Distribution-free estimation of zero-inflated models with unobserved heterogeneity
- Authors
- Gilles, Rodica; Kim, Seik
- Issue Date
- 6월-2017
- Publisher
- SAGE PUBLICATIONS LTD
- Keywords
- Excess zeros; zero inflation; nonnegative data; robust estimation; quasi-likelihood estimation
- Citation
- STATISTICAL METHODS IN MEDICAL RESEARCH, v.26, no.3, pp.1532 - 1542
- Indexed
- SCIE
SCOPUS
- Journal Title
- STATISTICAL METHODS IN MEDICAL RESEARCH
- Volume
- 26
- Number
- 3
- Start Page
- 1532
- End Page
- 1542
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/83189
- DOI
- 10.1177/0962280215588940
- ISSN
- 0962-2802
- Abstract
- This paper presents a quasi-conditional likelihood method for the consistent estimation of both continuous and count data models with excess zeros and unobserved individual heterogeneity when the true data generating process is unknown. Monte Carlo simulation studies show that our zero-inflated quasi-conditional maximum likelihood (ZI-QCML) estimator outperforms other methods and is robust to distributional misspecifications. We apply the ZI-QCML estimator to analyze the frequency of doctor visits.
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Collections - College of Political Science & Economics > Department of Economics > 1. Journal Articles
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