Increasing the share of vocational secondary schooling has been a mainstay of development policy for decades, perhaps nowhere more so than in formerly socialist countries. The transition, however, led to significant restructuring of school systems, including a declining share of vocational students. Exposing more students to a general curriculum could improve academic abilities. This paper analyzes Poland's significant improvement in international achievement tests and the restructuring of the education system that expanded general schooling to test the hypothesis that delayed vocational streaming improves outcomes. Using propensity score matching and differences-indifferences estimates, the authors show that delayed vocationalization had a positive and significant impact on student performance on the order of one standard deviation.

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The impact of the PISA study on Polish education policy has been significant, but probably different from any other country. Poland has not experienced the so‐called ‘PISA shock’, but its education system has been benefiting considerably from PISA. For experts and policy makers, it has been a useful and reliable instrument that has made it possible to measure the effects of consecutive reforms of the school education system. Moreover, PISA and other international studies have influenced the perception of education policy in Poland. The latter has shifted from an ideology‐driven, centralised policy to an evidence‐informed policy, developed with the involvement of multiple stakeholders, although this has mostly affected the thinking of experts and policy makers rather than the general public. The new government (in power from 2015), following public opinion polls, has reversed most of the previous education reforms, eliminating lower secondary schools introduced in 1999.

Delaying tracking, extending students' exposure to a general academic education and increasing their time on task on basic competences (reading, mathematics) could improve academic outcomes. To test the hypothesis that delayed vocational streaming improves academic outcomes, this paper analyzes Poland's significant improvements in international achievement tests and the restructuring of the system which expanded general schooling. Estimates using propensity-score matching and difference-in-differences estimates show that delaying vocational education and increasing time on task has a positive and significant impact on student performance on the order of a standard deviation.Abstract: Delaying tracking, extending students' exposure to a general academic education and increasing their time on task on basic competences (reading, mathematics) could improve academic outcomes. To test the hypothesis that delayed vocational streaming improves academic outcomes, this paper analyzes Poland's significant improvements in international achievement tests and the restructuring of the system which expanded general schooling. Estimates using propensity-score matching and difference-in-differences estimates show that delaying vocational education and increasing time on task has a positive and significant impact on student performance on the order of a standard deviation.JEL Code: I20, I21, I24

In this paper we analyze class size effects in the case of primary schools in Poland. We use two empirical strategies to avoid endogeneity bias. First, we use average class size in a grade as an instrumental variable for actual class size. This allows us to control for within school selection of pupils with different abilities to classes of different sizes. Additionally, we estimate fixed effects for schools to control for differences between them. Second, we exploit the fact that there is an informal maximum class size rule. We estimate class size effect only for those enrollment levels where some schools decide to add a new class and thus dramatically lower class sizes. For such enrollment levels variance of class size is mainly exogenous and we argue that this allows to estimate quasi-experimental class size effects. In this case we again use average class size as an instrument with enrollment as a key control variable. Using both strategies we obtain similar findings. We found that the positive effects observed with OLS regression disappear when we use instrumental variables. If we avoid endogeneity bias, then class size negatively affects student achievement. However, this effect is rather small. We discuss methodology, possible bias of results and the importance of our findings to current policy issues in Poland.JEL: I2, H52, C31

Over the last two decades, the Polish education system has been reformed several times, with the comprehensive structural reform in 1999, curriculum and evaluation reform in 2007, and early education reform introduced gradually until 2014. Student outcomes, as documented by PISA, but also other international assessments, largely improved over the last 20 years. Poland moved from below the OECD average to a group of top-performing countries in Europe. This chapter describes the reforms and research on their effects. It also discusses how it was possible to find political support for the reversal of changes that seemed to be highly successful. It provides three lessons from the Polish experience. First, the evidence should be widely disseminated among all stakeholders to sustain reforms. Second, the sole reliance on international studies is not sufficient. Additional investment into secondary analyses and national studies is necessary to develop evidence for better-informed political discussions. Third, some positive changes are more difficult to reverse. In Poland, increased school autonomy, but also external examinations, broader access to preschool and higher education, are among the changes that the new government could not alter.

This paper examines how including latent variables can benefit propensity score matching. Latent variables can be estimated from the observed manifest variables and used in matching. This paper demonstrates the benefits of such an approach by comparing it with a method where the manifest variables are directly used in matching. Estimating the propensity score on the manifest variables introduces a measurement error that can be limited with estimating the propensity score on the estimated latent variable. We use Monte Carlo simulations to test how the proposed approach behaves under distinct circumstances found in practice, and then apply it to real data. Using the estimated latent variable in the propensity score matching limits the measurement error bias of the treatment effects' estimates and increases their precision. The benefits are larger for small samples and with better information about the latent variable available.