In this chapter, we discuss when and why you may want to perform cross-country analysis. We outline the estimation technique of propensity score matching, how and when to use it, and some extensions to this estimation model. We provide an example looking at labour market outcomes in the UK for those diagnosed with a non-communicable disease. We also outline additional methods for cross-country analysis, such as the fixed effects approach.
KeywordsCross-country analysis Propensity score matching Propensity score matching with DiD
References and Further Reading
- Cerulli, G. (2013, September). TREATREW: A user–written Stata routine for estimating average treatment effects by reweighting on propensity score. In United Kingdom Stata Users’ Group Meetings 2013 (No. 02). Stata Users Group.Google Scholar
- University of Essex. Institute for Social and Economic Research, NatCen Social Research and Kantar Public, [producers]: Understanding Society: Waves 1–6, 2009–2015 [computer file], 8th ed. Colchester, Essex: UK Data Service [distributor], November 2016. SN: 6614.Google Scholar