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 (Tom Coupe) issued this report. It is usually issued weekly.

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

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, Stata Users Group, number 02, Jul.
• Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2022, "Long Story Short: Omitted Variable Bias in Causal Machine Learning," NBER Working Papers, National Bureau of Economic Research, Inc, number 30302, Jul.
• 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, Agricultural and Applied Economics Association, number 322473, Aug, DOI: 10.22004/ag.econ.322473.
• 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, Banco de España, number 2215, Apr.
• 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, CESifo, number 9812.
• Gustavo Silva Araujo & Wagner Piazza Gaglianone, 2022, "Machine Learning Methods for Inflation Forecasting in Brazil: new contenders versus classical models," Working Papers Series, Central Bank of Brazil, Research Department, number 561, Jul.
• Mostafa Shabani & Dat Thanh Tran & Juho Kanniainen & Alexandros Iosifidis, 2022, "Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification," Papers, arXiv.org, number 2207.11577, Jul.
• Baier, Scott & Regmi, Narendra, 2021, "Using Machine Learning to Capture Heterogeneity in Trade Agreements," Working Papers, George Mason University, Mercatus Center, number 11027, Mar.
• Item repec:ecr:col027:48018 is not listed on IDEAS anymore

• 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, National Bureau of Economic Research, Inc, number 30287, Jul.
• 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, Agricultural and Applied Economics Association, number 322557, Aug, DOI: 10.22004/ag.econ.322557.
• Fatemeh Nosrat, 2022, "Assortment Optimization with Customer Choice Modeling in a Crowdfunding Setting," Papers, arXiv.org, number 2207.07222, Jul.
• Saskia Opitz & Dirk Sliwka & Timo Vogelsang & Tom Zimmermann, 2022, "The Targeted Assignment of Incentive Schemes," ECONtribute Discussion Papers Series, University of Bonn and University of Cologne, Germany, number 187, Aug.
• Item repec:tiu:tiutis:d656c4b4-c3ea-4700-8c93-0e7ac7e96fd4 is not listed on IDEAS anymore

• Adamczyk, Willian, & Ehrl, Philipp, & Monasterio, Leonardo,, 2022, "Skills and employment transitions in Brazil," ILO Working Papers, International Labour Organization, number 995186192602676, DOI: 10.54394/ZWJU1062.
• 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, IZA Network @ LISER, number 15454, Jul.
• 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, arXiv.org, number 2208.00765, Jul.
• Kara Karpman & Sumanta Basu & David Easley, 2022, "Learning Financial Networks with High-frequency Trade Data," Papers, arXiv.org, number 2208.03568, Aug.
• Shaswat Mohanty & Anirudh Vijay & Nandagopan Gopakumar, 2022, "StockBot: Using LSTMs to Predict Stock Prices," Papers, arXiv.org, number 2207.06605, Jul, revised Jul 2022.
• Igor Sadoune & Andrea Lodi & Marcelin Joanis, 2022, "Implementing a Hierarchical Deep Learning Approach for Simulating Multi-Level Auction Data," Papers, arXiv.org, number 2207.12255, Jul, revised Feb 2024.
• Waddell, Glen R. & McDonough, Robert, 2022, "Mean Convergence, Combinatorics, and Grade-Point Averages," IZA Discussion Papers, IZA Network @ LISER, number 15414, Jul.
• Jacob Goldin & Julian Nyarko & Justin Young, 2022, "Forecasting Algorithms for Causal Inference with Panel Data," Papers, arXiv.org, number 2208.03489, Aug, revised Apr 2024.
• Cappelletti, Matilde & Giuffrida, Leonardo M., 2022, "Targeted bidders in government tenders," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 22-030.
• J. Sebastián Becerra & Alejandra Cruces, 2021, "Sentimiento en el Informe de Estabilidad Financiera del Banco Central de Chile," Working Papers Central Bank of Chile, Central Bank of Chile, number 930, Nov.
• Tomohiro Okubo & Koji Takahashi & Haruhiko Inatsugu & Masato Takahashi, , "Development of "Alternative Data Consumption Index":Nowcasting Private Consumption Using Alternative Data," Bank of Japan Working Paper Series, Bank of Japan, number 22-E-8.
• Elroi Hadad & Haim Kedar-Levy, 2022, "The Impact of Retail Investors Sentiment on Conditional Volatility of Stocks and Bonds," Papers, arXiv.org, number 2208.01538, Aug.

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 (Tom Coupe) issued this report. It is usually issued weekly.

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

Other reports in NEP-BIG

The following items were announced in this report: