BIVPOISSON_ATE: Stata module to estimate Average Treatment Effects in Seemingly Unrelated Count Regression

Abbie Zhang and James Fisher ()
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James Fisher: NA

Statistical Software Components from Boston College Department of Economics

Abstract: When we encounter correlated count-valued outcomes y1 in {0,1,...,M} and y2 in {0,1,...,M}, the identification and estimation of average treatment effects (ATEs) need to account for the correlation structure of the data-generating process. As illustrated by Fisher, Terza, and Zhang (2022), the Stata command bivpoisson estimates deep parameters in count-valued seemingly unrelated regression (count SUR) models via fully parametric MLE. The postestimation command bivpoisson_ate supports the estimation of ATEs, the standard errors of ATEs, and its p-values in our count SUR model. An example is provided to estimate the ATEs of private insurance status on the numbers of physician office visits and non-physician health professional office visits within two weeks. The user will specify outcome y1, outcome y2, a policy variable (must be placed at the first place of the independent variable list), and two vectors of control variables.

Language: Stata
Requires: Stata version 17 and bivpoisson from SSC (q.v.)
Keywords: average treatment effects; count data; seemingly unrelated regressions (search for similar items in EconPapers)
Date: 2023-08-10
Note: This module should be installed from within Stata by typing "ssc install bivpoisson_ate". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/b/bivpoisson_ate.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/b/bivpoisson_ate.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/b/bivpoisson_ate_example.do program code (text/plain)
http://fmwww.bc.edu/repec/bocode/h/Health_Data.dta supplementary data file (application/x-stata)

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