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. Stanley Miles issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

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, Bank of Russia, number wps43, Aug.
• Haoqian Li & Thomas Lau, 2019, "Reinforcement Learning: Prediction, Control and Value Function Approximation," Papers, arXiv.org, number 1908.10771, Aug.
• Item repec:bof:bofrdp:2019_014 is not listed on IDEAS anymore

• Stephan Leitner & Friederike Wall, 2019, "Decision-facilitating information in hidden-action setups: An agent-based approach," Papers, arXiv.org, number 1908.07998, Aug, revised Apr 2020.
• Francisco C. Pereira, 2019, "Rethinking travel behavior modeling representations through embeddings," Papers, arXiv.org, number 1909.00154, Aug.
• Kerda Varaku, 2019, "Stock Price Forecasting and Hypothesis Testing Using Neural Networks," Papers, arXiv.org, number 1908.11212, Aug.
• Freund, Florian & Pelikan, Janine & Banse, Martin, , "Losing Preferential Access to Third Countries After Brexit - What is at Stake?," 59th Annual Conference, Braunschweig, Germany, September 25-27, 2019, German Association of Agricultural Economists (GEWISOLA), number 292298, DOI: 10.22004/ag.econ.292298.
• Chen, Jian & Katchova, Ani, , "Agricultural Loan Delinquency Prediction Using Machine Learning Methods," 2019 Annual Meeting, July 21-23, Atlanta, Georgia, Agricultural and Applied Economics Association, number 290745, DOI: 10.22004/ag.econ.290745.
• Denis Belomestny & Leonid Iosipoi, 2019, "Fourier transform MCMC, heavy tailed distributions and geometric ergodicity," Papers, arXiv.org, number 1909.00698, Sep, 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, Joint Research Centre, number 2019-08, Aug.
• Pawel Kliber & Anna Rutkowska-Ziarko, 2019, "An algorithm for construction of a portfolio with a fundamental criterion," Proceedings of Economics and Finance Conferences, International Institute of Social and Economic Sciences, number 8911300, Jul.
• G'abor Petneh'azi, 2019, "Quantile Convolutional Neural Networks for Value at Risk Forecasting," Papers, arXiv.org, number 1908.07978, Aug, revised Sep 2020.
• Nobuhiro Hosoe, 2019, "Impact of Tighter Controls on Japanese Chemical Exports to Korea," GRIPS Discussion Papers, National Graduate Institute for Policy Studies, number 19-17, Sep.
• Gunawan, David & Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc, 2019, "Subsampling Sequential Monte Carlo for Static Bayesian Models," Working Paper Series, Sveriges Riksbank (Central Bank of Sweden), number 371, Apr.
• 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, Institute of Labor Economics (IZA), number 12526, Aug.
• Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019, "Predicting Returns With Text Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 26186, Aug.
• 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, Institute of Labor Economics (IZA), number 12557, Aug.
• Adam M. Guren & Timothy J. McQuade, 2019, "How Do Foreclosures Exacerbate Housing Downturns?," NBER Working Papers, National Bureau of Economic Research, Inc, number 26216, Aug.
• Samuel Asante Gyamerah, 2019, "Are Bitcoins price predictable? Evidence from machine learning techniques using technical indicators," Papers, arXiv.org, number 1909.01268, Sep.
• Zhou, Yujun & Baylis, Kathy, , "Predict Food Security with Machine Learning: Application in Eastern Africa," 2019 Annual Meeting, July 21-23, Atlanta, Georgia, Agricultural and Applied Economics Association, number 291056, DOI: 10.22004/ag.econ.291056.
• François Legendre, 2019, "L’émergence et la consolidation des méthodes de microsimulation en France," Erudite Working Paper, Erudite, number 2019-20.
• Emerson G. Escolar & Yasuaki Hiraoka & Mitsuru Igami & Yasin Ozcan, 2019, "Mapping Firms' Locations in Technological Space: A Topological Analysis of Patent Statistics," Papers, arXiv.org, number 1909.00257, Aug, revised Mar 2022.
• Ni, Yuanming, 2019, "Optimization of age-structured bioeconomic model: recruitment, weight gain and environmental effects," Discussion Papers, Norwegian School of Economics, Department of Business and Management Science, number 2019/4, Sep.
• Stefania Albanesi & Domonkos F. Vamossy, 2019, "Predicting Consumer Default: A Deep Learning Approach," Papers, arXiv.org, number 1908.11498, Aug, 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, Centre for Macroeconomics (CFM), number 1916, Aug.
• 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, Norwegian School of Economics, Department of Business and Management Science, number 2019/5, Sep.
• Huber, Martin, 2019, "An introduction to flexible methods for policy evaluation," FSES Working Papers, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland, number 504, Aug.
• Jayawickrema, Vishuddhi, 2019, "Monetary Policy Rules and Macroeconomic Stability," MPRA Paper, University Library of Munich, Germany, number 95590, Jan.
• Arthur Seibold, 2019, "Reference Points for Retirement Behavior: Evidence from German Pension Discontinuities," CESifo Working Paper Series, CESifo, number 7799.

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. Stanley Miles issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report: