Do school inspections improve primary school performance?

Inspectors from the Dutch Inspectorate of Education inspect primary schools, write inspection reports on each inspected school, and make recommendations as to how each school can improve. We test whether these inspections result in better school performance. Using a fixed-effects model, we find evidence that school inspections do lead to measurably better school performance. Our assessment of school performance is based on the Cito test scores of pupils in their final year of primary school. Therefore school improvement means increased Cito test scores. The results indicate that the Cito test scores improve by 2% to 3% of a standard deviation of the test score in the two years following an inspection. The arithmetic component shows the largest improvement. Our estimates are the result of an analysis of two types of school inspections performed between 1999 and 2002, where one type was more intensive than the other. In one fixed-effects model, we assume that the effect of the two types of school inspections was the same. We cannot, however, be sure that the estimates from this model are free from the problem of endogeneity bias. Therefore, we also obtain estimates for a less restrictive fixed-effects model. In this less restrictive model, we make use of the fact that a subset of the more intensive school inspections occurs at a representative selection of primary schools. Based on this smaller, essentially randomly drawn sample of schools, we can be confident that these estimates of the effect of school inspections are free from endogeneity bias. Due to the limited number of inspections at randomly selected schools, these estimates are not significantly different from zero. These estimates are, however, consistent with the effects found based on all inspections. The less restrictive model also allows for the effect of the more intensive inspections to differ from that for the less intensive ones. We find evidence that the more intensive inspections are responsible for larger increases in the Cito test scores than the less intensive ones.

Evaluating CPB's published GDP growth forecasts; a comparison with individual and pooled VAR based forecasts

We compare the accuracy of our published GDP growth forecasts from our large macro model, SAFFIER, to those produced by VAR based models using both classical and Bayesian estimation techniques. We employ a data driven methodology for selecting variables to include in our VAR models and we find that a randomly selected classical VAR model performs worse in most cases than the Bayesian equivalent, which performs worse than our published forecasts in most cases. However, when we pool forecasts across many VARs we can produce more accurate forecasts than we published. A review of the literature suggests that forecast accuracy is likely irrelevant for the non-forecasting activities the model is used for at CPB because they are fundamentally different activities.

Seasonality and Markov switching in an unobserved component time series model

It is generally acknowledged that the growth rate of output, the seasonal pattern, and the business cycle are best estimated simultaneously. To achieve this, we develop an unobserved component time series model for seasonally unadjusted US GDP. Our model incorporates a Markov switching regime to produce periods of expansion and recession, both of which are characterized by different underlying growth rates. Although both growth rates are time-varying, they are assumed to be cointegrated. The analysis is Bayesian, which fully accounts for all sources of uncertainty. Comparison with results from a similar model for seasonally adjusted data indicates that the seasonal adjustment of the data significantly alters several aspects of the full model. Copyright Springer-Verlag Berlin Heidelberg 2003Key words: Business cycle, Gibbs sampler, Kalman filter, Metropolis algorithm, Simulation smoother,

Breaks in the Variability and Comovement of G-7 Economic Growth

This paper investigates breaks in the variability and comovement of output, consumption, and investment in the G-7 economies. In contrast with most other papers on comovement, we test for changes in comovement, allowing for breaks in mean and variance. Despite claims that rising integration among these economies has increased output correlations among them, we find no clear evidence of an increase in correlation of growth rates of output, consumption, or investment. This finding is true even for the United States and Canada, which have seen a tremendous increase in bilateral trade shares, and for the euro-area members of the G-7. © 2005 President and Fellows of Harvard College and the Massachusetts Institute of Technology.