EDUCATION EXPENDITURE AND OUTCOME IN SENEGAL

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EDUCATION EXPENDITURE AND OUTCOME IN SENEGAL

• BY
• Aloysius Ajab AMIN
• and
• Tharcisse NTILIVAMUNDA

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OUTLINE

• Introduction
• Objective Scope
• Education Sector in Senegal
• Brief literature Review
• Methodology
• Analysis and Results
• Tentative Conclusion

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INTRODUCTION

• Senegal has about 11.6m people.
• Primary education is compulsory
• Average year of schooling of adults is about 2.6
• education spending is about 3.6 percent of GDP.
• Female enrolment share in primary school is about
  46.5 percent while it is about 39.6 percent in
  secondary schools.
• It is estimated that about 70 percent of the
  primary school aged-girls are in school.

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OBJECTIVE SCOPE

• To analyse the relationship between education
  expenditure and outcomes in Senegal and then,
  draw policy inference.
• Focus is on primary education.
• Study covers the period 1970 To 2008.

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WHAT THE LITERATURE IS SAYING

• The relationship between education resources and
  educational outcome is weak in cross-country
  analysis (Al- Samarrai, 2003).
• Why?
• poor data.
• failure to account for other factors such as
  household spending.
• Intensive use of existing school infrastructure (
  not taken account of).
• Efficiency level of public spending across
  countries.
• Heavy expenditure at general administration and
  not at school level.

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METHODOLOGY DATA

• Descriptive Analysis
• Econometric Modelling
• DATA SOURCES
• Statistical department of Ministry of Finance
• Ministry of Education and studies on Senegalese
  Education
• National household surveys including ESAM III
  and Other Surveys
• The World Bank and other sources

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Trend of Education Expenditure (EE) in GDP and
Government Budget (GB)
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Trend of the Staff and the Equipment budgets
(1970 to 2000)
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Trend of Education Expenditures (EE) as a ratio
of Capital Budget (CB) in the 2000s
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Distribution of recurrent budget by levels
(1983/84 to 1990/2000)
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Distribution of recurrent budget by education
level (1983/1984 to 1990/2000)
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Trend In Enrolment rates in the three levels from
1970 to 2000
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Trend In Enrolment rates in primary and secondary
levels in the 2000s.
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ECONOMETRIC MODEL

• We model expenditure-outcome relationship as
  follows
• Dependent Variable
• Enrolment
• Independent variables
• Expenditure
• DGP per capita
• Enr ? ?1Ex ?2Gdp ?
• Enr enrolment, Ex expenditure, Gdp GDP per
  capita

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Table 1 Estimates on Primary Education
enrolment
Dependent Variable LOG(ENR)        
Method Least Squares        
Number of observations  36
Variable Coefficient Std. Error t-Statistic Prob.
C -1.025048 0.423935 -2.417936 0.0221
LOG(ENR(-1)) 0.772326 0.058141 13.28365 0.0000
LOG(EXPENDSM) 0.080904 0.018677 4.331816 0.0002
LOG(GDP/TETE) 0.008072 0.063795 0.126523 0.9002
         
