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Report NEP-CMP-2021-09-27
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:
- Rudiger Frey & Verena Kock, 2021, "Deep Neural Network Algorithms for Parabolic PIDEs and Applications in Insurance Mathematics," Papers, arXiv.org, number 2109.11403, Sep, revised Sep 2021.
- Dylan Brewer & Alyssa Carlson, 2021, "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers, Department of Economics, University of Missouri, number 2114, Sep.
- Jascha Buchhorn & Berthold U. Wigger, 2021, "Predicting Student Dropout: A Replication Study Based on Neural Networks," CESifo Working Paper Series, CESifo, number 9300.
- Lin Li, 2021, "Financial Trading with Feature Preprocessing and Recurrent Reinforcement Learning," Papers, arXiv.org, number 2109.05283, Sep.
- Isaac K. Ofori, 2021, "Catching the Drivers of Inclusive Growth in Sub-Saharan Africa: An Application of Machine Learning," Research Africa Network Working Papers, Research Africa Network (RAN), number 21/044, Jan.
- Alexander Jaax & Frédéric Gonzales & Annabelle Mourougane, 2021, "Nowcasting aggregate services trade," OECD Trade Policy Papers, OECD Publishing, number 253, Sep, DOI: 10.1787/0ad7d27c-en.
- Pihnastyi, Oleh & Sytnikova, Anastasiya, 2021, "Construction of Control Systems of Flow Parameters of the Smart Conveyor using a Neural Network," MPRA Paper, University Library of Munich, Germany, number 109770, Sep, revised 03 Sep 2021.
- Jens Ludwig & Sendhil Mullainathan, 2021, "Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System," NBER Working Papers, National Bureau of Economic Research, Inc, number 29267, Sep.
- Solveig Flaig & Gero Junike, 2021, "Scenario generation for market risk models using generative neural networks," Papers, arXiv.org, number 2109.10072, Sep, revised Aug 2023.
- Nathan Ratledge & Gabriel Cadamuro & Brandon De la Cuesta & Matthieu Stigler & Marshall Burke, 2021, "Using Satellite Imagery and Machine Learning to Estimate the Livelihood Impact of Electricity Access," NBER Working Papers, National Bureau of Economic Research, Inc, number 29237, Sep.
- Pedro Salas-Rojo & Juan Gabriel Rodríguez, 2020, "Inheritances and Wealth Inequality: a Machine Learning Approach," LWS Working papers, LIS Cross-National Data Center in Luxembourg, number 32, Dec.
- Leogrande, Angelo & Costantiello, Alberto, 2021, "Human Resources in Europe. Estimation, Clusterization, Machine Learning and Prediction," MPRA Paper, University Library of Munich, Germany, number 109749, Sep.
- Lin William Cong & Ke Tang & Bing Wang & Jingyuan Wang, 2021, "An AI-assisted Economic Model of Endogenous Mobility and Infectious Diseases: The Case of COVID-19 in the United States," Papers, arXiv.org, number 2109.10009, Sep.