The influence of individual health outcomes on individual savings behavior

Abstract

In this essay, data from the 2006 wave of the National Longitudinal Survey of Youth (NLSY79-2006), and the two stage least squares (2SLS) estimation technique are used to investigate the relationship between health outcomes and the willingness of individuals (age 41–50) to save. Health perception, physical component score, mental component score, depression score and the diagnosis of a variety of health problems are used as health measures for the analysis described in this essay. We find that health perception and physical component score are positively related to the willingness of individuals to save; while the diagnosis of major health problems is negatively related to the willingness of individuals to save. The effect of mental component score and depression score on individuals’ willingness to save differs significantly between males and females. A higher mental component score is found to be positively related to the willingness of females to save; while depression score is found to affect the willingness of females to save negatively. Both mental component score and depression score are not related to the willingness of male respondents to save.

Keywords:

• Health
• Savings behavior (willingness to save)
• Gender

Notes

1 Order and rank conditions are met and the WTS and health measure equations are exactly identified. The weak instrument diagnostics test shows that the instruments for health measures are not weak.

2 Equals 1 if respondent's father or mother has/had major health problems and 0 otherwise.

3 Number of years since last doctor visit.

4 Weeks respondent was unemployed in 2005 (the previous year) – all respondents currently have a job.

5 See: ‘Convergence Failures in Logistic Regression’ by Paul D. Allison for details (Allison, 2008).

6 These results are available upon request.

7 Estimation results of the reduced form equations are available upon request.

8 The NLSY79 occupational classification is used to categorize the occupational groups, and it follows 2003 census codes. Nine additional categories are created by consolidating the occupational groups because some of the occupational groups have a small number of observations.