Abstract

With the rising popularity of field experiments in economics, re-randomization schemes have emerged as tools to induce balance in observable variables across treatment groups. However, re-randomization is not fully understood and the methodologies to estimate its effects on the distribution of parameters are still under-developed. This paper helps to close that gap by suggesting an asymptotically normal re-randomization scheme and bootstrapping procedure to carry inference under a wide range of estimators and re-randomization schemes.