Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2017

• Carlomagno Real, Guillermo & Espasa, Antoni, 2017, "Discovering pervasive and non-pervasive common cycles," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 25392, Sep.
• Mariti, Massimo B. & Gonçalves Mazzeu, Joao Henrique & Lopes Moreira da Veiga, María Helena, 2017, "Modeling and forecasting the oil volatility index," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 25985, Nov.
• Gonzalo Ruiz Díaz, 2017, "¿Están las proyecciones oficiales del PBI de los países de América Latina y El Caribe sesgadas hacia abajo?," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, volume 40, issue 114, pages 236-246, Septiembr.
• Afees A. Salisu & Idris Ademuyiwa & Kazeem Isah, 2017, "Revisiting the forecasting accuracy of Phillips curve: the role of oil price," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 022, Aug.
• Afees A. Salisu & Ahamuefula Ephraim Ogbonna, 2017, "Improving the Predictive ability of oil for inflation: An ADL-MIDAS Approach," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 025, Aug.
• Afees A. Salisu & Kazeem Isah, 2017, "Predicting US CPI-Inflation in the presence of asymmetries, persistence, endogeneity, and conditional heteroscedasticity," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 026, Aug.
• Afees A. Salisu & Raymond Swaray, 2017, "Forecasting the return volatility of energy prices: A GARCH MIDAS approach," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 029, Sep.
• Afees A. Salisu & Umar B. Ndako, 2017, "A new look at the stock price-exchange rate nexus," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 031, Oct.
• Afees A. Salisu & Umar B. Ndako, 2017, "Modelling stock price-exchange rate nexus in OECD countries - A new perspective," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 038, Dec.
• Afees A. Salisu & Kazeem Isah, 2017, "Predicting US Inflation: Evidence from a New Approach," Working Papers, Centre for Econometric and Allied Research, University of Ibadan, number 039, Dec.
• Ouael EL JEBARI & Abdelati HAKMAOUI, 2017, "Modeling persistence of volatility in the Moroccan exchange market using a fractionally integrated EGARCH," Turkish Economic Review, EconSciences 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, EconSciences Journals, volume 4, issue 3, pages 203-221, September.
• Răzvan BOLOGA & Ana Ramona LUPU, 2017, "A Model for Predicting Future Demand for ICT Specialists in Romania," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, volume 51, issue 1, pages 151-168.
• Narges TALEBIMOTLAGH & Farzad HASHEMZADEH & Amir RIKHTEHGAR GHIASI & Sehraneh GHAEMI, 2017, "A Novel Method of Modeling Dynamic Evolutionary Game with Rational Agents for Market Forecasting," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, volume 51, issue 1, pages 281-302.
• Kyoung-SookMOON & Heejean KIM & Hongjoong KIM, 2017, "A Prediction Methodology for the Change of the Values of Financial Products," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, volume 51, issue 3, pages 197-210.
• Konstantin A. Kholodilin & Claus Michelsen, 2017, "No Germany-Wide Housing Bubble but Overvaluation in Regional Markets and Segments," DIW Economic Bulletin, DIW Berlin, German Institute for Economic Research, volume 7, issue 25/26, pages 255-264.
• Konstantin A. Kholodilin & Claus Michelsen, 2017, "Keine Immobilienpreisblase in Deutschland – aber regional begrenzte Übertreibungen in Teilmärkten," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, volume 84, issue 25, pages 503-513.
• Benjamin Beckers & Konstantin A. Kholodilin & Dirk Ulbricht, 2017, "Reading between the Lines: Using Media to Improve German Inflation Forecasts," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1665.
• Chevillon, Guillaume, 2017, "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers, ESSEC Research Center, ESSEC Business School, number WP1710, Jul.
• Strasser, Georg, 2017, "What determines the impact of macroeconomic news on asset markets?," Research Bulletin, European Central Bank, volume 37.
• Sousa, João & Falagiarda, Matteo, 2017, "Forecasting euro area inflation using targeted predictors: is money coming back?," Working Paper Series, European Central Bank, number 2015, Feb.
• Sarlin, Peter & von Schweinitz, Gregor, 2017, "Optimizing policymakers' loss functions in crisis prediction: before, within or after?," Working Paper Series, European Central Bank, number 2025, Feb.
• Bengtsson, Elias & Grothe, Magdalena & Lepers, Etienne, 2017, "Home, safe home: cross-country monitoring framework for vulnerabilities in the residential real estate sector," Working Paper Series, European Central Bank, number 2096, Aug.
• Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017, "Common factors of commodity prices," Working Paper Series, European Central Bank, number 2112, Nov.
• Maryam Hosseinzadeh & Saeed Daei-Karimzadeh, 2017, "Investigate the Effect of Exchange Rate Volatility on the Demand for Life Insurance in Iran," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 2, pages 166-174.
• Khalil Abbasi Museloo & Shaker Abartavi, 2017, "Incorrect Pricing Impact on Investment and the Capital Structure of Companies with Financial Constraints," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 2, pages 319-324.
