Accounting for Selective Mortality Bias on Health Outcomes: A Case Study of the Great Chinese Famine Public Deposited

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Last Modified
  • February 26, 2019
Creator
  • Huang, Alice
    • Affiliation: College of Arts and Sciences, Department of Economics
Abstract
  • Using individual-level variation in famine exposure and intensity based on individual month-year-region of birth and historical data on the size of narrowly-defined birth cohorts, I find that exposure to famine negatively impacts adult height, lowers BMI, negatively affects health status, and reduces incidence of serious illness and hypertension. I use Inverse Probability Weighting and Joint Modeling of Longitudinal and Survival Data to account for selective mortality bias in health outcome equations. Contributions are mainly threefold: first, I exploit individual-level variation in timing and length of exposure, which serves as a more precise proxy for famine. Secondly, I include additional health variables into my analysis. Finally, I apply innovative techniques to account for selective mortality bias.
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Rights statement
  • In Copyright
Note
  • Funding: Morehead-Cain Foundation
Advisor
  • Peter, Klara
Degree
  • Bachelor of Arts
Honors level
  • Highest Honors
Degree granting institution
  • University of North Carolina at Chapel Hill
Extent
  • 68 p.
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