Nonparametric segmentation methods: Applications of unsupervised machine learning and revealed preference-Reference-Cited by-同舟云学术

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Nonparametric segmentation methods: Applications of unsupervised machine learning and revealed preference

Published:2021-08-18 Issue: Volume: Page:
ISSN:0002-9092
Container-title:American Journal of Agricultural Economics
language:en
Short-container-title:American Journal of Agricultural Economics

Author:

Blumberg Joey¹,Thompson Gary²

Affiliation:

1. Department of Agricultural and Resource Economics Colorado State University Ft. Collins Colorado USA

2. Department of Agricultural and Resource Economics University of Arizona Tucson Arizona USA

Funder

Economic Research Service

National Institute of Food and Agriculture

U.S. Department of Agriculture

Publisher

Wiley

Subject

Economics and Econometrics,Agricultural and Biological Sciences (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ajae.12257

Reference67 articles.

1. The Construction of a Utility Function from Expenditure Data;Afriat Sidney;International Economic Review,1967

2. The State of Applied Econometrics: Causality and Policy Evaluation;Athey Susan;Journal of Economic Perspectives,2017

3. Machine Learning Methods that Economists Should Know About;Athey Susan;Annual Review of Economics,2019

4. Fruit and Vegetable Intake and the Risk of Cardiovascular Disease, Total Cancer and all‐Cause Mortality—a Systematic Review and Dose‐Response Meta‐Analysis of Prospective Studies;Aune D.;International Journal of Epidemiology,2017

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