Report NEP-BIG-2023-05-22

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:

• Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2023, "Generative AI at Work," Papers, arXiv.org, number 2304.11771, Apr, revised Nov 2024.
• Kreitmeir, David & Raschky, Paul Anton, 2023, "The Unintended Consequences of Censoring Digital Technology - Evidence from Italy's ChatGPT Ban," SocArXiv, Center for Open Science, number v3cgs, Apr, DOI: 10.31219/osf.io/v3cgs.
• John J. Horton & Apostolos Filippas & Benjamin S. Manning, 2023, "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," NBER Working Papers, National Bureau of Economic Research, Inc, number 31122, Apr.
• Kasy, Maximilian, 2023, "The Political Economy of AI: Towards Democratic Control of the Means of Prediction," SocArXiv, Center for Open Science, number x7pcy, Apr, DOI: 10.31219/osf.io/x7pcy.
• Maximilian Andres, 2023, "Communication in the Infinitely Repeated Prisoner's Dilemma: Theory and Experiments," Papers, arXiv.org, number 2304.12297, Apr.
• Erik Brynjolfsson & Danielle Li & Lindsey R. Raymond, 2023, "Generative AI at Work," NBER Working Papers, National Bureau of Economic Research, Inc, number 31161, Apr.
• Kroetz, Kailin & Leonard, Bryan & Gigliotti, Laura & Middleton, Arthur, 2022, "The Value of Remotely-Sensed Data in Terrestrial Habitat Corridor Design for Large Migratory Species," RFF Working Paper Series, Resources for the Future, number 22-21, Oct.
• Borowitz, Mariel & Zhou, Janet & Azelton, Krystal & Nassar, Isabelle-Yara, 2022, "Examining the Value of Satellite Data in Halting Transmission of Polio in Nigeria: A Socioeconomic Analysis," RFF Working Paper Series, Resources for the Future, number 22-20, Oct.
• Andrés Alonso-Robisco & José Manuel Carbó & José Manuel Marqués, 2023, "Machine Learning methods in climate finance: a systematic review," Working Papers, Banco de España, number 2310, Feb, DOI: https://doi.org/10.53479/29594.
• Vitaly Meursault & Daniel Moulton & Larry Santucci & Nathan Schor, 2022, "One Threshold Doesn’t Fit All: Tailoring Machine Learning Predictions of Consumer Default for Lower-Income Areas," Working Papers, Federal Reserve Bank of Philadelphia, number 22-39, Nov, DOI: 10.21799/frbp.wp.2022.39.
• Simon, Frederik & Weibels, Sebastian & Zimmermann, Tom, 2025, "Deep parametric portfolio policies," CFR Working Papers, University of Cologne, Centre for Financial Research (CFR), number 23-01, revised 2025.
• Kyungsub Lee, 2023, "Recurrent neural network based parameter estimation of Hawkes model on high-frequency financial data," Papers, arXiv.org, number 2304.11883, Apr.
• Csaba Burger & Mihály Berndt, 2023, "Error Spotting with Gradient Boosting: A Machine Learning-Based Application for Central Bank Data Quality," MNB Occasional Papers, Magyar Nemzeti Bank (Central Bank of Hungary), number 2023/148.
• Kakuho Furukawa & Yoshihiko Hogen & Yosuke Kido, , "Labor Market of Regular Workers in Japan: A Perspective from Job Advertisement Data," Bank of Japan Working Paper Series, Bank of Japan, number 23-E-7.
• Ryuichiro Hashimoto & Kakeru Miura & Yasunori Yoshizaki, 2023, "Application of Machine Learning to a Credit Rating Classification Model: Techniques for Improving the Explainability of Machine Learning," Bank of Japan Working Paper Series, Bank of Japan, number 23-E-6, Apr.
• Raj G. Patel & Tomas Dominguez & Mohammad Dib & Samuel Palmer & Andrea Cadarso & Fernando De Lope Contreras & Abdelkader Ratnani & Francisco Gomez Casanova & Senaida Hern'andez-Santana & 'Alvaro D'iaz, 2023, "Application of Tensor Neural Networks to Pricing Bermudan Swaptions," Papers, arXiv.org, number 2304.09750, Apr, revised Mar 2024.
• Simon Briole & Augustin Colette & Emmanuelle Lavaine, 2023, "The Heterogeneous Effects of Lockdown Policies on Air Pollution," Working Papers, HAL, number hal-04084912, Apr.
