Dear colleagues, I am conducting a quasi experimental analysis focused on the Italian labor market. More specifically, I would like to evaluate the impact of a specific reform over the probability (after some specific time period, e.g., 1 year) of being employed (or not) after the implementation of the reform. Therefore, the outcome variabile is a dichotomous variable equal to 1 if the individual is employed after the specific time period, 0 if not. In the literature, as far as I know, quasi-experimental studies are conducted using mainly continuous response variables. My idea is to rely on a Propensity Score Matching (PSM) approach. However, I would like to ask you for some suggestions and works to consult in order to properly undertake this analysis of mine. Thank you in advance.
I would do a survey using Likert scales and analyse with Chi Square tests :)
Dear Andrew, thank you for your reply. However, I do not have the possibility to conduct a survey. I already have my data - compulsory communication data provided by the ministry of labor - on work histories (up to now) for each Italian employees (I am working on a sample - quite large and highly representative of the entire population). My fault for not having spent a few more words explaining by data.
The particular model (logit or OLS) is not so relevant. What matters is the research design of the quasi-experiment, i.e., whether it allows you to estimate the causal effect in a credible way. E.g., if you have a randomised experiment, the results are going to be the same using OLS or a logit model. For instance, OLS require less assumption, even if standard errors could be larger than using a logit. Overall, PSM is going to provide you the same outcomes as the OLS model (only the functional form of controls change a little bit).
See Angrist & Pischke's (2008) Mostly harmless econometrics for further information.
check this out:
https://link.springer.com/content/pdf/10.1007/s12197-020-09525-5.pdf
- Badges
- Science topic
- Similar topics
- Social Science
- Media
- Journalism