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Report NEP-BIG-2023-10-02
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:
- Timothy Besley & Thiemo Fetzer & Hannes Mueller, 2023, "How Big Is the Media Multiplier? Evidence from Dyadic News Data," CESifo Working Paper Series, CESifo, number 10619.
- Alexander Yarkin, 2023, "Learning from the Origins," CESifo Working Paper Series, CESifo, number 10626.
- Patrick Rehill & Nicholas Biddle, 2023, "Fairness Implications of Heterogeneous Treatment Effect Estimation with Machine Learning Methods in Policy-making," Papers, arXiv.org, number 2309.00805, Sep.
- Timothy DeLise, 2023, "Deep Semi-Supervised Anomaly Detection for Finding Fraud in the Futures Market," Papers, arXiv.org, number 2309.00088, Aug.
- Damien Challet & Vincent Ragel, 2023, "Recurrent Neural Networks with more flexible memory: better predictions than rough volatility," Papers, arXiv.org, number 2308.08550, Aug.
- Brunori, Paolo & Hufe, Paul & Mahler, Daniel, 2023, "The roots of inequality: estimating inequality of opportunity from regression trees and forests," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 118220, Oct.
- Kelvin J. L. Koa & Yunshan Ma & Ritchie Ng & Tat-Seng Chua, 2023, "Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction," Papers, arXiv.org, number 2309.00073, Aug, revised Oct 2023.
- Morande, Swapnil & Arshi, Tahseen & Gul, Kanwal & Amini, Mitra, 2023, "Harnessing the Power of Artificial Intelligence to Forecast Startup Success: An Empirical Evaluation of the SECURE AI Model," SocArXiv, Center for Open Science, number p3gyb, Aug, DOI: 10.31219/osf.io/p3gyb.
- Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2023, "Asymmetric AdaBoost for High-dimensional Maximum Score Regression," Working Papers, University of California at Riverside, Department of Economics, number 202306, Aug.
- Kwok Ping Tsang & Zichao Yang, 2023, "Agree to Disagree: Measuring Hidden Dissent in FOMC Meetings," Papers, arXiv.org, number 2308.10131, Aug, revised Oct 2025.
- Ali Asgarov, 2023, "Predicting Financial Market Trends using Time Series Analysis and Natural Language Processing," Papers, arXiv.org, number 2309.00136, Aug.
- Eugene Kharitonov & Oksana Zakharchuk & Lin Mei, 2023, "Long-term Effects of Temperature Variations on Economic Growth: A Machine Learning Approach," Papers, arXiv.org, number 2308.06265, Jun.
- Kasey Buckles & Adrian Haws & Joseph Price & Haley E.B. Wilbert, 2023, "Breakthroughs in Historical Record Linking Using Genealogy Data: The Census Tree Project," NBER Working Papers, National Bureau of Economic Research, Inc, number 31671, Sep.
- Leogrande, Angelo & Costantiello, Alberto & Leogrande, Domenico, 2023, "The Socio-Economic Determinants of the Number of Physicians in Italian Regions," MPRA Paper, University Library of Munich, Germany, number 118460, Sep.
- Oschinski, Matthias, 2023, "Assessing the Impact of Artificial Intelligence on Germany's Labor Market: Insights from a ChatGPT Analysis," MPRA Paper, University Library of Munich, Germany, number 118300, Aug.
- Young Sik JEONG & Yaein BAEK, 2023, "Decoding Financial Crises: Analyzing Predictors and Evolution," World Economy Brief, Korea Institute for International Economic Policy, number 23-28, Aug.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023, "Econometrics of Machine Learning Methods in Economic Forecasting," Papers, arXiv.org, number 2308.10993, Aug.
- Kapil Panda, 2023, "Analysis of Optimal Portfolio Management Using Hierarchical Clustering," Papers, arXiv.org, number 2308.11202, Aug.
- van den Berg, Gerard J. & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023, "Predicting Re-Employment: Machine Learning versus Assessments by Unemployed Workers and by Their Caseworkers," IZA Discussion Papers, IZA Network @ LISER, number 16426, Sep.
- Zunaidah Sulong & Mohammad Abdullah & Emmanuel J. A. Abakah & David Adeabah & Simplice Asongu, 2023, "Russia-Ukraine war and G7 debt markets: Evidence from public sentiment towards economic sanctions during the conflict," Working Papers, European Xtramile Centre of African Studies (EXCAS), number 23/057, Jan.
- Daniel Bussell & Camilo Andr'es Garc'ia-Trillos, 2023, "Deep multi-step mixed algorithm for high dimensional non-linear PDEs and associated BSDEs," Papers, arXiv.org, number 2308.14487, Aug.
- Lohani, Fazle & Rahman, Mostafizur & Shaturaev, Jakhongir, 2023, "The Impact of Artificial Intelligence on Economic Patterns," MPRA Paper, University Library of Munich, Germany, number 118316, Jan, revised 08 Mar 2023.
- Julia Schmidt & Graham Pilgrim & Annabelle Mourougane, 2023, "What is the role of data in jobs in the United Kingdom, Canada, and the United States?: A natural language processing approach," OECD Statistics Working Papers, OECD Publishing, number 2023/05, Sep, DOI: 10.1787/fa65d29e-en.
- Callan Windsor & Max Zang, 2023, "Firms' Price-setting Behaviour: Insights from Earnings Calls," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2023-06, Sep, DOI: 10.47688/rdp2023-06.