Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2018

• Inske Pirschel & Maik H. Wolters, 2018, "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, volume 55, issue 2, pages 573-596, September, DOI: 10.1007/s00181-017-1286-6.
• Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2018, "Nowcasting Indonesia," Empirical Economics, Springer, volume 55, issue 2, pages 597-619, September, DOI: 10.1007/s00181-017-1288-4.
• Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2018, "Speculative price bubbles in urban housing markets," Empirical Economics, Springer, volume 55, issue 4, pages 1957-1983, December, DOI: 10.1007/s00181-017-1347-x.
• C. Orsenigo & C. Vercellis, 2018, "Anthropogenic influence on global warming for effective cost-benefit analysis: a machine learning perspective," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, volume 45, issue 3, pages 425-442, September, DOI: 10.1007/s40812-018-0092-2.
• Manhal Ali & Reza Salehnejad & Mohaimen Mansur, 2018, "Hospital heterogeneity: what drives the quality of health care," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 19, issue 3, pages 385-408, April, DOI: 10.1007/s10198-017-0891-9.
• Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018, "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 1, pages 1-46, April, DOI: 10.1007/s41549-017-0022-9.
• Fritz Breuss, 2018, "Would DSGE Models Have Predicted the Great Recession in Austria?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 1, pages 105-126, April, DOI: 10.1007/s41549-018-0025-1.
• Pablo Duarte & Bernd Süssmuth, 2018, "Implementing an Approximate Dynamic Factor Model to Nowcast GDP Using Sensitivity Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 1, pages 127-141, April, DOI: 10.1007/s41549-018-0026-0.
• Alain Galli, 2018, "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 2, pages 179-218, November, DOI: 10.1007/s41549-018-0030-4.
• KhasadYahu ZarBabal & Jocelyn Evans, 2018, "Does wall street affect main street? examining potential spillovers from investor stock market sentiment to personal consumption expenditures," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 42, issue 2, pages 293-314, April, DOI: 10.1007/s12197-017-9394-x.
• Vugar Ahmadov & Salman Huseynov & Shaig Adigozalov & Fuad Mammadov & Vugar Rahimov, 2018, "Forecasting inflation in post-oil boom years: A case for regime switches?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 42, issue 2, pages 369-385, April, DOI: 10.1007/s12197-017-9410-1.
• Muhammad Aamir Khan & Naseeb Zada & Kakali Mukhopadhyay, 2018, "Economic implications of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) on Pakistan: a CGE approach," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), volume 7, issue 1, pages 1-20, December, DOI: 10.1186/s40008-017-0103-x.
• M. L. Bertotti & G. Modanese, 2018, "Mathematical models describing the effects of different tax evasion behaviors," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, volume 13, issue 2, pages 351-363, July, DOI: 10.1007/s11403-016-0185-9.
• Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018, "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, volume 46, issue C, pages 111-129, DOI: 10.1016/j.jempfin.2017.12.008.
• Sander, Magnus, 2018, "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, volume 46, issue C, pages 130-145, DOI: 10.1016/j.jempfin.2017.12.002.
• Chen, Ying & Han, Qian & Niu, Linlin, 2018, "Forecasting the term structure of option implied volatility: The power of an adaptive method," Journal of Empirical Finance, Elsevier, volume 49, issue C, pages 157-177, DOI: 10.1016/j.jempfin.2018.09.006.
• Zhu, Bangzhu & Ye, Shunxin & Wang, Ping & He, Kaijian & Zhang, Tao & Wei, Yi-Ming, 2018, "A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting," Energy Economics, Elsevier, volume 70, issue C, pages 143-157, DOI: 10.1016/j.eneco.2017.12.030.
• Wang, Delu & Wang, Yadong & Song, Xuefeng & Liu, Yun, 2018, "Coal overcapacity in China: Multiscale analysis and prediction," Energy Economics, Elsevier, volume 70, issue C, pages 244-257, DOI: 10.1016/j.eneco.2018.01.004.
• Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018, "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, volume 70, issue C, pages 334-356, DOI: 10.1016/j.eneco.2018.01.018.
• Özmen, Ayşe & Yılmaz, Yavuz & Weber, Gerhard-Wilhelm, 2018, "Natural gas consumption forecast with MARS and CMARS models for residential users," Energy Economics, Elsevier, volume 70, issue C, pages 357-381, DOI: 10.1016/j.eneco.2018.01.022.
• Ziel, Florian & Weron, Rafał, 2018, "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, volume 70, issue C, pages 396-420, DOI: 10.1016/j.eneco.2017.12.016.
• Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018, "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, volume 70, issue C, pages 472-483, DOI: 10.1016/j.eneco.2018.01.027.
• Presno, María José & Landajo, Manuel & Fernández González, Paula, 2018, "Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis," Energy Economics, Elsevier, volume 70, issue C, pages 563-581, DOI: 10.1016/j.eneco.2015.10.001.
