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Report NEP-CMP-2021-04-26
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:
- Renne, Rachel & Schlaepfer, Daniel & Palmquist, Kyle & Lauenroth, William & Bradford, John, 2021, "Estimating complex ecological variables at high resolution in heterogeneous terrain using multivariate matching algorithms," EcoEvoRxiv, Center for Open Science, number b2ux7, Apr, DOI: 10.31219/osf.io/b2ux7.
- Ekaterina Zolotareva, 2021, "Aiding Long-Term Investment Decisions with XGBoost Machine Learning Model," Papers, arXiv.org, number 2104.09341, Apr.
- Berthine Nyunga Mpinda & Jules Sadefo-Kamdem & Salomey Osei & Jeremiah Fadugba, 2021, "Accuracies of Model Risks in Finance using Machine Learning," Working Papers, HAL, number hal-03191437, Apr.
- Salomey Osei & Berthine Nyunga Mpinda & Jules Sadefo-Kamdem & Jeremiah Fadugba, 2021, "Accuracies of some Learning or Scoring Models for Credit Risk Measurement," Working Papers, HAL, number hal-03194081, Mar.
- Damiano Brigo & Xiaoshan Huang & Andrea Pallavicini & Haitz Saez de Ocariz Borde, 2021, "Interpretability in deep learning for finance: a case study for the Heston model," Papers, arXiv.org, number 2104.09476, Apr.
- Oscar Claveria & Enric Monte & Salvador Torra, 2021, "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 202101, Feb, revised Feb 2021.
- Steinbacher, Mitja & Raddant, Matthias & Karimi, Fariba & Camacho-Cuena, Eva & Alfarano, Simone & Iori, Giulia & Lux, Thomas, 2021, "Advances in the Agent-Based Modeling of Economic and Social Behavior," MPRA Paper, University Library of Munich, Germany, number 107317, Jan.
- Denis Shibitov & Mariam Mamedli, 2021, "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series, Bank of Russia, number wps70, Apr.
- Sylvia Klosin, 2021, "Automatic Double Machine Learning for Continuous Treatment Effects," Papers, arXiv.org, number 2104.10334, Apr.
- Paranhos, Livia, 2021, "Predicting Inflation with Neural Networks," The Warwick Economics Research Paper Series (TWERPS), University of Warwick, Department of Economics, number 1344.
- Mingli Chen & Andreas Joseph & Michael Kumhof & Xinlei Pan & Xuan Zhou, 2021, "Deep Reinforcement Learning in a Monetary Model," Papers, arXiv.org, number 2104.09368, Apr, revised Jan 2023.
- Daniel Jacob, 2021, "CATE meets ML -- The Conditional Average Treatment Effect and Machine Learning," Papers, arXiv.org, number 2104.09935, Apr, revised Apr 2021.
- Dueñas, Marco & Ortiz, Víctor & Riccaboni, Massimo & Serti, Francesco, 2021, "Assessing the Impact of COVID-19 on Trade: a Machine Learning Counterfactual Analysis," Working papers, Red Investigadores de Economía, number 79, Apr.
- Elliott Ash & Sergio Galletta & Tommaso Giommoni, 2021, "A Machine Learning Approach to Analyze and Support Anti-Corruption Policy," CESifo Working Paper Series, CESifo, number 9015.
- Ugo Colombino & Nizamul Islam, 2020, "Combining microsimulation and optimization to identify optimal flexible tax-transfer rule," CHILD Working Papers Series, Centre for Household, Income, Labour and Demographic Economics (CHILD) - CCA, number 86 JEL Classification: H2.
- Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021, "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/21/07, Apr.
- Ivan Jericevich & Murray McKechnie & Tim Gebbie, 2021, "Calibrating an adaptive Farmer-Joshi agent-based model for financial markets," Papers, arXiv.org, number 2104.09863, Apr.
- Minkyung Kim & K. Sudhir & Kosuke Uetake, 2019, "A Structural Model of a Multitasking Salesforce: Multidimensional Incentives and Plan Design," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2199R, Sep, revised Apr 2021.
- Hügle, Dominik, 2021, "The decision to enrol in higher education," Discussion Papers, Free University Berlin, School of Business & Economics, number 2021/8, DOI: 10.17169/refubium-29947.
- Davcheva, Elena, 2021, "Applications of Machine Learning in Mental Healthcare," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 126173.
- Guanghua Chi & Han Fang & Sourav Chatterjee & Joshua E. Blumenstock, 2021, "Micro-Estimates of Wealth for all Low- and Middle-Income Countries," Papers, arXiv.org, number 2104.07761, Apr.