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Report NEP-CMP-2021-11-29
This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-CMP
The following items were announced in this report:
- Item repec:iim:iimawp:14665 is not listed on IDEAS anymore
- Ananda Chatterjee & Hrisav Bhowmick & Jaydip Sen, 2021, "Stock Price Prediction Using Time Series, Econometric, Machine Learning, and Deep Learning Models," Papers, arXiv.org, number 2111.01137, Nov.
- Narayanan, Sridhar & Kalyanam, Kirthi, 2020, "Behavioral Targeting, Machine Learning and Regression Discontinuity Designs," Research Papers, Stanford University, Graduate School of Business, number 3925, Dec.
- Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021, "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2021-020.
- Vito Polito & Yunyi Zhang, 2021, "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series, CESifo, number 9395.
- Isaac K. Ofori & Christopher Quaidoo & Pamela E. Ofori, 2021, "What Drives Financial Sector Development in Africa? Insights from Machine Learning," Working Papers, European Xtramile Centre of African Studies (EXCAS), number 21/074, Jan.
- Jean-Charles Bricongne & Baptiste Meunier & Thomas Pical, 2021, "Can satellite data on air pollution predict industrial production?," Working papers, Banque de France, number 847.
- Tobias Schultheiss & Uschi Backes-Gellner, 2021, "Different degrees of skill obsolescence across hard and soft skills and the role of lifelong learning for labor market outcomes," Economics of Education Working Paper Series, University of Zurich, Department of Business Administration (IBW), number 0188, Nov, revised Sep 2022.
- David Karpa & Torben Klarl & Michael Rochlitz, 2021, "Artificial Intelligence, Surveillance, and Big Data," Papers, arXiv.org, number 2111.00992, Nov.
- Nhan Huynh & Mike Ludkovski, 2021, "Joint Models for Cause-of-Death Mortality in Multiple Populations," Papers, arXiv.org, number 2111.06631, Nov.
- Asier Guti'errez-Fandi~no & Miquel Noguer i Alonso & Petter Kolm & Jordi Armengol-Estap'e, 2021, "FinEAS: Financial Embedding Analysis of Sentiment," Papers, arXiv.org, number 2111.00526, Oct, revised Nov 2021.
- Pallavi Basu & Luella Fu & Alessio Saretto & Wenguang Sun, 2021, "Empirical Bayes Control of the False Discovery Exceedance," Working Papers, Federal Reserve Bank of Dallas, number 2115, Nov, DOI: 10.24149/wp2115.
- Francisco Estrada & Oscar Calder'on-Bustamante & Wouter Botzen & Juli'an A. Velasco & Richard S. J. Tol, 2021, "AIRCC-Clim: a user-friendly tool for generating regional probabilistic climate change scenarios and risk measures," Papers, arXiv.org, number 2111.01762, Oct.
- Angela E. Kilby & Charlie Denhart, 2021, "Location inference on social media data for agile monitoring of public health crises: An application to opioid use and abuse during the Covid-19 pandemic," Papers, arXiv.org, number 2111.01778, Nov.
- Luo, Danqi & Bayati, Mohsen & Plambeck, Erica L. & Aratow, Michael, 2021, "Low-Acuity Patients Delay High-Acuity Patients in EDs," Research Papers, Stanford University, Graduate School of Business, number 3281.