The effects of a disability on labor market performance: the case of epilepsy.

• Author: Famulari, Melissa

Introduction

In 1985, 14% of the civilian non-institutional population in the U.S., reported they had an activity limitation(1) Having a disability is therefore not an uncommon event, yet there are relatively few empirical studies which examines the effect of a disability on labor market performance(2) This study examines educational attainment, probability of employment, and wages for one group of disabled individual: people with epilepsy.

To determine the impact of a disability on labor market performance two issues seem particularly relevant. First, it is important to control for the severity of a health limitation because the effects of a disorder may not be uniform across levels of impairment. Second, while having a disability and the severity of the disability are exogenous to the individual, measuring the wage effects of activity limitations can be greatly affected by the employment and educational choices disabled individuals make.

Since many disabilities have varying degrees of severity, it may be seriously misleading to simply include a dichotomous variable to control for the effect of having a disability. Wages and the probability of employment are expected to be decreasing functions of severity. Capturing the average severity effect through a dichotomous variable may mask important differences across individuals. More importantly, the effect of a disability on some labor market phenomena may not be uniform across all levels of severity. For example, it is not necessarily the case that increases in the severity of a disability affect the marginal costs and benefits of schooling equally. While a more severe disability reduces market wages and increases the incentives to attend school, it may also reduces the amount of human capital acquired per year of schooling and decrease incentives to attend school, ceteris paribus. The effect of severity on the number of years of education is therefore an empirical question. Including only a dummy variable for a disability in an education regression would not allow for possible differences in the effects of severity on human capital acquisition.

Second, individual choices depend not only on the severity of the limitation, but also on unobservable factors such as the individual's motivation or ability to cope with the disorder. Modelling the effect of severity on the choices of educational attainment and employment are particularly important for the estimation of a wage equation. In particular, the degree of severity is expected to impact the choice of whether or not to work. The OLS estimates of the effect of a disability on wages from a sample of working individuals suffers from selection bias; working persons with a disability do not comprise a random sample of people with a disability. People whose disorder is the most severe are less likely to work than people whose disorder only slightly affects their functioning. Therefore, those who have the most severe forms of disability who still choose to work may be even more motivated than those with mild forms of disorder. Accounting for selection bias is expected to increase the estimated impact of severity on earnings. The importance of correcting for selection bias when estimating the wages of those with a disability was noted by Mitchell and Butler [8], though the authors do not focus on the effect of selection bias on the coefficient estimate on severity in their wage equation. Mitchell and Butler estimated an annual earnings equation for those with arthritis and, although they never found that the severity of arthritis significantly affected the annual earnings of those with the disorder, accounting for selection bias increased the point estimate on the effect of severity of arthritis sixteen fold.

The estimated effect of the severity of a disability on earnings may be further increased if the endogeneity of education is modeled. The level of education is generally assumed to be a predetermined variable in a wage regression. However, if the severity of a disability affects the level of education, to determine the full effects of severity on earnings, the indirect effect of severity through educational attainment should be taken into account.

To obtain estimates of the effects of a disability on labor market performance, samples of people with epilepsy and a control group were collected from the Regional Epilepsy and Burn Clinics, respectively, at Harborview Medical Center in Seattle, Washington. Because disabilities are quite varied in their impact on individual functioning, a narrowly defined group of disabled individuals was chosen in order to obtain a reasonable measure of the severity of the disability. Epilepsy was chosen not only because approximately 1-2% of the population have the disorder, but also because of the tremendous variation in the severity of this disability. This variation provides a more powerful test of the importance of severity on labor market performance because it is more likely that the effects of severity can be statistically distinguished from the effects of simply having the disorder. Importantly, the medical community has developed a measure of the severity of a seizure disorder. In this study a summary measure of severity based upon this medical measure is developed.

This data set contains actual measures of labor market experience and tenure on the job, parent's education, significant other's income, and the number of children less than six years old. It is particularly important in studies of the disabled to have measures of actual experience and tenure because the standard potential experience variable, age--education--6, may be a poor proxy for actual time spent in the labor market. In addition, determining who has epilepsy and the severity of their disorder was not based on self-reported information, but rather was determined from the individual's medical chart. Two different control groups, patients at the Burn clinic and individuals in Washington State who participated in the 1986 Current Population Survey (CPS), were used in the empirical analysis. While the CPS is missing several key explanatory variables, results based on the CPS are used as a benchmark for the results found using the Burn control sample.

The paper is organized as follows. First, the measurement of the severity of a seizure disorder for the individuals in this study is described. Then data collection methods, a description of the samples used in the hypothesis tests, and summary statistics are presented. The effects of seizure severity on education regressions, employment probits, and wage equations are estimated and presented in the next section. The estimated effects of seizure severity are compared across an OLS wage regression, a selection bias corrected wage regression, and the selectivity corrected wage equation when accounting for the endogeneity of education. The assumption of equal effects of severity by sex is tested. Finally, conclusions are drawn.

2. The Measure of Seizure Severity

   The measure of seizure severity used in this study is an individual's predicted score on the Halstead-Reitan Neuropsychological Test Battery, where the prediction is based upon the individual's seizure characteristics. The Halstead-Reitan test battery is the standard tool used by the medical community, both in terms of patient management and in terms of measuring research outcomes, to assess the functional capacity of individuals with epilepsy. The high cost of administering the test battery precluded testing the individuals in this study directly. As an alternative, a sample of 787 people with epilepsy collected by Dr. Carl Dodrill, a neuropsychologist at Harborview Medical Center was used to derive a prediction equation. The Halstead-Reitan test battery score was regressed on the seizure characteristics for the Dodrill sample of 787 people with epilepsy. Since the same seizure characteristics for the people with epilepsy in this study's sample, it was possible to compute a predicted Halstead-Reitan test score. Comparisons of seizure characteristic means between the Dodrill sample and the sample of people with epilepsy used in this analysis and the coefficient estimates of the prediction equation are presented in Appendices 1 and 2.

   Seizure characteristics explain about 15 percent of the individual variation in Halstead-Reitan test scores. Thus the variation in predicted severity for the people with epilepsy in my sample is much less than the variation in measured severity obtained if the test battery had been administered directly. Nonetheless, any variation in severity is an improvement over a dichotomous representation of epilepsy. Given the relatively small amount of test score variation which is explained by seizure characteristics, it seems more reasonable to assume that the predicted Halstead score appropriately assigns individuals into low, medium, and high impairment...