• Nozomu Kobayashi & Yoshiyuki Suimon & Koichi Miyamoto & Kosuke Mitarai, 2023, "The cross-sectional stock return predictions via quantum neural network and tensor network," Papers, arXiv.org, number 2304.12501, Apr, revised Feb 2024.
• Athey, Susan & Karlan, Dean & Palikot, Emil & Yuan, Yuan, 2022, "Smiles in Profiles: Improving Fairness and Efficiency Using Estimates of User Preferences in Online Marketplaces," Research Papers, Stanford University, Graduate School of Business, number 4071, Nov.
• Ginevra Buratti & Alessio D'Ignazio, 2023, "Improving the effectiveness of financial education programs. A targeting approach," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 765, Apr.
• Breen, Casey & Seltzer, Nathan, 2023, "The Unpredictability of Individual-Level Longevity," SocArXiv, Center for Open Science, number znsqg, Apr, DOI: 10.31219/osf.io/znsqg.
• Jean-Charles Bricongne & Baptiste Meunier & Sylvain Pouget, 2023, "Web-scraping housing prices in real-time: The Covid-19 crisis in the UK," Sciences Po Economics Publications (main), HAL, number hal-04064185, Mar, DOI: 10.1016/j.jhe.2022.101906.
• A. Hennessy, Christopher & Goodhart, C. A. E., 2023, "Goodhart's law and machine learning: a structural perspective," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 118656, Mar.
• Li Tang & Chuanli Tang & Qi Fu, 2023, "Enhanced multilayer perceptron with feature selection and grid search for travel mode choice prediction," Papers, arXiv.org, number 2304.12698, Apr, revised Oct 2023.
• Sylvain Barthélémy & Fabien Rondeau & Virginie Gautier, 2023, "Early Warning System for Currency Crises using Long Short-Term Memory and Gated Recurrent Unit Neural Networks," Economics Working Paper Archive (University of Rennes & University of Caen), Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS, number 2023-05, Apr.
• Kapoor, Anuj & Narayanan, Sridhar & Manchanda, Puneet, 2023, "Does Access to Human Coaches Lead to More Weight Loss than with AI Coaches Alone?," Research Papers, Stanford University, Graduate School of Business, number 4070, Jan.
• Ajit Desai, 2023, "Machine Learning for Economics Research: When What and How?," Papers, arXiv.org, number 2304.00086, Mar, revised Apr 2023.
• Hannes Wallimann & Silvio Sticher, 2023, "On suspicious tracks: machine-learning based approaches to detect cartels in railway-infrastructure procurement," Papers, arXiv.org, number 2304.11888, Apr.
• Prest, Brian C. & Wichman, Casey & Palmer, Karen, 2021, "RCTs Against the Machine: Can Machine Learning Prediction Methods Recover Experimental Treatment Effects?," RFF Working Paper Series, Resources for the Future, number 21-30, Sep.
• Mayank Ratan Bhardwaj & Jaydeep Pawar & Abhijnya Bhat & Deepanshu & Inavamsi Enaganti & Kartik Sagar & Y. Narahari, 2023, "An innovative Deep Learning Based Approach for Accurate Agricultural Crop Price Prediction," Papers, arXiv.org, number 2304.09761, Apr.
• Martina Jakob & Sebastian Heinrich, 2023, "Measuring Human Capital with Social Media Data and Machine Learning," University of Bern Social Sciences Working Papers, University of Bern, Department of Social Sciences, number 46, May, DOI: 10.48350/182366.
• Mullan, Katrina & Biggs, Trent & Caviglia-Harris, Jill & Rodrigues Ribeiro, Jime & Ottoni Santiago, Thaís & Sills, Erin & AP West, Thales, 2022, "Estimating the Value of Near-Real-Time Satellite Information for Monitoring Deforestation in the Brazilian Amazon," RFF Working Paper Series, Resources for the Future, number 22-22, Oct.
• Vafa, Keyon & Palikot, Emil & Du, Tianyu & Kanodia, Ayush & Athey, Susan & Blei, David M., 2022, "CAREER: Transfer Learning for Economic Prediction of Labor Sequence Data," Research Papers, Stanford University, Graduate School of Business, number 4074, Oct.
• Jiwook Kim & Minhyeok Lee, 2023, "Portfolio Optimization using Predictive Auxiliary Classifier Generative Adversarial Networks with Measuring Uncertainty," Papers, arXiv.org, number 2304.11856, Apr.

Report NEP-BIG-2023-05-22

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: