Treatment Effect Heterogeneity in Theory and Practice

Instrumental Variables (IV) methods identify internally valid causal effects for individuals whose treatment status is manipulable by the instrument at hand. Inference for other populations requires some sort of homogeneity assumption. This paper outlines a theoretical framework that nests all possible homogeneity assumptions for a causal treatment-effects model with a binary instrument. The framework suggests strategies for using IV estimates for extrapolation, while making it clear that efforts to go from local average treatment effects (LATE) to population average treatment effects are inherently speculative. These ideas are illustrated in an application using sibling-sex composition to estimate the effect of child-bearing on economic and marital outcomes for mothers with two or more children. The application is motivated by welfare reform, which penalizes further childbearing by welfare mothers on the grounds that more children make continued poverty and welfare receipt more likely. The empirical results generally support the notion of reduced labor supply and increased poverty rates as a consequence of additional childbearing, but evidence on the impact of childbearing on marital stability and welfare use is more tenuous. Another interesting finding is that for the sample of teen mothers, LATE is essentially equal to the population average treatment effect.

Does Teacher Testing Raise Teacher Quality? Evidence from State Certification Requirements

The education reform movement includes efforts to raise teacher quality through stricter certification and licensing provisions. Most US states now require public school teachers to pass a standardized test such as the National Teacher Examination. Although any barrier to entry is likely to raise wages in the affected occupation, the theoretical effects of such requirements on teacher quality are ambiguous. Teacher testing places a floor on whatever skills are measured by the required test, but testing is also costly for applicants. These costs shift teacher supply to the left and may be especially likely to deter high-quality applicants from teaching in the public schools. We use the Schools and Staffing Survey to estimate the effect of state teacher testing requirements on teacher wages and teacher quality as measured by educational background. The results suggest that state-mandated teacher testing increases teacher wages with no corresponding increase in quality.

The Effect of High School Matriculation Awards: Evidence from Randomized Trials

In Israel, as in many other countries, a high school matriculation certificate is required by universities and some jobs. In spite of the certificate's value, Israeli society is marked by vast differences in matriculation rates by region and socioeconomic status. We attempted to increase the likelihood of matriculation among low-achieving students by offering substantial cash incentives in two demonstration programs. As a theoretical matter, cash incentives may be helpful if low-achieving students reduce investment in schooling because of high discount rates, part-time work, or face peer pressure not to study. A small pilot program selected individual students within schools for treatment, with treatment status determined by previous test scores and a partially randomized cutoff for low socioeconomic status. In a larger follow-up program, entire schools were randomly selected for treatment and the program operated with the cooperation of principals and teachers. The results suggest the Achievement Awards program that randomized treatment at the school level raised matriculation rates, while the student-based program did not.

Sources of Identifying Information in Evaluation Models

The average effect of social programs on outcomes such as earnings is a parameter of primary interest in econometric evaluations studies. New results on using exclusion restrictions to identify and estimate average treatment effects are presented. Identification is achieved given a minimum of parametric assumptions, initially without reference to a latent index framework. Most econometric analyses of evaluation models motivate identifying assumptions using models of individual behavior. Our technical conditions do not fit easily into a conventional discrete choice framework, rather they fit into a framework where the source of identifying information is institutional knowledge regarding program administration. This framework also suggests an attractive experimental design for research using human subjects, in which eligible participants need not be denied treatment. We present a simple instrumental variables estimator for the average effect of treatment on program participants, and show that the estimator attains Chamberlain's semi-parametric efficiency bound. The bias of estimators that satisfy only exclusion restrictions is also considered.

Long-term consequences of vietnam-era conscription: schooling, experience, and earnings

This paper uses the 2000 Census 1-in-6 sample to look at the long-term impact of Vietnam-era military service. Instrumental Variables estimates using draft-lottery instruments show post-service earnings losses close to zero in 2000, in contrast with earlier results showing substantial earnings losses for white veterans in the 1970s and 1980s. The estimates also point to a marked increase in schooling that appears to be attributable to the Vietnam-era GI Bill. The net wage effects observed in the 2000 data can be explained by a flattening of the experience profile in middle age and a modest return to the increased schooling generated by the GI Bill. Evidence on disability effects is mixed but seems inconsistent with a long-term effect of Vietnam-era military service on health.

Schooling and Labor Market Consequences of the 1970 State Abortion Reforms

This study uses the 1970 state abortion reforms to estimate the effect of teen and out-of-wedlock childbearing on the schooling and labor market outcomes of mothers observed in 1980 and 1990 Census microdata. Reduced-form estimates suggest that state abortion reforms had a negative impact on teen marriage, teen fertility, and teen out- of-wedlock childbearing. The teen marriage effects are largest and most precisely estimated for white women while the teen fertility and out-of-wedlock childbearing effects are largest and most precisely estimated for black women. The relatively modest fertility and marriage consequences of abortion reform for white women do not appear to have changed schooling or labor market outcomes. In contrast, black women who were exposed to abortion reforms experienced large reductions in teen fertility and teen out-of-wedlock fertility that appear to have led to increased schooling and employment rates. Instrumental variables estimates of the effects of teen and out-of- wedlock childbearing on the schooling and employment status of black women, using measures of exposure to abortion reform as instruments, are marginally significant and larger than the corresponding OLS estimates.

Semiparametric Causality Tests Using the Policy Propensity Score

Time series data are widely used to explore causal relationships, typically in a regression framework with lagged dependent variables. Regression-based causality tests rely on an array of functional form and distributional assumptions for valid causal inference. This paper develops a semi-parametric test for causality in models linking a binary treatment or policy variable with unobserved potential outcomes. The procedure is semiparametric in the sense that we model the process determining treatment -- the policy propensity score -- but leave the model for outcomes unspecified. This general approach is motivated by the notion that we typically have better prior information about the policy determination process than about the macro-economy. A conceptual innovation is that we adapt the cross-sectional potential outcomes framework to a time series setting. This leads to a generalized definition of Sims (1980) causality. We also develop a test for full conditional independence, in contrast with the usual focus on mean independence. Our approach is illustrated using data from the Romer and Romer (1989) study of the relationship between the Federal reserve's monetary policy and output.