The Effect on Earnings of School and College Investment Expenditures

T is widely acknowledged that time spent in school is an important determinant of earnings. There is less agreement about the effects of expenditures per year of schooling on earnings. Most studies of the returns to schooling consider only the extensiveness (time in school) and not the intensiveness (resources invested per year) of investments. ' If schools are efficient users of resources, then intensiveness of investment can be called the quality of schooling. 2 Several studies have examined the effects on earnings of school quality (see Morgan and Sirageldin, Johnson and Stafford, Wachtel, and Welch) and college quality (Solmon, Wachtel), but no one has examined the trade-off between the two. In this study I provide some strong additional evidence that expenditures at both the school and college level are important determinants of earnings and examine the relative importance of expenditures at each level. Our examination of school expenditures is based on the NBER-TH sample of World War II veterans whose socio-economic background and life cycle behavior have been followed through test data collected by the Army in 1943 and subsequent surveys by Thorndike and Hagen in 1955 and the National Bureau of Economic Research (NBER) in 1969. Among the extensive background data collected by the NBER was information on schools attended and levels attained. Earnings data were collected in both the 1955 and 1969 surveys. These data follow the respondents through a large part of their life cycles as the mean age in 1969 was 47. The respondents chosen for the initial sample were all volunteers for Army pilot or navigator training qualification tests in 1943. Thus, the sample is all male and probably all white and is also drawn from the top half of the population intelligence distribution. Thus, it is not surprising that they attained high levels of education and earnings in the postwar period. School expenditure data for the pre-college level are difficult to obtain. Most previous studies have used state-wide average data which obscure a great deal of the variation in expenditures. Data for individual school districts are available but are incomplete. These data are used even though we are forced to reduce the potential size of the sample. 3 About 85 % of the respondents who attended college provided the names of the colleges, which were matched with expenditure data. The sample size for the model estimated is 1, 633. The availability of school expenditure data accounts for most of the reduction from an initial sample of 5, 084 NBER-TH respondents. The sample was made more homogeneous by eliminating those in poor health in 1969, those with zero or nominal earnings or real earnings in excess of 75, 000 in 1955 or 1969, and airplane pilots. An earnings function similar to many estimated before (see, for example, Griliches and Mason) is used to examine the effect of school expenditures. It includes background measures, labor force experience variables, as well as measures of the extensiveness and intensiveness of Received for publication August 16, 1974. Revision accepted for publication July 21, 1975. *This research has been supported by NIE Grant No. OEG 2-71-04798. The author is grateful to Moshe Ben Horim for research assistance. This paper has not undergone the National Bureau of Economic Research review procedures. 1 The terminology is introduced by Leibowitz. Estimates of the rate of return to investments in higher education which measure both theextensive and intensive costs are found in Leibowitz (1974) and Wachtel (1975). 2Although the profit motive is absent, there are incentives for the efficient use of resources by school administrators that suggest that expenditure levels are a reasonable quality index. A related problem is that expenditure differences reflect regional or other variations in the cost of inputs and not differences in the amount of resources used. This is true for some inputs (e. g. , land on which schools are built) but it is not true for most resources. 3 About 80% of the respondents to the 1969 survey provided the name and location of their high school. About half of these responses could be matched with available data on expenditures by school district. Missing data are due to incomplete information provided by the respondents and incomplete data available from the Office of Education. In addition, no data were available for those who attended private high schools, some 8% of the sample.