An Analysis of the Health and Retirement Status of the Elderly

in this paper we specify and estimate a structural limited dependent variable model with which we study both the health and retirement status of the elderly. Standard linear estimators, which assume that these variable sare continuous, are not appropriate and categorical estimation techniques are preferred. Our model differs from previous work in that we have longitudinal data and random effects that are correlated over time for different individuals. The problem is made more complicated because there is sample truncation, which could potentially bias coefficient estimates, since approximately twenty percent of the individuals in our sample die. We outline the full information maximum likelihood estimator for such a model and implement it in our empirical analysis. With our structural estimates we analyze, among other things, the degree to which endogeneously determined health status affects the probability of retirement and how changes in social security benefits and eligibility for transfer payments modify both healthiness and the demand for leisure.

Health, Mental Health and Labor Productivity: The Role of Self-Reporting Bias

This paper relates physical and mental health status to labor force participation and compares these relationships among self-report and proxy respondents. Previous research has conjectured that self-reports of health status may lead to an upward bias in the estimated effect of health on labor productivity because subjects who are out of the labor force may be more likely to understate their health status so as to justify their lack of employment. Also, we integrate mental health into our study by using two alternative approaches-logistic regression analysis and propensity scoring methods. We find that among the cohort of self-reporters, physical health has a substantially stronger impact on labor productivity than mental health; precisely the opposite patterns were obtained when physical and mental health status were reported by proxy respondents. These results suggest the self-reports may lead to a bias in estimating labor productivity costs of physical versus mental health on labor force participation by overestimating the importance of good physical health and underestimating the role of good mental health. This in turn suggests that the benefits of more generous mental health insurance benefits may have been underappreciated in the medical policy debates.

Bootstrapping Unit Root Tests with Covariates

We consider the bootstrap method for the covariates augmented Dickey-Fuller (CADF) unit root test suggested in Hansen (1995) which uses related variables to improve the power of univariate unit root tests. It is shown that there are substantial power gains from including correlated covariates. The limit distribution of the CADF test, however, depends on the nuisance parameter that represents the correlation between the equation error and the covariates. Hence, inference based directly on the CADF test is not possible. To provide a valid inferential basis for the CADF test, we propose to use the bootstrap procedure to obtain critical values, and establish the asymptotic validity of the bootstrap CADF test. Simulations show that the bootstrap CADF test significantly improves the finite sample size performances of the CADF test, especially when the covariates are highly correlated with the error. Indeed, the bootstrap CADF test offers drastic power gains over the conventional ADF test. We apply our testing procedures to the extended Nelson-Plosser data set for the post-1929 samples as well as postwar annual CPI-based real exchange rates for 14 OECD countries.

Two-measured variable method for wall interference assessment/correction

An iterative method for wall interference assessment and/or correction is presented for transonic flow conditions in wind tunnels equipped with two component velocity measurements on a single interface. The iterative method does not require modeling of the test article and tunnel wall boundary conditions. Analytical proof for the convergence and stability of the iterative method is shown in the subsonic flow regime. The numerical solutions are given for both 2-D and axisymmetrical cases at transonic speeds with the application of global Mach number correction