• Chai, Jian & Xing, Li-Min & Zhou, Xiao-Yang & Zhang, Zhe George & Li, Jie-Xun, 2018, "Forecasting the WTI crude oil price by a hybrid-refined method," Energy Economics, Elsevier, volume 71, issue C, pages 114-127, DOI: 10.1016/j.eneco.2018.02.004.
• Wang, Minggang & Tian, Lixin & Zhou, Peng, 2018, "A novel approach for oil price forecasting based on data fluctuation network," Energy Economics, Elsevier, volume 71, issue C, pages 201-212, DOI: 10.1016/j.eneco.2018.02.021.
• Sephton, Peter & Mann, Janelle, 2018, "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, volume 71, issue C, pages 273-281, DOI: 10.1016/j.eneco.2018.02.022.
• Pan, Zhiyuan & Wang, Qing & Wang, Yudong & Yang, Li, 2018, "Forecasting U.S. real GDP using oil prices: A time-varying parameter MIDAS model," Energy Economics, Elsevier, volume 72, issue C, pages 177-187, DOI: 10.1016/j.eneco.2018.04.008.
• Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018, "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, volume 72, issue C, pages 321-330, DOI: 10.1016/j.eneco.2018.04.023.
• Cheng, Fangzheng & Fan, Tijun & Fan, Dandan & Li, Shanling, 2018, "The prediction of oil price turning points with log-periodic power law and multi-population genetic algorithm," Energy Economics, Elsevier, volume 72, issue C, pages 341-355, DOI: 10.1016/j.eneco.2018.03.038.
• Hahn, Warren J. & DiLellio, James A. & Dyer, James S., 2018, "Risk premia in commodity price forecasts and their impact on valuation," Energy Economics, Elsevier, volume 72, issue C, pages 393-403, DOI: 10.1016/j.eneco.2018.04.018.
• Uddin, Gazi Salah & Rahman, Md Lutfur & Shahzad, Syed Jawad Hussain & Rehman, Mobeen Ur, 2018, "Supply and demand driven oil price changes and their non-linear impact on precious metal returns: A Markov regime switching approach," Energy Economics, Elsevier, volume 73, issue C, pages 108-121, DOI: 10.1016/j.eneco.2018.05.024.
• Jiao, Lei & Liao, Yin & Zhou, Qing, 2018, "Predicting carbon market risk using information from macroeconomic fundamentals," Energy Economics, Elsevier, volume 73, issue C, pages 212-227, DOI: 10.1016/j.eneco.2018.05.008.
• Drachal, Krzysztof, 2018, "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, volume 74, issue C, pages 208-251, DOI: 10.1016/j.eneco.2018.04.043.
• Gong, Xu & Lin, Boqiang, 2018, "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, volume 74, issue C, pages 370-386, DOI: 10.1016/j.eneco.2018.06.005.
• Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018, "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, volume 74, issue C, pages 628-643, DOI: 10.1016/j.eneco.2018.07.009.
• Smith, Michael Stanley & Shively, Thomas S., 2018, "Econometric modeling of regional electricity spot prices in the Australian market," Energy Economics, Elsevier, volume 74, issue C, pages 886-903, DOI: 10.1016/j.eneco.2018.07.013.
• Liu, Li & Wang, Yudong & Yang, Li, 2018, "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, volume 75, issue C, pages 193-205, DOI: 10.1016/j.eneco.2018.08.010.
• Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018, "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, volume 75, issue C, pages 400-409, DOI: 10.1016/j.eneco.2018.09.006.
• Poblete-Cazenave, Miguel & Pachauri, Shonali, 2018, "A structural model of cooking fuel choices in developing countries," Energy Economics, Elsevier, volume 75, issue C, pages 449-463, DOI: 10.1016/j.eneco.2018.09.003.
• Prakash Ranjan, Ravi & Bhattachharyya, Malay, 2018, "Does investor attention to energy stocks exhibit power law?," Energy Economics, Elsevier, volume 75, issue C, pages 573-582, DOI: 10.1016/j.eneco.2018.09.005.
• Funk, Christoph, 2018, "Forecasting the real price of oil - Time-variation and forecast combination," Energy Economics, Elsevier, volume 76, issue C, pages 288-302, DOI: 10.1016/j.eneco.2018.04.016.
• Degiannakis, Stavros & Filis, George, 2018, "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, volume 76, issue C, pages 388-402, DOI: 10.1016/j.eneco.2018.10.026.
• Zhang, Jin & Li, Pujiang & Zhao, Guochang, 2018, "Is power generation really the gold measure of the Chinese economy? A conceptual and empirical assessment," Energy Policy, Elsevier, volume 121, issue C, pages 211-216, DOI: 10.1016/j.enpol.2018.06.030.
• Lyócsa, Štefan & Molnár, Peter, 2018, "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, volume 155, issue C, pages 462-473, DOI: 10.1016/j.energy.2018.04.194.
• de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018, "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, volume 155, issue C, pages 578-591, DOI: 10.1016/j.energy.2018.04.187.
• Elamin, Niematallah & Fukushige, Mototsugu, 2018, "Modeling and forecasting hourly electricity demand by SARIMAX with interactions," Energy, Elsevier, volume 165, issue PB, pages 257-268, DOI: 10.1016/j.energy.2018.09.157.
• Antonakakis, Nikolaos & Chang, Tsangyao & Cunado, Juncal & Gupta, Rangan, 2018, "The relationship between commodity markets and commodity mutual funds: A wavelet-based analysis," Finance Research Letters, Elsevier, volume 24, issue C, pages 1-9, DOI: 10.1016/j.frl.2017.03.005.
• Gupta, Rangan & Mwamba, John W. Muteba & Wohar, Mark E., 2018, "The role of partisan conflict in forecasting the U.S. equity premium: A nonparametric approach," Finance Research Letters, Elsevier, volume 25, issue C, pages 131-136, DOI: 10.1016/j.frl.2017.10.023.
• Ping, Yuan & Li, Rui, 2018, "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, volume 25, issue C, pages 222-229, DOI: 10.1016/j.frl.2017.10.028.
• van der Merwe, C.J. & Heyman, D. & de Wet, T., 2018, "Approximating risk-free curves in sparse data environments," Finance Research Letters, Elsevier, volume 26, issue C, pages 112-118, DOI: 10.1016/j.frl.2017.12.016.
• Kim, Donghan & Kim, Jun Sik & Seo, Sung Won, 2018, "What options to trade and when: Evidence from seasoned equity offerings," Journal of Financial Markets, Elsevier, volume 37, issue C, pages 70-96, DOI: 10.1016/j.finmar.2016.09.006.
• Barunik, Jozef & Vacha, Lukas, 2018, "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, volume 37, issue C, pages 97-119, DOI: 10.1016/j.finmar.2017.11.004.
• Lin, Qi, 2018, "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, volume 38, issue C, pages 103-123, DOI: 10.1016/j.finmar.2017.09.003.
• Baltas, Nick & Karyampas, Dimitrios, 2018, "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, volume 38, issue C, pages 83-102, DOI: 10.1016/j.finmar.2017.11.002.
• Papanikolaou, Nikolaos I., 2018, "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, volume 34, issue C, pages 61-85, DOI: 10.1016/j.jfs.2017.11.005.
• Kupiec, Paul H., 2018, "On the accuracy of alternative approaches for calibrating bank stress test models," Journal of Financial Stability, Elsevier, volume 38, issue C, pages 132-146, DOI: 10.1016/j.jfs.2018.08.001.
• Jåstad, Eirik Ogner & Mustapha, Walid Fayez & Bolkesjø, Torjus Folsland & Trømborg, Erik & Solberg, Birger, 2018, "Modelling of uncertainty in the economic development of the Norwegian forest sector," Journal of Forest Economics, Elsevier, volume 32, issue C, pages 106-115, DOI: 10.1016/j.jfe.2018.04.005.
• Bruszas, Sandy & Kaschützke, Barbara & Maurer, Raimond & Siegelin, Ivonne, 2018, "Unisex pricing of German participating life annuities—Boon or bane for customer and insurance company?," Insurance: Mathematics and Economics, Elsevier, volume 78, issue C, pages 230-245, DOI: 10.1016/j.insmatheco.2017.09.012.
• Börger, Matthias & Schupp, Johannes, 2018, "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, volume 78, issue C, pages 369-380, DOI: 10.1016/j.insmatheco.2017.09.024.
• Doan, Bao & Papageorgiou, Nicolas & Reeves, Jonathan J. & Sherris, Michael, 2018, "Portfolio management with targeted constant market volatility," Insurance: Mathematics and Economics, Elsevier, volume 83, issue C, pages 134-147, DOI: 10.1016/j.insmatheco.2018.09.010.
• Franses, Philip Hans & Janssens, Eva, 2018, "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 57, issue C, pages 261-292, DOI: 10.1016/j.intfin.2018.09.005.
• Knüppel, Malte, 2018, "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," International Journal of Forecasting, Elsevier, volume 34, issue 1, pages 105-116, DOI: 10.1016/j.ijforecast.2017.08.006.
• Clements, Michael P., 2018, "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, volume 34, issue 2, pages 181-198, DOI: 10.1016/j.ijforecast.2017.10.004.
• Smeekes, Stephan & Wijler, Etienne, 2018, "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, volume 34, issue 3, pages 408-430, DOI: 10.1016/j.ijforecast.2018.01.001.
• Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018, "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, volume 34, issue 4, pages 774-787, DOI: 10.1016/j.ijforecast.2018.06.004.
• Berge, Travis J., 2018, "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, volume 34, issue 4, pages 788-801, DOI: 10.1016/j.ijforecast.2018.07.003.
• Herrera, R. & Clements, A.E., 2018, "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, volume 88, issue C, pages 161-175, DOI: 10.1016/j.jbankfin.2017.12.001.
• Grigoli, Francesco & Mansilla, Mario & Saldías, Martín, 2018, "Macro-financial linkages and heterogeneous non-performing loans projections: An application to Ecuador," Journal of Banking & Finance, Elsevier, volume 97, issue C, pages 130-141, DOI: 10.1016/j.jbankfin.2018.09.023.
