Printed from https://ideas.repec.org/n/nep-cmp/2022-07-25.html
Report NEP-CMP-2022-07-25
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:
- Marcus Buckmann & Andreas Joseph, 2022, "An interpretable machine learning workflow with an application to economic forecasting," Bank of England working papers, Bank of England, number 984, Jun.
- Callum Rhys Tilbury, 2022, "Reinforcement Learning for Economic Policy: A New Frontier?," Papers, arXiv.org, number 2206.08781, Jun, revised Feb 2023.
- Farmer, J. Doyne & Axtell, Robert L., 2022, "Agent-Based Modeling in Economics and Finance: Past, Present, and Future," INET Oxford Working Papers, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, number 2022-10, Jun.
- Kevin Kamm & Michelle Muniz, 2022, "A novel approach to rating transition modelling via Machine Learning and SDEs on Lie groups," Papers, arXiv.org, number 2205.15699, May.
- Karim Barhoumi & Seung Mo Choi & Tara Iyer & Jiakun Li & Franck Ouattara & Mr. Andrew J Tiffin & Jiaxiong Yao, 2022, "Overcoming Data Sparsity: A Machine Learning Approach to Track the Real-Time Impact of COVID-19 in Sub-Saharan Africa," IMF Working Papers, International Monetary Fund, number 2022/088, May.
- Kaiser, Caspar & Oparina, Ekaterina & Gentile, Niccolò & Tkatchenko, Alexandre & Clark, Andrew E. & De Neve, Jan-Emmanuel & D’Ambrosio, Conchita, 2022, "Human Wellbeing and Machine Learning," INET Oxford Working Papers, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, number 2022-11, Jun.
- Sara B. Heller & Benjamin Jakubowski & Zubin Jelveh & Max Kapustin, 2022, "Machine Learning Can Predict Shooting Victimization Well Enough to Help Prevent It," NBER Working Papers, National Bureau of Economic Research, Inc, number 30170, Jun.
- Diana Gabrielyan & Lenno Uusküla, 2022, "Inflation Expectations And Consumption With Machine Learning," University of Tartu - Faculty of Economics and Business Administration Working Paper Series, Faculty of Economics and Business Administration, University of Tartu (Estonia), number 142.
- Naphtal Hakizimana & John Karangwa & Jesse Lastunen & Aimable Nsabimana & Innocente Murasi & Lucie Niyigena & Michael Noble & Gemma Wright, 2022, "Tax-benefit microsimulation model in Rwanda: A feasibility study," WIDER Working Paper Series, World Institute for Development Economic Research (UNU-WIDER), number wp-2022-72.
- Daniel Bjorkegren & Joshua E. Blumenstock & Samsun Knight, 2022, "(Machine) Learning What Policies Value," Papers, arXiv.org, number 2206.00727, Jun.
- Valerio Astuti & Marta Crispino & Marco Langiulli & Juri Marcucci, 2022, "Textual analysis of a Twitter corpus during the COVID-19 pandemics," Questioni di Economia e Finanza (Occasional Papers), Bank of Italy, Economic Research and International Relations Area, number 692, Jun.
- Majid Ahmadi & Nathan Durst & Jeff Lachman & Mason List & Noah List & John List & Atom Vayalinkal, 2022, "Nothing Propinks Like Propinquity: Using Machine Learning to Estimate the Effects of Spatial Proximity in the Major League Baseball Draft," Artefactual Field Experiments, The Field Experiments Website, number 00758.
- Veli Andirin & Yusuf Neggers & Mehdi Shadmehr & Jesse M. Shapiro, 2022, "Surveillance of Repression: Theory and Implementation," NBER Working Papers, National Bureau of Economic Research, Inc, number 30167, Jun.