• Mehdi Behrad-Amin & Gholamreza Zamanian & Marzie Esfandiari, 2017, "The Effect of Oil Shocks on Foreign Trade under Inflation and Exchange Rate Targeting Policies (In the Form of a Dynamic Stochastic General Equilibrium Model for Iran)," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 3, pages 342-351.
• Abbas Taleb Bidokhti & Ali Akbar Esmailpour, 2017, "Examining the Effect of Social and Intellectual Value on Organizational Performance Based on the Balanced Evaluation Method and Structural Equations in the Iranian Oil Terminals Company," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 3, pages 404-410.
• Ghazi Al-Assaf, 2017, "An Early Warning System for Currency Crisis: A Comparative Study for the Case of Jordan and Egypt," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 3, pages 43-50.
• Shahram Fattahi & Kiomars Sohaili & Hamed Monkaresi & Fatemeh Mehrabi, 2017, "Modelling and Forecasting Recessions in Oil-exporting Countries: The Case of Iran," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 3, pages 569-574.
• Morteza Doosti Seyyed Shekari & Babak Jamshidinavid, 2017, "Study of Information Asymmetry Effect on Price Synchronism in Tehran Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 4, pages 343-346.
• Daniel Toth & Lenka Kuc rkov, 2017, "Macroeconomic Prognosis of Employment in the Czech Republic," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 4, pages 730-736.
• Songul Cinaroglu, 2017, "A Fresh Look at Out-of-Pocket Health Expenditures after More than a Decade Health Reform Experience in Turkey: A Data Mining Application," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 5, pages 33-40.
• Lana V. L. Costa-Silva & Vinicio S. Almeida & Felipe M. Pimenta & Giovanna T. Segantini, 2017, "Time Span does Matter for Offshore Wind Plant Allocation with Modern Portfolio Theory," International Journal of Energy Economics and Policy, Econjournals, volume 7, issue 3, pages 188-193.
• Hassan Mehrmanesh & Seyed Rahim Safavi Mirmahalleh, 2017, "Examining the Relationship between Supply Chain Relationships and Practice of Distributors (Case Study: NoshinCo)," International Review of Management and Marketing, Econjournals, volume 7, issue 2, pages 67-70.
• Neda Sharifi Asadi Malafe & Masoud Ahmadi & Fahime Baei, 2017, "The Relationship between Demographic Characteristics with Information and Communication Technology and Empowerment in General Organizations (Case Study: Sari Municipality)," International Review of Management and Marketing, Econjournals, volume 7, issue 2, pages 71-75.
• Rasool Sarihi Asfestani & Mehraban Hadi Peykani & Akbar Eetebaryan, 2017, "Design and Presentation of Professional Ethics Criteria and Indicators for the Promotion of Political Accountability within Iranian’s Government Organizations (Case Study: National Chief Executive Devices)," International Review of Management and Marketing, Econjournals, volume 7, issue 2, pages 226-232.
• Hassan Mehrmanesh & Seyed Rahim Safavi Mirmahalleh, 2017, "Studying the Relationship among Character, Phantasm and Environment with Customers’ Loyalty in Iran’s Hotel Industry (Case Study: Hotels of Ardabil)," International Review of Management and Marketing, Econjournals, volume 7, issue 2, pages 233-236.
• Mahdi Rezapour & Mehraban Hadi Peykani, 2017, "Compare Customer Satisfaction with the Quality of E-banking Services among State, Private and Altered Banks in Isfahan," International Review of Management and Marketing, Econjournals, volume 7, issue 2, pages 237-243.
• Fahime Baei & Masoud Ahmadi & Neda Sharifi Asadi Malafeh & Abbasali Baee, 2017, "The Relationship between Manager’s Strategic Intelligence and Organization Development in Governmental Agencies in Iran (Case Study: Office of Cooperatives Labor and Social Welfare)," International Review of Management and Marketing, Econjournals, volume 7, issue 2, pages 244-249.
• Azade Aryana & Reza Ameri Siyahouei & Tahereh Mahmoudi, 2017, "Investigating the Relationship between Employee Empowerment and the Development of an Entrepreneurial Culture at Fatemieh Technical and Vocational University of Bandar Abbas," International Review of Management and Marketing, Econjournals, volume 7, issue 2, pages 250-255.
• Bella, Giovanni, 2017, "Homoclinic bifurcation and the Belyakov degeneracy in a variant of the Romer model of endogenous growth," Chaos, Solitons & Fractals, Elsevier, volume 104, issue C, pages 452-460, DOI: 10.1016/j.chaos.2017.08.025.
• Cantore, Cristiano & Ferroni, Filippo & León-Ledesma, Miguel A., 2017, "The dynamics of hours worked and technology," Journal of Economic Dynamics and Control, Elsevier, volume 82, issue C, pages 67-82, DOI: 10.1016/j.jedc.2017.05.009.
• Wei, Yu & Cao, Yang, 2017, "Forecasting house prices using dynamic model averaging approach: Evidence from China," Economic Modelling, Elsevier, volume 61, issue C, pages 147-155, DOI: 10.1016/j.econmod.2016.12.002.
