THE EFFECTS OF HIGH SCHOOL ATHLETIC PARTICIPATION ON EDUCATION AND LABOR MARKET OUTCOMES.(Statistical Data Included)

 
   Sports and other forms of vigorous physical activity provide educational 
   experience which cannot be duplicated in the classroom. They are an 
   uncompromising laboratory in which we must think and act quickly and 
   efficiently under pressure and then force us to meet our own inadequacies 
   face-to-face and to do something about them, as nothing else does.... 
   Sports resemble life in capsule form and the participant quickly learns 
   that his performance depends upon the development of strength, stamina, 
   self-discipline and a sure and steady judgment. 

--Supreme Court Justice Byron White

I. Introduction

IN recent years, many communities have had to face the difficult choice of reducing the funding of their high school athletic programs.(1) Yet, as the above quote suggests, some would argue that such sports programs should be an integral part of the learning experience. This paper considers evidence of the effects of participation in high school athletics on later educational attainment and labor market outcomes in terms of wages and employment. Examining the raw differences, one might argue that athletic participation is quite important. From the National Longitudinal Survey of Youth, one discovers that men at an average age of 32 who had participated in high school athletics were paid 31% higher wages than those who had not participated. From the National Longitudinal Study of the High School Class of 1972, one finds that men at an average age of 31 who had participated in high school athletics were paid 12% higher wages than those who had not participated. To correctly interpret such evidence, however, we must first understand the choice of athletic participation. In section I, we introduce a simple allocation-of-time model as a vehicle for explaining the athletic participation choice and the implications of this choice for educational and labor market outcomes. Four different factors that could explain athletic participation are identified in the context of this model.

Section II then considers more carefully the evidence drawn from the above-mentioned two data sets: the National Longitudinal Survey of Youth (NLSY) and the National Longitudinal Study of the High School Class of 1972 (NLS-72). Our empirical results are similar across these two data sets. There is a clear direct link for men between athletic participation and both additional formal education and wages. These results rule out two of the four contributing factors for athletic participation in the simple allocation-of-time model as dominant factors. However, this need not imply that we must modify the model to incorporate a role for athletic participation as a contributor to individual productivity. The simple allocation-of-time model suggests two additional factors that not only explain athletic participation but are largely consistent with the findings. These two factors are ability and preference for leisure. Higher-ability individuals or individuals with a reduced preference for leisure are more likely to choose to participate in athletic events. In such cases, athletic participation can be viewed as a signal of individuals with higher ability or greater "work ethic" or industriousness. The resulting higher educational attainment and improved labor market outcomes that are linked to athletic participation then simply become a reflection of the inherent capabilities of more able or industrious individuals.

The view that differential ability or value of leisure is behind the correlation between athletic participation and both educational attainment and wages is partially supported by the fact that, when one introduces controls for ability, the strength of the relationships between athletic participation and educational and labor market outcomes is reduced. Further evidence is then considered in an attempt to distinguish between athletic participation that serves as a signal of an individual's ability or industriousness from athletic participation that provides individuals valuable training. We find, for instance, evidence of sorting by those who participated in athletics into positions that link wages to job performance; this favors the interpretation of athletic participation as a proxy for heterogeneity in the underlying characteristics of individuals in terms of ability or industriousness. Similarly, an application of the instrumental-variable approach of two-stage least squares to an analysis of wages offers little support for an expanded model of athletic participation that incorporates a potential team production and human-capital enhancement outcome to athletic participation. However, we do find across both data sets that athletic participation is distinct from participation in other extracurricular activities in terms of its link to wages. This one finding does suggest that athletic participation may in fact serve as a training activity. Concluding remarks appear in section III.

The research in this paper builds on the existing work of Long and Caudill (1991), who studied the effects of college athletic participation, and several sociologists who investigated the effects of high school athletics. Long and Caudill find that male varsity collegiate athletes receive greater incomes, measured ten years after entering college, than their non-athlete counterparts. They also find that these male varsity college athletes are more likely to have graduated from college than their non-athlete counterparts.(2) They interpret these findings to suggest that "[varsity college] athletic participation may enhance the development of discipline, confidence, motivation ... or other subjective traits that encourage success" (p. 529). Maloney and McCormick (1993) examine the effects that college athletic participation has on various measures of academic achievement, focusing on the classroom success of athletes at a large land-grant institution. Overall, they find that athletes do not fare as well academically as non-athletes. However, most of this difference can be explained by background factors. Additionally, this "under performance" is greatest for athletes in the revenue sports, in which a seasonal phenomenon is found to exist.

Sociologists have studied the subject of high-school athletic participation, and their literature contains mixed results. Howell, Miracle, and Rees (1984) examine the earnings of males one year and five years after high school graduation. They find that no premium is earned by varsity high school athletes for those who did not attend college. They suggest that the lack of a significant effect of athletic participation on earnings may not have had time to manifest itself given the small number of years between high school and the year for which they estimate earnings equations. They do find some evidence that these athletes obtain higher levels of schooling.

Picou, McCarter, and Howell (1985) consider the effect that varsity high school athletic participation has on income and educational attainment eleven years after high school graduation for whites and blacks by gender. Their results indicate that only white males gain in terms of income and educational attainment from participating in varsity high school sports. Several other papers in the sociology literature have also considered the effects of participation in varsity high school athletics. Their major focus, however, has been on occupational status, "self-concepts," and various types of aspirations. See, for instance, Marsh (1993) and Sabo, Melnick, and Vanfossen (1993).

In general, the sociology papers ignore the human-capital model of income determination and presume that income determination is solely a function of background variables and high school performance. Ignoring variables known to affect wages (such as tenure at the firm, experience, and compensating differentials for urban areas) may bias the results. Further, the sociological studies have not formally modeled the underlying sorting/signaling aspect of athletic participation. Thus, the purpose of this paper is two-fold. First, we seek to develop a simple theoretical model for predicting relationships between high school athletic participation and educational and labor market outcomes. Second, we seek to provide empirical analysis across multiple data sets concerning the effects of athletic participation that includes controls that economists typically identify as important.

II. Models of High School Athletic Participation

To examine the potential implications of athletic participation, we first have to understand why some individuals choose to participate in athletic activities while others do not. To do so, consider a simple two-period model of time allocation as suggested by Becker (1965). In the first period, utility depends on leisure and the consumption of athletics. Leisure can be reduced in two ways. First, there is the fraction [T.sub.e1] of the first period that is devoted to acquiring an education. The reward to time spent acquiring an education is a higher future stock of human capital and the resulting greater future income. Leisure in the first period can also be reduced by the fraction of the period devoted to participating in athletics, denoted by [T.sub.a]. The gain to the time allocated to athletics is the utility value of the consumption of the good "athletics." Assuming utility is separable in leisure and the consumption of athletic activity, we have

(1) utility in first period = [Alpha]u([T.sub.a]) + [Theta]v(1 - [T.sub.a] - [T.sub.e1])

in which the fraction of the first period spent in athletics and on education ([T.sub.a] and [T.sub.e1], respectively) are constrained to be non-negative. We make the natural assumption of a positive but declining marginal utility to athletic participation and leisure, such that v' [is greater than] 0, u' [is greater than] 0, v" [is less than] 0 and u" [is less than] 0. In equation (1), differences across individuals in the parameters [Alpha] and [Theta] reflect differences in the consumption value of athletic activities and the value of leisure, respectively.

In the second period, utility depends on leisure and income. Income depends on the fraction of the period spent working, [T.sub.w], and on the individual's wage, w. During the second period, the individual can also devote time to the acquisition of additional education, [T.sub.e2], with [T.sub.e2] [is greater than or equal to] 0.(3) Thus, we have

(2) utility in second period = w[T.sub.w] + [Theta]v(1 - [T.sub.w] - [T.sub.e2]).

The wage received by the individual in the second period reflects the individual's stock of human capital H accumulated during the first and second periods. The stock of human capital acquired during the first period (the high school experience) depends on the time devoted toward studies, [T.sub.e1], and on the individual's ability level, [Gamma]. Additional human capital acquired during the second period reflects the time devoted to education during that period, [T.sub.e2]. In particular,

(3) w = H([T.sub.e1] + [Gamma], [T.sub.e2], k),

where H([multiplied by]) denotes the stock of human capital. Note tire specific form in which ability differences are introduced in equation (3), by the parameter [Gamma]. As we discuss in more detail below, this form will result in higher-ability individuals having more "free time" in high school to devote to athletics.(4) The parameter k in equation (3) captures other factors that influence the extent of human capital acquired by an individual. Later, we interpret k as reflecting the potential training provided to athletic participants. We assume that time devoted to acquiring human capital through formal education both during high school and beyond has positive but diminishing returns. That is, [H.sub.1] [is greater than] 0, [H.sub.2] [is greater than] 0, [H.sub.11] [is less than] 0, and [H.sub.22] [is less than] 0. Finally, human capital acquired during high school in the first period is assumed to complement the return to education in the second period, in that [H.sub.12] [is greater than] 0.

The objective of the individual is to choose [T.sub.a], [T.sub.e1], [T.sub.e2], and [T.sub.w] to maximize two period utility:

(4) [Alpha] [multiplied by] [T.sub.a] + [Theta] [multiplied by] v(1 - [T.sub.a] - [T.sub.e1]) + [Beta][w [multiplied by] [T.sub.w] + [Theta] [multiplied by] v(1 - [T.sub.w] - [T.sub.e2])],

subject to [T.sub.a] [is greater than or equal to] 0, [T.sub.e1] [is greater than or equal to] 0, [T.sub.e2] [is greater than] 0, 1 [is greater than or equal to] [T.sub.a] + [T.sub.e2], and 1 [is greater than or equal to] [T.sub.w] + [T.sub.e2]. (Note that 1 [is greater than or equal to] [Beta] [is greater than or equal to] 0 is the discount factor.)

In the above setting, individuals who choose [T.sub.a] [is greater than] 0 are identified as ones who participate in high school athletics. It is important to note that the above analysis assumes that athletic participation involves only the allocation of time away from two activities: leisure and the acquisition of human capital. Athletic participation makes no direct contribution to an individual's stock of human capital. Later, in addition to the "fun" aspect of athletics, we expand the model to allow athletics to have a separate contribution to human-capital development. This will capture the idea that athletic participation can develop discipline, confidence, and motivation that enhance human-capital acquisition.

Comparative static analysis, summarized in table 1, identifies changes in parameter values that increase the likelihood of participation in athletics.(5) Table 1 also indicates the likely accompanying changes in the optimal levels of [T.sub.e1] + [Gamma] (the acquisition of human capital during high school), [T.sub.w] (the extent of participation in the labor …