Report NEP-BIG-2024-03-04

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:

• Rennae Cherry & Eric Tong, 2023, "Words of the RBNZ: Textual analysis of Monetary Policy Statements," Reserve Bank of New Zealand Analytical Notes series, Reserve Bank of New Zealand, number AN2023/03, Jul.
• David Almog & Romain Gauriot & Lionel Page & Daniel Martin, 2024, "AI Oversight and Human Mistakes: Evidence from Centre Court," Papers, arXiv.org, number 2401.16754, Jan, revised Feb 2025.
• Tin Cheuk Leung & Koleman Strumpf, 2024, "Disentangling Demand and Supply of Media Bias: The Case of Newspaper Homepages," CESifo Working Paper Series, CESifo, number 10890.
• Franck Ramaharo & Fitiavana Randriamifidy, 2023, "Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms," Papers, arXiv.org, number 2401.13671, Oct.
• Gómez Julián, José Mauricio, 2024, "Quantitative Theory of Mony or Prices? A Historical, Theoretical, and Econometric Analysis," OSF Preprints, Center for Open Science, number eskmx, Feb, DOI: 10.31219/osf.io/eskmx.
• Brunori, Paolo & Ferreira, Francisco H. G. & Salas-Rojo, Pedro, 2024, "Inherited Inequality: A General Framework and an Application to South Africa," SocArXiv, Center for Open Science, number rgq7t, Jan, DOI: 10.31219/osf.io/rgq7t.
• Diwas Paudel & Tapas K. Das, 2024, "Tacit algorithmic collusion in deep reinforcement learning guided price competition: A study using EV charge pricing game," Papers, arXiv.org, number 2401.15108, Jan, revised May 2024.
• M. Shabani & M. Magris & George Tzagkarakis & J. Kanniainen & A. Iosifidis, 2023, "Predicting the state of synchronization of financial time series using cross recurrence plots," Post-Print, HAL, number hal-04415269, Jun, DOI: 10.1007/s00521-023-08674-y.
• Huo, Shutong & Feng, Derek & Gill, Thomas M. & Chen, Xi, 2024, "Childhood Circumstances and Health of American and Chinese Older Adults: A Machine Learning Evaluation of Inequality of Opportunity in Health," IZA Discussion Papers, IZA Network @ LISER, number 16764, Jan.
• Zhiyu Quan & Changyue Hu & Panyi Dong & Emiliano A. Valdez, 2024, "Improving Business Insurance Loss Models by Leveraging InsurTech Innovation," Papers, arXiv.org, number 2401.16723, Jan.
• Costantiello, Alberto & Leogrande, Angelo, 2024, "The Determinants Of Co2 Emissions In The Context Of Esg Models At World Level," SocArXiv, Center for Open Science, number 53djm, Jan, DOI: 10.31219/osf.io/53djm.
• Kim, Dongin, 2022, "Preferential Trading in Agriculture: New Insights from a Structural Gravity Analysis and Machine Learning," 2022: Transforming Global Value Chains, December 11-13, Clearwater Beach, FL, International Agricultural Trade Research Consortium, number 339469, Dec, DOI: 10.22004/ag.econ.339469.
• Leogrande, Angelo & Costantiello, Alberto & Leogrande, Domenico & Anobile, Fabio, 2024, "Beds In Health Facilities In The Italian Regions: A Socio-Economic Approach," SocArXiv, Center for Open Science, number shkjt, Jan, DOI: 10.31219/osf.io/shkjt.
• Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024, "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202402, Feb, revised Feb 2024.
• Franck Ramaharo & Gerzhino Rasolofomanana, 2023, "Nowcasting Madagascar's real GDP using machine learning algorithms," Papers, arXiv.org, number 2401.10255, Dec.
• Valentin Lindlacher & Gustav Pirich, 2024, "The Impact of China’s “Stadium Diplomacy” on Local Economic Development in Sub-Saharan Africa," CESifo Working Paper Series, CESifo, number 10893.
• Weidong Lin & Abderrahim Taamouti, 2023, "Portfolio Selection Under Non-Gaussianity And Systemic Risk: A Machine Learning Based Forecasting Approach," Working Papers, University of Liverpool, Department of Economics, number 202310, Aug.
• Hauke Licht & Ronja Sczepanski & Moritz Laurer & Ayjeren Bekmuratovna, 2024, "No More Cost in Translation: Validating Open-Source Machine Translation for Quantitative Text Analysis," ECONtribute Discussion Papers Series, University of Bonn and University of Cologne, Germany, number 276, Feb.
• Hauke Licht & Ronja Sczepanski, 2024, "Who are They Talking About? Detecting Mentions of Social Groups in Political Texts with Supervised Learning," ECONtribute Discussion Papers Series, University of Bonn and University of Cologne, Germany, number 277, Feb.
• Weidong Lin & Abderrahim Taamouti, 2023, "Machine Learning Based Portfolio Selection Under Systemic Risk," Working Papers, University of Liverpool, Department of Economics, number 202311.
• Leonard Mushunje & Maxwell Mashasha, 2023, "Non-Banking Sector development effect on Economic Growth. A Nighttime light data approach," Papers, arXiv.org, number 2401.08596, Nov.
• Churchill, Alexander & Pichika, Shamitha & Xu, Chengxin, 2024, "Using Generative Pre-Trained Transformers (GPT) for Supervised Content Encoding: An Application in Corresponding Experiments," SocArXiv, Center for Open Science, number 6fpgj, Jan, DOI: 10.31219/osf.io/6fpgj.
• Sander, Julian, 2024, "The Role of Emotions in Investment Decisions: The Effects of Vividness of a Crowdfunding Campaign Video," Thesis Commons, Center for Open Science, number 6gptv, Jan, DOI: 10.31219/osf.io/6gptv.
• Huo, Shutong & Feng, Derek & Gill, Thomas M. & Chen, Xi, 2024, "Childhood Circumstances and Health of American and Chinese Older Adults: A Machine Learning Evaluation of Inequality of Opportunity in Health," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1384.
• Mario Sanz-Guerrero & Javier Arroyo, 2024, "Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending," Papers, arXiv.org, number 2401.16458, Jan, revised Mar 2025.
• Pierre Renucci, 2023, "Optimal Linear Signal: An Unsupervised Machine Learning Framework to Optimize PnL with Linear Signals," Papers, arXiv.org, number 2401.05337, Nov.
• Bartosz Bieganowski & Robert Ślepaczuk, 2024, "Supervised Autoencoder MLP for Financial Time Series Forecasting," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2024-03.
• Gordeev, Stepan & Jelliffe, Jeremy & Kim, Dongin & Steinbach, Sandro, 2023, "What Matters for Agricultural Trade? Assessing the Role of Trade Deal Provisions using Machine Learning," 2023: The Future of (Ag-) Trade and Trade Governance in Times of Economic Sanctions and Declining Multilateralism, December 10-12, Clearwater Beach, FL, International Agricultural Trade Research Consortium, number 339533, Dec, DOI: 10.22004/ag.econ.339533.
• Dimitrios Kanelis & Pierre L. Siklos, 2024, "The ECB Press Conference Statement Deriving a New Sentiment Indicator for the Euro Area," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-10, Jan.
• Dengxin Huang, 2023, "Application of Machine Learning in Stock Market Forecasting: A Case Study of Disney Stock," Papers, arXiv.org, number 2401.10903, Dec.

Report NEP-BIG-2024-03-04

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: