1. Free Education and Student Test Scores in Chad Gbetonmasse B. Somasse Worcester Polytechnic Institute (WPI) International Conference on Sustainable Development in Africa Dakar– November 26-27, 2015 G. Somasse, Economics 1

2. Context “Fundamental education is compulsory.“ (Primary and middle) for 6-14 years old since 2006 Key Issues Has Free education led to lower test scores? What are the determinants of teacher’s value-added? Relevance Understanding the determinants teacher’s value- added helps promote student’s learning The Problem Research Questions and Relevance

3. Background Primary Education in Chad 6-4-3 education system  6 years in primary school  exit exam (CEP).  4 more years  middle school exam (BEPC)  3 other years  senior high school exam (BAC) Compulsory Primary Education  “Fundamental education is compulsory.“ (Primary and middle) schools for 6- 16 years old since 2006 Mostly Community Schools.  51% of primary schools are managed by communities (2012)  Community teachers represent 74% of the teaching personnel  48% of schools do not provide a full cycle of learning (In N'Djamena less than 8% of schools are incomplete v. nearly 90 % in Tibesti.)  Only 33% of enrolled children are taught by qualified teachers.

4. Significant differences in access, completion, and learning in primary schools across region and gender.  Gross enrollment ranges from 21% in the region of Ennedi to 124% in the capital region N'Djamena. PASEC results suggest that 2nd graders scores  39.1 in language (French), 2 percentage points lower than in 2004  40.3 or 2.5 percentage points less than in 2004. For fifth graders, the results are slightly better:  38 in French in 2010 against 32.1 in 2004  38.1 in math against 34 in 2004 Teacher’s absenteeism and strikes are common. Background Primary Education in Chad

5. Methodology A Difference-in-Difference Analysis of Achievement

6. Challenges in evaluating effectiveness of teachers and schools:  Self-selection: Schools are chosen by students and their parents  Classroom assignments are not random – based on prior test performance (Chetty etal, 2014). A solution: value-added (VA) of student achievement.  Pionnered by Hanushek (1971) and Murnane (1975).  Recently: Rockoff (2004), Rivkin, Hanushek, and Kain (2005)  Use a student’s prior scores and characteristics to predict test score.  Prediction residual as a measure of the contribution of school- teacher to student achievement. Methodology A Value-Added Model of Teacher’s Effectiveness

7. Methodology Stage 1: Student-Level Regression

8. Methodology Stage 2 – Classroom-Level Regression

9. Methodology Stage 3 – Determinants of Teacher’s Value-added

10. Cross-sectional data from PASEC 2004 and 2010 Stratified random sample of 2 nd and 5 th graders  3 types of schools: community, public, private  Learning language : French, Arabic, or bilingual For each year,  Pre- and post-test scores for literacy and mathematics  Student and family characteristics  Classroom conditions and characteristics of school principal  Teacher profile Restrict sample to students in grade 5 for whom both the pretest and posttest are available for both subjects (1237 students in 2004 and 1453 in 2010). Data PASEC Data

11. Results Summary Stats – Test Scores

12. Results Summary Stats – Student & Teacher’s Characteristics 20042010Change Female Student0.3560.3870.032 Student Age12.50612.5960.090 Student With Grade Repetition0.7150.656-0.060 Father Is Literate0.6360.595-0.041 Mother is Literate0.2770.2810.004 Fraction of Time Student Absence0.099 Student Speaks French at Home0.0880.0930.005 Bounded Class Size64.11652.838-11.277 Class Size67.34055.677-11.663 Students in Private Schools0.0710.0970.025 Students in Rural Areas0.5380.6420.104 Students in Community Schools0.1400.2160.076 20042010Change Education Level of School Principal7.1247.4860.362 Teacher Has Middle School Degree0.0970.4710.374 Teacher Absence0.0420.1220.080 Student's Teacher Age35.0833.543-1.536 Teacher Is Female0.0950.089-0.007 Teacher Is Civil Servant0.4270.310-0.116 Teacher Is on Short Term Contract0.0870.083 Teacher Is Volunteer0.013 Student's Teacher Has High School Degree0.4460.5130.066 Teacher Has Primary School Degree0.0000.001

