Report NEP-CMP-2018-09-24

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:

• Eitan Sapiro-Gheiler, 2018. ""Read My Lips": Using Automatic Text Analysis to Classify Politicians by Party and Ideology," Papers 1809.00741, arXiv.org.
• Nazareth, M. & Cunha, D. & Gurgel, A., 2018. "Climate Change, Agricultural Productivity and Economic Performance: an exercise using a Dynamic CGE Model," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275876, International Association of Agricultural Economists.
• Somsri Banditvilai & Siriluck Anansatitzin, 2018. "Comparative Study of Three Time Series Methods in Forecasting Dengue Hemorrhagic Fever Incidence in Thailand," Proceedings of International Academic Conferences 6409199, International Institute of Social and Economic Sciences.
• Akina Ikudo & Julia Lane & Joseph Staudt & Bruce Weinberg, 2018. "Occupational Classifications: A Machine Learning Approach," NBER Working Papers 24951, National Bureau of Economic Research, Inc.
• Verteramo Chiu, Leslie J. & Tauer, Loren W. & Al-Mamun, Mohammad A. & Kaniyamattam, Karun & Smith, Rebecca L. & Grohn, Yrjo, 2017. "An Agent-Based Model Evaluation of Economic Control Strategies for Paratuberculosis in a Dairy Herd," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258216, Agricultural and Applied Economics Association.
• ARNOLD, Florian & SÖRENSEN, Kenneth, 2019. "A progressive filtering heuristic for the location-routing problem and variants," Working Papers 2018010, University of Antwerp, Faculty of Business and Economics.
• Ikudo, Akina & Lane, Julia & Staudt, Joseph & Weinberg, Bruce A., 2018. "Occupational Classifications: A Machine Learning Approach," IZA Discussion Papers 11738, Institute of Labor Economics (IZA).
• Itf, 2017. "Shared Mobility Simulations for Auckland," International Transport Forum Policy Papers 41, OECD Publishing.
• Akina Ikudo & Julia Lane & Joseph Staudt & Bruce Weinberg, 2018. "Occupational Classifications: A Machine Learning Approach," Working Papers 18-37, Center for Economic Studies, U.S. Census Bureau.
• Farah Zawaideh & Raed Sahawneh, 2018. "Improve Naïve Bayesian Classifier by Using Genetic Algorithm for Arabic Document," Proceedings of International Academic Conferences 6409186, International Institute of Social and Economic Sciences.
• Victor Chernozhukov & Whitney K Newey & Rahul Singh, 2018. "Automatic Debiased Machine Learning of Causal and Structural Effects," Papers 1809.05224, arXiv.org, revised Oct 2022.
• Mallory, Mindy & Kuethe, Todd & Hubbs, Todd, 2018. "Can Machine Learning Techniques Predict Non-performance of Farm Non-Real Estate Loans in the Ag Finance Databook," SCC-76 Meeting, 2018, April 5-7, Kansas City, Missouri 276141, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.