• Badarinza, Cristian & Ramadorai, Tarun, 2018, "Home away from home? Foreign demand and London house prices," Journal of Financial Economics, Elsevier, volume 130, issue 3, pages 532-555, DOI: 10.1016/j.jfineco.2018.07.010.
• Foroni, Claudia & Ravazzolo, Francesco & Sadaba, Barbara, 2018, "Assessing the predictive ability of sovereign default risk on exchange rate returns," Journal of International Money and Finance, Elsevier, volume 81, issue C, pages 242-264, DOI: 10.1016/j.jimonfin.2017.12.001.
• Amat, Christophe & Michalski, Tomasz & Stoltz, Gilles, 2018, "Fundamentals and exchange rate forecastability with simple machine learning methods," Journal of International Money and Finance, Elsevier, volume 88, issue C, pages 1-24, DOI: 10.1016/j.jimonfin.2018.06.003.
• Ismailov, Adilzhan & Rossi, Barbara, 2018, "Uncertainty and deviations from uncovered interest rate parity," Journal of International Money and Finance, Elsevier, volume 88, issue C, pages 242-259, DOI: 10.1016/j.jimonfin.2017.07.012.
• Proaño, Christian R. & Tarassow, Artur, 2018, "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," Journal of the Japanese and International Economies, Elsevier, volume 50, issue C, pages 60-71, DOI: 10.1016/j.jjie.2018.08.002.
• Debnath, Deepayan & Babu, Suresh & Ghosh, Parijat & Helmar, Michael, 2018, "The impact of India’s food security policy on domestic and international rice market," Journal of Policy Modeling, Elsevier, volume 40, issue 2, pages 265-283, DOI: 10.1016/j.jpolmod.2017.08.006.
• Chen, Junyi & Kibriya, Shahriar & Bessler, David & Price, Edwin, 2018, "The relationship between conflict events and commodity prices in Sudan," Journal of Policy Modeling, Elsevier, volume 40, issue 4, pages 663-684, DOI: 10.1016/j.jpolmod.2018.01.014.
• Bonato, Matteo & Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian, 2018, "Gold futures returns and realized moments: A forecasting experiment using a quantile-boosting approach," Resources Policy, Elsevier, volume 57, issue C, pages 196-212, DOI: 10.1016/j.resourpol.2018.03.004.
• Pan, Zhiyuan & Liu, Li, 2018, "Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 492, issue C, pages 168-180, DOI: 10.1016/j.physa.2017.09.030.
• Fang, Libing & Xiao, Binqing & Yu, Honghai & You, Qixing, 2018, "A stable systemic risk ranking in China’s banking sector: Based on principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 492, issue C, pages 1997-2009, DOI: 10.1016/j.physa.2017.11.115.
• Duan, Yinying & Chen, Wang & Zeng, Qing & Liu, Zhicao, 2018, "Leverage effect, economic policy uncertainty and realized volatility with regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 493, issue C, pages 148-154, DOI: 10.1016/j.physa.2017.10.040.
• Chen, Yanhui & Zhang, Chuan & He, Kaijian & Zheng, Aibing, 2018, "Multi-step-ahead crude oil price forecasting using a hybrid grey wave model," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 501, issue C, pages 98-110, DOI: 10.1016/j.physa.2018.02.061.
• Bonaccolto, G. & Caporin, M. & Gupta, R., 2018, "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 507, issue C, pages 446-469, DOI: 10.1016/j.physa.2018.05.061.
• Hassani, Hossein & Silva, Emmanuel Sirimal & Gupta, Rangan & Das, Sonali, 2018, "Predicting global temperature anomaly: A definitive investigation using an ensemble of twelve competing forecasting models," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 509, issue C, pages 121-139, DOI: 10.1016/j.physa.2018.05.147.
• He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018, "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, volume 510, issue C, pages 15-25, DOI: 10.1016/j.physa.2018.05.135.
• Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018, "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, volume 68, issue C, pages 132-142, DOI: 10.1016/j.qref.2017.11.007.
• Nowotarski, Jakub & Weron, Rafał, 2018, "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, volume 81, issue P1, pages 1548-1568, DOI: 10.1016/j.rser.2017.05.234.
• Skjerpen, Terje & Storrøsten, Halvor Briseid & Rosendahl, Knut Einar & Osmundsen, Petter, 2018, "Modelling and forecasting rig rates on the Norwegian Continental Shelf," Resource and Energy Economics, Elsevier, volume 53, issue C, pages 220-239, DOI: 10.1016/j.reseneeco.2018.05.004.
• Zhu, Min & Chen, Rui & Du, Ke & Wang, You-Gan, 2018, "Dividend growth and equity premium predictability," International Review of Economics & Finance, Elsevier, volume 56, issue C, pages 125-137, DOI: 10.1016/j.iref.2017.10.020.
• Ari, Ali & Cergibozan, Raif, 2018, "Currency crises in Turkey: An empirical assessment," Research in International Business and Finance, Elsevier, volume 46, issue C, pages 281-293, DOI: 10.1016/j.ribaf.2018.04.001.
