The classic regression based estimator of counterfactual means studied by Ronald Oaxaca (1973) and Alan Blinder (1973) is shown to constitute a propensity score reweighting estimator based upon a linear model for the conditional odds of being treated.

Like politics, the process of economic development is intrinsically local. Communities vie ferociously for jobs, offering tax credits, infrastructure improvements, and in some cases cash to attract investment to particular regions, cities, or even neighborhoods. In the U.S., federal and state governments target resources towards particular areas in the hopes of stimulating investment, alleviating poverty, and in some cases even recovering from natural disasters. These place based policies, though hardly new, have just begun to attract serious attention from economists. 1 As evidence on the effects of these programs begins to trickle in, it is useful to develop a theoretical framework within which to evaluate them. To many observers, spatially targeted policies are a sign of waste – an unfortunate cost of the political process. Why after all should governments pay firms to move to less productive areas and incentivize workers to live in neighborhoods they don’t like? Moreover, serious questions exist about the winners and losers of such policies in a general equilibrium environment. I study here the welfare implications of place based policies using some stylized models of spatial equilibrium incorporating taste heterogeneity and agglomeration economies. I. Baseline Model Consider a continuum of workers of measure one, faced with the decision of locating in one of two communities j ��1 � 2 � where they will work and inelastically demand a single unit of housing. 2 Agents have quasi-linear preferences over local amenities and consumption. The value to worker i oflocatingincom-

This paper develops methods for detecting discrimination by individual employers using correspondence experiments that send fictitious resumes to real job openings. We establish identification of higher moments of the distribution of job‐level callback rates as a function of the number of resumes sent to each job and propose shape‐constrained estimators of these moments. Applying our methods to three experimental data sets, we find striking job‐level heterogeneity in the extent to which callback probabilities differ by race or sex. Estimates of higher moments reveal that while most jobs barely discriminate, a few discriminate heavily. These moment estimates are then used to bound the share of jobs that discriminate and the posterior probability that each individual job is engaged in discrimination. In a recent experiment manipulating racially distinctive names, we find that at least 85% of jobs that contact both of two white applications and neither of two black applications are engaged in discrimination. To assess the potential value of our methods for regulators, we consider the accuracy of decision rules for investigating suspicious callback behavior in various experimental designs under a simple two‐type model that rationalizes the experimental data. Though we estimate that only 17% of employers discriminate on the basis of race, we find that an experiment sending 10 applications to each job would enable detection of 7–10% of discriminatory jobs while yielding Type I error rates below 0.2%. A minimax decision rule acknowledging partial identification of the distribution of callback rates yields only slightly fewer investigations than a Bayes decision rule based on the two‐type model. These findings suggest illegal labor market discrimination can be reliably monitored with relatively small modifications to existing correspondence designs.

We study the short-term impact of Connecticut's Jobs First welfare reform experiment on women's labor supply and welfare participation decisions. A nonparametric optimizing model is shown to restrict the set of counterfactual choices compatible with each woman's actual choice. These revealed preference restrictions yield informative bounds on the frequency of several intensive and extensive margin responses to the experiment. We find that welfare reform induced many women to work but led some others to reduce their earnings in order to receive assistance. The bounds on this latter “ opt-in” effect imply that intensive margin labor supply responses are nontrivial.

We use data from the Head Start Impact Study (HSIS) to evaluate the cost-effectiveness of Head Start, the largest early childhood education program in the United States. Head Start draws roughly a third of its participants from competing preschool programs, many of which receive public funds. We show that accounting for the fiscal impacts of such program substitution pushes estimates of Head Start’s benefit-cost ratio well above one under a wide range of assumptions on the structure of the market for preschool services and the dollar value of test score gains. To parse the program’s test score impacts relative to home care and competing preschools, we selection-correct test scores in each care environment using excluded interactions between experimental assignments and household characteristics. We find that Head Start generates larger test score gains for children who would not otherwise attend preschool and for children who are less likely to participate in the program.

Structural econometric methods are often criticized for being sensitive to functional form assumptions. We study parametric estimators of the local average treatment effect (LATE) derived from a widely used class of latent threshold crossing models and show they yield LATE estimates algebraically equivalent to the instrumental variables (IV) estimator. Our leading example is Heckman's (1979) two‐step (“Heckit”) control function estimator which, with two‐sided non‐compliance, can be used to compute estimates of a variety of causal parameters. Equivalence with IV is established for a semiparametric family of control function estimators and shown to hold at interior solutions for a class of maximum likelihood estimators. Our results suggest differences between structural and IV estimates often stem from disagreements about the target parameter rather than from functional form assumptions per se. In cases where equivalence fails, reporting structural estimates of LATE alongside IV provides a simple means of assessing the credibility of structural extrapolation exercises.

We study the results of a massive nationwide correspondence experiment sending more than 83,000 fictitious applications with randomized characteristics to geographically dispersed jobs posted by 108 of the largest U.S. employers. Distinctively Black names reduce the probability of employer contact by 2.1 percentage points relative to distinctively white names. The magnitude of this racial gap in contact rates differs substantially across firms, exhibiting a between-company standard deviation of 1.9 percentage points. Despite an insignificant average gap in contact rates between male and female applicants, we find a between-company standard deviation in gender contact gaps of 2.7 percentage points, revealing that some firms favor male applicants and others favor women. Company-specific racial contact gaps are temporally and spatially persistent, and negatively correlated with firm profitability, federal contractor status, and a measure of recruiting centralization. Discrimination exhibits little geographical dispersion, but two-digit industry explains roughly half of the cross-firm variation in both racial and gender contact gaps. Contact gaps are highly concentrated in particular companies, with firms in the top quintile of racial discrimination responsible for nearly half of lost contacts to Black applicants in the experiment. Controlling false discovery rates to the 5% level, 23 companies are found to discriminate against Black applicants. Our findings establish that discrimination against distinctively Black names is concentrated among a select set of large employers, many of which can be identified with high confidence using large-scale inference methods.

We study the long-run effects of one of the most ambitious regional development programs in U.S. history: the Tennessee Valley Authority (TVA). Using as controls authorities that were proposed but never approved by Congress, we find that the TVA led to large gains in agricultural employment that were eventually reversed when the program’s subsidies ended. Gains in manufacturing employment, by contrast, continued to intensify well after federal transfers had lapsed—a pattern consistent with the presence of agglomeration economies in manufacturing. Because manufacturing paid higher wages than agriculture, this shift raised aggregate income in the TVA region for an extended period of time. Economists have long cautioned that the local gains created by place-based policies may be offset by losses elsewhere. We develop a structured approach to assessing the TVA’s aggregate consequences that is applicable to other place-based policies. In our model, the TVA affects the national economy both directly through infrastructure improvements and indirectly through agglomeration economies. The model’s estimates suggest that the TVA’s direct investments yielded a significant increase in national manufacturing productivity, with benefits exceeding the program’s costs. However, the program’s indirect effects appear to have been limited: agglomeration gains in the TVA region were offset by losses in the rest of the country. Spillovers in manufacturing appear to be the rare example of a localized market failure that cancels out in the aggregate.

We develop an empirical Bayes ranking procedure that assigns ordinal grades to noisy measurements, balancing the information content of the assigned grades against the expected frequency of ranking errors. Applying the method to a massive correspondence experiment, we grade the race and gender contact gaps of 97 US employers, the identities of which we disclose for the first time. The grades are presented alongside measures of uncertainty about each firm’s contact gap in an accessible report card that is easily adaptable to other settings where ranks and levels are of simultaneous interest.