1. Education in developing countries, Michael Kremer Economics 1386, Fall 2006

2. Outline Background: Education in Developing Countries Methodology Reducing the Cost of Education Changing Education Behavior Improving Provision of Education Inputs Incentives for Providers Changing the Interaction of Consumers and Providers Local Control and Participation Contracting and Choice Conclusion

3. Background: Motivation Widely held belief that education can play a critical role in development Macro- impact of education on economic growth Lucas (1988), Barro (1991), Mankiw et al. (1992) Causal relationship (Pritchett, Bils & Klenow) Returns: old OLS literature, new IV literature Psacharopoulos 1985; Duflo 2001 Adoption of new technologies Foster and Rozenzweig (1996) Means to improve health, reduce fertility Schultz (1997), Strauss and Thomas (1995) Education as an intrinsic good Sen (1999)

4. Background: Motivation Development policy makers also enthusiastic about education 2 of the 8 Millennium Development Goals Universal primary education Gender equity at all education levels

5. Background: Motivation Rich set of experiences to examine Wide variation in input levels and education systems across developing countries In recent years, dramatic policy changes and reforms in many developing countries In last 10 years: many randomized evaluations of education policies (rare in developed countries)

6. Background: Quantity Gross Enrollment Growth 19602000 PrimaryLow income65102 Middle income83110 High income109102 SecondaryLow income1754 Middle income2177 High income63101

7. Background: Quantity (II) Primary Schooling 2000 net enrollment 1999 grade 4 completion Low-income8580 Middle-income88 High-income9598

8. Background: Quantity (III) Average Years of Schooling (Age 15+) 19602000Change Low income1.65.23.6 Middle income2.85.93.1 High income7.410.12.7 Source: Barro and Lee (2000)

9. Background: Quantity (IV) Room for Improvement 1 of 4 adults in developing countries illiterate UNESCO (2002) Today 113M primary age children not in school UNDP (2003); UNESCO (2002) 4 out of 10 primary-age children in sub-Saharan Africa do not go to school In Niger, only 26% of primary-age children go to school UNESCO (2003)

10. Background: Educational Finance Government Expenditures on Education Expenditure as % of GDP Expenditure per student as % of GDP per capita PrimarySecondaryPrimarySecondary Low-income1.01.17.016.7 Middle-income1.81.413.315.5 High-income1.41.918.821.5

11. Background: Educational Finance (II) Government Expenditures and Teachers Teacher salaries 74% of recurrent expenditures (Bruns et al. 2003) Teacher salary/ per-capita GDP Sub-Saharan Africa6.7 Latin America1.4 OECD1.3

12. Background: Educational Finance (III) Class Size Pupil-teacher ratio PrimarySecondary Low-income3225 Middle- income 2520 High-income1614

13. Background: Educational Finance (IV) Teacher Training % Trained Teachers PrimarySecondary Low-income9069 Middle- income 9083 High-income--

14. Background: Educational Finance (V) In many developing countries: School systems are highly centralized Teachers’ unions are strong Teacher incentives are weak

15. Background: Educational Finance (VI) Centralized Education, Heterogeneous Needs Heterogeneity within developing countries Educational background School quality Language Makes designing single curriculum for all students difficult

16. Background: Educational Finance (VII) Households help bear education costs Sometimes households pay for private schools Sometimes parents pay costs at public schools Parents must provide basic school inputs (e.g. textbooks, uniforms) Some costs are collective responsibility of parents (e.g. school roof) Some costs are passed on through official or unofficial school fees

17. Background: Educational Finance (VIII) Private funding Per-pupil primary school spending $US GovernmentPrivate Jamaica$221$178 Philippines$110$309 Vietnam$23$14

18. Quality of Education Lack of basic equipment and supplies Textbooks: only 20% of Kenya primary students had their own (recent changes) Blackboards: lacking in 39% schools in rural northern Vietnam Building: lacking in 8% of schools in India

19. Quality (II) PISA Study: Mathematics and Reading Achievement of 15-year-olds CountryMean math scoreMean reading score% very low skills France5175054.2 Japan5575222.7 UK5295233.6 US4935046.4 Argentina38841822.6 Brazil33439623.3 Chile38439623.3 Indonesia36737131.1 Mexico38742216.1 Peru29232754.1 South Korea5475250.9 Thailand43243110.4

20. Quality (III) Quality even lower in low-income countries Bangladesh: 58% of rural children 11 and older failed to identify 7 of 8 presented letters Greany, Khandker and Alam (1999) India: 36% of 6th graders unable to answer: “The dog is black with a white spot on his back and one white leg. The color of the dog is mostly: (a) black, (b) brown, or (c) grey” Lockheed and Verspoor (1991)

21. Quality: Teacher Absence Chaudhury, Hammer, Kremer, Muralidharan and Rogers Survey methods Absence rates across countries and sectors Concentration of absence Correlates of absence Institutional forms Conclusion

22. Teacher Absence: Sampling Unannounced visits to public primary schools, health centers Bangladesh, Ecuador, Indonesia, Peru and Uganda:  ~100 schools, ~1000 teachers, 2000+ observations per country India sample is much larger  3,750 schools, 16,500 teachers, ~50,000 observations

