Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2014

• 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.
• Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014, "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, volume 40, issue C, pages 321-329, DOI: 10.1016/j.jbankfin.2013.12.009.
• Cordis, Adriana S. & Kirby, Chris, 2014, "Discrete stochastic autoregressive volatility," Journal of Banking & Finance, Elsevier, volume 43, issue C, pages 160-178, DOI: 10.1016/j.jbankfin.2014.03.020.
• Zieling, Daniel & Mahayni, Antje & Balder, Sven, 2014, "Performance evaluation of optimized portfolio insurance strategies," Journal of Banking & Finance, Elsevier, volume 43, issue C, pages 212-225, DOI: 10.1016/j.jbankfin.2014.03.027.
• 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.
• Bernales, Alejandro & Guidolin, Massimo, 2014, "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, volume 46, issue C, pages 326-342, DOI: 10.1016/j.jbankfin.2014.06.002.
• Yun, Jaeho, 2014, "Out-of-sample density forecasts with affine jump diffusion models," Journal of Banking & Finance, Elsevier, volume 47, issue C, pages 74-87, DOI: 10.1016/j.jbankfin.2014.06.024.
• 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.
• Sager, Michael & Taylor, Mark P., 2014, "Generating currency trading rules from the term structure of forward foreign exchange premia," Journal of International Money and Finance, Elsevier, volume 44, issue C, pages 230-250, DOI: 10.1016/j.jimonfin.2013.03.005.
• 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.
• Moosa, Imad & Burns, Kelly, 2014, "The unbeatable random walk in exchange rate forecasting: Reality or myth?," Journal of Macroeconomics, Elsevier, volume 40, issue C, pages 69-81, DOI: 10.1016/j.jmacro.2014.03.003.
• 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.
• Aastveit, Knut Are & Trovik, Tørres, 2014, "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, volume 54, issue 2, pages 180-193, DOI: 10.1016/j.qref.2013.09.003.
• 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.
• Su, Jung-Bin & Lee, Ming-Chih & Chiu, Chien-Liang, 2014, "Why does skewness and the fat-tail effect influence value-at-risk estimates? Evidence from alternative capital markets," International Review of Economics & Finance, Elsevier, volume 31, issue C, pages 59-85, DOI: 10.1016/j.iref.2013.12.001.
• 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.
• Jacobs, Michael & Karagozoglu, Ahmet K., 2014, "On the characteristics of dynamic correlations between asset pairs," Research in International Business and Finance, Elsevier, volume 32, issue C, pages 60-82, DOI: 10.1016/j.ribaf.2014.03.004.
• Hayashi, Masayoshi, 2014, "Forecasting welfare caseloads: The case of the Japanese public assistance program," Socio-Economic Planning Sciences, Elsevier, volume 48, issue 2, pages 105-114, DOI: 10.1016/j.seps.2013.10.002.
• Sanidas, Elias, 2014, "Four harmonic cycles explain and predict commodity currencies' wide long term fluctuations," Technological Forecasting and Social Change, Elsevier, volume 87, issue C, pages 135-151, DOI: 10.1016/j.techfore.2013.11.008.
• 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.
• Nicholas Fawcett & George Kapetanios & James Mitchell & Simon Price, 2014, "Generalised Density Forecast Combinations," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2014-24, Mar.
• 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.
• Giannone, Domenico & Monti, Francesca & Reichlin, Lucrezia, 2014, "Exploiting the monthly data-flow in structural forecasting," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 57998, Jun.
• Schöni, Olivier, 2014, "Asymptotic properties of imputed hedonic price indices," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 64500, Oct.
• Alex Maynard & Dongmeng Ren, 2014, "Assessing the Power of Long-Horizon Predictive Tests in Models of Bull and Bear Markets," Advances in Econometrics, Emerald Group Publishing Limited, "Essays in Honor of Peter C. B. Phillips", DOI: 10.1108/S0731-905320140000033019.
