Title

Program Evaluation and Research Designs

Author(s)

John DiNardo John DiNardo (University of Michigan and NBER)

David S. Lee David Lee (Princeton University and NBER)

Abstract

This chapter provides a selective review of some contemporary approaches to program evaluation. One motivation for our review is the recent emergence and increasing use of a particular kind of program in applied microeconomic research, the so-called Regression Discontinuity (RD) Design of Thistlethwaite and Campbell (1960). We organize our discussion of these various research designs by how they secure internal validity: in this view, the RD design can been seen as a close cousin of the randomized experiment. An important distinction which emerges from our discussion of heterogeneous treatment effects is between ex post (descriptive) and ex ante (predictive) evaluations; these two types of evaluations have distinct, but complementary goals. A second important distinction we make is between statistical statements that are descriptions of our knowledge of the program assignment process and statistical statements that are structural assumptions about individual behavior. Using these distinctions, we examine some commonly employed evaluation strategies, and assess them with a common set of criteria for internal validity, the foremost goal of an ex post evaluation. In some cases, we also provide some concrete illustrations of how internally valid causal estimates can be supplemented with specific structural assumptions to address external validity: the estimate from an internally valid "experimental" estimate can be viewed as a leading term in an extrapolation for a parameter of interest in an ex ante evaluation.

Creation Date

2010-04

Section URL ID

IRS

Paper Number

555

URL

https://dataspace.princeton.edu/bitstream/88435/dsp01ms35t863r/1/555.pdf

File Function

Jel

C10, C50, C52, H00, I00, J00, J24

Keyword(s)

Regression Discontinuity Design, program evaluation, heterogeneous treatment effects

Suppress

false

Series

1