Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217175 
Year of Publication: 
2019
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 10 [Issue:] 4 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2019 [Pages:] 1579-1618
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
This paper considers identification and estimation of the Quantile Treatment Effect on the Treated (QTT) under a straightforward distributional extension of the most commonly invoked Mean Difference in Differences Assumption used for identifying the Average Treatment Effect on the Treated (ATT). Identification of the QTT is more complicated than the ATT though because it depends on the unknown dependence (or copula) between the change in untreated potential outcomes and the initial level of untreated potential outcomes for the treated group. To address this issue, we introduce a new Copula Stability Assumption that says that the missing dependence is constant over time. Under this assumption and when panel data is available, the missing dependence can be recovered, and the QTT is identified. We use our method to estimate the effect of increasing the minimum wage on quantiles of local labor markets' unemployment rates and find significant heterogeneity.
Subjects: 
Quantile Treatment Effect on the Treated
Difference in Differences
copula
panel data
propensity score reweighting
JEL: 
C14
C20
C23
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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