Instrumental Variables Methods in Experimental Criminological Research: What, Why, and How?

Quantitative criminology focuses on straightforward causal questions that are ideally addressed with randomized experiments. In practice, however, traditional randomized trials are difficult to implement in the untidy world of criminal justice. Even when randomized trials are implemented, not everyone is treated as intended and some control subjects may obtain experimental services. Treatments may also be more complicated than a simple yes/no coding can capture. This paper argues that the instrumental variables methods (IV) used by economists to solve omitted variables bias problems in observational studies also solve the major statistical problems that arise in imperfect criminological experiments. In general, IV methods estimate the causal effect of treatment on subjects that are induced to comply with a treatment by virtue of the random assignment of intended treatment. The use of IV in criminology is illustrated through a re-analysis of the Minneapolis Domestic Violence Experiment.

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.

Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments

instrumental variables, natural experiment

Long-Term Economic Consequences of Vietnam-Era Conscription: Schooling, Experience and Earnings

Military service reduces civilian labor market experience but subsidizes higher education through the GI Bill. Both of these channels are likely to affect civilian earnings. New estimates of the effects of military service using Vietnam-era draft-lottery instruments show post-service earnings effects close to zero in 2000, in contrast with earlier results showing substantial earnings losses for white Vietnam veterans in the 1970s and 1980s. The recent estimates also point to a marked increase in post-secondary schooling that appears to be attributable to the Vietnam-era GI Bill. Seen through the lens of a Mincer wage equation, the wage effects observed in 2000 data can be explained by a flattening of the experience profile in middle age and a modest return to the additional schooling funded by the GI Bill. In particular, IV estimates of the returns to GI Bill-funded schooling are well below OLS estimates. Wage equations that allow for nonlinearities in the returns to schooling and a possible negative effect of military service on health, leave the main findings unchanged.veterans, returns to schooling, instrumental variables

Protective or Counter-Productive? European Labor Market Institutions and the Effect of Immigrants on EU Natives

We estimate the effect of immigrant flows on native employment in Western Europe, and then ask whether the employment consequences of immigration vary with institutions that affect labor market flexibility. Reduced flexibility may protect natives from immigrant competition in the near term, but our theoretical framework suggests that reduced flexibility is likely to increase the negative impact of immigration on equilibrium employment. In models without interactions, OLS estimates for a panel of European countries in the 1980s and 1990s show small, mostly negative immigration effects. To reduce bias from the possible endogeneity of immigration flows, we use the fact that many immigrants arriving after 1991 were refugees from the Balkan wars. An IV strategy based on variation in the number of immigrants from former Yugoslavia generates larger though mostly insignificant negative estimates. We then estimate models allowing interactions between the employment response to immigration and institutional characteristics including business entry costs. These results, limited to the sample of native men, generally suggest that reduced flexibility increases the negative impact of immigration. Many of the estimated interaction terms are significant, and imply a significant negative effect on employment in countries with restrictive institutions.

How Large are the Social Returns to Education? Evidence from Compulsory Schooling Laws

Average schooling in US states is highly correlated with state wage levels, even after controlling for the direct effect of schooling on individual wages. We use an instrumental variables strategy to determine whether this relationship is driven by social returns to education. The instrumentals for average schooling are derived from information on the child labor laws and compulsory attendance laws that affected men in our Census samples, while quarter of birth is used as an instrument for individual schooling. This results in precisely estimated private returns to education of about seven percent, and small social returns, typically less than one percent, that are not significantly different from zero.

Causal Effects of Monetary Shocks: Semiparametric Conditional Independence Tests with a Multinomial Propensity Score

Macroeconomists have long been concerned with the causal effects of monetary policy. When the identification of causal effects is based on a selection-on-observables assumption, non-causality amounts to the conditional independence of outcomes and policy changes. This paper develops a semiparametric test for conditional independence in time series models linking a multinomial policy variable with unobserved potential outcomes. Our approach to conditional independence testing is motivated by earlier parametric tests, as in Romer and Romer (1989, 1994, 2004). The procedure developed here is semiparametric in the sense that we model the process determining the distribution of treatment – the policy propensity score – but leave the model for outcomes unspecified. 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. A technical contribution is the development of root-T consistent distribution-free inference methods for full conditional independence testing, appropriate for dependent data and allowing for first-step estimation of the propensity score.monetary policy, propensity score, multinomial treatments, causality

The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics

This essay reviews progress in empirical economics since Leamer's (1983) critique. Leamer highlighted the benefits of sensitivity analysis, a procedure in which researchers show how their results change with changes in specification or functional form. Sensitivity analysis has had a salutary but not a revolutionary effect on econometric practice. As we see it, the credibility revolution in empirical work can be traced to the rise of a design-based approach that emphasizes the identification of causal effects. Design-based studies typically feature either real or natural experiments and are distinguished by their prima facie credibility and by the attention investigators devote to making the case for a causal interpretation of the findings their designs generate. Design-based studies are most often found in the microeconomic fields of Development, Education, Environment, Labor, Health, and Public Finance, but are still rare in Industrial Organization and Macroeconomics. We explain why IO and Macro would do well to embrace a design-based approach. Finally, we respond to the charge that the design-based revolution has overreached.research design, natural experiments, structural models, quasi-experiments

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.