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Safety Valve or Sinkhole? Vocational Schooling in South Africa. (2012). Pugatch, Todd.
In: IZA Discussion Papers.
RePEc:iza:izadps:dp7015.

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  4. Altonji et al. (2005) formalize this argument. The interpretation of this ratio becomes somewhat clearer if I further assume that δv = θv = θX = 0, in which case we have: δa = cov(Sa, u) var(Sa) θa = cov(Sa, ˜u) var(Sa) plim ˆβa,NC − ˆβa,C = γ cov(Sa, u − ˜u) var(Sa) = γ cov(Sa, XβX) var(Sa) Again setting βa = 0 under the null hypothesis yields: plim ˆβa,C ˆβa,NC − ˆβa,C =
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  5. Altonji, Joseph G., Todd E. Elder, and Christopher R. Taber, “Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools,” Journal of Political Economy, February 2005, 113 (1), 151–184.

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  9. Becker, Gary S., Human Capital a Theoretical and Empirical Analysis, With Special Reference to Education, Columbia University Press, 1967.
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  15. cov(Sa, ˜u) cov(Sa, XβX) (17) The ratio on the right-hand side represents how strong the relationship between the residual unobservable ˜u and Sa must be relative to that of the controls X to explain a non-zero estimate of ˆβa when βa = 0. A large ratio suggests that omitted variable bias is unlikely to explain away the entire effect of academic schooling on y. Altonji et al. (2005) interpret ratios greater than 3 as large, and ratios greater than 1 as suggestive of non-zero treatment effects in the presence of possible selection on unobservables. A similar argument can be made for the corresponding expression for the vocational schooling coefficient βv.
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  16. Duflo, Esther, “Grandmothers and Granddaughters: Old-Age Pensions and Intrahousehold Allocation in South Africa,” World Bank Economic Review, 2003, 17 (1), 1–25.
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  18. El-Hamidi, Fatma, “General or Vocational Schooling? Evidence on School Choice, Returns, and ’Sheepskin’ Effects from Egypt 1998,” Journal of Policy Reform, June 2006, 9 (2), 157–176.

  19. Fiske, Edward B. and Helen F. Ladd, Elusive Equity: Education Reform in Post Apartheid South Africa, Brookings Institution Press, July 2004.
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  20. Following Bellows and Miguel’s (2009) application of Altonji et al.’s (2005) methodology, taking the ratio of (16) over the difference in the probability limits (12)-(16) under the null hypothesis βa = 0 yields: plim ˆβa,C ˆβa,NC − ˆβa,C = θa δa − θa The numerator on the right-hand side is the partial correlation between academic schooling Sa and ˜u, the remaining selection term after including the controls X. The denominator is this term subtracted from the partial correlation between academic schooling Sa and u, the selection term that includes the controls X. If the denominator is small relative to the numerator and the controls X are representative of all possible controls,46 then the selection term remaining after controls are included (˜u) is not likely to be an important source of inconsistency for βa.
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  24. Labor force participation variables (i.e., work and search) and wages are conditional on non42 The Cape Area Panel Study Waves 1-2-3 were collected between 2002 and 2005 by the University of Cape Town and the University of Michigan, with funding provided by the US National Institute for Child Health and Human Development and the Andrew W. Mellon Foundation. Wave 4 was collected in 2006 by the University of Cape Town, University of Michigan and Princeton University. Major funding for Wave 4 was provided by the National Institute on Aging through a grant to Princeton University, in addition to funding provided by NICHD through the University of Michigan. enrollment at a given age, where reports of enrollment supersede reports of labor market participation.
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  30. Needham, Seamus and Joy Papier, “Practical matters: What young people think about vocational education in South Africa,” Technical Report, City & Guilds Centre for Skills Development, London June 2011.
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  31. Newhouse, David and Daniel Suryadarma, “The Value of Vocational Education: High School Type and Labor Market Outcomes in Indonesia,” World Bank Economic Review, 2011, 25 (2), 296–322.

  32. Nkosi, Bongani, “Vocational educational not an ’option for losers’,” The M&G Online, November 2012.
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  34. Oxford Business Group, “South Africa: Raising higher education,” http://www.oxfordbusinessgroup.com/economic updates/south-africa-raising-highereducation February 2012.
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  35. Pugatch, Todd, “Bumpy Rides: School to Work Transitions in South Africa,” Unpublished paper, University of Michigan, 2011.

  36. Roy, A. D., “Some Thoughts on the Distribution of Earnings,” Oxford Economic Papers, June 1951, 3 (2), 135–146. ArticleType: research-article / Full publication date: Jun., 1951 / Copyright 1951 Oxford University Press.

  37. Souza, P., “Moral Hazard in the Family,” Unpublished paper, Yale University, 2010.
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  38. The assumptions used to arrive at (17) are admittedly restrictive. In particular, the assumptions that δv = θv = 0 are potentially problematic, as they require that vocational schooling Sv is unrelated to the unobservables u and ˜u that determine selection into academic schooling. (The assumption θX = 0 is not problematic, as it follows from the definition of a linear projection.) Nonetheless, these assumptions are required to arrive at the familiar omitted variables bias formula when there are more than two regressors, and are therefore often invoked (Wooldridge 2001, p. 62).
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  39. This derivation of omitted variable bias follows Wooldridge (2001) closely. u = δaSa + δvSv + r (10) Substituting (10) into (9) yields: y = (βa + γδa)Sa + (βv + γδv)Sv + γr + (11) Written in this form, the familiar omitted variables bias formula for ˆβa follows: plim ˆβa,NC = βa + γδa (12) where the subscript NC denotes “no controls.” Now suppose there is a set of controls X that is related to the selection term u in the following way: u = XβX + ˜u The availability of these controls allows me to rewrite the model as: y = βaSa + βvSv + γ(XβX + ˜u) + (13) Analogously to (10), write the linear projection of the omitted variable ˜u on the observables as: ˜u = θaSa + θvSv + XθX + ν (14) Substituting (14) into (13) yields the counterparts to (11) and (12): y = (βa + γθa)Sa + (βv + γθv)Sv + X(βX + γθX) + γν + (15) plim ˆβa,C = βa + γθa (16) where C refers to the model with controls.
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  40. van der Meulen Rodgers, Yana, Joseph E. Zveglich, and Laura Wherry, “Gender Differences in Vocational School Training and Earnings Premiums in Taiwan,” Feminist Economics, October 2006, 12 (4), 527–560.

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  49. Selection into skill accumulation: evidence using observational and experimental data. (2011). Mani, Subha ; Maitra, Pushkar ; Gangadharan, Lata ; Dasgupta, Utteeyo ; Subramanian, Samyukta .
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