Working paper: Matching, differencing on repeat
An innovative approach to analysing data
-
Date
January 2018
-
Area of expertiseResearch and Evidence (R&E)
-
CountryTanzania, United Republic of
-
KeywordMonitoring, Evaluation, and Learning [MEL]
-
OfficeOPM Tanzania
-
ISSN
2042-1265
When evaluating programme impact in a context where a randomised control trial is either infeasible or not appropriate, the quasi-experimental approach of Propensity Score Matching (PSM) is often used to construct a counterfactual. However, if there are imbalances remaining after PSM, selection bias may persist.
Increasingly, researchers combine PSM and Difference-in-Differences (DID) to counter such imbalances. While there is guidance on applying this combined approach using panel data, applications of this approach in repeated cross-section settings are less frequent. In this paper, we present an innovative approach to combining PSM and DID when only cross-sections of data are available.