13. Dependent Variable: Standardized Score Posttest MathPosttest Literacy (1)(3) MoreTreated-.02824-.5975** Post Policy Dummy1.506***.6886 MoreTreated x Post Policy Dummy-1.442*.5555 (.815)(.7805) Class Size-.0002497-.001611 Standardized Pretest Score in Math.2135***.3454*** Standardized Posttest Score Literacy.2387***.1963*** Female Student-.06702***-.04106* N2690 R-SQ.7405.762 Results Decrease in Math Scores, Not in Literacy Scores

14. Student characteristics  Pretest scores affect positively posttest  Girls’ average score in math is lower than boys’  Grade repetition leads to poorer scores School characteristics  Class size matters for student scores both in math and literacy  Composition of the classroom (average pretest, gender, days absent, rural) Results Determinants of Student’s Test Scores

15. Standardized Pretest Math Standardized Posttest Literacy Standardized Pretest Literacy.2104***.3182*** Standardized Pretest Math.1972***.1757*** Female Student-.09556***-.02767 Student's Age.002096-.01314 Student Repeats at Least a Grade-.08515**-.1401*** Father Is Literate-.03145-.02255 Mother Is Literate.03685.06908* Percent days student is absent.1296-.1442 Student Speaks French at Home.0124.06221 N1111 R-sq.8112.8152 Results VA Model – Student Level Analysis

16. Standardized Posttest Adjusted for Student's Characteristics MathLiterature Class Average Standardized Pretest Literacy.393***.4566*** Class Average Standardized Pretest Math.3631***.3536*** Class Proportion of Female Student.5471***.03546 Class Average Student's Age-.04085-.007651 Student Repeats at Least a Grade.3118***.542*** Class Proportion - Father Is Literate.1284-.09727 Class Proportion - Mother Is Literate.09474.3889*** Class Average Percent days student is absent-.5475***-.3346** Class % of Students Speaking French at Home.1575-.2946** Class Size.006859***.005321*** Years of Schooling of Principal.0284*-.0156 School In Private-.1592*-.01401 School in Rural Area.1878***.04727 Is Community School.06021.02243 N1090 R-sq.484.482 Results VA Model – Classroom Level Analysis

17. MathLiteracy Teacher's Absence-.1045-.008617 Teacher's Age-.006841-.01 Female Teacher-.2174-.4291* Civil Servant Teacher.2419*.1894 Contractual Teacher-.1832.04306 Volunteer Teacher-.7639-.8452 Teacher Holds BAC degree or higher-.0897-.1156 N94 R-sq.096.090 Results VA Model – Determinants of Value Added

18. MathLiteracy Rural Area Community Schools Public Schools Rural Area Community Schools Public Schools Teacher's Absence-.15822.047-.1339-.16533.323-.1594 Teacher's Age-.0176*0-.00159-.0206*-.01318-.0074 Female Teacher-.064690-.2077-.20610-.4256* Civil Servant Teacher.3362*-.2665.2343.18170.1766 Contractual Teacher-.4979-.9497*-.3937-.3949-.2298-.3899 Volunteer Teacher-.91-.29310-1.01*-.70960 Teacher Holds BAC degree or higher-.1567-.05961-.1914-.09235-.09871 N591769591769 R-sq.2086.5341.0632.1622.316.091 Results VA Model – Determinants of Value Added

19.  Type of contract: Tenured civil servant has on average a value-added in math that is 0.24 higher than a community teacher.  Gender: female teacher has a lower value added that her male counterpart  Diploma: a teacher with a high school diploma or higher tends to be less effective than a teacher who holds a middle school degree. Results Determinants of Teacher’s Value-Added

20. Making schooling more affordable and available may  reduce education disparities with implications for growth and Inequality  lead to overcrowded classroom if more teachers are not recruited In Chad:  Pretest, grade repetition, and gender are associated with posttest scores  In Chad FPE lead to significant decrease in Math scores but not in literacy scores  Teacher’s type of contract is important for value added Mere fee elimination may not be enough  Complement with a set of measures to increase supply and inputs in order to match the increased demand of schooling Conclusion Summary

21. Questions or Comments?