Report NEP-BIG-2018-09-24

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé issued this report. It is usually issued weekly.

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Other reports in NEP-BIG

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.
• 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).
• Naudé, Wim & Dimitri, Nicola, 2018. "The Race for an Artificial General Intelligence: Implications for Public Policy," IZA Discussion Papers 11737, Institute of Labor Economics (IZA).
• Oliver Kirchkamp & Christina Strobel, 2018. "Sharing Responsibility with a Machine," Jena Economics Research Papers 2018-014, Friedrich-Schiller-University Jena.
• Everett Grant, 2018. "The Double-Edged Sword of Global Integration: Robustness, Fragility \& Contagion in the International Firm Network," 2018 Meeting Papers 506, Society for Economic Dynamics.
• Boxell, Levi, 2018. "Slanted images: Measuring nonverbal media bias," MPRA Paper 89047, University Library of Munich, Germany.
• Will Dobbie & Andres Liberman & Daniel Paravisini & Vikram Pathania, 2018. "Measuring Bias in Consumer Lending," NBER Working Papers 24953, National Bureau of Economic Research, Inc.
• Dario Buono & George Kapetanios & Massimiliano Marcellino & Gianluigi Mazzi & Fotis Papailias, 2018. "Big Data Econometrics: Now Casting and Early Estimates," BAFFI CAREFIN Working Papers 1882, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers 24967, National Bureau of Economic Research, Inc.
• Twomey, Paul, 2018. "Building on the Hamburg Statement and the G20 Roadmap for Digitalization: Toward a G20 framework for artificial intelligence in the workplace," Economics Discussion Papers 2018-63, Kiel Institute for the World Economy (IfW Kiel).
• 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.
• 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.
• Asgari, Mahdi & Nemati, Mehdi & Zheng, Yuqing, 2018. "Nowcasting Food Stock Movement using Food Safety Related Web Search Queries," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266323, Southern Agricultural Economics Association.
• Ying-Hui Chiang, 2018. "Affordable or Unaffordable? Social Housing Rent in Taipei," ERES eres2018_246, European Real Estate Society (ERES).
• 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.
• Mills, Brian & Brorsen, Wade & Tostão, Emílio, 2017. "Wheat Nitrogen Response Conditional on Past Yield and Weather: A Step in Making Use of Big Data," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258269, Agricultural and Applied Economics Association.
• 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.
• Bergemann, Dirk & Bonatti, Alessandro, 2018. "Markets for Information: An Introduction," CEPR Discussion Papers 13148, C.E.P.R. Discussion Papers.