Journal ArticleDOI
Difference‐in‐differences when the treatment status is observed in only one period
TLDR
In this paper, the authors propose a new method that point-identifies the average treatment effect on the treated (ATT) via a difference-in-differences (DID) method when the data come from repeated cross-sections and the treatment status is observed either before or after the implementation of a program.Abstract:
Summary
This paper considers the difference-in-differences (DID) method when the data come from repeated cross-sections and the treatment status is observed either before or after the implementation of a program. We propose a new method that point-identifies the average treatment effect on the treated (ATT) via a DID method when there is at least one proxy variable for the latent treatment. Key assumptions are the stationarity of the propensity score conditional on the proxy and an exclusion restriction that the proxy must satisfy with respect to the change in average outcomes over time conditional on the true treatment status. We propose a generalized method of moments estimator for the ATT and we show that the associated overidentification test can be used to test our key assumptions. The method is used to evaluate JUNTOS, a Peruvian conditional cash transfer program. We find that the program significantly increased the demand for health inputs among children and women of reproductive age.read more
Citations
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Journal ArticleDOI
Difference-in-Differences with multiple time periods
TL;DR: It is shown that a family of causal effect parameters are identified in staggered DiD setups, even if differences in observed characteristics create non-parallel outcome dynamics between groups, and the asymptotic properties of the proposed estimators are established.
Posted Content
Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects
Sarah Abraham,Liyang Sun +1 more
TL;DR: In this article, the authors proposed an alternative estimator that is free of contamination, and illustrate the relative shortcomings of two-way fixed effects regressions with leads and lags through an empirical application.
Journal ArticleDOI
Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects
Liyang Sun,Sarah Abraham +1 more
TL;DR: In this article, the authors proposed an alternative estimator that is free of contamination, and illustrate the relative shortcomings of two-way fixed effects regressions with leads and lags through an empirical application.
Journal ArticleDOI
Loan-to-value policy and housing finance: Effects on constrained borrowers
Douglas Kiarelly Godoy de Araujo,João Barata Ribeiro Blanco Barroso,Rodrigo Barbone Gonzalez +2 more
TL;DR: In this article, the effects of an LTV limit on constrained borrowers using comprehensive loan-and borrower-level data from Brazil were explored using an adjusted difference-in-difference method, focusing on the average treatment effect on the treated borrowers.
Journal ArticleDOI
Difference-in-Differences Estimators of Intertemporal Treatment Effects
TL;DR: In this paper, the authors consider the estimation of the effect of a treatment, using panel data where groups of units are exposed to different doses of the treatment at different times, and show that under common trends conditions, all these parameters are unbiasedly estimated by weighted sums of differences-in-differences.
References
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Journal ArticleDOI
Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme
TL;DR: This paper decompose the conventional measure of evaluation bias into several components and find that bias due to selection on unobservables, commonly called selection bias in econometrics, is empirically less important than other components, although it is still a sizeable fraction of the estimated programme impact.
ReportDOI
Identification and Estimation of Local Average Treatment Effects
TL;DR: In this article, the authors investigated conditions sufficient for identification of average treatment effects using instrumental variables and showed that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect.
Journal ArticleDOI
Does matching overcome LaLonde's critique of nonexperimental estimators?
Jeffrey A. Smith,Petra E. Todd +1 more
TL;DR: The authors applied cross-sectional and longitudinal propensity score matching estimators to data from the National Supported Work (NSW) Demonstration that have been previously analyzed by LaLonde (1986) and Dehejia and Wahba (1999, 2002).
Posted Content
Large sample estimation and hypothesis testing
Whitney K. Newey,Daniel McFadden +1 more
TL;DR: In this article, conditions for obtaining cosistency and asymptotic normality of a very general class of estimators (extremum estimators) are presented, and the results are also extended to two-step estimators.
Journal ArticleDOI
Characterizing selection bias using experimental data
TL;DR: In this article, a semiparametric method is developed to estimate the bias that arises from using nonexperimental comparison groups to evaluate social programs and to test the identifying assumptions that justify matching, selection models, and the method of difference-in-differences.
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