• Panayiotis F. Diamandis & Anastassios A. Drakos & Georgios P. Kouretas, 2014, "Exchange Rates, Fundamentals, and Nonlinearities: A Review and Some Further Evidence from a Century of Data," International Symposia in Economic Theory and Econometrics, Emerald Group Publishing Limited, "Macroeconomic Analysis and International Finance", DOI: 10.1108/S1571-038620140000023004.
• Lorenzo Cappellari & Stephen P. Jenkins, 2014, "The Dynamics of Social Assistance Benefit Receipt in Britain," Research in Labor Economics, Emerald Group Publishing Limited, "Safety Nets and Benefit Dependence", DOI: 10.1108/S0147-912120140000039000.
• 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.
• Goodness C. Aye & Mehmet Balcilar Author-Name-First Mehmet & Rangan Gupta & Anandamayee Majumdar, 2014, "Forecasting Aggregate Retail Sales: The Case of South Africa," Working Papers, Eastern Mediterranean University, Department of Economics, number 15-21.
• Mahua Barari & Nityananda Sarkar & Srikanta Kundu & Kushal Banik Chowdhury, 2014, "Forecasting House Prices in the United States with Multiple Structural Breaks," International Econometric Review (IER), Econometric Research Association, volume 6, issue 1, pages 1-23, April.
• Figari, Francesco & Colombino, Ugo & Coda Moscarola, Flavia & Locatelli, Marilena, 2014, "Shifting taxes from labour to property. A simulation under labour market equilibrium," EUROMOD Working Papers, EUROMOD at the Institute for Social and Economic Research, number EM20/14, Dec.
• IIBOSHI Hirokuni & MATSUMAE Tatsuyoshi & NISHIYAMA Shin-Ichi, 2014, "Sources of the Great Recession：A Bayesian Approach of a Data-Rich DSGE model with Time-Varying Volatility Shocks," ESRI Discussion paper series, Economic and Social Research Institute (ESRI), number 313, Dec.
• Merola, Rossana & Pérez, Javier J., 2014, "Fiscal Forecast Errors: Governments Versus Independent Agencies?," Papers, Economic and Social Research Institute (ESRI), number RB2014/1/1, Jan.
• Alessandro Girardi & Andreas Reuter & Christian Gayer, 2014, "The role of survey data in nowcasting euro area GDP growth," European Economy - Economic Papers 2008 - 2015, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, number 538, Dec.
• Alfonso Arpaia & Aron Kiss & Balazs Palvolgyi & Alessandro Turrini, 2014, "Labour mobility and labour market adjustment in the EU," European Economy - Economic Papers 2008 - 2015, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, number 539, Dec.
• Wilko Bolt & Maria Demertzis & Cees Diks & Cars Hommes & Marco van der Leij, 2014, "Identifying Booms and Busts in House Prices under Heterogeneous Expectations," European Economy - Economic Papers 2008 - 2015, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, number 540, Dec.
• Janos Varga & Jan in 't Veld, 2014, "The potential growth impact of structural reforms in the EU. A benchmarking exercise," European Economy - Economic Papers 2008 - 2015, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, number 541, Dec.
• Alexander HARIN, 2014, "Partially Unforeseen Events. Corrections and Correcting Formulae for Forecasts," Expert Journal of Economics, Sprint Investify, volume 2, issue 2, pages 69-79.
• Fahriye Öztürk & İbrahim Tokatlıoğlu & Hakan Naim Ardor, 2014, "Türkiye Ekonomisi İçin ARIMA ve Phillips Eğrisi Modellerinin Enflasyon Tahmin Performanslarının Karşılaştırılması: 1995-2014," Ekonomik Yaklasim, Ekonomik Yaklasim Association, volume 25, issue 92, pages 19-53, DOI: 10.5455/ey.35511.
• Jozef Barunik & Tomáš Krehlik, 2014, "Coupling high-frequency data with nonlinear models in multiple-step-ahead forecasting of energy markets' volatility," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2014/30, Sep, revised Sep 2014.
