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Report NEP-BIG-2024-01-01
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:
- Parth Daxesh Modi & Kamyar Arshi & Pertami J. Kunz & Abdelhak M. Zoubir, 2023, "A Data-driven Deep Learning Approach for Bitcoin Price Forecasting," Papers, arXiv.org, number 2311.06280, Oct.
- Khaled AlAjmi & Jose Deodoro & Mr. Ashraf Khan & Kei Moriya, 2023, "Predicting the Law: Artificial Intelligence Findings from the IMF’s Central Bank Legislation Database," IMF Working Papers, International Monetary Fund, number 2023/241, Nov.
- Stempel, Daniel & Zahner, Johannes, 2023, "Whose Inflation Rates Matter Most? A DSGE Model and Machine Learning Approach to Monetary Policy in the Euro Area," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage", Verein für Socialpolitik / German Economic Association, number 277627.
- Md Sabbirul Haque & Md Shahedul Amin & Jonayet Miah & Duc Minh Cao & Ashiqul Haque Ahmed, 2023, "Boosting Stock Price Prediction with Anticipated Macro Policy Changes," Papers, arXiv.org, number 2311.06278, Oct.
- Holtemöller, Oliver & Kozyrev, Boris, 2023, "Forecasting Economic Activity with a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to German GDP," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage", Verein für Socialpolitik / German Economic Association, number 277688.
- Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2023, "Estimation of Semiparametric Multi-Index Models Using Deep Neural Networks," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 21/23.
- Jose E. Gomez-Gonzalez & Jorge M. Uribe & Oscar M. Valencia, 2023, "Sovereign Risk and Economic Complexity: Machine Learning Insights on Causality and Prediction," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202315, Nov, revised Nov 2023.
- Ksenia E. Chistyakova & Tatiana B. Kazakova, 2023, "Grammar In Language Models: Bert Study," HSE Working papers, National Research University Higher School of Economics, number WP BRP 115/LNG/2023.
- Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner Piazza Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Artur Brasil Fialho Rodrigues, 2023, "Predicting Recessions in (almost) Real Time in a Big-data Setting," Working Papers Series, Central Bank of Brazil, Research Department, number 587, Nov.
- Di Stefano, Roberta & Resce, Giuliano, , "The Determinants of Missed Funding: Predicting the Paradox of Increased Need and Reduced Allocation," Economics & Statistics Discussion Papers, University of Molise, Department of Economics, number esdp23092.
- Osman, Adam & Speer, Jamin D., 2023, "Stigma and Take-up of Labor Market Assistance: Evidence from Two Field Experiments," IZA Discussion Papers, IZA Network @ LISER, number 16599, Nov.
- Yuxi Heluo & Kexin Wang & Charles W. Robson, 2023, "Do we listen to what we are told? An empirical study on human behaviour during the COVID-19 pandemic: neural networks vs. regression analysis," Papers, arXiv.org, number 2311.13046, Nov.
- Matteo Foglia & Vasilios Plakandaras & Rangan Gupta & Elie Bouri, 2023, "Multi-Layer Spillovers between Volatility and Skewness in International Stock Markets Over a Century of Data: The Role of Disaster Risks," Working Papers, University of Pretoria, Department of Economics, number 202337, Dec.
- Karina Acosta & Yuri Reina-Aranza, 2023, "Categorías municipales en Colombia: Avanzando hacia un modelo de descentralización asimétrica," Documentos de trabajo sobre Economía Regional y Urbana, Banco de la Republica de Colombia, number 321, Dec, DOI: 10.32468/dtseru.321.
- Thomas Chalaux & David Turner, 2023, "Doombot: a machine learning algorithm for predicting downturns in OECD countries," OECD Economics Department Working Papers, OECD Publishing, number 1780, Dec, DOI: 10.1787/4ed7acc3-en.