Report NEP-CMP-2019-09-09

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• Denis Shibitov & Mariam Mamedli, 2019. "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series wps43, Bank of Russia.
• Haoqian Li & Thomas Lau, 2019. "Reinforcement Learning: Prediction, Control and Value Function Approximation," Papers 1908.10771, arXiv.org.
• Tölö, Eero, 2019. "Predicting systemic financial crises with recurrent neural networks," Research Discussion Papers 14/2019, Bank of Finland.
• Stephan Leitner & Friederike Wall, 2019. "Decision-facilitating information in hidden-action setups: An agent-based approach," Papers 1908.07998, arXiv.org, revised Apr 2020.
• Francisco C. Pereira, 2019. "Rethinking travel behavior modeling representations through embeddings," Papers 1909.00154, arXiv.org.
• Kerda Varaku, 2019. "Stock Price Forecasting and Hypothesis Testing Using Neural Networks," Papers 1908.11212, arXiv.org.
• Freund, Florian & Pelikan, Janine & Banse, Martin, 2019. "Losing Preferential Access to Third Countries After Brexit - What is at Stake?," 59th Annual Conference, Braunschweig, Germany, September 25-27, 2019 292298, German Association of Agricultural Economists (GEWISOLA).
• Chen, Jian & Katchova, Ani, 2019. "Agricultural Loan Delinquency Prediction Using Machine Learning Methods," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 290745, Agricultural and Applied Economics Association.
• Denis Belomestny & Leonid Iosipoi, 2019. "Fourier transform MCMC, heavy tailed distributions and geometric ergodicity," Papers 1909.00698, arXiv.org, revised Dec 2019.
• Francesco Di Comite & Giovanni Mandras & Stylianos Sakkas, 2019. "The impact of the Grand Paris Express on the European regions: a RHOMOLO analysis," JRC Working Papers on Territorial Modelling and Analysis 2019-08, Joint Research Centre.
• Pawel Kliber & Anna Rutkowska-Ziarko, 2019. "An algorithm for construction of a portfolio with a fundamental criterion," Proceedings of Economics and Finance Conferences 8911300, International Institute of Social and Economic Sciences.
• G'abor Petneh'azi, 2019. "Quantile Convolutional Neural Networks for Value at Risk Forecasting," Papers 1908.07978, arXiv.org, revised Sep 2020.
• Nobuhiro Hosoe, 2019. "Impact of Tighter Controls on Japanese Chemical Exports to Korea," GRIPS Discussion Papers 19-17, National Graduate Institute for Policy Studies.
• Gunawan, David & Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc, 2019. "Subsampling Sequential Monte Carlo for Static Bayesian Models," Working Paper Series 371, Sveriges Riksbank (Central Bank of Sweden).
• Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2019. "Does the Estimation of the Propensity Score by Machine Learning Improve Matching Estimation? The Case of Germany's Programmes for Long Term Unemployed," IZA Discussion Papers 12526, Institute of Labor Economics (IZA).
• Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
• Sagyndykova, Galiya & Oaxaca, Ronald L., 2019. "Raising the Overtime Premium and Reducing the Standard Workweek: Short-Run Impacts on U.S. Manufacturing," IZA Discussion Papers 12557, Institute of Labor Economics (IZA).
• Adam M. Guren & Timothy J. McQuade, 2019. "How Do Foreclosures Exacerbate Housing Downturns?," NBER Working Papers 26216, National Bureau of Economic Research, Inc.
• Samuel Asante Gyamerah, 2019. "Are Bitcoins price predictable? Evidence from machine learning techniques using technical indicators," Papers 1909.01268, arXiv.org.
• Zhou, Yujun & Baylis, Kathy, 2019. "Predict Food Security with Machine Learning: Application in Eastern Africa," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291056, Agricultural and Applied Economics Association.
• François Legendre, 2019. "L’émergence et la consolidation des méthodes de microsimulation en France," Erudite Working Paper 2019-20, Erudite.
• Emerson G. Escolar & Yasuaki Hiraoka & Mitsuru Igami & Yasin Ozcan, 2019. "Mapping Firms' Locations in Technological Space: A Topological Analysis of Patent Statistics," Papers 1909.00257, arXiv.org, revised Mar 2022.
• Ni, Yuanming, 2019. "Optimization of age-structured bioeconomic model: recruitment, weight gain and environmental effects," Discussion Papers 2019/4, Norwegian School of Economics, Department of Business and Management Science.
• Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," Papers 1908.11498, arXiv.org, revised Oct 2019.
• Ben Broadbent & Federico Di Pace & Thomas Drechsel & Richard Harrison & Silvana Tenreyro, 2019. "The Brexit Vote, Productivity Growth and Macroeconomic Adjustments in the United Kingdom," Discussion Papers 1916, Centre for Macroeconomics (CFM).
• Ni, Yuanming & Sandal, Leif K. & Kvamsdal, Sturla F. & Poudel, Diwakar, 2019. "Greed is good: from super-harvest to recovery in a stochastic predator-prey system," Discussion Papers 2019/5, Norwegian School of Economics, Department of Business and Management Science.
• Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
• Jayawickrema, Vishuddhi, 2019. "Monetary Policy Rules and Macroeconomic Stability," MPRA Paper 95590, University Library of Munich, Germany.
• Arthur Seibold, 2019. "Reference Points for Retirement Behavior: Evidence from German Pension Discontinuities," CESifo Working Paper Series 7799, CESifo.