Online Program Home
My Program

Abstract Details

Activity Number: 330 - Bayesian Analysis of Latent Variable Models in Economics
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2018 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract #330487
Title: Integrated Analysis of the Life-Cycle Interactions Between Health and Socioeconomic Status
Author(s): Ivan Jeliazkov* and Angela Vossmeyer
Companies: University of California - Irvine and Claremont McKenna College
Keywords: discrete data; Markov chain Monte Carlo; health and wealth interactions; endogeneity; simultaneity; joint modeling

This article presents a joint multivariate model of the life-cycle interactions between health and socioeconomic status and addresses concerns that emerge in the analysis. A key complicating factor is that outcome variables in the data are discrete, and hence the likelihood function is analytically intractable. Another problem is the presence of endogeneity and simultaneity, which, in conjunction with the discrete dependent variables, renders standard estimators inapplicable. Motivated by these difficulties, we present a simulation-based estimation method that circumvents the intractability of the likelihood, makes inference possible, and allows joint modeling and simultaneous estimation of the interactions of interest. These aspects of the inferential framework are of fundamental importance in dealing with misspecification issues. The methodology is also appealing because it is flexible, computationally efficient, and can be easily modified to capture a variety of interactions in the system.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2018 program