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Does the type of higher education affect labor market outcomes? Evidence from Egypt and Jordan

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Abstract

In Egypt and Jordan, there is a substantial mismatch between the output of the higher education system and the needs of the labor market. Both demand and supply-side factors could be driving this mismatch. This paper tests a key supply-side issue, whether differences in the institutional structures and incentives in higher education affect the labor market outcomes of graduates. Specifically, we ask if the stronger alignment of incentives in private relative to public higher education institutions produces more employable human capital and better labor market outcomes. We examine the impact of the type of higher education institution a person attends on several labor market outcomes while controlling for his or her pre-enrollment characteristics. The results demonstrate that supply-side issues and institutional incentives have little impact on labor market outcomes while family background plays by far the largest role. Proposed reforms for higher education often suggest increasing the role of the private sector in provision of higher education. Our findings indicate that this approach is unlikely to improve labor market outcomes.

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Notes

  1. This dynamic was common throughout the MENA region and is sometimes referred to as the credentialist equilibrium (Salehi-Isfahani 2012).

  2. For more information on the structure, governance, and financing of HEIs in Egypt and Jordan, see Barsoum and Mryyan (2014) and Barsoum (2014).

  3. See Assaad, Badawy, and Krafft (2016) for more details about the distribution of commerce and IT students across public and private institutions in both countries.

  4. See also Said (2013), Barsoum (2014) and Barsoum and Mryyan (2014) for further discussion of university governance and autonomy in Egypt and Jordan.

  5. The exception to this is the American University in Cairo, which was established in 1919.

  6. Although private higher education is relatively new, the average ages across public and private higher education within our sample are similar (Assaad, Badawy, and Krafft 2016).

  7. Non-wage employment includes self-employment and unpaid family work.

  8. The data and metadata from the HEGS surveys are available for public use from the ERF Open Access Microdata Initiative (www.erf.org.eg)

  9. We tested excluding women from the sample and re-running the regressions with only men. The key results around higher education incentives were robust to excluding women. Although our sample size precludes estimation split by gender, the robustness of our main results to excluding women suggests that gender differences/interactions are not driving our results.

  10. We estimate propensity scores using the psmatch2 command in STATA version 14.2. Testing, presented in Appendix 2, is undertaken using the accompanying pstest and psgraph commands.

  11. In 2012, the official exchange rate was £E 6.06 = 1 U.S. Dollar and JD 0.71 = 1 U.S. Dollar. The PPP adjusted rate was JD 0.33 = 1 international dollar and £E 1.89 = 1 international dollar (World Bank 2016).

  12. A median spline was tested, but did not show substantively different results.

  13. Krafft and Assaad (2016) explore the extent and drivers of inequality of opportunity in the labor market for higher education graduates.

  14. A rich body of qualitative research demonstrates that social connections provide access to job opportunities, and that employers commonly inquire about a potential employee’s socioeconomic background, for instance father’s employment status, or whether the family owns a microwave oven (Moghadam 2003; e.g. Barsoum 2004; Shaalan 2014; Salemi 2015).

  15. Other research, comparing access to formal jobs across generations in Egypt, suggests that access to formal jobs for higher education graduates has become increasingly predicated on social class (Assaad and Krafft 2014).

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Acknowledgements

The authors wish to acknowledge generous financial support for this research from the Ford Foundation in a grant to the Economic Research Forum (ERF). We also thank participants at two ERF workshops for their valuable comments and suggestions.

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Author notes

  1. Caroline Krafft

    Present address: Department of Economics, St. Catherine University, 2004 Randolph Ave., Saint Paul, MN, 55105, USA

Authors and Affiliations

  1. Humphrey School of Public Affairs, University of Minnesota, 301 19th Ave. S, Minneapolis, MN, 55455, USA

    Ragui Assaad

  2. Department of Applied Economics, University of Minnesota, 1994 Buford Avenue, Saint Paul, MN, 55108, USA

    Caroline Krafft

  3. Department of Economics, Virginia Tech, Blacksburg, VA, 24061, USA

    Djavad Salehi-Isfahani

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  1. Ragui Assaad
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Correspondence to Caroline Krafft.

Appendix 1

Appendix 1

Fig. 8
figure 8

Distribution of propensity score for private higher education and common support in Egypt

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Fig. 9
figure 9

Distribution of propensity score for private higher education and common support in Jordan

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Table 10 Descriptive statistics. Cells are proportions or means
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Table 11 Marginal effects from probit models for attending private higher education institution
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Table 12 Regressions for labor market outcomes in Egypt
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Table 13 Regressions for labor market outcomes in Jordan
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Table 14 Cox proportional hazard model for time to first formal job in Egypt
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Table 15 Cox proportional hazard model for time to first formal job in Jordan
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Table 16 Distribution of covariates before and after matching
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Assaad, R., Krafft, C. & Salehi-Isfahani, D. Does the type of higher education affect labor market outcomes? Evidence from Egypt and Jordan. High Educ 75, 945–995 (2018). https://doi.org/10.1007/s10734-017-0179-0

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