• Daniel Bencik, 2014, "Range-based Volatility Estimation and Forecasting," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2014/34, Dec, revised Dec 2014.
• Zhi Su, 2014, "Chinese Online Unemployment-Related Searches and Macroeconomic Indicators," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, volume 9, issue 4, pages 573-605, December.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014, "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Working Papers, Fondazione Eni Enrico Mattei, number 2014.21, Mar.
• Patrick C. Higgins, 2014, "GDPNow: A Model for GDP \"Nowcasting\"," FRB Atlanta Working Paper, Federal Reserve Bank of Atlanta, number 2014-7, Jul.
• Edward S. Knotek & Saeed Zaman, 2014, "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1403, May, DOI: 10.26509/frbc-wp-201403.
• Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014, "Have Standard VARs Remained Stable since the Crisis?," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1411, Sep, DOI: 10.26509/frbc-wp-201411.
• Kristle Romero Cortes & Philip E. Strahan, 2014, "Tracing Out Capital Flows: How Financially Integrated Banks Respond to Natural Disasters," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1412, Sep, DOI: 10.26509/frbc-wp-201412.
• Todd E. Clark & Michael W. McCracken, 2014, "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1413, Oct, DOI: 10.26509/frbc-wp-201413.
• Simone Auer, 2014, "Monetary policy shocks and foreign investment income: evidence from a large Bayesian VAR," Globalization Institute Working Papers, Federal Reserve Bank of Dallas, number 170, Feb, DOI: 10.24149/gwp170.
• Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014, "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers, Federal Reserve Bank of Dallas, number 213, Nov, DOI: 10.24149/gwp213.
• Laura Coroneo & Domenico Giannone & Michele Modugno, 2014, "Unspanned macroeconomic factors in the yield curve," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2014-57, Jul.
• Daniela Bragoli & Luca Metelli & Michele Modugno, 2014, "The Importance of Updating: Evidence from a Brazilian Nowcasting Model," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2014-94, Nov.
• Stefania D'Amico & Athanasios Orphanides, 2014, "Inflation Uncertainty and Disagreement in Bond Risk Premia," Working Paper Series, Federal Reserve Bank of Chicago, number WP-2014-24, Jan.
• Sean P. Grover & Michael W. McCracken, 2014, "Factor-based prediction of industry-wide bank stress," Review, Federal Reserve Bank of St. Louis, volume 96, issue 2, pages 173-194.
• Todd E. Clark & Michael W. McCracken, 2014, "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers, Federal Reserve Bank of St. Louis, number 2014-25, Sep, DOI: 10.20955/wp.2014.025.
• Weiling Liu & Emanuel Moench, 2014, "What predicts U.S. recessions?," Staff Reports, Federal Reserve Bank of New York, number 691, Sep.
• Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2014, "Dynamic prediction pools: an investigation of financial frictions and forecasting performance," Staff Reports, Federal Reserve Bank of New York, number 695, Oct.
• Dean Croushore & Keith Sill, 2014, "Analyzing data revisions with a dynamic stochastic general equilibrium model," Working Papers, Federal Reserve Bank of Philadelphia, number 14-29, Sep.
• Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014, "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", number 2014_01, Feb, revised Feb 2014.
• Schöni, Olivier & Seger, Lukas, 2014, "Comparing Mobile Communication Service Prices Among Providers: A Hedonic Approach," FSES Working Papers, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland, number 448, Apr.
• Giovanis, Eleftherios, 2014, "Study Of Discrete Choice Models And Fuzzy Rule Based Systems In The Prediction Of Economic Crisis Periods In Usa," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), volume 0, issue 1, pages 3-18, May.
• Sergey Tsukhlo, 2014, "Russian Industrial Enterprises in 2013," Published Papers, Gaidar Institute for Economic Policy, number 178, revised 2014.
