jan, 2014, "Forecasting macroeconomic variables using collapsed dynamic factor analysis," International Journal of Forecasting, Elsevier, volume 30, issue 3, pages 572-584, DOI: 10.1016/j.ijforecast.2013.03.004.
• Kock, Anders Bredahl & Teräsvirta, Timo, 2014, "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, volume 30, issue 3, pages 616-631, DOI: 10.1016/j.ijforecast.2013.01.003.
• Giannone, Domenico & Lenza, Michele & Momferatou, Daphne & Onorante, Luca, 2014, "Short-term inflation projections: A Bayesian vector autoregressive approach," International Journal of Forecasting, Elsevier, volume 30, issue 3, pages 635-644, DOI: 10.1016/j.ijforecast.2013.01.012.
• Andrade, Philippe & Fourel, Valère & Ghysels, Eric & Idier, Julien, 2014, "The financial content of inflation risks in the euro area," International Journal of Forecasting, Elsevier, volume 30, issue 3, pages 648-659, DOI: 10.1016/j.ijforecast.2013.02.004.
• Rossi, Barbara & Sekhposyan, Tatevik, 2014, "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, volume 30, issue 3, pages 662-682, DOI: 10.1016/j.ijforecast.2013.03.005.
• Weron, Rafał, 2014, "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, volume 30, issue 4, pages 1030-1081, DOI: 10.1016/j.ijforecast.2014.08.008.
• Golinelli, Roberto & Parigi, Giuseppe, 2014, "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, volume 30, issue 4, pages 847-862, DOI: 10.1016/j.ijforecast.2014.01.008.
• Bekiros, Stelios D., 2014, "Exchange rates and fundamentals: Co-movement, long-run relationships and short-run dynamics," Journal of Banking & Finance, Elsevier, volume 39, issue C, pages 117-134, DOI: 10.1016/j.jbankfin.2013.11.007.
• Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2014, "Modeling and predicting the CBOE market volatility index," Journal of Banking & Finance, Elsevier, volume 40, issue C, pages 1-10, DOI: 10.1016/j.jbankfin.2013.11.004.
• Taylor, Nick, 2014, "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, volume 40, issue C, pages 286-302, DOI: 10.1016/j.jbankfin.2013.12.004.
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• Temesvary, Judit, 2014, "The determinants of U.S. banks’ international activities," Journal of Banking & Finance, Elsevier, volume 44, issue C, pages 233-247, DOI: 10.1016/j.jbankfin.2014.04.014.
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• Kalotychou, Elena & Staikouras, Sotiris K. & Zhao, Gang, 2014, "The role of correlation dynamics in sector allocation," Journal of Banking & Finance, Elsevier, volume 48, issue C, pages 1-12, DOI: 10.1016/j.jbankfin.2014.06.025.
• Ziggel, Daniel & Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2014, "A new set of improved Value-at-Risk backtests," Journal of Banking & Finance, Elsevier, volume 48, issue C, pages 29-41, DOI: 10.1016/j.jbankfin.2014.07.005.
• Filipova, Kameliya & Audrino, Francesco & De Giorgi, Enrico, 2014, "Monetary policy regimes: Implications for the yield curve and bond pricing," Journal of Financial Economics, Elsevier, volume 113, issue 3, pages 427-454, DOI: 10.1016/j.jfineco.2014.05.006.
• Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2014, "Sticky prices or economically-linked economies: The case of forecasting the Chinese stock market," Journal of International Money and Finance, Elsevier, volume 41, issue C, pages 95-109, DOI: 10.1016/j.jimonfin.2013.11.001.
• Ince, Onur, 2014, "Forecasting exchange rates out-of-sample with panel methods and real-time data," Journal of International Money and Finance, Elsevier, volume 43, issue C, pages 1-18, DOI: 10.1016/j.jimonfin.2013.12.004.
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• Urasawa, Satoshi, 2014, "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, volume 34, issue C, pages 116-134, DOI: 10.1016/j.jjie.2014.05.005.
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• Paredes, Joan & Pedregal, Diego J. & Pérez, Javier J., 2014, "Fiscal policy analysis in the euro area: Expanding the toolkit," Journal of Policy Modeling, Elsevier, volume 36, issue 5, pages 800-823, DOI: 10.1016/j.jpolmod.2014.07.003.
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• Zietz, Joachim & Traian, Anca, 2014, "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, volume 54, issue 2, pages 271-281, DOI: 10.1016/j.qref.2013.12.004.
• Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014, "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, volume 54, issue 2, pages 292-305, DOI: 10.1016/j.qref.2014.01.002.
• Presno, María José & Landajo, Manuel & Fernández, Paula, 2014, "Non-renewable resource prices: A robust evaluation from the stationarity perspective," Resource and Energy Economics, Elsevier, volume 36, issue 2, pages 394-416, DOI: 10.1016/j.reseneeco.2014.01.003.
• Tsuchiya, Yoichi, 2014, "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, volume 29, issue C, pages 599-618, DOI: 10.1016/j.iref.2013.09.002.
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• Kumar, Dilip & Maheswaran, S., 2014, "A new approach to model and forecast volatility based on extreme value of asset prices," International Review of Economics & Finance, Elsevier, volume 33, issue C, pages 128-140, DOI: 10.1016/j.iref.2014.04.001.
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• Alessandro Olivo, 2014, "Inference Under Weak or Partial Identification," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 57, issue 1, pages 54-80.
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• Patrick Doupe, 2014, "The Costs of Error in Setting Reference Rates for Reduced Deforestation," CCEP Working Papers, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University, number 1415, Aug.
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• Mehmet Balcilar & Rangan Gupta & Charl Jooste, 2014, "The Role of Economic Policy Uncertainty in Forecasting US Inflation Using a VARFIMA Model," Working Papers, Eastern Mediterranean University, Department of Economics, number 15-12.
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