Report NEP-BIG-2022-09-05

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:

• Giovanni Cerulli, 2022. "Machine learning using Stata/Python," Italian Stata Users' Group Meetings 2022 02, Stata Users Group.
• Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2022. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," NBER Working Papers 30302, National Bureau of Economic Research, Inc.
• Qin, Fei & Wu, Steven Y., 2022. "Estimating Consumer Segments and Choices from Limited Information: The Application of Machine Learning Methods," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322473, Agricultural and Applied Economics Association.
• José Manuel Carbó & Sergio Gorjón, 2022. "Application of machine learning models and interpretability techniques to identify the determinants of the price of bitcoin," Working Papers 2215, Banco de España.
• Daniel Goller & Andrea Diem & Stefan C. Wolter, 2022. "Sitting Next to a Dropout - Academic Success of Students with More Educated Peers," CESifo Working Paper Series 9812, CESifo.
• Gustavo Silva Araujo & Wagner Piazza Gaglianone, 2022. "Machine Learning Methods for Inflation Forecasting in Brazil: new contenders versus classical models," Working Papers Series 561, Central Bank of Brazil, Research Department.
• Mostafa Shabani & Dat Thanh Tran & Juho Kanniainen & Alexandros Iosifidis, 2022. "Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification," Papers 2207.11577, arXiv.org.
• Baier, Scott & Regmi, Narendra, 2021. "Using Machine Learning to Capture Heterogeneity in Trade Agreements," Working Papers 11027, George Mason University, Mercatus Center.
• Cornejo, Magdalena & Sosa Escudero, Walter, 2022. "Predicciones agregadas de pobreza con información a escala micro y macro: evaluación, diagnóstico y propuestas," Estudios Estadísticos 48018, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
• Ian Burn & Daniel Firoozi & Daniel Ladd & David Neumark, 2022. "Help Really Wanted? The Impact of Age Stereotypes in Job Ads on Applications from Older Workers," NBER Working Papers 30287, National Bureau of Economic Research, Inc.
• Bora, Siddhartha S. & Katchova, Ani, 2022. "Multi-horizon Forecasts of Agricultural Commodity Prices using Deep Learning," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322557, Agricultural and Applied Economics Association.
• Fatemeh Nosrat, 2022. "Assortment Optimization with Customer Choice Modeling in a Crowdfunding Setting," Papers 2207.07222, arXiv.org.
• Saskia Opitz & Dirk Sliwka & Timo Vogelsang & Tom Zimmermann, 2022. "The Targeted Assignment of Incentive Schemes," ECONtribute Discussion Papers Series 187, University of Bonn and University of Cologne, Germany.
• Aarts, Emile, 2022. "Artificial Intelligence : up to here ... and on again," Other publications TiSEM d656c4b4-c3ea-4700-8c93-0, Tilburg University, School of Economics and Management.
• Adamczyk, Willian, & Ehrl, Philipp, & Monasterio, Leonardo,, 2022. "Skills and employment transitions in Brazil," ILO Working Papers 995186192602676, International Labour Organization.
• Yu, Lamont Bo & Tran, Trang My & Lee, Wang-Sheng, 2022. "Revitalising the Silk Road: Evidence from Railway Infrastructure Investments in Northwest China," IZA Discussion Papers 15454, Institute of Labor Economics (IZA).
• Leonardo Kanashiro Felizardo & Elia Matsumoto & Emilio Del-Moral-Hernandez, 2022. "Solving the optimal stopping problem with reinforcement learning: an application in financial option exercise," Papers 2208.00765, arXiv.org.
• Kara Karpman & Sumanta Basu & David Easley, 2022. "Learning Financial Networks with High-frequency Trade Data," Papers 2208.03568, arXiv.org.
• Shaswat Mohanty & Anirudh Vijay & Nandagopan Gopakumar, 2022. "StockBot: Using LSTMs to Predict Stock Prices," Papers 2207.06605, arXiv.org, revised Jul 2022.
• Igor Sadoune & Andrea Lodi & Marcelin Joanis, 2022. "Implementing a Hierarchical Deep Learning Approach for Simulating Multi-Level Auction Data," Papers 2207.12255, arXiv.org, revised Feb 2024.
• Waddell, Glen R. & McDonough, Robert, 2022. "Mean Convergence, Combinatorics, and Grade-Point Averages," IZA Discussion Papers 15414, Institute of Labor Economics (IZA).
• Jacob Goldin & Julian Nyarko & Justin Young, 2022. "Forecasting Algorithms for Causal Inference with Panel Data," Papers 2208.03489, arXiv.org, revised Apr 2024.
• Cappelletti, Matilde & Giuffrida, Leonardo M., 2022. "Targeted bidders in government tenders," ZEW Discussion Papers 22-030, ZEW - Leibniz Centre for European Economic Research.
• J. Sebastián Becerra & Alejandra Cruces, 2021. "Sentimiento en el Informe de Estabilidad Financiera del Banco Central de Chile," Working Papers Central Bank of Chile 930, Central Bank of Chile.
• Tomohiro Okubo & Koji Takahashi & Haruhiko Inatsugu & Masato Takahashi, "undated". "Development of "Alternative Data Consumption Index":Nowcasting Private Consumption Using Alternative Data," Bank of Japan Working Paper Series 22-E-8, Bank of Japan.
• Elroi Hadad & Haim Kedar-Levy, 2022. "The Impact of Retail Investors Sentiment on Conditional Volatility of Stocks and Bonds," Papers 2208.01538, arXiv.org.