An Analysis of the Factors that Influence Student Performance: A Fresh Approach to an Old Debate

I. INTRODUCTION There is a general consensus that the performance of students exiting the elementary and secondary school system has been slipping. In the past it was popular to believe that raising educational standards meant investing more money in schools; i.e., the best schools were the ones that spent the most money. Today, inner-city schools typically spend at least 50% more on per pupil expenditures than the U.S. average, yet these schools are failures by almost any measure. This suggests that spending more on a school does not necessarily mean that its students will learn more. Most research attempting to link student performance and expenditures stems from the conclusions drawn from the Coleman report (Coleman et al., 1966). In brief, this report finds that school expenditures have only a minor influence on student achievement. Instead, variations in family background and in the backgrounds of other students in the school are the primary determinants of students' performance. Nearly three decades after the Coleman report, Hanushek (1986, 1989, 1996) surveys most of the recent published empirical literature and also concludes that there is no clear relationship between school expenditures and student performance. Hedges et al. (1994) and Hedges and Greenwald (1996) reanalyze essentially the same studies summarized by Hanushek, yet their statistical evidence suggests that school expenditures have a statistically significant and positive influence on student achievement. Sander (1993) and Ferguson and Ladd (1996) also conclude that school expenditures can have significant effects on educational outcomes. Other studies explore the relationship between expenditures on schools and future earnings and arrive at the same conflicting results. Card and Krueger (1992) estimate the relationship between the return to schooling in a given state and several attributes of a state's educational system. Their results indicate that additional school resources are powerfully linked to increases in students' earnings as adults. Heckman et al. (1996) find that Card and Krueger's conclusions are very sensitive to their assumption of strict linearity. Once this assumption is relaxed, the importance of school resources shrinks dramatically. For example, school resources appear to have little or no effect on the earnings of workers who have not completed college. Lastly, Betts (1995) examines three commonly used measures of school quality, class size, teachers' salaries, and teachers' level of education, and also finds no significant relation between them and subsequent earnings of workers. From an economist's point of view, the connection between money and education is maddeningly unclear. A number of difficulties plague earlier studies on this subject. This paper seeks to remedy this state of affairs by offering a better data design and a sounder methodology. First, the data set is comprehensive and includes virtually every 4th, 8th, and 12th grade student in the state of Massachusetts. Other commonly used measures of student performance, like the SAT scores, are not reliable since they suffer from selectivity bias (Hanushek and Taylor, 1990) and are taken only by older students. Further, since each observation in the data set is for an individual school district and all school districts lie within the same state (following the same laws and regulations), the problem of omitted variable bias is reduced. This less aggregated data set contains more information about community characteristics and tends to produce more reliable estimates of the tree impact of school expenditure on attainment (see Hanushek et al., 1996). Second, the estimation method is statistically sound and captures the nonlinearities inherent in the model.(1) This study uses the 1992 Massachusetts Educational Assessment Program (MEAP) test scores for the three aforementioned grade levels to measure student performance. Since MEAP scores can fall into one of five different categories, there is no unique dependent variable measuring student performance in this application. …