• Paret, Anne-Charlotte, 2017, "Debt sustainability in emerging market countries: Some policy guidelines from a fan-chart approach," Economic Modelling, Elsevier, volume 63, issue C, pages 26-45, DOI: 10.1016/j.econmod.2017.01.010.
• Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017, "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, volume 64, issue C, pages 26-39, DOI: 10.1016/j.econmod.2017.03.003.
• Doumpos, Michael & Hasan, Iftekhar & Pasiouras, Fotios, 2017, "Bank overall financial strength: Islamic versus conventional banks," Economic Modelling, Elsevier, volume 64, issue C, pages 513-523, DOI: 10.1016/j.econmod.2017.03.026.
• Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017, "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, volume 66, issue C, pages 132-138, DOI: 10.1016/j.econmod.2017.06.005.
• Pop, Raluca-Elena, 2017, "A small-scale DSGE-VAR model for the Romanian economy," Economic Modelling, Elsevier, volume 67, issue C, pages 1-9, DOI: 10.1016/j.econmod.2016.07.011.
• Siliverstovs, Boriss, 2017, "Dissecting models' forecasting performance," Economic Modelling, Elsevier, volume 67, issue C, pages 294-299, DOI: 10.1016/j.econmod.2017.01.008.
• Zhang, Heng-Guo & Su, Chi-Wei & Song, Yan & Qiu, Shuqi & Xiao, Ran & Su, Fei, 2017, "Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model," Economic Modelling, Elsevier, volume 67, issue C, pages 355-367, DOI: 10.1016/j.econmod.2017.02.014.
• Chen, Cathy W.S. & Wang, Zona & Sriboonchitta, Songsak & Lee, Sangyeol, 2017, "Pair trading based on quantile forecasting of smooth transition GARCH models," The North American Journal of Economics and Finance, Elsevier, volume 39, issue C, pages 38-55, DOI: 10.1016/j.najef.2016.10.015.
• Li, Leon, 2017, "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, volume 40, issue C, pages 116-135, DOI: 10.1016/j.najef.2017.02.006.
• Jung, Alexander, 2017, "Forecasting broad money velocity," The North American Journal of Economics and Finance, Elsevier, volume 42, issue C, pages 421-432, DOI: 10.1016/j.najef.2017.08.005.
• Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017, "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, volume 42, issue C, pages 448-460, DOI: 10.1016/j.najef.2017.08.009.
• Ñíguez, Trino-Manuel & Perote, Javier, 2017, "Moments expansion densities for quantifying financial risk," The North American Journal of Economics and Finance, Elsevier, volume 42, issue C, pages 53-69, DOI: 10.1016/j.najef.2017.06.002.
• Xie, Tian, 2017, "Heteroscedasticity-robust model screening: A useful toolkit for model averaging in big data analytics," Economics Letters, Elsevier, volume 151, issue C, pages 119-122, DOI: 10.1016/j.econlet.2016.12.019.
• Bürgi, Constantin, 2017, "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, volume 154, issue C, pages 113-116, DOI: 10.1016/j.econlet.2017.03.002.
• Guérin, Pierre & Leiva-Leon, Danilo, 2017, "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, volume 157, issue C, pages 45-49, DOI: 10.1016/j.econlet.2017.05.027.
• Fosten, Jack, 2017, "Confidence intervals in regressions with estimated factors and idiosyncratic components," Economics Letters, Elsevier, volume 157, issue C, pages 71-74, DOI: 10.1016/j.econlet.2017.05.034.
• Zhang, Keyi & Gençay, Ramazan & Ege Yazgan, M., 2017, "Application of wavelet decomposition in time-series forecasting," Economics Letters, Elsevier, volume 158, issue C, pages 41-46, DOI: 10.1016/j.econlet.2017.06.010.
• Sensoy, Ahmet & Fabozzi, Frank J. & Eraslan, Veysel, 2017, "Predictability dynamics of emerging sovereign CDS markets," Economics Letters, Elsevier, volume 161, issue C, pages 5-9, DOI: 10.1016/j.econlet.2017.09.015.
• Galvão, Ana Beatriz, 2017, "Data revisions and DSGE models," Journal of Econometrics, Elsevier, volume 196, issue 1, pages 215-232, DOI: 10.1016/j.jeconom.2016.09.006.
• Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017, "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, volume 196, issue 1, pages 55-67, DOI: 10.1016/j.jeconom.2016.03.006.
• Tu, Yundong & Yi, Yanping, 2017, "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, volume 196, issue 1, pages 83-98, DOI: 10.1016/j.jeconom.2016.09.012.
• Engle, Robert & Roussellet, Guillaume & Siriwardane, Emil, 2017, "Scenario generation for long run interest rate risk assessment," Journal of Econometrics, Elsevier, volume 201, issue 2, pages 333-347, DOI: 10.1016/j.jeconom.2017.08.012.
• Amador-Torres, J. Sebastián, 2017, "Finance-neutral potential output: An evaluation in an emerging market monetary policy context," Economic Systems, Elsevier, volume 41, issue 3, pages 389-407, DOI: 10.1016/j.ecosys.2016.09.003.
• Roesel, Felix, 2017, "The causal effect of wrong-hand drive vehicles on road safety," Economics of Transportation, Elsevier, volume 11, issue , pages 15-22, DOI: 10.1016/j.ecotra.2017.10.002.