• Stahl, Dale O., 2018, "Assessing the forecast performance of models of choice," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, volume 73, issue C, pages 86-92, DOI: 10.1016/j.socec.2018.02.006.
• Deaton, Angus & Cartwright, Nancy, 2018, "Understanding and misunderstanding randomized controlled trials," Social Science & Medicine, Elsevier, volume 210, issue C, pages 2-21, DOI: 10.1016/j.socscimed.2017.12.005.
• Gurgul, Henryk & Lach, Łukasz, 2018, "On using dynamic IO models with layers of techniques to measure value added in global value chains," Structural Change and Economic Dynamics, Elsevier, volume 47, issue C, pages 155-170, DOI: 10.1016/j.strueco.2018.07.004.
• Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018, "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, volume 128, issue C, pages 104-117, DOI: 10.1016/j.techfore.2017.11.001.
• Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018, "International Transmissions of Aggregate Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2018-16, Apr.
• Joshua C.C. Chan & Liana Jacobi & Dan Zhu, 2018, "How Sensitive Are VAR Forecasts to Prior Hyperparameters? An Automated Sensitivity Analysis," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2018-25, May.
• Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018, "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2018-26, May.
• Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018, "Stochastic Volatility Models with ARMA Innovations: An Application to G7 Inflation Forecasts," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2018-32, Jun.
• Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2018, "Real-Time Forecast Combinations for the Oil Price," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2018-38, Aug.
• Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018, "Nowcasting New Zealand GDP Using Machine Learning Algorithms," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2018-47, Sep.
• Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018, "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 90382, Aug.
• Paule Vianez, Jessica & Granado Sánchez, Manuel & Coca Pérez, José Luis, 2018, "Método Bootstrap para el cálculo de provisiones técnicas por siniestros," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).
• Jens Prüfer & Patricia Prüfer, 2018, "Data science for institutional and organizational economics," Chapters, Edward Elgar Publishing, chapter 28, in: Claude Ménard & Mary M. Shirley, "A Research Agenda for New Institutional Economics".
• Pan Feng & Junhui Qian, 2018, "Analyzing and forecasting the Chinese term structure of interest rates using functional principal component analysis," China Finance Review International, Emerald Group Publishing Limited, volume 8, issue 3, pages 275-296, April, DOI: 10.1108/CFRI-06-2017-0065.
• Qi Deng, 2018, "A generalized VECM/VAR-DCC/ADCC framework and its application in the Black-Litterman model," China Finance Review International, Emerald Group Publishing Limited, volume 8, issue 4, pages 453-467, March, DOI: 10.1108/CFRI-07-2016-0095.
• Juan DU, 2018, "Empirical differences between the overnight and day trading hour returns," China Finance Review International, Emerald Group Publishing Limited, volume 8, issue 3, pages 315-331, May, DOI: 10.1108/CFRI-10-2017-0213.
• Rosylin Mohd Yusof & Farrell Hazsan Usman & Akhmad Affandi Mahfudz & Ahmad Suki Arif, 2018, "Macroeconomic shocks, fragility and home financing in Malaysia: can rental index be the answer?," Journal of Islamic Accounting and Business Research, Emerald Group Publishing Limited, volume 9, issue 1, pages 17-44, January, DOI: 10.1108/JIABR-11-2015-0058.
• Pierre Rostan & Alexandra Rostan, 2018, "Will Saudi Arabia get older? Will its pension system be sustainable? Spectral answers," PSU Research Review, Emerald Group Publishing Limited, volume 2, issue 3, pages 189-205, April, DOI: 10.1108/PRR-12-2017-0045.
• Franses, Ph.H.B.F., 2018, "Model-based forecast adjustment; with an illustration to inflation," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2018-14, Mar.
• Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2018, "Dynamic return and volatility spillovers among S&P 500, crude oil and gold," Working Papers, Eastern Mediterranean University, Department of Economics, number 15-46.
• George A. Dyer & Alan Hernández-Solano & Pablo Meza-Pale & Héctor Robles-Berlanga & Antonio Yúnez-Naude, 2018, "Mexican agriculture and policy under NAFTA," Serie documentos de trabajo del Centro de Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, number 2018-04, Jun.
• Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018, "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, number 2018-05, Jul.
• Carlos A. Rodríguez, 2018, "Fuentes de las fluctuaciones macroeconómicas en Puerto Rico\Sources of macroeconomic fluctuations in Puerto Rico," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, volume 33, issue 2, pages 219-252.
• R.G. Akhmadeev & O.A. Bykanova & N.V. Philippova & I.V. Vashchekina & T.B. Turishcheva, 2018, "Macroeconomic Indicators and their Impact on the Foreign Debt Burden: The Case of BRICS Countries," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), volume 0, issue 2, pages 68-82.
• M. Kruk & A. Semenov & A. Cherepovitsyn & A. Nikulina, 2018, "Environmental and Economic Damage from the Development of Oil and Gas Fields in the Arctic Shelf of the Russian Federation," European Research Studies Journal, European Research Studies Journal, volume 0, issue Special 2, pages 423-433.
• Josep Lluís Raymond & Dolors Cotrina & Àlex Costa & Enric Puig & Vittorio Galletto & Sandra Aguilera & Marc Fíguls, 2018, "GDP estimation for Barcelona and the Barcelona Metropolitan Area. Methodological improvement in the estimation of productivity dynamics with wage information," Institut Metròpoli Working Paper in economics, Institut Metròpoli, number 1801, Feb.
• Korobilis, Dimitris & Koop, Gary, 2018, "Variational Bayes inference in high-dimensional time-varying parameter models," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 22665, Jul.
• Gustavo Félix Verduzco. & David Castro Lugo. & Gilberto Aboites Manrique., 2018, "Nuevas barreras comerciales de EU a las importaciones automotrices y posibles efectos en el empleo regional," Economía: teoría y práctica, Universidad Autónoma Metropolitana, México, volume 0, issue 2, pages 125-176, Agosto, DOI: 10.24275/ETYPUAM/NE/E042018/Felix.
• Natalya Gennadievna Dzhurka, 2018, "Spatial Concentration of Industrial Production in Russia: Testing the Home Market Effectûíêà," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 3, pages 19-42, DOI: 10.14530/se.2018.3.019-042.
• Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018, "A model of FED'S view on inflation," Documents de Travail de l'OFCE, Observatoire Francais des Conjonctures Economiques (OFCE), number 2018-03, Jan.
• Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018, "On the robustness of the principal volatility components," Textos para discussão, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil), number 474, Mar.
• Ellis W. Tallman & Saeed Zaman, 2018, "Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1809, Jun, DOI: 10.26509/frbc-wp-201809.
• Jonathan Benchimol & Lahcen Bounader, 2018, "Optimal Monetary Policy Under Bounded Rationality," Globalization Institute Working Papers, Federal Reserve Bank of Dallas, number 336, Jan, DOI: 10.24149/gwp336.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz & Tyler Radler, 2018, "Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2018-005, Jan, DOI: 10.17016/FEDS.2018.005.
• Andrew C. Chang, 2018, "The Fed's Asymmetric Forecast Errors," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2018-026, Apr, DOI: 10.17016/FEDS.2018.026.
• Laura Liu, 2018, "Density Forecasts in Panel Data Models : A Semiparametric Bayesian Perspective," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2018-036, May, DOI: 10.17016/FEDS.2018.036.
• Daniel Baquero & Manuel Gonzalez-Astudillo, 2018, "A Nowcasting Model for the Growth Rate of Real GDP of Ecuador : Implementing a Time-Varying Intercept," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2018-044, Jul, DOI: 10.17016/FEDS.2018.044.
• Jun Nie & Amy Oksol, 2018, "Forecasting Current-Quarter U.S.Exports Using Satellite Data," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 5-24, DOI: 10.18651/ER/2q18nieoksol.
• Aaron Smalter Hall, 2018, "Machine Learning Approaches to Macroeconomic Forecasting," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 63-81, DOI: 10.18651/ER/4q18SmalterHall.
• Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018, "Economic predictions with big data: the illusion of sparsity," Staff Reports, Federal Reserve Bank of New York, number 847, Apr.
• Eyyüp Ensari ŞAHİN, 2018, "Crypto Money Bitcoin: Price Estimation with ARIMA and Artificial Neural Networks," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 3.
• Samvel S. Lazaryan & Nikita E. German, 2018, "Forecasting Current GDP Dynamics With Google Search Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 83-94, December, DOI: 10.31107/2075-1990-2018-6-83-94.
• Cornel Coca Constantinescu & Ion Stancu & Iulian Panait, 2018, "Studiu de impact al asigurărilor auto telematice," Journal of Financial Studies, Institute of Financial Studies, volume 4, issue 3, pages 19-38, June.
• Knobel Alexander & Firanchuk Alexander & Tsukhlo Sergey & Uzun Vasily & Tishchenko Tatiana, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 10, pages 1-24, May.
• Trunin Pavel & Tsukhlo Sergey & Kiyutsevskaya Anna & Poliakova Aleksandra & Polbin Andrei, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 12, pages 1-18, June.
• Trunin Pavel & Khromov Mikhail & Lyashok Viktor & Kiyutsevskaya Anna & Gadiy Ludmila & Sherbustanova Maria, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 17, pages 1-18, October.
• Avraamova Elena & Loginov Dmitry & Khromov Mikhail & Tsukhlo Sergey & Kaukin Andrey & Miller Evgenia & Khudko Elizaveta, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 19, pages 1-20, November.
• Sinelnikov-Murylev Sergey & Drobyshevsky Sergey & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Khromov Mikhail & Tsukhlo Sergey & Khasanova Ramilya, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 2, pages 1-27, February.
• Khromov Mikhail & Tsukhlo Sergey & Uzun Vasily & Zubarevich Natalia, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 21, pages 1-20, December.
• Avraamova Elena & Loginov Dmitry & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Khromov Mikhail & Tsukhlo Sergey, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 4, pages 1-27, March.
• Bobylev Yuri & Khromov Mikhail & Tsukhlo Sergey & Khasanova Ramilya & Tretiakova Elena & Osmakov Vasiliy, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 6, pages 1-25, March.
• Knobel Alexander & Firanchuk Alexander & Tsukhlo Sergey & Uzun Vasily & Tishchenko Tatiana, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 10, pages 1-23, May.
• Trunin Pavel & Tsukhlo Sergey & Kiyutsevskaya Anna & Poliakova Aleksandra & Polbin Andrei, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 1-18, June.
• Trunin Pavel & Khromov Mikhail & Lyashok Viktor & Kiyutsevskaya Anna & Gadiy Ludmila & Sherbustanova Maria, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 17, pages 1-16, October.
• Sinelnikov-Murylev Sergey & Drobyshevsky Sergey & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Khromov Mikhail & Tsukhlo Sergey & Khasanova Ramilya, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 2, pages 1-27, February.
• Khromov Mikhail & Tsukhlo Sergey & Uzun Vasily & Zubarevich Natalia, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 21, pages 1-17, December.
• Avraamova Elena & Loginov Dmitry & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Khromov Mikhail & Tsukhlo Sergey, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 4, pages 1-27, March.
• Bobylev Yuri & Tsukhlo Sergey & Khasanova Ramilya & Tretiakova Elena & Osmakov Vasiliy, 2018, "Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 6, pages 1-20, March.
• Tsukhlo Sergey, 2018, "Russian industrial enterprises in 2017 (on business surveys’ findings)," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2018-307, revised 2018.
• Barinova Vera & Zemtsov Tsepan & Tsareva Yulia, 2018, "Small and medium-sized enterprises in 2016–2017," Published Papers, Gaidar Institute for Economic Policy, number ppaper-2018-312, revised 2018.
• Bartosz Uniejewski & Rafał Weron, 2018, "Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models," Energies, MDPI, volume 11, issue 8, pages 1-26, August.
• Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018, "Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, volume 11, issue 9, pages 1-20, September.
• Pedro Gajardo & Luc Doyen, 2018, "Viability standards and multi-criteria maximin," Cahiers du GREThA (2007-2019), Groupe de Recherche en Economie Théorique et Appliquée (GREThA), number 2018-04.
• Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2018, "Choice of Benchmark When Forecasting Long-term Stock Returns," Graz Economics Papers, University of Graz, Department of Economics, number 2018-08, Apr.
• Jonas Dovern & Hans Manner, 2018, "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," Graz Economics Papers, University of Graz, Department of Economics, number 2018-09, Apr.
• Gabriel Mathy & Christian Roatta, 2018, "Forecasting the 1937-1938 Recession: Quantifying Contemporary Newspaper Forecasts," Working Papers, The George Washington University, The Center for Economic Research, number 2018-004, Nov.
• Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018, "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers, The George Washington University, The Center for Economic Research, number 2018-005, Nov, revised May 2019.
• Carl Singleton & J. James Reade & Alsdair Brown, 2018, "Going with your Gut: The (In)accuracy of Forecast Revisions in a Football Score Prediction Game," Working Papers, The George Washington University, The Center for Economic Research, number 2018-006, Nov.
• Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018, "Nowcasting GDP Growth by Reading Newspapers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number hal-03205161, DOI: 10.24187/ecostat.2018.505d.1964.
• Stephen Bazen & Jean-Marie Cardebat, 2018, "Forecasting Bordeaux wine prices using state-space methods," Post-Print, HAL, number hal-01867216, Oct, DOI: 10.1080/00036846.2018.1472740.
• Serge Darolles & Christian Francq & Sébastien Laurent, 2018, "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print, HAL, number hal-01980815, Jun, DOI: 10.1016/j.jeconom.2018.02.003.
• Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018, "Nowcasting GDP Growth by Reading Newspapers," Post-Print, HAL, number hal-03205161, DOI: 10.24187/ecostat.2018.505d.1964.
• Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2018, "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print, HAL, number hal-04590149, Dec.
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• Serge Darolles & Christian Francq & Sébastien Laurent, 2018, "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print, HAL, number hal-04590232, Jun.
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• Serge Darolles & Christian Francq & Sébastien Laurent, 2018, "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print, HAL, number hal-05417292, Jun, DOI: 10.1016/j.jeconom.2018.02.003.
• David Lee, 2018, "Pricing Financial Derivatives Subject to Counterparty Risk and Credit Value Adjustment," Working Papers, HAL, number hal-01758922, Apr.
• Marcel Bräutigam & Michel Dacorogna & Marie Kratz, 2018, "Predicting risk with risk measures : an empirical study," Working Papers, HAL, number hal-01791026, Feb.
• Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018, "A model of the FED's view on inflation," Working Papers, HAL, number hal-03458456, Jan.
• Serge Darolles & Christian Francq & Sébastien Laurent, 2018, "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers, HAL, number halshs-01944656, Dec.
• Vanella, Patrizio & Deschermeier, Philipp, 2018, "A Principal Component Simulation of Age-Specific Fertility - Impacts of Family and Social Policy on Reproductive Behavior in Germany," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, number dp-630, Apr.
• Vanella, Patrizio & Deschermeier, Philipp, 2018, "A Probabilistic Cohort-Component Model for Population Forecasting - The Case of Germany," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, number dp-638, Sep.
• Steffen Q. Mueller, 2018, "Pre- and within-season attendance forecasting in Major League Baseball: A random forest approach," Working Papers, Chair for Economic Policy, University of Hamburg, number 065, Jun.
• Mirjana Čižmešija & Zrinka Orlović, 2018, "Consumer Confidence Indicator As A Leading Indicator Of Changes In Retail Trade Turnover," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), volume 69, issue 1, pages 3-19.
• Lindholm, Unn & Mossfeldt, Marcus & Stockhammar, Pär, 2018, "Forecasting Inflation in Sweden," Working Papers, National Institute of Economic Research, number 152, Nov.
• George Borshchevskiy, 2018, "Improvement of Evaluation Approaches of the Russian Public Programs," HSE Economic Journal, National Research University Higher School of Economics, volume 22, issue 1, pages 110-134.
• Igor Gurkov & Evgeniy Morgunov & Zokirzhon Saidov & Alexander Arshavsky, 2018, "Perspectives of Manufacturing Subsidiaries of Foreign Companies in Russia: Frontier, Faubourg or Sticks?," Foresight and STI Governance, National Research University Higher School of Economics, volume 12, issue 2, pages 24-35.
• Ricardo Seidl da Fonseca & Alex Pinheiro Veloso, 2018, "The Practice and Future of Financing Science, Technology, and Innovation," Foresight and STI Governance, National Research University Higher School of Economics, volume 12, issue 2, pages 6-22.
• Timofei Nestik, 2018, "The Psychological Aspects of Corporate Foresight," Foresight and STI Governance, National Research University Higher School of Economics, volume 12, issue 2, pages 78-90.
• Evgeniy M. Ozhegov & Alina Ozhegova, 2018, "Segmentation of Theatre Audiences: A Latent Class Approach for Combined Data," HSE Working papers, National Research University Higher School of Economics, number WP BRP 198/EC/2018.
• Evgeniy M. Ozhegov & Daria Teterina, 2018, "The Ensemble Method For Censored Demand Prediction," HSE Working papers, National Research University Higher School of Economics, number WP BRP 200/EC/2018.
• Li, Jinjing & Wang, Xinmei & Yuan, Chang & Xu, Jing, 2018, "The Role of Public Pensions in Income Inequality among Elderly Households in China 1988–2013," CIS Discussion paper series, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University, number 674, Dec.
• Xu, Jing & Wang, Xinmei, 2018, "Working Longer in China: Implicit Tax or Subsidy?," CIS Discussion paper series, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University, number 675, Dec.
• Garegnani, Lorena & Gómez Aguirre, Maximiliano, 2018, "Forecasting Inflation in Argentina," IDB Publications (Working Papers), Inter-American Development Bank, number 8940, Jun, DOI: http://dx.doi.org/10.18235/0001160.
• Libonatti, Luis, 2018, "MIDAS Modeling for Core Inflation Forecasting," IDB Publications (Working Papers), Inter-American Development Bank, number 9035, Jul, DOI: http://dx.doi.org/10.18235/0001250.
• Castañeda-Fuentes, Juan Carlos & Valle-Samayoa, Héctor Augusto & Catalán-Herrera, Juan Carlos & Arriaza-Herrera, Juan Carlos & Gutiérrez-Morales, José & Castillo-Maldonado, Carlos Eduardo & Galindo-Go, 2018, "Evaluation of Inflation Forecasting Models in Guatemala," IDB Publications (Working Papers), Inter-American Development Bank, number 9054, Jul, DOI: http://dx.doi.org/10.18235/0001266.
• Saiful Anwar & A.M Hasan Ali, 2018, "ANNs-BASED EARLY WARNING SYSTEM FOR INDONESIAN ISLAMIC BANKS," Bulletin of Monetary Economics and Banking, Bank Indonesia, volume 20, issue 3, pages 325-342, January, DOI: https://doi.org/10.21098/bemp.v20i3.
• Tarsidin & Idham & Robbi Nur Rakhman, 2018, "Nowcasting Household Consumption And Investment In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, volume 20, issue 3, pages 375-403, January, DOI: https://doi.org/10.21098/bemp.v20i3.
• Profita Sumunar Luthfiana & Nasrudin, 2018, "Disaggregation And Forecasting Of The Monthly Indonesian Gross Domestic Product (Gdp)," Bulletin of Monetary Economics and Banking, Bank Indonesia, volume 20, issue 4, pages 529-556, April, DOI: https://doi.org/10.21098/bemp.v20i4.
• Luigi Grossi & Fany Nan, 2018, "The influence of renewables on electricity price forecasting: a robust approach," Working Papers, Institut d'Economia de Barcelona (IEB), number 2018/10.
• Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2018, "LASSO-driven inference in time and space," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP36/18, Jun.