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Report NEP-BIG-2022-08-29
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:
- Achim Ahrens, 2022, "Double/debiased machine learning in Stata," Italian Stata Users' Group Meetings 2022, Stata Users Group, number 06, Jul.
- Achim Ahrens, 2022, "Stacking generalization and machine learning in Stata," Italian Stata Users' Group Meetings 2022, Stata Users Group, number 05, Jul.
- Koffi, Siméon, 2022, "Prévision de l’inflation en Côte D’ivoire : Analyse Comparée des Modèles Arima, Holt-Winters, et Lstm
[Inflation Forecasting in Côte D'Ivoire: A Comparative Analysis of the Arima, Holt-Winters, and Lstm Models]," MPRA Paper, University Library of Munich, Germany, number 113961, Aug. - Andrés Alonso & José Manuel Carbó, 2022, "Accuracy of explanations of machine learning models for credit decisions," Working Papers, Banco de España, number 2222, Jun.
- Luo, Yufeng & Smith,, Travis A. & Chen,, Feifei, 2022, "Prediction of WIC Program Participation: A Machine Learning Approach to Fix Reporting Error," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322555, Aug, DOI: 10.22004/ag.econ.322555.
- Muriuki, James M. & Fuad, Syed M. & Badruddoza, Syed, 2022, "Can Machine Learning Predict Defaults in Peer-to-Peer Small Loans?," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322533, Aug, DOI: 10.22004/ag.econ.322533.
- Bhaskarjit Sarmah & Nayana Nair & Dhagash Mehta & Stefano Pasquali, 2022, "Learning Embedded Representation of the Stock Correlation Matrix using Graph Machine Learning," Papers, arXiv.org, number 2207.07183, Jul.
- Kim, Dongin & Steinbach, Sandro, 2022, "Preferential Trading in Agricultural and Food Products: New Insights from a Structural Gravity Analysis and Machine Learning," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322200, Aug, DOI: 10.22004/ag.econ.322200.
- Jos'e Pombal & Andr'e F. Cruz & Jo~ao Bravo & Pedro Saleiro & M'ario A. T. Figueiredo & Pedro Bizarro, 2022, "Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions," Papers, arXiv.org, number 2207.06273, Jul.
- Greyling, Talita & Rossouw, Stephanié, 2022, "Re-examining adaptation theory using Big Data: Reactions to external shocks," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1129.
- Fantazzini, Dean, 2022, "Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death," MPRA Paper, University Library of Munich, Germany, number 113744.
- Qian, Yilin & Thompson, Ryan & Vasnev, Andrey L, 2022, "Global combinations of expert forecasts," Working Papers, University of Sydney Business School, Discipline of Business Analytics, number BAWP-2022-02, Jul.
- Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022, "Distributional neural networks for electricity price forecasting," Papers, arXiv.org, number 2207.02832, Jul, revised Dec 2022.
- Benjamin C. Chu, 2022, "Who Did the Affordable Care Act Medicaid Expansion Impact? Using Linear Discriminant Analysis to Estimate the Probability of Being a Complier," Working Papers, University of Hawaii at Manoa, Department of Economics, number 202202, Aug.
- Takashi Nakazawa, 2022, "Constructing GDP Nowcasting Models Using Alternative Data," Bank of Japan Working Paper Series, Bank of Japan, number 22-E-9, Jul.
- Brunori, Paolo & Salas-Rojo, Pedro & Verme, Paolo, 2022, "Estimating Inequality with Missing Incomes," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1138.
- Eleni Fotopoulou & Ioanna Mandilara & Anastasios Zafeiropoulos & Chrysi Laspidou & Giannis Adamos & Phoebe Koundouri & Symeon Papavassiliou, 2022, "SustainGraph: a Knowledge Graph for tracking Evolution and Interlinking of Sustainable Development Goals' Targets," DEOS Working Papers, Athens University of Economics and Business, number 2220, Jul.
- Loïck Simon & Philippe Rauffet & Clément Guérin & Cédric Seguin, 2022, "Trust in an autonomous agent for predictive maintenance: how agent transparency could impact compliance," Post-Print, HAL, number hal-03536524, Jul, DOI: 10.54941/ahfe1001602.
- Pumplun, Luisa, 2022, "Developing a Pathway for the Adoption of Machine Learning Systems in Organizations: An Analysis of Drivers, Barriers, and Impacts with a Focus on the Healthcare Sector," 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 133617.