• Huber, Peter & Oberhofer, Harald & Pfaffermayr, Michael, 2017, "Who creates jobs? Econometric modeling and evidence for Austrian firm level data," European Economic Review, Elsevier, volume 91, issue C, pages 57-71, DOI: 10.1016/j.euroecorev.2016.09.008.
• Meinen, Philipp & Roehe, Oke, 2017, "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," European Economic Review, Elsevier, volume 92, issue C, pages 161-179, DOI: 10.1016/j.euroecorev.2016.12.002.
• Harris, Richard D.F. & Stoja, Evarist & Tan, Linzhi, 2017, "The dynamic Black–Litterman approach to asset allocation," European Journal of Operational Research, Elsevier, volume 259, issue 3, pages 1085-1096, DOI: 10.1016/j.ejor.2016.11.045.
• Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2017, "Forecasting with temporal hierarchies," European Journal of Operational Research, Elsevier, volume 262, issue 1, pages 60-74, DOI: 10.1016/j.ejor.2017.02.046.
• Guarin, Alexander & Lozano, Ignacio, 2017, "Credit funding and banking fragility: A forecasting model for emerging economies," Emerging Markets Review, Elsevier, volume 32, issue C, pages 168-189, DOI: 10.1016/j.ememar.2017.06.004.
• Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2017, "Relation between higher order comoments and dependence structure of equity portfolio," Journal of Empirical Finance, Elsevier, volume 40, issue C, pages 101-120, DOI: 10.1016/j.jempfin.2016.11.007.
• Nonejad, Nima, 2017, "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, volume 42, issue C, pages 131-154, DOI: 10.1016/j.jempfin.2017.03.003.
• Fries, Christian P. & Nigbur, Tobias & Seeger, Norman, 2017, "Displaced relative changes in historical simulation: Application to risk measures of interest rates with phases of negative rates," Journal of Empirical Finance, Elsevier, volume 42, issue C, pages 175-198, DOI: 10.1016/j.jempfin.2017.03.004.
• Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017, "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, volume 42, issue C, pages 199-211, DOI: 10.1016/j.jempfin.2017.03.005.
• Han, Xing & Li, Youwei, 2017, "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, volume 42, issue C, pages 212-239, DOI: 10.1016/j.jempfin.2017.04.001.
• Risse, Marian & Ohl, Ludwig, 2017, "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, volume 44, issue C, pages 158-176, DOI: 10.1016/j.jempfin.2017.09.005.
• Gupta, Rangan & Kotzé, Kevin, 2017, "The role of oil prices in the forecasts of South African interest rates: A Bayesian approach," Energy Economics, Elsevier, volume 61, issue C, pages 270-278, DOI: 10.1016/j.eneco.2016.11.017.
• Gupta, Rangan & Wohar, Mark, 2017, "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, volume 62, issue C, pages 181-186, DOI: 10.1016/j.eneco.2017.01.001.
• Bennedsen, Mikkel, 2017, "A rough multi-factor model of electricity spot prices," Energy Economics, Elsevier, volume 63, issue C, pages 301-313, DOI: 10.1016/j.eneco.2017.02.007.
• Bataille, Chris & Melton, Noel, 2017, "Energy efficiency and economic growth: A retrospective CGE analysis for Canada from 2002 to 2012," Energy Economics, Elsevier, volume 64, issue C, pages 118-130, DOI: 10.1016/j.eneco.2017.03.008.
• Pinheiro Neto, Daywes & Domingues, Elder Geraldo & Coimbra, António Paulo & de Almeida, Aníbal Traça & Alves, Aylton José & Calixto, Wesley Pacheco, 2017, "Portfolio optimization of renewable energy assets: Hydro, wind, and photovoltaic energy in the regulated market in Brazil," Energy Economics, Elsevier, volume 64, issue C, pages 238-250, DOI: 10.1016/j.eneco.2017.03.020.
• Lof, Matthijs & Nyberg, Henri, 2017, "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, volume 65, issue C, pages 424-433, DOI: 10.1016/j.eneco.2017.05.024.
• Zhang, Lei & Li, Yaoyu, 2017, "Regime-switching based vehicle-to-building operation against electricity price spikes," Energy Economics, Elsevier, volume 66, issue C, pages 1-8, DOI: 10.1016/j.eneco.2017.05.019.
• Campos, I. & Cortazar, G. & Reyes, T., 2017, "Modeling and predicting oil VIX: Internet search volume versus traditional mariables," Energy Economics, Elsevier, volume 66, issue C, pages 194-204, DOI: 10.1016/j.eneco.2017.06.009.
• Mirakyan, Atom & Meyer-Renschhausen, Martin & Koch, Andreas, 2017, "Composite forecasting approach, application for next-day electricity price forecasting," Energy Economics, Elsevier, volume 66, issue C, pages 228-237, DOI: 10.1016/j.eneco.2017.06.020.
• Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017, "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, volume 66, issue C, pages 337-348, DOI: 10.1016/j.eneco.2017.07.007.
