When public acts like private:

1. When public acts like private: THE FAILURE OF ESTONIA’S SCHOOL CHOICE MECHANISM Kaire Põder (TUT) & Triin Lauri (TLU) kaire.poder@ttu.eetriin.lauri@tlu.ee

2. School choice as the allocation problem : who is accepted to the ‘good’ (elite) school • Entrance game is played to the basic school level and within public sector • Why is important? • Educational outcomes depend on: background effect (unavoidable bias); teacher effect; peer/class effect; extra- curriculum/curriculum effect. • Early grouping by background characteristics makes teacher, peer and possibly also extra-curriculum effects bigger. AND CREATES ‘BAD’ INEQUALITY – educational achievements are not independent from the circumstances beyond person’s control Theproblem

3. 1993 onwards inter (over-demanded, central location, 8 schools) and intra-district (usual, 56 schools) • Market experiment in 2011 - all schools were intra-district • 45% of public places within universities is taken by elite-school graduates; 5 times more probable to get into public place for elite school student • League tables (source of info) • Selection criteria – autonomous decision of the school – last years all perform independent entrance tests (ability test) + some cases legal address registration in the centre of the city • Test – information trap • Prep-school (also competitive entrance)– market solution • AGAIN – ALL THIS IS WITHIN PUBLIC SCHOOL ‘MARKET’ Case - Tallinn

4. Well recognised empirical result, but theoretical arguments? • Rational choice literature (RC) – constraints and preferences • Cultural capital theory (CC) (Bourdieu) • RC: low-SES has informational constraints (higher opportunity cost) or income constraints (are they minimal in our case?, also these are related to opportunity costs). Preferences differ (?) –social demotion argument (relative risk aversion). Education as position good. • CC: high-SES has ‘legitimate good taste’, recent literature stresses also social demotion argument. • Empirical strategies of RC and CC more or less overlap • Family background matters (how to make distinction between preferences and constraints????) • Players (families) are strategic (mainly middle-SES families) Literature – why choice segregates?

5. Background effects • Strategic behaviour (prep-schooling, central location) • Middle-income families struggle more What we expect to see

6. Internet survey conducted via TallinnaHaridusamet, approx. 900 responded, after ‘cleaning’840 parents • 34,6% elite school parents • 31.1% attending elite prep-school • 47,5 attended entrance tests (high achievers) Internet survey: 2011

7. Binary outcome and many independent binary variables • Empirical model: π(Y)=β_0+β_1 F+β_2 S+β_3 L+ε. • Here, Y is the binary outcome capturing the acceptance or not acceptance to the elite school and function π indicates probability. Vector F captures student family background characteristics (background effect); vector S measures the effect of parental strategies (educational strategy effect); vector L indicates location effect; and ε indicates error term. • + ‘participation in the tests’ was used as a latent variable (preferences indicator) to divide data-set into two sub-groups – high- and low-achievers Method: Logit

8. Results

9. We see all that we expected to see: • Background effects: • Higher education mother and father 10% and • Income higher category 20% • Strategy effect: • Attending elite prep-school 55% • Trying hard 50% • Central location 66% • Driving children to school 13% • Surprises: • High-achievers: mother matters not father; income effect smaller. • …also their education strategy effect is smaller • interaction variable: has negative sign; • attending ‘usual’ prep-school creates negative prob. of getting accepted to elite Discussion

10. No robustness check • So we don’t know whether some omitted variables may create unobserved heterogenity problem • Interpretation of marginal effects is problematic Mood (2010) shows that marginal effects are not comparable across groups and even not across samples. Moreover, they are not comparable across models. Average marginal effect alleviates the problem a bit, but don’t capture non-linearity • To improve: IV estimation helps to get rid of endogeneity problem • Problem: must calculate direct and indirect effects (we calculated only for elite prep-school) Problems with the interpretation

11. Biprobit 1: prep-school variable is engogeneous

12. Biprobit 2

13. LOGIT OVERESTIMATED THE PREP-SCHOOL EFFECT and THE DIRECT EFFECTS OF MANY VARIABLES (BACKGROUND EFFECT) • OTHER RESULTS: • Mothers education affects only prep-school attendance; • Prep-school is increasingly middle class phenomenon (it used to be ‘more intelligent’ families’ phenomenon; • Centre of the city families are forced to the prep-school (probably because otherwise their children are assigned to the not walking-distance schools). Interpretation: what market did?

14. Information to the parents about ‘opportunity set’ • Not only league tables because it creates incentives for selectivity based on academic record only • Limit/abolish school autonomy for accepting students • Alternative mechanism is needed • Or quota for low ability (+ extra money incentivising intake) • Competition must be real • Money follows child (negative side – topped off vouchers) • How to implement variability(path-dependency) Policy relevance(inspired by literature and our case knowledege)