• Sergey Tsukhlo, 2014, "Russian Industrial Enterprises in 2014," Published Papers, Gaidar Institute for Economic Policy, number 207, revised 2014.
• Bruno Lanz & Simon Dietz & Tim Swanson, 2014, "Global Population Growth, Technology and Malthusian Constraints: A Quantitative Growth Theoretic Perspective," CIES Research Paper series, Centre for International Environmental Studies, The Graduate Institute, number 25-2014, Jun, revised 01 May 2016.
• Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014, "Exchange Rate Predictability in a Changing World," Working Papers, Business School - Economics, University of Glasgow, number 2014_03, Feb.
• Dimitris Korobilis, 2014, "Data-based priors for vector autoregressions with drifting coefficients," Working Papers, Business School - Economics, University of Glasgow, number 2014_04, Jan.
• Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014, "On the Sources of Uncertainty in Exchange Rate Predictability," Working Papers, Business School - Economics, University of Glasgow, number 2014_16, Sep.
• Udichibarna Bose & Ronald MacDonald & Serafeim Tsoukas, 2014, "The role of education in equity portfolios during the recent financial crisis," Working Papers, Business School - Economics, University of Glasgow, number 2014_17, Oct.
• António Alberto Santos & João Andrade, 2014, "Stochastic Volatility Estimation with GPU Computing," GEMF Working Papers, GEMF, Faculty of Economics, University of Coimbra, number 2014-10, Apr.
• Dr. Thomas Drosdowski & Dr. Christian Lutz, 2014, "Weiterentwicklung des aktualisierten Panta Rhei Modells um sozioökonomische Aspekte," GWS Research Report Series, GWS - Institute of Economic Structures Research, number 14-1.
• Rémy Charleroy & Michael A. Stemmer, 2014, "An Emerging Market Financial Conditions Index: A VAR Approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number halshs-01110688, Oct.
• Samir Elhedhli & Canan Akdemir & Thomas Astebro, 2014, "Classification models via Tabu search: An application to early stage venture classification," Post-Print, HAL, number hal-01066492, Dec, DOI: 10.1016/j.eswa.2014.07.010.
• Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2014, "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Post-Print, HAL, number hal-01385941.
• Rémy Charleroy & Michael A. Stemmer, 2014, "An Emerging Market Financial Conditions Index: A VAR Approach," Post-Print, HAL, number halshs-01110688, Oct.
• Laurent E. Calvet & Veronika Czellar, 2014, "Through the Looking Glass: Indirect Inference via Simple Equilibria," Working Papers, HAL, number hal-02058272, Jun, DOI: 10.2139/ssrn.2444445.
• Adama Bah, 2015, "Estimating Vulnerability to Poverty using Panel data: Evidence from Indonesia," Working Papers, HAL, number halshs-00936199, Jun.
• Christophe Amat & Tomasz Michalski & Gilles Stoltz, 2018, "Fundamentals and exchange rate forecastability with simple machine learning methods," Working Papers, HAL, number halshs-01003914, May.
• Gianni Amisano & Roberta Colavecchio & Gabriel Fagan, 2014, "A money-based indicator for deflation risk," Macroeconomics and Finance Series, University of Hamburg, Department of Socioeconomics, number 201403, Apr.
• Li, Yushu & Andersson, Jonas, 2014, "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2014/12, Mar.
• Biørn, Erik, 2014, "Serially Correlated Measurement Errors in Time Series Regression: The Potential of Instrumental Variable Estimators," Memorandum, Oslo University, Department of Economics, number 28/2014, Dec.
• Ranganathan, Shyam & Bali Swain, Ranjula & Sumpter, David, 2014, "A Dynamical Systems Approach To Modeling Human Development," Working Paper Series, Uppsala University, Department of Economics, number 2014:9, Oct.
• Ranganathan, Shyam & Bali Swain, Ranjula, 2014, "Analysing Mechanisms for Meeting Global Emissions Target - A Dynamical Systems Approach," Working Paper Series, Uppsala University, Department of Economics, number 2014:10, Oct.