• Taylor, Nick, 2017, "Timing strategy performance in the crude oil futures market," Energy Economics, Elsevier, volume 66, issue C, pages 480-492, DOI: 10.1016/j.eneco.2017.07.019.
• Sukcharoen, Kunlapath & Leatham, David J., 2017, "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, volume 66, issue C, pages 493-507, DOI: 10.1016/j.eneco.2017.07.012.
• Lyu, Yongjian & Wang, Peng & Wei, Yu & Ke, Rui, 2017, "Forecasting the VaR of crude oil market: Do alternative distributions help?," Energy Economics, Elsevier, volume 66, issue C, pages 523-534, DOI: 10.1016/j.eneco.2017.06.015.
• Han, Liyan & Lv, Qiuna & Yin, Libo, 2017, "Can investor attention predict oil prices?," Energy Economics, Elsevier, volume 66, issue C, pages 547-558, DOI: 10.1016/j.eneco.2017.04.018.
• Zhao, Yang & Li, Jianping & Yu, Lean, 2017, "A deep learning ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, volume 66, issue C, pages 9-16, DOI: 10.1016/j.eneco.2017.05.023.
• Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017, "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, volume 67, issue C, pages 136-145, DOI: 10.1016/j.eneco.2017.08.004.
• Charles, Amélie & Darné, Olivier, 2017, "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, volume 67, issue C, pages 508-519, DOI: 10.1016/j.eneco.2017.09.002.
• Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017, "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, volume 68, issue C, pages 77-88, DOI: 10.1016/j.eneco.2017.09.010.
• Croonenbroeck, Carsten & Hüttel, Silke, 2017, "Quantifying the economic efficiency impact of inaccurate renewable energy price forecasts," Energy, Elsevier, volume 134, issue C, pages 767-774, DOI: 10.1016/j.energy.2017.06.077.
• Alexopoulos, Thomas A., 2017, "The growing importance of natural gas as a predictor for retail electricity prices in US," Energy, Elsevier, volume 137, issue C, pages 219-233, DOI: 10.1016/j.energy.2017.07.002.
• Moral-Carcedo, Julián & Pérez-García, Julián, 2017, "Integrating long-term economic scenarios into peak load forecasting: An application to Spain," Energy, Elsevier, volume 140, issue P1, pages 682-695, DOI: 10.1016/j.energy.2017.08.113.
• Degiannakis, Stavros & Potamia, Artemis, 2017, "Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data," International Review of Financial Analysis, Elsevier, volume 49, issue C, pages 176-190, DOI: 10.1016/j.irfa.2016.10.008.
• Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017, "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, volume 50, issue C, pages 52-66, DOI: 10.1016/j.irfa.2016.12.009.
• Tunaru, Radu & Zheng, Teng, 2017, "Parameter estimation risk in asset pricing and risk management: A Bayesian approach," International Review of Financial Analysis, Elsevier, volume 53, issue C, pages 80-93, DOI: 10.1016/j.irfa.2017.08.004.
• Svec, Jiri & Katrak, Xerxis, 2017, "Forecasting volatility with interacting multiple models," Finance Research Letters, Elsevier, volume 20, issue C, pages 245-252, DOI: 10.1016/j.frl.2016.10.005.
• Chen, Cathy W.S. & Lin, Tsai-Yu, 2017, "Nonparametric tolerance limits for pair trading," Finance Research Letters, Elsevier, volume 21, issue C, pages 1-9, DOI: 10.1016/j.frl.2016.11.002.
• Kinateder, Harald & Hofstetter, Benedikt & Wagner, Niklas, 2017, "Do liquidity variables improve out-of-sample prediction of sovereign spreads during crisis periods?," Finance Research Letters, Elsevier, volume 21, issue C, pages 144-150, DOI: 10.1016/j.frl.2016.11.006.
• Klein, Tony & Walther, Thomas, 2017, "Fast fractional differencing in modeling long memory of conditional variance for high-frequency data," Finance Research Letters, Elsevier, volume 22, issue C, pages 274-279, DOI: 10.1016/j.frl.2016.12.020.
• Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017, "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, volume 22, issue C, pages 35-41, DOI: 10.1016/j.frl.2016.12.032.
• Mendes, Beatriz Vaz de Melo & Lavrado, Rafael Coelho, 2017, "Implementing and testing the Maximum Drawdown at Risk," Finance Research Letters, Elsevier, volume 22, issue C, pages 95-100, DOI: 10.1016/j.frl.2017.06.001.
• Lyócsa, Štefan & Molnár, Peter, 2017, "The effect of non-trading days on volatility forecasts in equity markets," Finance Research Letters, Elsevier, volume 23, issue C, pages 39-49, DOI: 10.1016/j.frl.2017.07.002.
• Dawood, Mary & Horsewood, Nicholas & Strobel, Frank, 2017, "Predicting sovereign debt crises: An Early Warning System approach," Journal of Financial Stability, Elsevier, volume 28, issue C, pages 16-28, DOI: 10.1016/j.jfs.2016.11.008.
• Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2017, "Credit risk interconnectedness: What does the market really know?," Journal of Financial Stability, Elsevier, volume 29, issue C, pages 1-12, DOI: 10.1016/j.jfs.2017.01.002.
• Kolo, Horst & Tzanova, Polia, 2017, "Forecasting the German forest products trade: A vector error correction model," Journal of Forest Economics, Elsevier, volume 26, issue C, pages 30-45, DOI: 10.1016/j.jfe.2016.11.001.
• Ince, Onur & Molodtsova, Tanya, 2017, "Rationality and forecasting accuracy of exchange rate expectations: Evidence from survey-based forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 47, issue C, pages 131-151, DOI: 10.1016/j.intfin.2016.11.002.
• Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017, "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 51, issue C, pages 228-247, DOI: 10.1016/j.intfin.2017.08.005.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017, "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, volume 33, issue 1, pages 153-173, DOI: 10.1016/j.ijforecast.2016.02.004.
• Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate, 2017, "Visualising forecasting algorithm performance using time series instance spaces," International Journal of Forecasting, Elsevier, volume 33, issue 2, pages 345-358, DOI: 10.1016/j.ijforecast.2016.09.004.
• Hendry, David F. & Martinez, Andrew B., 2017, "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, volume 33, issue 2, pages 359-372, DOI: 10.1016/j.ijforecast.2016.08.007.
• Tallman, Ellis W. & Zaman, Saeed, 2017, "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, volume 33, issue 2, pages 442-457, DOI: 10.1016/j.ijforecast.2016.10.004.
• Delle Monache, Davide & Petrella, Ivan, 2017, "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, volume 33, issue 2, pages 482-501, DOI: 10.1016/j.ijforecast.2016.11.007.
• Ericsson, Neil R., 2017, "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, volume 33, issue 2, pages 523-542, DOI: 10.1016/j.ijforecast.2016.10.001.
• Ericsson, Neil R., 2017, "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, volume 33, issue 2, pages 543-559, DOI: 10.1016/j.ijforecast.2016.09.001.
• Rua, António, 2017, "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, volume 33, issue 3, pages 581-590, DOI: 10.1016/j.ijforecast.2017.01.007.
• Hännikäinen, Jari, 2017, "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 1044-1064, DOI: 10.1016/j.ijforecast.2017.05.006.
• Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017, "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 1065-1081, DOI: 10.1016/j.ijforecast.2017.06.007.
• Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017, "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 745-759, DOI: 10.1016/j.ijforecast.2017.02.003.
• Taylor, Nick, 2017, "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 770-785, DOI: 10.1016/j.ijforecast.2017.04.001.
• Bragoli, Daniela & Modugno, Michele, 2017, "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 786-800, DOI: 10.1016/j.ijforecast.2017.03.002.
• D’Amuri, Francesco & Marcucci, Juri, 2017, "The predictive power of Google searches in forecasting US unemployment," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 801-816, DOI: 10.1016/j.ijforecast.2017.03.004.
• Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017, "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 915-935, DOI: 10.1016/j.ijforecast.2017.05.002.
• Kolev, Gueorgui I. & Karapandza, Rasa, 2017, "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, volume 84, issue C, pages 188-201, DOI: 10.1016/j.jbankfin.2016.07.017.
• Bella, Giovanni & Mattana, Paolo & Venturi, Beatrice, 2017, "Shilnikov chaos in the Lucas model of endogenous growth," Journal of Economic Theory, Elsevier, volume 172, issue C, pages 451-477, DOI: 10.1016/j.jet.2017.09.010.
• Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017, "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, volume 70, issue C, pages 183-203, DOI: 10.1016/j.jimonfin.2016.08.007.
• Degiannakis, Stavros & Filis, George, 2017, "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, volume 76, issue C, pages 28-49, DOI: 10.1016/j.jimonfin.2017.05.006.
• David, Benjamin, 2017, "Computer technology and probable job destructions in Japan: An evaluation," Journal of the Japanese and International Economies, Elsevier, volume 43, issue C, pages 77-87, DOI: 10.1016/j.jjie.2017.01.001.
• Fanelli, Luca & Sorge, Marco M., 2017, "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, volume 53, issue C, pages 57-70, DOI: 10.1016/j.jmacro.2017.05.007.
• Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017, "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, volume 6, issue C, pages 66-87, DOI: 10.1016/j.jcomm.2017.05.002.
• Ekici, Oya & Nemlioğlu, Karun, 2017, "Emerging economies’ short-term private external debt as evidence of economic crisis," Journal of Policy Modeling, Elsevier, volume 39, issue 2, pages 232-246, DOI: 10.1016/j.jpolmod.2017.01.002.
• Atashbar, Tohid & Arani, Abbas Assari & Antoun, Joseph & Bossert, Thomas, 2017, "Health reform policy-making: Fiscal sustainability matters (The case of Iran’s PresidentCare)," Journal of Policy Modeling, Elsevier, volume 39, issue 6, pages 1086-1101, DOI: 10.1016/j.jpolmod.2017.07.005.
• Gilbert, Thomas & Scotti, Chiara & Strasser, Georg & Vega, Clara, 2017, "Is the intrinsic value of a macroeconomic news announcement related to its asset price impact?," Journal of Monetary Economics, Elsevier, volume 92, issue C, pages 78-95, DOI: 10.1016/j.jmoneco.2017.09.008.
