The effect of school resources on pupil attainment: A multilevel simultaneous equation modelling approach

(2007) - Fiona Steele, Anna Vignoles, Andrew Jenkins

Journal: Journal of the Royal Statistical Society: Series A (Statistics in Society)
Link:: https://onlinelibrary.wiley.com/doi/10.1111/j.1467-985X.2007.00476.x
DOI:: 10.1111/j.1467-985X.2007.00476.x
Links::
Tags:: #paper #Attainment #Education
Cite Key:: [@steeleEffectSchoolResources2007]

Abstract

Improving educational achievement in UK schools is a priority, and of particular concern is the low achievement of specific groups, such as those from lower socio-economic backgrounds. An obvious question is whether we should be improving the outcomes of these pupils by spending more on their education. The literature on the effect of educational spending on pupil achievement has a number of methodological difficulties, in particular the endogeneity of school resource levels, and the intra-school correlations in pupil responses. In this paper, we adopt a multilevel simultaneous equation modelling approach to assess the impact of school resources on pupil attainment at age 14. This paper is the first to apply a simultaneous equation model to estimate the impact of school resources on pupil achievement, using the newly available National Pupil Database/Pupil Level Annual School Census (NPDB/PLASC).

Notes

“Currently, the UK spends around 5% of its annual Gross Domestic Product on education, including primary, secondary and postsecondary (compared to an OECD mean of 5.6%), and expenditure has been increasing since the mid 1990s.” (Steele et al., 2007, p. 2)

“For example, one factor in the funding allocation formula used by LEAs is the proportion of socially disadvantaged pupils in a school, which is also associated with pupil outcomes.” (Steele et al., 2007, p. 4)

“Angrist and Lavy (1999) and Jepson and Rivkin (2002) found positive effects of smaller class size on pupil attainment for Israel and California respectively. However, Hoxby (2000) found no effect of class size in Connecticut, while Dobbelsteen et al. (2002), instrumenting on teacher allocation rules, reported a significant positive effect of larger class size on attainment for the Netherlands” (Steele et al., 2007, p. 4)

“Another method tried by Hakkinen et al. (2003) is to use panel data over a number of years to difference out school and district effects. They find no effects on exam scores in Finnish upper secondary schools of changes in per pupil spending from 1990-98” (Steele et al., 2007, p. 4)

“UK studies that have made some attempt to address endogeneity have generally found small but statistically significant positive effects from school resourc” (Steele et al., 2007, p. 4)

“5 variables on educational outcomes (Dearden et al., 2001; Dolton and Vignoles, 2000; Dustmann et al., 2003; Iacovou, 2002).” (Steele et al., 2007, p. 5)

“Aggregation bias is therefore a problem for some of the studies in this field (Hanushek et al., 1996).” (Steele et al., 2007, p. 5)

“The need to control for clustering in the analysis of hierarchically structured data is well known (see, e.g., Goldstein, 2003).” (Steele et al., 2007, p. 5)

“A multilevel model is used to allow for clustering of pupil outcomes by school and LEA, and clustering of school resources by LEA. A simultaneous equation model is used to adjust for the endogeneity of school resource allocation. In this approach, pupil attainment and a measure of school resources are treated as a bivariate response.” (Steele et al., 2007, p. 5)

“In England, educational spending on both primary and secondary schooling is administered by 150 local education authorities (LEAs), which are under local government control.” (Steele et al., 2007, p. 6)