XTDHAZARD: Stata module to perform Own-Differences IV/CF Estimation of the Discrete-Time Hazard Model

xtdhazard implements the linear (first) differences instrumental variables estimator, suggested by Farbmacher & Tauchmann (2023) for dealing with unit-level unobserved heterogeneity (possibly correlated with explanatory variables) in the discrete-time hazard model. xtdhazard also implements related non-linear control-function (cf) estimators. These procedures address the issue that, conventional (linear) fixed-effects panel estimators (within-transformation, first-differences), fail to eliminate unobserved time-invariant heterogeneity and are biased and inconsistent if the dependent variable is a binary dummy indicating an absorbing state. xtdhazard is essentially a wrapper for ivregress 2sls and, depending on which estimator is specified, for community-contributed command cfbinout. xtdhazard temporarily generates first and/or, depending on how the option difference(#) is specified, higher-order own-differences of the explanatory variables, and uses them as instruments for the levels. With estimator 2sls, estimation is by 2sls for which xtdhazard calls ivregress 2sls. With estimators logit, probit, or cloglog, xtdhazard, instead of ivregress, calls the community contributed command cfbinout to run a non-linear control-function (cf, two-stage residuals inclusion) regression; cf. Wooldridge (2015). Unlike conventional fixed effects estimation, these estimators (both, 2sls and cf) rest on the assumption that the unobserved heterogeneity is uncorrelated with the first (or higher-order) own-differences of the explanatory variables.