23. Teacher Absence: Survey Methodology and Absence Definition Measurement: Direct observation of each teacher, not administrative records Definition of absence: Teacher was considered absent if he/she could not be found anywhere in the school Excluded from the sample: part-time teachers; teachers reported as “on another shift” Exclude cases where the school is closed due to: Official/Scheduled Holidays Bad weather (rain, heat wave) Construction/repairs School Functions (Sports day, picnics, exams)

24. Absence: Multi-country Results on Extent of Absence

25. 25 Absence: Teacher Activity at Time of Observation in India Teacher Observation % of Observations In class, teaching45.0 In class, not teaching5.9 In school, idle/on a break9.5 Doing administrative work6.2 Accompanying the surveyor8.7 Can’t find the teacher (School Open)19.4 Can’t find the teacher (School Closed)5.2 Others0.2

26. Absence: Absence rates vs. GDP per capita (for sample countries and Indian states) BNG ECU IDN PER UGA 0 20 40 60 Absence rate (%) 6.577.588.5 Per-capita income (GDP, 2002, PPP-adjusted) Teachers BNG IDN PER UGA 0 20 40 60 Absence rate (%) 6.577.588.5 Per-capita income (GDP, 2002, PPP-adjusted) Health Workers CountriesFitted values Indian states

27. Absence: Raw figures on distribution of absence across teachers

28. Absence: Estimated distribution of teacher absence

29. 29 Absence: Stated Reasons for teacher absence in India School Closed % of Observations Teachers have not yet come1.0% Local/Other Holiday1.0% School Closed Early0.7% Teachers Meeting/Training0.6% Other Government Work0.1% Don't Know/Others1.7% Teacher cannot be found Authorized/Informed Leave6.7% Official Teaching Related Duty4.9% Sick1.5% Official Non Teaching Duty0.8% Not yet arrived0.6% Left Early0.6% Uninformed Absence/Don't Know/Others4.3%

30. Absence: Multicountry Correlates of Teacher Absence – HLM Estimates

31. 31 Absence: Indian teachers More powerful teachers absent more Older teachers (1% more for every 10 years) More educated teachers (2-2.5% more with a college degree) Head teachers (4-5% more) Males (1.5-2% more) Teacher pay (within scale, across states)

32. Absence: Multicountry Correlates of Teacher Absence – HLM Estimates (continued)

34. 34 Absence: School Conditions Better infrastructure is associated with significantly lower absence Infrastructure Index from 0-5, which includes existence of covered classrooms, non-mud floors, teachers’ toilet, electricity connection, library In India, each measure significant on its own, average impact of 1.4% for each 1 point increase in the index In multicountry sample, correlation is even larger quantitatively and highly significant, at over 2% for each 1 point increase

35. Absence: Multicountry Correlates of Teacher Absence – HLM Estimates (continued)

36. Absence: Private Schooling and Teacher Absence in India Surveyed private schools in villages visited Teachers have much lower pay More likely to be fired for absence Indian private school absence about 2 percentage points lower in sum stats, baseline multivariate regression. 8 percentage points lower with village fixed effects Absence in public schools high in villages with private schools. Explanations?

37. Absence: Private Schooling and Teacher Absence in India (continued)

38. 38 Absence: Correlation with education outcomes in India Teacher absence is a significant (but weak) predictor of lower student attendance A 10% increase in teacher absence is associated with a 1.8% decrease in student attendance Teacher absence is also a significant predictor of lower student test scores We conducted a simple 14-question test (2 Verbal, 12 Math) to a randomly selected sample of 10 4 th grade children in the schools that we covered A 20% decrease in teacher attendance is associated with a 2% decrease in test scores

39. Absence: Multi-country correlates of health worker absence

40. Absence: Why is Absence So High? High levels of absence are not efficient – no coordination Technically possible to monitor attendance Logbook/HM/inspection system Duflo and Hanna (2005) cameras Political economy In some authoritarian, colonial regimes, absence reportedly been less of a problem Not an electoral issue Powerful often outside public system Tradeoff between political and civil service systems

41. Absence: Conclusions One in five teachers is absent, on average Institutional failure Evidence from randomized evaluations Teacher incentives in Kenya (Glewwe, Ilias, Kremer) Merit scholarships (Kremer, Miguel, Thornton) Cameras in Indian NGO schools (Duflo and Hanna) Range of interventions could be tested: Improve facilities Intensify and upgrade inspections Empower school committees Publicize absence statistics Increase choice

42. Outline Background: Education in Developing Countries Methodology Reducing the Cost of Education Changing Education Behavior Improving Provision of Education Inputs Incentives for Providers Changing the Interaction of Consumers and Providers Local Control and Participation Contracting and Choice Conclusion

43. 113 million children not in school How expensive to address? Is their labor needed by household? Debate on user fees in health and education Impact on provider Impact on consumer Strong ideological component to debate, need for evidence

44. Methods Problem: Omitted Variable Bias y i = α+δd i +X i β+ε i We want to know δ, the effect of d i on y i X i is a vector of observable factors, and ε i contains the unobserved factors determining y i If ε i is correlated with d i, OLS estimate of δ will be biased. Its impossible to be certain because we can’t observe ε i !

45. Methods (II) Solution: Instrumental Variables Instrumental variables (IV) can address the omitted variables problem An instrument z i must be correlated with d i and uncorrelated with ε i

46. Methods (III) Solution: IV with Random Assignment Randomly altering d i for some individuals provides an instrument we can be confident in z i = 1 for individuals who had their d i randomly decreased and z i = 0 otherwise. We know E(z i ε i )=0 because randomization ensures it