Education, Employment and Earnings of Secondary School-Leavers ...

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1. IntroductionInformation on labour market outcomes, including the earnings of educated groups, inSub-Saharan Africa is limited. Government and individuals in this region investheavily in education and training but little is generally known about how theseinvestments generate rewards in the labour market. This is particularly so forindividuals who fail to gain access to wage employment and are required to rely onexploiting self-employment opportunities. The current paper, using a recentlycompleted tracer survey of secondary school completers from Tanzania, analyses theimpact of education and training on individual welfare through the estimation ofearnings equations.Earnings equations provide a convenient framework within which average privaterates of return to educational qualifications and training can be computed. 1 There is adearth of evidence on the magnitude of these rates for wage employees in Tanzaniaand almost none for individuals in self-employment. Given the increasing number ofsecondary school-leavers entering self-employment this represents a substantiallacuna in the literature. The aim of this paper is to partially fill this gap by estimatingsectoral-specific earnings equations for employees and the self-employed from acohort of secondary school students who completed junior secondary schooling inTanzania in the 1990s.Tracer surveys of the kind used in this paper, unlike conventional labour force orhousehold surveys, permit the collection of additional information on parentalbackground and schooling quality. This allows for some important refinements to thespecification of the earnings equations. In particular, the independent role of parentalbackground and, inter alia, schooling quality can be explored and the extent to whichthe estimated returns to the general human capital measures alter with the inclusion ofthese variables investigated.1 Card (1999) provides a detailed review of methodological and other issues germane to the estimationand interpretation of earnings equations.1
The structure of the paper can now be outlined. In order to place our empiricalanalysis in context the next section provides a brief history of the education system inTanzania and reviews the changes in the labour market over the 1990s. This sectionalso summarises some of the findings from a small number of earlier studies that haveestimated earnings equations for Tanzania. Section 3 outlines the data and describessome of the advantages and drawbacks in estimating earnings equations using tracersurvey data. Given the recorded nature of the earnings data and potential selectionissues, section 4 outlines the econometric methodology and details how the estimatedregression models are evaluated. Section 5 reports the empirical results and section 6offers some conclusions.2
Page 1: Education, Employment and Earnings
Page 5 and 6: Despite large absolute increases in
Page 7 and 8: nine studies reviewed for sub-Sahar
Page 9 and 10: It should be noted, however, that e
Page 11 and 12: history, current activity and incom
Page 13 and 14: In order to understand how the mode
Page 16 and 17: freedom for this test. In regard to
Page 18 and 19: where φ(·) denotes the probabilit
Page 20 and 21: 5.1 Earnings Equation - The Employe
Page 22 and 23: 4.8% per annum in the first three s
Page 24 and 25: confirm to some extent that unobser
Page 26 and 27: The ceteris paribus earnings for th
Page 28 and 29: [Table 7]The rate of return for a u
Page 30 and 31: 6. ConclusionsA key finding of our
Page 32 and 33: that the rates of return to educati
Page 34 and 35: Knight, J.B. and Sabot, R.H. (1981)
Page 36 and 37: Table 1: Highest level of education
Page 38 and 39: Table 4 (Cont’d)SelectionCorrecti
Page 40 and 41: Table 5 (cont’d)Selection Correct
Page 42 and 43: Table A1: Variable DescriptionVaria

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