archives@tulane.edu / It is well known that estimates of average treatment effects may obscure heterogeneous responses within treatment subgroups. In this dissertation, I use a common methodology—the triple differences estimator—to investigate subgroup heterogeneity within treatment cohorts. Within each chapter, I begin by using the difference-in-differences estimator to determine the average treatment effect of a natural experiment on a particular group. I then use the triple differences estimator to investigate whether subgroups within the treatment population respond differentially to the same intervention.
The chapter “Fertility Responses to the 1994 Earned Income Tax Credit (EITC) Expansion” investigates whether groups that have a revealed preference for larger families respond to the EITC expansion by increasing family size. The chapter “Non-Income Behavioral Responses to the 1994 EITC Expansion” uses a similar definition for revealed preference for family size. This chapter investigates whether families who used paid tax preparers or who do not have a revealed preference for larger size respond to the EITC expansion by reducing the number of children claimed on their taxes. The fianl chapter, “Worker-level Responses to Trade Shocks”, estimates whether the welfare of certain classes of fragile manufacturing workers responds differentially to a sharp reduction and recovery in import penetration.
Each chapter uncovers surprising heterogeneity that diverges from the average treatment cohort effect. Families that prefer larger families increase family size post-expansion; post-expansion, families that use paid preparers reduce large family claims. For two out of three classes of fragile workers, increases in import penetration are associated with increased wage once manufacturing output recovers from shock. As a whole, this work points to the importance of taking a second look at salient underlying differences that may necessitate varied policy solutions to a common, unexpected occurrence. / 1 / Stephanie Fortune-Taylor
Identifer | oai:union.ndltd.org:TULANE/oai:http://digitallibrary.tulane.edu/:tulane_110876 |
Date | January 2019 |
Contributors | Stephanie Fortune-Taylor (author), Steven M. Sheffrin (Thesis advisor), School of Liberal Arts Economics (Degree granting institution) |
Publisher | Tulane University |
Source Sets | Tulane University |
Language | English |
Detected Language | English |
Type | Text |
Format | electronic, pages: 170 |
Rights | No embargo, Copyright is in accordance with U.S. Copyright law. |
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