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Heterogeneous treatment-effect analysis


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  • Ben Jann

    (ETH Z├╝rich)

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Methods for causal inference and the estimation of treatment effects have received much attention in recent years. Most of the methodological and applied work focuses on the identification of so-called average treatment effects, possibly restricted to the treated or the untreated. However, treatment effects may vary (hence the averaging), and it can be interesting to analyze the patterns of effect heterogeneity. In this talk, I will present a new command called hte that is used for heterogeneous treatment-effect analysis in Stata. hte first constructs balanced propensity-score strata and, within each stratum, estimates the average treatment effect. hte then tests for a linear trend in effects across the strata. The stratum-specific treatment effects and the estimated linear trend are displayed in a two-way graph. hte results from joint work with Jennie E. Brand (UCLA) and Yu Xie (University of Michigan).

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Bibliographic Info

Paper provided by Stata Users Group in its series German Stata Users' Group Meetings 2010 with number 03.

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Date of creation: 13 Jul 2010
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Handle: RePEc:boc:dsug10:03

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Cited by:
  1. Mutuc, Maria Erlinda M. & Rejesus, Roderick M. & Yorobe, Jose M., Jr., 2012. "Which Farmers Benefit the Most from Bt Corn Adoption in the Philippines? Estimating Heterogeneity Effects," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126363, International Association of Agricultural Economists.


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