Application of Logistic Regression in Counterfactual Impact Evaluation of Graduate Practice Measure in Slovakia - Švábová, Lucia; Ďurica, Marek (Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu, 2017)
In the paper we discuss the results of Counterfactual impact evaluation of Graduate practice that is one of Active labour market policy (ALMP) interventions in Slovakia for unemployed jobseekers. Counterfactual impact evaluation is usually made using various multivariate statistical methods; one of the most used methods is Propensity score matching. Propensity score for every individual jobseeker means the probability of taking a part of an ALMP intervention and can be obtained using logistic regression model. Counterfactual evaluation is based on comparison of placeability and sustainability of treated and non-treated jobseekers on open labour market and is very important for valuation of impact of intervention not only on individual jobseekers and their employability but also for valuation of whole intervention and its economic impact
20-th AMSE. Applications of Mathematics and Statistics in Economics. International Scientific Conference: Szklarska Poręba, 30 August- 3 September 2017. Conference Proceedings Full Text Papers, s. 473-482
Keywords: logistic regression; Propensity score matching; Counterfactual impact evaluation; Active labour market policy; Intervention