Printed from https://ideas.repec.org/n/nep-big/2024-04-15.html
Report NEP-BIG-2024-04-15
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:
- Mueller, H. & Rauh, C. & Seimon, B., 2024, "Introducing a Global Dataset on Conflict Forecasts and News Topics," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2404, Feb.
- Yuxiang Sun & Jingyi Li & Mengdie Lu & Zongying Guo, 2024, "Study of the Impact of the Big Data Era on Accounting and Auditing," Papers, arXiv.org, number 2403.07180, Mar.
- Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024, "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202403, Feb, DOI: 10.48720/IAB.DP.2403.
- Junyi Ye & Bhaskar Goswami & Jingyi Gu & Ajim Uddin & Guiling Wang, 2024, "From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing," Papers, arXiv.org, number 2403.06779, Mar.
- Tsendsuren Batsuuri & Shan He & Ruofei Hu & Jonathan Leslie & Flora Lutz, 2024, "Predicting IMF-Supported Programs: A Machine Learning Approach," IMF Working Papers, International Monetary Fund, number 2024/054, Mar.
- João A. Bastos & Maria Inês Bernardes, 2024, "Understanding online purchases with explainable machine learning," Working Papers REM, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa, number 2024/0313, Mar.
- Yaein Baek & Sang-Ha Yoon & Hyun Hak Kim & Jiyun Lee, 2023, "빅데이터 기반의 국제거시경제 전망모형 개발 연구(Developing an International Macroeconomic Forecasting Model Based on Big Data)," Policy Analyses, Korea Institute for International Economic Policy, number 23-24, Dec.
- Xinyi Wang & Qing Zhao & Lang Tong, 2024, "Probabilistic Forecasting of Real-Time Electricity Market Signals via Interpretable Generative AI," Papers, arXiv.org, number 2403.05743, Mar, revised Sep 2024.
- Matteo Rizzato & Julien Wallart & Christophe Geissler & Nicolas Morizet & Noureddine Boumlaik, 2023, "Generative Adversarial Networks Applied to Synthetic Financial Scenarios Generation
[Data Latent space]," Post-Print, HAL, number hal-03716692, Aug, DOI: 10.1016/j.physa.2023.128899. - Brendan J. Chapuis & John Coglianese, 2024, "Measuring Unemployment Risk," FEDS Notes, Board of Governors of the Federal Reserve System (U.S.), number 2024-03-08-1, Mar, DOI: 10.17016/2380-7172.3453.
- Njiru, Ruth & Appel, Franziska & Dong, Changxing & Balmann, Alfons, 2024, "Application of Deep Learning to Emulate an Agent-Based Model," FORLand Project Publications, University of Natural Resources and Applied Life Sciences, Vienna, Department of Economics and Social Sciences, number 340874, Mar, DOI: 10.22004/ag.econ.340874.
- Andre Guettler & Mahvish Naeem & Lars Norden & Bernardus Van Doornik, 2024, "Pre-Publication Revisions of Bank Financial Statements: a novel way to monitor banks?," Working Papers Series, Central Bank of Brazil, Research Department, number 590, Mar.
- Koresh Galil & Ami Hauptman & Rosit Levy Rosenboim, 2023, "Prediction of Corporate Credit Ratings with Machine Learning: Simple Interpretative Models," Working Papers, Ben-Gurion University of the Negev, Department of Economics, number 2308.
- Masahiro Kato, 2024, "Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects," Papers, arXiv.org, number 2403.03240, Mar.
- Stelios Michalopoulos & Christopher Rauh, 2024, "Movies," NBER Working Papers, National Bureau of Economic Research, Inc, number 32220, Mar.
- Buczak, Philip & Horn, Daniel & Pauly, Markus, 2024, "Old but Gold or New and Shiny? Comparing Tree Ensembles for Ordinal Prediction with a Classic Parametric Approach," OSF Preprints, Center for Open Science, number v7bcf, Mar, DOI: 10.31219/osf.io/v7bcf.
- GIBSON, John & ZHANG, Xiaoxuan & PARK, Albert & YI, Jiang & XI, Li, 2024, "Remotely measuring rural economic activity and poverty : Do we just need better sensors?," CEI Working Paper Series, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University, number 2023-08, Mar.
- Hainaut, Donatien & Casas, Alex, 2024, "Option pricing in the Heston model with Physics inspired neural networks," LIDAM Discussion Papers ISBA, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA), number 2024002, Feb.
- Bertsch, Christoph & Hull, Isaiah & Lumsdaine, Robin L. & Zhang, Xin, 2024, "Four Facts about International Central Bank Communication," Working Paper Series, Sveriges Riksbank (Central Bank of Sweden), number 432, Mar.
- Glas, Alexander & Müller, Lena, 2023, "Talking in a language that everyone can understand? Clarity of speeches by the ECB Executive Board," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 23-073.
- Valerio Capraro & Roberto Di Paolo & Matjaz Perc & Veronica Pizziol, 2024, "Language-based game theory in the age of artificial intelligence," Papers, arXiv.org, number 2403.08944, Mar.