Report NEP-BIG-2019-03-11

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:

• Sara Moricz, 2019. "Using Artificial Intelligence to Recapture Norms: Did #metoo change gender norms in Sweden?," Papers 1903.00690, arXiv.org.
• Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," NBER Working Papers 25619, National Bureau of Economic Research, Inc.
• Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
• Rohan Arora & Chen Fan & Guillaume Ouellet Leblanc, 2019. "Liquidity Management of Canadian Corporate Bond Mutual Funds: A Machine Learning Approach," Staff Analytical Notes 2019-7, Bank of Canada.
• Giorgia Giovannetti & Elena Perra, 2019. "Syria in the Dark: Estimating the Economic Consequences of the Civil War through Satellite-Derived Night Time Lights," Working Papers - Economics wp2019_05.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
• Sima Siami-Namini & Akbar Siami Namin, 2018. "Forecasting Economics and Financial Time Series: ARIMA vs. LSTM," Papers 1803.06386, arXiv.org.
• Clotilde Coron, 2019. "Big Data et pratiques de GRH," Post-Print halshs-01961214, HAL.
• Dmitry I. Ivanov & Alexander S. Nesterov, 2019. "Stealed-bid Auctions: Detecting Bid Leakage via Semi-Supervised Learning," Papers 1903.00261, arXiv.org, revised Nov 2020.
• Jonas Rothfuss & Fabio Ferreira & Simon Walther & Maxim Ulrich, 2019. "Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks," Papers 1903.00954, arXiv.org, revised Apr 2019.
• Robert J. Shiller, 2019. "Narratives About Technology-Induced Job Degradation Then and Now," Cowles Foundation Discussion Papers 2168, Cowles Foundation for Research in Economics, Yale University.
• Jiun-Hua Su, 2019. "Model Selection in Utility-Maximizing Binary Prediction," Papers 1903.00716, arXiv.org, revised Jul 2020.
• Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2019. "Gaussian Process Regression for Pricing Variable Annuities with Stochastic Volatility and Interest Rate," Papers 1903.00369, arXiv.org, revised Jul 2019.
• Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2019. "On binscatter," Staff Reports 881, Federal Reserve Bank of New York.