@TechReport{iza:izadps:dp7742,
            	author={Brewer, Mike and Crossley, Thomas F. and Joyce, Robert},
            	title={Inference with Difference-in-Differences Revisited},
            	year={2013},
	month={Nov},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={7742},
            	url={https://www.iza.org/publications/dp7742},
	abstract={A growing literature on inference in difference-in-differences (DiD) designs with grouped errors has been pessimistic about obtaining hypothesis tests of the correct size, particularly with few groups. We provide Monte Carlo evidence for three points: (i) it is possible to obtain tests of the correct size even with few groups, and in many settings very straightforward methods will achieve this; (ii) the main problem in DiD designs with grouped errors is instead low power to detect real effects; and (iii) feasible GLS estimation combined with robust inference can increase power considerably whilst maintaining correct test size – again, even with few groups.},
	keywords={difference in differences;hypothesis test;power;cluster robust;feasible GLS},
            }