R-squared 0.996533 Mean dependent var Mean dependent var -0.575458
Adjusted R-squared 0.996055 S.D. dependent var S.D. dependent var 0.240447
S.E. of regression 0.015102 Akaike info criterion Akaike info criterion -5.412920
Sum squared resid 0.006614 Schwarz criterion Schwarz criterion -5.188455
Log likelihood 97.01964 F-statistic   2084.078
Durbin-Watson stat 2.160272 Prob(F-statistic) Prob(F-statistic) 0.000000
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Table 2 Primary Education Enrolment Female
Dependent Variable LOG(MAL_ENSM) Dependent Variable LOG(MAL_ENSM)      
Method Least Squares        
Included observations 36 Included observations 36      
Variable Coefficient Std. Error t-Statistic Prob.
C -0.202591 0.684821 -0.295831 0.7693
LOG(MAL_ENSM(-1)) 0.791555 0.091105 8.688339 0.0000
LOG(EXPENDSM) 0.057290 0.025579 2.239773 0.0322
LOG(GDPTETE/1000) 0.079586 0.107602 0.739635 0.4649
R-squared 0.975389 Mean dependent var Mean dependent var 4.131460
Adjusted R-squared 0.973081 S.D. dependent var S.D. dependent var 0.201349
S.E. of regression 0.033035 Akaike info criterion Akaike info criterion -3.878050
Sum squared resid 0.034922 Schwarz criterion Schwarz criterion -3.702103
Log likelihood 73.80489 F-statistic   422.7394
Durbin-Watson stat 1.514704 Prob(F-statistic) Prob(F-statistic) 0.000000
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Table 3 Primary Education Enrolment - male
Dependent Variable LOG(ENR_FESM) Dependent Variable LOG(ENR_FESM)      
Method Least Squares        
Included observations 34 Included observations 34      
Variable Coefficient Std. Error t-Statistic Prob.
C -0.043634 0.892582 -0.048885 0.9613
LOG(ENR_FESM(-1)) 0.698184 0.110855 6.298147 0.0000
LOG(EXPENDSM) 0.100989 0.040529 2.491747 0.0185
LOG(GDPTETE/1000) 0.022322 0.139882 0.159575 0.8743
R-squared 0.982749 Mean dependent var Mean dependent var 3.817069
Adjusted R-squared 0.981024 S.D. dependent var S.D. dependent var 0.248613
S.E. of regression 0.034247 Akaike info criterion Akaike info criterion -3.800306
Sum squared resid 0.035186 Schwarz criterion Schwarz criterion -3.620734
Log likelihood 68.60520 F-statistic   569.6907
Durbin-Watson stat 1.742046 Prob(F-statistic) Prob(F-statistic) 0.000000
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Table 4 Completion Rate
Dependent Variable LOG(COMPLETION)  Dependent Variable LOG(COMPLETION)  Dependent Variable LOG(COMPLETION)  Dependent Variable LOG(COMPLETION)  Dependent Variable LOG(COMPLETION) 
Method Least Squares        
Sample 1989 to 2006   Sample 1989 to 2006   Sample 1989 to 2006   Sample 1989 to 2006   Sample 1989 to 2006  
Variable Coefficient Std. Error t-Statistic Prob.
C -3.366836 0.835848 -4.028048 0.0024
LOG(EXPENDSM) 0.047894 0.051209 0.935275 0.3717
LOG(COMPLETION(-1)) 0.396958 0.167285 2.372938 0.0391
LOG(GDP/TETE) 0.883666 0.289275 3.054765 0.0122

R-squared 0.933523 Mean dependent var Mean dependent var 3.696027
Adjusted R-squared 0.906932 S.D. dependent var S.D. dependent var 0.069921
S.E. of regression 0.021331 Akaike info criterion Akaike info criterion -4.596123
Sum squared resid 0.004550 Schwarz criterion Schwarz criterion -4.360106
Log likelihood 39.47092 F-statistic   35.10693
Durbin-Watson stat 2.448932 Prob(F-statistic) Prob(F-statistic) 0.000007
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FINDINGS FROM MODEL

• Enrolment significantly depends on previous
  enrolment.
• enrolment significantly depends on public
  expenditures.
• Per capita income does not have much impact on
  enrolment
• Expenditure is more important in the case of
  girls primary education enrolment than that of
  the boys.
• In general an increase in the expenditure in
  primary education of 10 would tend to increase
  primary education enrolment rate by 8.1.
• In the case of girls an increase in expenditure
  of 10 tend to improve enrolment rate of 10.1 as
  against that of boys of 5.7

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FURTHER RESEARCH ISSUES.

• What remains to be done include the following
• Estimating an earning model.
• A complete discussion of the four main outcomes
  (Enrolment, completion, repetition and drop out
  rates) and linking them to education spending,
  including the composition of expenditure- using
  micro and macro data.
• If possible, this would be also examined at the
  regional level of Senegal.
• Updating or completing the data set
• Completing literature review
• More analysis and discussion of the results
• Policy implications and conclusion

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• THANK YOU