RDHonest-vStata

This Stata package calculates honest and nearly-optimal one- and two-sided confidence intervals in fuzzy and sharp regression discontinuity designs based on local linear regression, see RDHonest package for an R version.

See the vignette for a description of the package, and the package manual available through help rdhonest once the package is installed.

Installation

Install via SSC

The released version of rdhonest is coming soon.

Install development version via github

To install the package

* Remove program if it existed previously
capture ado uninstall rdhonest
* Install most up-to-date version
net install rdhonest, from("https://raw.githubusercontent.com/tbarmstr/RDHonest-vStata/master/")

Manual Installation

To download the development version of these packages from GitHub, download the files rdhonest.ado, rdhonest.sthlp, and put them into Stata's personal ado directory, typically

• c:\ado\personal on Windows

• ~/Documents/Stata/ado on a Mac

• ~/ado on Linux

  Or run sysdir in Stata to find out local directories.

For more information on how to use personal ado files, please refer to Stata Official FAQ.

Structure

• the master folder contains the up-to-date version of the Stata package, including

  • codes: rdhonest.ado
  • help file: rdhonest.sthlp
  • Stata installation files: rdhonest.pkg and stata.toc

• subfolder tests contains testing documentations:

  • testing script: rdhonest_test.do
  • log file rdhonest_test.log

• subfolder data contains 5 exemplary data sets, including

  • cghs.dta: from Oreopoulos (2006)
  • headst.dta: from Ludwig and Miller (2007)
  • lee08.dta: from Lee (2008)
  • rcp.dta: from Battistin, Brugiavini, Rettore and Weber (2009)
  • rebp.dta: from Lalive (2008)

• subfolder vignette contains the vignette

Bug reporting and Questions

Please open issues and leave feedback, use click on the Issues tab.

References

• Main references:

  Armstrong, T. B., & Kolesár, M. (2018). Optimal inference in a class of regression models. Econometrica, 86, 655-683. doi:10.3982/ECTA14434.

  Armstrong, T. B., & Kolesár, M. (2020). Simple and honest confidence intervals in nonparametric regression. Quantitative Economics, 11(1), 1-39. doi:10.3982/QE1199

  Kolesár, M., & Rothe, C. (2018). Inference in regression discontinuity designs with a discrete running variable. American Economic Review, 108, 2277–2304. doi:10.1257/aer.20160945

• Data references:

  • cghs.dta: Oreopoulos, P. (2006). Estimating average and local average treatment effects of education when compulsory schooling laws really matter. American Economic Review, 96(1), 152-175. doi: 10.1257/000282806776157641
  • headst.dta: Ludwig, J., & Miller, D. L. (2007). Does Head Start improve children's life chances? Evidence from a regression discontinuity design. The Quarterly journal of economics, 122(1), 159-208. doi:10.1162/qjec.122.1.159
  • lee08.dta: Lee, D. S. (2008). Randomized experiments from non-random selection in US House elections. Journal of Econometrics, 142(2), 675-697. doi:10.1016/j.jeconom.2007.05.004
  • rcp.dta: Battistin, E., Brugiavini, A., Rettore, E., & Weber, G. (2009). The retirement consumption puzzle: evidence from a regression discontinuity approach. American Economic Review, 99(5), 2209-26. doi:10.1257/aer.99.5.2209
  • rebp.dta: Lalive, R. (2008). How do extended benefits affect unemployment duration? A regression discontinuity approach. Journal of econometrics, 142(2), 785-806. doi:10.1016/j.jeconom.2007.05.013