• Davor Kunovac & Borna Špalat, 2014, "Nowcasting GDP Using Available Monthly Indicators," Working Papers, The Croatian National Bank, Croatia, number 39, Oct.
• Erginbay UGURLU & Irena JINDRICHOVSKA & Dana KUBICKOVA, 2014, "Working Capital Management in Czech SMEs: An Econometric Approach," International Conference on Economic Sciences and Business Administration, Spiru Haret University, volume 1, issue 1, pages 311-317, December.
• Omer ZEYBEK & Erginbay UGURLU, 2014, "Nowcasting Credit Demand in Turkey with Google Trends Data," International Conference on Economic Sciences and Business Administration, Spiru Haret University, volume 1, issue 1, pages 333-340, December.
• Raffaella Giacomini, 2014, "Economic theory and forecasting: lessons from the literature," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP41/14, Sep.
• Costantini, Mauro & Cuaresma, Jesus Crespo & Hlouskova, Jaroslava, 2014, "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Economics Series, Institute for Advanced Studies, number 305, Sep.
• Cenktan ÖZYILDIRIM & Mehmet Fuat BEYAZIT, 2014, "Forecasting and Modelling of Electricity Prices by Radial Basis Functions: Turkish Electricity Market Experiment," Iktisat Isletme ve Finans, Bilgesel Yayincilik, volume 29, issue 344, pages 31-54.
• Okan EREN, 2014, "Forecasting the Relative Direction of Economic Growth by Using the Purchasing Managers` Index," Iktisat Isletme ve Finans, Bilgesel Yayincilik, volume 29, issue 344, pages 55-72.
• Matteo Luciani & Lorenzo Ricci, 2014, "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, volume 10, issue 4, pages 215-248, December.
• Matteo Richiardi & Ambra Poggi, 2014, "Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy," International Journal of Microsimulation, International Microsimulation Association, volume 7, issue 2, pages 3-39.
• Mr. Troy D Matheson & Mr. Emil Stavrev, 2014, "News and Monetary Shocks at a High Frequency: A Simple Approach," IMF Working Papers, International Monetary Fund, number 2014/167, Sep.
• Mostefa BELMOKADDEM & Omar BENATEK & Abdelkrim BENAMEUR & Rabiaa MELLAL, 2014, "Methods of sales forecasting and modeling of supply chains. Case study: Atlas Chimie Algeria," Romanian Journal of Economics, Institute of National Economy, volume 39, issue 2(48), pages 19-33, December.
• Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014, "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, volume 60, issue 7, pages 1772-1791, July, DOI: 10.1287/mnsc.2013.1838.
• Achim Zeileis & Christoph Leitner & Kurt Hornik, 2014, "Home Victory for Brazil in the 2014 FIFA World Cup," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2014-17, Jun.
• Karolin Kirschenmann & Tuomas Malinen & Henri Nyberg, 2014, "The risk of financial crises: Is it in real or financial factors?," Working Papers, ECINEQ, Society for the Study of Economic Inequality, number 336, Jun.
• Julien Chevallier & Stéphane Goutte, 2014, "The goodness-of-fit of the fuel-switching price using the mean-reverting Lévy jump process," Working Papers, Department of Research, Ipag Business School, number 2014-285, Jan.
• Bertrand Candelon & Jameel Ahmed & Stefan Straetmans, 2014, "Predicting and Capitalizing on Stock Market Bears in the U.S," Working Papers, Department of Research, Ipag Business School, number 2014-409, Jan.
• Rangan Gupta & Shawkat Hammoudeh & Mampho P. Modise & Duc Khuong Nguyen, 2014, "Can Economic Uncertainty, Financial Stress and Consumer Senti-ments Predict U.S. Equity Premium?," Working Papers, Department of Research, Ipag Business School, number 2014-436, Jan.