Estimating Dynamic Treatment Effects from Project STAR (Working Paper 36)

This paper considers the analysis of data from randomized trials which offer a sequence of interventions and suffer from a variety of problems in implementation. In experiments that provide treatment in multiple periods (T>1), subjects have up to 2^{T}-1 counterfactual outcomes to be estimated to determine the full sequence of causal effects from the study. Traditional program evaluation and non-experimental estimators are unable to recover parameters of interest to policy makers in this setting, particularly if there is non-ignorable attrition. We examine these issues in the context of Tennessee's highly influential randomized class size study, Project STAR. We demonstrate how a researcher can estimate the full sequence of dynamic treatment effects using a sequential difference in difference strategy that accounts for attrition due to observables using inverse probability weighting M-estimators. These estimates allow us to recover the structural parameters of the small class effects in the underlying education production function and construct dynamic average treatment effects. We present a complete and different picture of the effectiveness of reduced class size and find that accounting for both attrition due to observables and selection due to unobservable is crucial and necessary with data from Project STAR

An Evidence-Based Approach to Access Reform (Working Paper 22)

In August 2000, the federal government began an internal review of the Access to Information Act (ATIA). The ATIA gives Canadians a qualified right of access to records held by federal institutions. Decisions about reform should be based on good evidence about the operation of the Act and the likely impact of proposed reforms. This paper describes how data on ATIA operations is collected by federal institutions and provides a guide to academic researchers interested in conducting empirical research on the operation of the law. It constructs a small dataset that describes the processing of a sample of 663 requests received in 1999, and uses this dataset to illustrate the potential of an evidence-based approach to ATIA reform. The dataset can be downloaded from http://evidence.foilaw.net. The project was supported by a $4,800 grant from the Principal’s Development Fund of Queen’s University awarded in May 2001. Comments should be sent to the principal investigator, Alasdair Roberts, at roberts@policystudies.ca.