Report NEP-BIG-2023-07-24

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:

• Hanemaaijer, Kyra & Marie, Olivier & Musumeci, Marco, 2023. "The Fast and the Studious? Ramadan Observance and Student Performance," IZA Discussion Papers 16249, Institute of Labor Economics (IZA).
• Wassim Le Lann & Gauthier Delozière & Yann Le Lann, 2023. "Greenwashing the Talents: attracting human capital through environmental pledges," SciencePo Working papers Main hal-04140191, HAL.
• Item repec:ags:aaea22:335521 is not listed on IDEAS anymore

• Evelina Gavrilova & Audun Langørgen & Floris T. Zoutman & Floris Zoutman, 2023. "Dynamic Causal Forests, with an Application to Payroll Tax Incidence in Norway," CESifo Working Paper Series 10532, CESifo.
• Thibault Collin, 2023. "Using Deep Learning to Hedge Rainbow Options," Working Papers hal-04060013, HAL.
• Ilias Chronopoulos & Katerina Chrysikou & George Kapetanios & James Mitchell & Aristeidis Raftapostolos, 2023. "Deep Neural Network Estimation in Panel Data Models," Working Papers 23-15, Federal Reserve Bank of Cleveland.
• Xinli Yu & Zheng Chen & Yuan Ling & Shujing Dong & Zongyi Liu & Yanbin Lu, 2023. "Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting," Papers 2306.11025, arXiv.org.
• Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023. "Amortized Neural Networks for Agent-Based Model Forecasting," Bank of Russia Working Paper Series wps115, Bank of Russia.
• Kai Feng & Han Hong & Ke Tang & Jingyuan Wang, 2023. "Statistical Tests for Replacing Human Decision Makers with Algorithms," Papers 2306.11689, arXiv.org, revised Dec 2024.
• Gavrilova, Evelina & Langørgen, Audun & Zoutman, Floris T., 2023. "Dynamic Causal Forests, with an Application to Payroll Tax Incidence in Norway," Discussion Papers 2023/9, Norwegian School of Economics, Department of Business and Management Science.
• Cassidy K. Buhler & Hande Y. Benson, 2023. "Efficient Solution of Portfolio Optimization Problems via Dimension Reduction and Sparsification," Papers 2306.12639, arXiv.org.
• Marc-André Gosselin & Temel Taskin, 2023. "What Can Earnings Calls Tell Us About the Output Gap and Inflation in Canada?," Discussion Papers 2023-13, Bank of Canada.
• Carlo Drago & Loris Di Nallo & Maria Lucetta Russotto, 2023. "Social Sustainability in European Banks: A Machine Learning Approach using Interval- Based Composite Indicators," Working Papers 2023.13, Fondazione Eni Enrico Mattei.
• Zhi Su & Danni Wu & Zhenkun Zhou & Junran Wu & Libo Yin, 2023. "The Impact of Customer Online Satisfaction on Stock Returns: Evidence from the E-commerce Reviews in China," Papers 2306.12119, arXiv.org.
• Fabio Baschetti & Giacomo Bormetti & Pietro Rossi, 2023. "Deep calibration with random grids," Papers 2306.11061, arXiv.org, revised Jan 2024.
• Drago, Carlo & Di Nallo, Loris & Russotto, Maria Lucetta, 2023. "Social Sustainability in European Banks: A Machine Learning Approach using Interval- Based Composite Indicators," FEEM Working Papers 336986, Fondazione Eni Enrico Mattei (FEEM).
• Alex Kim & Maximilian Muhn & Valeri Nikolaev, 2023. "Bloated Disclosures: Can ChatGPT Help Investors Process Information?," Papers 2306.10224, arXiv.org, revised Feb 2024.
• Wassim Le Lann & Gauthier Delozière & Yann Le Lann, 2023. "Greenwashing the Talents: attracting human capital through environmental pledges," Working Papers hal-04140191, HAL.
• Simon Montfort, 2023. "Key predictors for climate policy support and political mobilization: The role of beliefs and preferences," Papers 2306.10144, arXiv.org.