• Mei, Dexiang & Liu, Jing & Ma, Feng & Chen, Wang, 2017, "Forecasting stock market volatility: Do realized skewness and kurtosis help?," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 481, issue C, pages 153-159, DOI: 10.1016/j.physa.2017.04.020.
• Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2017, "Measuring firm size distribution with semi-nonparametric densities," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 485, issue C, pages 35-47, DOI: 10.1016/j.physa.2017.05.019.
• Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017, "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, volume 65, issue C, pages 276-284, DOI: 10.1016/j.qref.2017.01.005.
• Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017, "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, volume 65, issue C, pages 50-60, DOI: 10.1016/j.qref.2017.01.002.
• Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2017, "Do cay and cayMS predict stock and housing returns? Evidence from a nonparametric causality test," International Review of Economics & Finance, Elsevier, volume 48, issue C, pages 269-279, DOI: 10.1016/j.iref.2016.12.007.
• Suh, Sangwon, 2017, "Sudden stops of capital flows to emerging markets: A new prediction approach," International Review of Economics & Finance, Elsevier, volume 48, issue C, pages 289-308, DOI: 10.1016/j.iref.2016.12.013.
• Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2017, "Further evidence on bear market predictability: The role of the external finance premium," International Review of Economics & Finance, Elsevier, volume 50, issue C, pages 106-121, DOI: 10.1016/j.iref.2017.03.019.
• Park, Hail & Shin, Yongcheol, 2017, "Exploring international linkages using generalised connectedness measures: The case of Korea," International Review of Economics & Finance, Elsevier, volume 50, issue C, pages 49-64, DOI: 10.1016/j.iref.2017.03.029.
• Caraiani, Petre, 2017, "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, volume 51, issue C, pages 60-81, DOI: 10.1016/j.iref.2017.05.002.
• Buncic, Daniel & Tischhauser, Martin, 2017, "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, volume 51, issue C, pages 621-644, DOI: 10.1016/j.iref.2017.07.006.
• Jalles, João Tovar, 2017, "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, volume 40, issue C, pages 175-189, DOI: 10.1016/j.ribaf.2017.01.007.
• Walther, Thomas & Klein, Tony & Thu, Hien Pham & Piontek, Krzysztof, 2017, "True or spurious long memory in European non-EMU currencies," Research in International Business and Finance, Elsevier, volume 40, issue C, pages 217-230, DOI: 10.1016/j.ribaf.2017.01.003.
• Maggi, Bernardo, 2017, "A technology-based countries-interaction dynamic model for the study of European growth and stability: Were there the conditions for convergence?," Technological Forecasting and Social Change, Elsevier, volume 125, issue C, pages 275-288, DOI: 10.1016/j.techfore.2017.07.002.
• Jason Allen, 2017, "Loan pricing, stress testing and capital allocation," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 60, issue 2, pages 39-64.
• Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017, "Do Central Banks Respond Timely to Developments in the Global Economy?," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2017-20, Mar.
• George Kapetanios & Simon Price & Garry Young, 2017, "A UK Financial Conditions Index Using Targeted Data Reduction: Forecasting and Structural Identification," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2017-58, Sep.
• Thomas Goodwin & Jing Tian, 2017, "A State Space Approach to Evaluate Multi-horizon Forecasts," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2017-67, Nov.
• Beili Zhu, 2017, "Forecasting the Real Price of Oil Under Alternative Specifications of Constant and Time-Varying Volatility," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2017-71, Nov.
• Gómez-Zamudio, Luis M. & Ibarra, Raúl, 2017, "Are daily financial data useful for forecasting GDP? Evidence from Mexico," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 123310, Apr.
• Dassios, Angelos & Zhao, Hongbiao, 2017, "Efficient simulation of clustering jumps with CIR intensity," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 74205, Nov.
• Zivile Zekaite & Gabe de Bondt & Elke Hahn, 2017, "Alice: A New Inflation Monitoring Tool," EcoMod2017, EcoMod, number 10414, Jul.
• Alberto Urtasun & Mara Gil & Javier J. Perez, 2017, "Nowcasting private consumption: traditional indicators, uncertainty measures, and the role of internet search query data," EcoMod2017, EcoMod, number 10745, Jul.
• Jaume García & Levi Pérez & Plácido Rodríguez, 2017, "Forecasting football match results: are the many smarter than the few?," Chapters, Edward Elgar Publishing, chapter 5, in: Plácido Rodríguez & Brad R. Humphreys & Robert Simmons, "The Economics of Sports Betting".
• Worawuth Kongsilp & Cesario Mateus, 2017, "Volatility risk and stock return predictability on global financial crises," China Finance Review International, Emerald Group Publishing Limited, volume 7, issue 1, pages 33-66, February, DOI: 10.1108/CFRI-04-2016-0021.
• Dilip Kumar & Srinivasan Maheswaran, 2017, "Value-at-risk and expected shortfall using the unbiased extreme value volatility estimator," Studies in Economics and Finance, Emerald Group Publishing Limited, volume 34, issue 4, pages 506-526, October, DOI: 10.1108/SEF-03-2016-0061.
• Asai, M. & McAleer, M.J., 2017, "Forecasting the Volatility of Nikkei 225 Futures," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number TI 2017-017/III, Jan.
• Rocío Elizondo, 2017, "Pronósticos de la estructura temporal de las tasas de interés en México con base en un modelo afín," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, volume 32, issue 2, pages 213-253.
• Korobilis, D, 2017, "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 19565, May.
• Kapetanios, G & Price, SG & Young, G, 2017, "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 20328, Aug.
• Dorin JULA & Nicolae Marius JULA, 2017, "Mixed Sampling Panel Data Model for Regional Job Vacancies Forecasting," Eco-Economics Review, Ecological University of Bucharest, Economics Faculty and Ecology and Environmental Protection Faculty, volume 3, issue 1, pages 3-20, June.
• Caterina Astarita & Gaetano D'Adamo, 2017, "Inequality and Structural Reforms: Methodological Concerns and Lessons from Policy," European Economy - Discussion Papers, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, number 071, Dec.
• Matan Mayer & Martin Bechthold, 2017, "Development of policy metrics for circularity assessment in building assemblies," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, volume 2017, issue 1-2, pages 57-84.
• Matej Nevrla, 2017, "Systemic Risk in the European Financial and Energy Sector: Dynamic Factor Copula Approach," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2017/11, May, revised May 2017.
• Jonathan Benchimol & Makram El-Shagi, 2017, "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China, number 2017/1, Dec.
• Makram El-Shagi & Yizhuang Zheng, 2017, "Money Demand in China: A Meta-Study," CFDS Discussion Paper Series, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China, number 2017/3, Dec.
• Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2017, "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," Working Papers, Fondazione Eni Enrico Mattei, number 2017.06, Feb.
• Hovick Shahnazarian & Martin Solberger & Erik Spånberg, 2017, "Forecasting and Analysing Corporate Tax Revenues in Sweden Using Bayesian VAR Models," Finnish Economic Papers, Finnish Economic Association, volume 28, issue 1, pages 50-74, Autumn.
• Michelle L. Barnes & Giovanni P. Olivei, 2017, "Financial variables and macroeconomic forecast errors," Working Papers, Federal Reserve Bank of Boston, number 17-17, Oct.
• Edward S. Knotek & Saeed Zaman, 2017, "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1702, Mar, DOI: 10.26509/frbc-wp-201702.
• Christian Garciga & Edward S. Knotek, 2017, "Forecasting GDP Growth with NIPA Aggregates," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1708, May, DOI: 10.26509/frbc-wp-201708.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017, "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1715, Sep, DOI: 10.26509/frbc-wp-201715.
• Andrew Martinez, 2017, "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1717, Nov, DOI: 10.26509/frbc-wp-201717.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017, "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers, Federal Reserve Bank of Cleveland, number 17-15R, Sep, DOI: 10.26509/frbc-wp-201715r.
• Ayse Kabukcuoglu & Enrique Martínez García & Mehmet A. Soytas, 2017, "Exploring the Nexus Between Inflation and Globalization Under Inflation Targeting Through the Lens of New Zealand’s Experience," Globalization Institute Working Papers, Federal Reserve Bank of Dallas, number 308, Mar, DOI: 10.24149/gwp308.
• Alessandro Barbarino & Efstathia Bura, 2017, "A Unified Framework for Dimension Reduction in Forecasting," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-004, Jan, DOI: 10.17016/FEDS.2017.004.
• Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2017, "What's the Story? A New Perspective on the Value of Economic Forecasts," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-107, Nov, DOI: 10.17016/FEDS.2017.107r1.
• Pablo Guerrón-Quintana & Molin Zhong, 2017, "Macroeconomic Forecasting in Times of Crises," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-018, Jan, DOI: 10.17016/FEDS.2017.018.
• David L. Reifschneider & Peter Tulip, 2017, "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-020, Feb, DOI: 10.17016/FEDS.2017.020.
• Travis J. Berge, 2017, "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-046, Apr, DOI: 10.17016/FEDS.2017.046.
• Todd Prono, 2017, "Regular Variation of Popular GARCH Processes Allowing for Distributional Asymmetry," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-095, Sep, DOI: 10.17016/FEDS.2017.095.
• Neil R. Ericsson, 2017, "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1189, Jan, DOI: 10.17016/IFDP.2017.1189.
• Thomas R. Cook & Aaron Smalter Hall, 2017, "Macroeconomic Indicator Forecasting with Deep Neural Networks," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 17-11, Sep, DOI: 10.18651/RWP2017-11.
• Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017, "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers, Federal Reserve Bank of St. Louis, number 2017-026, Aug, DOI: 10.20955/wp.2017.026.
• Michael W. McCracken & Joseph McGillicuddy, 2017, "An Empirical Investigation of Direct and Iterated Multistep Conditional Forecasts," Working Papers, Federal Reserve Bank of St. Louis, number 2017-40, Nov, DOI: 10.20955/wp.2017.040.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017, "Macroeconomic nowcasting and forecasting with big data," Staff Reports, Federal Reserve Bank of New York, number 830, Nov.