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 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:

• Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2023. "Generative AI at Work," Papers 2304.11771, arXiv.org, revised Nov 2024.
• Kreitmeir, David & Raschky, Paul Anton, 2023. "The Unintended Consequences of Censoring Digital Technology - Evidence from Italy's ChatGPT Ban," SocArXiv v3cgs, Center for Open Science.
• John J. Horton, 2023. "Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?," NBER Working Papers 31122, National Bureau of Economic Research, Inc.
• Kasy, Maximilian, 2023. "The Political Economy of AI: Towards Democratic Control of the Means of Prediction," SocArXiv x7pcy, Center for Open Science.
• Maximilian Andres, 2023. "Communication in the Infinitely Repeated Prisoner's Dilemma: Theory and Experiments," Papers 2304.12297, arXiv.org.
• Erik Brynjolfsson & Danielle Li & Lindsey R. Raymond, 2023. "Generative AI at Work," NBER Working Papers 31161, National Bureau of Economic Research, Inc.
• Leonard, Bryan & Gigliotti, Laura & Middleton, Arthur & Kroetz, Kailin, 2022. "The Value of Remotely-Sensed Data in Terrestrial Habitat Corridor Design for Large Migratory Species," RFF Working Paper Series 22-21, Resources for the Future.
• Zhou, Janet & Azelton, Krystal & Nassar, Isabelle-Yara & Borowitz, Mariel, 2022. "Examining the Value of Satellite Data in Halting Transmission of Polio in Nigeria: A Socioeconomic Analysis," RFF Working Paper Series 22-20, Resources for the Future.
• Andrés Alonso-Robisco & José Manuel Carbó & José Manuel Marqués, 2023. "Machine Learning methods in climate finance: a systematic review," Working Papers 2310, Banco de España.
• 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 22-39, Federal Reserve Bank of Philadelphia.
• Simon, Frederik & Weibels, Sebastian & Zimmermann, Tom, 2023. "Deep parametric portfolio policies," CFR Working Papers 23-01, University of Cologne, Centre for Financial Research (CFR).
• Kyungsub Lee, 2023. "Recurrent neural network based parameter estimation of Hawkes model on high-frequency financial data," Papers 2304.11883, arXiv.org.
• Csaba Burger & Mihály Berndt, 2023. "Error Spotting with Gradient Boosting: A Machine Learning-Based Application for Central Bank Data Quality," MNB Occasional Papers 2023/148, Magyar Nemzeti Bank (Central Bank of Hungary).
• Kakuho Furukawa & Yoshihiko Hogen & Yosuke Kido, "undated". "Labor Market of Regular Workers in Japan: A Perspective from Job Advertisement Data," Bank of Japan Working Paper Series 23-E-7, Bank of Japan.
• 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 23-E-6, Bank of Japan.
• 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 2304.09750, arXiv.org, revised Mar 2024.
• Simon Briole & Augustin Colette & Emmanuelle Lavaine, 2023. "The Heterogeneous Effects of Lockdown Policies on Air Pollution," Working Papers hal-04084912, HAL.
• Nozomu Kobayashi & Yoshiyuki Suimon & Koichi Miyamoto & Kosuke Mitarai, 2023. "The cross-sectional stock return predictions via quantum neural network and tensor network," Papers 2304.12501, arXiv.org, 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 4071, Stanford University, Graduate School of Business.
• Ginevra Buratti & Alessio D'Ignazio, 2023. "Improving the effectiveness of financial education programs. A targeting approach," Questioni di Economia e Finanza (Occasional Papers) 765, Bank of Italy, Economic Research and International Relations Area.
• Breen, Casey & Seltzer, Nathan, 2023. "The Unpredictability of Individual-Level Longevity," SocArXiv znsqg, Center for Open Science.
• Jean-Charles Bricongne & Baptiste Meunier & Sylvain Pouget, 2023. "Web-scraping housing prices in real-time: The Covid-19 crisis in the UK," SciencePo Working papers Main hal-04064185, HAL.
• A. Hennessy, Christopher & Goodhart, C. A. E., 2023. "Goodhart's law and machine learning: a structural perspective," LSE Research Online Documents on Economics 118656, London School of Economics and Political Science, LSE Library.
• Li Tang & Chuanli Tang & Qi Fu, 2023. "Enhanced multilayer perceptron with feature selection and grid search for travel mode choice prediction," Papers 2304.12698, arXiv.org, 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) 2023-05, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
• Kapoor, Anuj & Narayanan, Sridhar & Manchanda, Puneet, 2023. "Does Access to Human Coaches Lead to More Weight Loss than with AI Coaches Alone?," Research Papers 4070, Stanford University, Graduate School of Business.
• Ajit Desai, 2023. "Machine Learning for Economics Research: When What and How?," Papers 2304.00086, arXiv.org, revised Apr 2023.
• Hannes Wallimann & Silvio Sticher, 2023. "On suspicious tracks: machine-learning based approaches to detect cartels in railway-infrastructure procurement," Papers 2304.11888, arXiv.org.
• 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 21-30, Resources for the Future.
• 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 2304.09761, arXiv.org.
• Martina Jakob & Sebastian Heinrich, 2023. "Measuring Human Capital with Social Media Data and Machine Learning," University of Bern Social Sciences Working Papers 46, University of Bern, Department of Social Sciences.
• Biggs, Trent & Caviglia-Harris, Jill & Rodrigues Ribeiro, Jime & Ottoni Santiago, Thaís & Sills, Erin & AP West, Thales & Mullan, Katrina, 2022. "Estimating the Value of Near-Real-Time Satellite Information for Monitoring Deforestation in the Brazilian Amazon," RFF Working Paper Series 22-22, Resources for the Future.
• 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 4074, Stanford University, Graduate School of Business.
• Jiwook Kim & Minhyeok Lee, 2023. "Portfolio Optimization using Predictive Auxiliary Classifier Generative Adversarial Networks with Measuring Uncertainty," Papers 2304.11856, arXiv.org.