Skip to main content
SpringerLink
Log in

Why is fertility on the rise in Egypt? The role of women’s employment opportunities

  • Original Paper
  • Published:
Journal of Population Economics Aims and scope Submit manuscript

A Correction to this article was published on 15 August 2020

This article has been updated

Abstract

Can declining employment opportunities for women reverse the fertility transition? This paper presents evidence that the demographic transition has not just stalled but in fact reversed in Egypt. After falling for decades, fertility rates increased. The paper examines the drivers of rising fertility rates, with a particular focus on the role of declining public sector employment opportunities for women. Estimates show the effect of public sector employment on the spacing and occurrence of births using discrete-time hazard models. The paper then uses the results to simulate total fertility rates. The models address the potential endogeneity of employment by incorporating woman-specific fixed effects, incorporating local employment opportunities rather than women’s own employment, and using local employment opportunities as an instrument. Results indicate that the decrease in public sector employment, which is particularly appealing to women, may have contributed to the rise in fertility but is unlikely to be its main cause.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Change history

  • 15 August 2020

    The Responsible Editor indicated in the original article is incorrect, the correct Responsible Editor for this paper is Junsen Zhang.

Notes

  1. See Krafft (2016) for the derivation of this ambiguous result and a discussion of its applicability to Egypt.

  2. Retherford et al. (2010 show that estimates of TFR using ASFRs are similar but not identical to estimates of TFR using PPR. The different methods and assumptions are expected to generate slightly different estimates.

  3. See Assaad and Krafft (2013) for additional information on the ELMPS. Weights are used with this paper’s descriptive statistics. Regressions do not use sampling weights since sampling is unrelated to the dependent variable and in such a case unweighted methods are preferred (Deaton 1997; Winship and Radbill 1994).

  4. Comparisons of annual fertility rates for the early 2000s indicate relatively comparable data for that period across the ELMPS 2006 and ELMPS 2012.

  5. Data quality is always a concern for surveys, particularly when relying on retrospective data. Assaad et al. (2018b) exploit the panel nature of the ELMPS to validate the retrospective data. The key covariate (public sector employment) performs well in these checks. Consistency of reporting across panel and retrospective data for public sector jobs was in the range of 85–89% (Assaad et al. 2018b). Additionally, Assaad and Krafft (2013) validate the 2012 data against other labor force surveys and censuses.

  6. Single calendar years are also included in the IV models since they include annual estimates of employment.

  7. Throughout the paper, although descriptive statistics are presented for the mean observed values of the incorporated continuous variables, all the continuous variables (prenatal care, life expectancy, adult literacy, GDP per capita, and local public sector employment) are shifted to have a mean of zero in the multivariate analyses (the observed mean is subtracted from the observed values). This allows the baseline hazard across parities and births to be a more meaningful reference value.

  8. See Krafft (2016) for details on how crude birth rates (CBRs) have been evolving as well. CBRs are available annually and, starting in 2007, began to rise substantially and track quite closely with the TFRs, corroborating their trends.

  9. Ages 25–39 are used to capture employment during peak fertility years. Ages 20–24 are not included since many of those employed in the public sector are university graduates and would still be in school and then job hunting in this age range.

  10. This paper focuses on public sector employment rather than unemployment since unemployment is much more difficult to detect accurately in retrospective data than public sector employment (Assaad et al. 2018b). The effects of unemployment are also more challenging to causally identify.

  11. General secondary graduates also had a large increase, however, this small group (6% of women ages 15–64 in 2012) is primarily composed of students who are enrolled in higher education and thus neither married nor bearing children. When restricting the analysis of general secondary to non-students, their TFR was nearly constant, 3.9 in 2006 and 4.0 in 2012.

  12. Marriage is nearly universal in Egypt (Salem 2015).

  13. Figure 9, in Appendix 1, shows the results interacting age groups and single calendar years, which are quite noisy.

  14. Throughout, fifth and higher order parities are coded as a single category for estimation, as are intervals of 10 years and longer.

  15. Shifting religious values over time or across generations are another potential explanation. Unfortunately, religious affiliation is available for only a subset of women (married and 18–39 in 2012), precluding the calculation of a TFR. Models of childbearing estimated for the subset of women with religion data and adding interactions between years and religion are noisy but suggest that fertility has been rising for Muslim women to a greater extent than Christian women.

  16. The effects of various covariates, such as women’s own public sector employment, can be identified only from those women with variation in these characteristics, since fixed effects estimates are based on within-woman variation. Among the women who are observed working in the public sector at some point in the time period analyzed, 33% varied over time in their public sector status.

  17. For all of the simulations, individuals’ characteristics, aside from public sector employment, are as observed in the sample. In the 3SRI models, the residual is assumed to be zero.

  18. That spouse employment in the public sector is statistically insignificant and relatively small in magnitude compared to the odds ratios for women also suggests that the old-age security rationale for fertility is not driving the impact of public sector work. Having either the husband or the wife in the public sector would secure such a pension.

References

  • Abou-Ali H, El-Azony H, El-Laithy H, Haughton J, Khandker S (2010) Evaluating the impact of Egyptian social fund for development programmes. Journal of Development Effectiveness 2(4):521–555

    Google Scholar 

  • Adams R, Almeida H, Ferreira D (2009) Understanding the relationship between founder-CEOs and firm performance. J Empir Financ 16(1):136–150

    Google Scholar 

  • Ahn N, Mira P (2002) A note on the changing relationship between fertility and female employment rates in developed countries. J Popul Econ 15(4):667–682

    Google Scholar 

  • Al Zalak Z, Goujon A (2017) Exploring the fertility trend in Egypt. Demogr Res 37:995–1030

    Google Scholar 

  • Ali FRM, Gurmu S (2018) The impact of female education on fertility: a natural experiment from Egypt. Rev Econ Househ 16(3):681–712

    Google Scholar 

  • Allison PD (2009) Fixed effects regression models. SAGE Publications, Inc., Thousand Oaks

    Google Scholar 

  • Amer M (2015) Patterns of labor market insertion in Egypt, 1998-2012. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 70–89

    Google Scholar 

  • Angrist JD, Pischke J-S (2009) Mostly harmless econometrics. Princeton University Press, Princeton

    Google Scholar 

  • Assaad R (1997) The effects of public sector hiring and compensation policies on the Egyptian labor market. World Bank Econ Rev 11(1):85–118

    Google Scholar 

  • Assaad R, Krafft C (2013) The Egypt labor market panel survey: introducing the 2012 round. IZA Journal of Labor & Development 2(8):1–30

    Google Scholar 

  • Assaad R, Krafft C (2014) Youth transitions in Egypt: school, work, and family formation in an era of changing opportunities. Silatech working paper no. 14–1. Doha: Silatech

  • Assaad R, Krafft C (2015a) The evolution of labor supply and unemployment in the Egyptian economy: 1988-2012. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 1–26

    Google Scholar 

  • Assaad R, Krafft C (2015b) The structure and evolution of employment in Egypt: 1998-2012. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 27–51

    Google Scholar 

  • Assaad R, Krafft C, Selwaness I (2017) The impact of marriage on women’s employment in the Middle East and North Africa. Economic Research Forum working paper series no. 1086. Cairo, Egypt

  • Assaad R, Hendy R, Lassassi M, Yassin S (2018a) Explaining the MENA paradox: rising educational attainment, yet stagnant female labor force participation. IZA discussion paper series no. 11385. Bonn, Germany

  • Assaad R, Krafft C, Yassin S (2018b) Comparing retrospective and panel data collection methods to assess labor market dynamics. IZA Journal of Development and Migration 8(17):1–34

    Google Scholar 

  • Barsoum G (2015) Young people’s job aspirations in Egypt and the continued preference for a government job. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 108–126

    Google Scholar 

  • Becker GS (1960) An economic analysis of fertility. In Demographic and economic change in developed countries (pp. 209–240). Princeton, NJ: National Bureau of Economic Research Special Conference Series 11, Princeton University Press

  • Biørn E, Gaure S, Markussen S, Røed K (2013) The rise in absenteeism: disentangling the impacts of cohort, age and time. J Popul Econ 26(4):1585–1608

    Google Scholar 

  • Bloom DE, Canning D, Fink G, Finlay JE (2009) Fertility, female labor force participation, and the demographic dividend. J Econ Growth 14(2):79–101

    Google Scholar 

  • Bongaarts J (2003) Completing the fertility transition in the developing world: the role of educational differences and fertility preferences. Popul Stud 57(3):321–335

    Google Scholar 

  • Bongaarts J (2006) The causes of stalling fertility transitions. Stud Fam Plan 37(1):1–16

    Google Scholar 

  • Bongaarts J, Feeney G (1998) On the quantum and tempo of fertility. Popul Dev Rev 24(2):271–291

    Google Scholar 

  • Canning D, Schultz TP (2012) The economic consequences of reproductive health and family planning. Lancet 380(9837):165–171

    Google Scholar 

  • Carlin CS, Solid CA (2014) An approach to addressing selection bias in survival analysis. Stat Med 33:4073–4086

    Google Scholar 

  • Conesa JC (2000) Educational attainment and timing of fertility decisions. Mimeo.

  • Courbage Y (2015) The political dimensions of fertility decrease and family transformation in the Arab context. DIFI Family Research and Proceedings 3:1–16

  • Cygan-Rehm K, Maeder M (2013) The effect of education on fertility: evidence from a compulsory schooling reform. Labour Econ 25:35–48

    Google Scholar 

  • De Gobbi MS, Nesporova A (2005) Towards a new balance between labour market flexibility and employment security for Egypt. ILO employment strategy papers no. 2005/10

  • Deaton A (1997) The analysis of household surveys: a microeconometric approach to development policy. Johns Hopkins University Press, Baltimore

    Google Scholar 

  • Devarajan S, Ianchovichina E (2018) A broken social contract, not high inequality, led to the Arab spring. Rev Income Wealth 64(S1):S5–S25

    Google Scholar 

  • Dreze J, Murthi M (2001) Fertility, education, and development: evidence from India. Popul Dev Rev 27(1):33–63

    Google Scholar 

  • Elbadawy A (2015) Education in Egypt: improvements in attainment, problems with quality and inequality. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 127–146

    Google Scholar 

  • El-Zanaty F, Way AA (2001) Egypt demographic and health survey 2000. Ministry of Health and Population [Egypt], National Population Council, and ORC Macro

  • El-Zanaty F, Way A (2009) Egypt demographic and health survey 2008. Ministry of Health, El-Zanaty and Associates, and Macro International, Cairo

    Google Scholar 

  • Fang H, Eggleston KN, Rizzo JA, Zeckhauser RJ (2013) Jobs and kids: female employment and fertility in China. IZA Journal of Labor & Development 2(12):1–25

    Google Scholar 

  • Ferre C (2009) Age at first child: does education delay fertility timing? The case of Kenya. World Bank policy research working paper series no. 4833

  • Galor O, Weil DN (1996) The gender gap, fertility, and growth. Am Econ Rev 86(3):374–387

    Google Scholar 

  • Gatti R, Angel-Urdinola DF, Silva J, Bodor A (2014) Striving for better jobs: the challenge of informality in the Middle East and North Africa. World Bank, Washington

    Google Scholar 

  • Goujon A, Al Zalak Z (2018) Why has fertility been increasing in Egypt? Population & Societies 551

  • Heckman JJ, Walker JR (1990) The relationship between wages and income and the timing and spacing of births: evidence from Swedish longitudinal data. Econometrica 58(6):1411–1441

    Google Scholar 

  • Hendy R (2015) Women’s participation in the Egyptian labor market. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 147–161

    Google Scholar 

  • Hoodfar H (1997) Between marriage and the market: intimate politics and survival in Cairo. University of California Press, Berkeley

    Google Scholar 

  • Institute of National Planning (1995) Egypt human development report 1995. Cairo, Egypt

  • Institute of National Planning (2000) Egypt human development report 1998/1999. Cairo, Egypt

  • Jenkins SP (1995) Easy estimation methods for discrete-time duration models. Oxf Bull Econ Stat 57(1):129–138

    Google Scholar 

  • Jensen R (2012) Do labor market opportunities affect young women’s work and family decisions? Experimental evidence from India. Q J Econ 127(2):753–792

  • Kim J (2010) Women’s education and fertility: an analysis of the relationship between education and birth spacing in Indonesia. Econ Dev Cult Chang 58(4):739–774

    Google Scholar 

  • Kirk D (1996) Demographic transition theory. Popul Stud 50(3):361–387

    Google Scholar 

  • Kögel T (2004) Did the association between fertility and female employment within OECD countries really change its sign? J Popul Econ 17(1):45–65

    Google Scholar 

  • Krafft C (2016) Why is fertility on the rise in Egypt? The role of women’s employment opportunities. Economic Research Forum working paper series no. 1050. Cairo, Egypt

  • Krafft C, Assaad R (2014) Beware of the echo: the impending return of demographic pressures in Egypt. Economic Research Forum policy perspective no. 12. Cairo, Egypt

  • Krafft C, Assaad R (2015) Promoting successful transitions to employment for Egyptian youth. Economic Research Forum policy perspective no. 15. Economic Research Forum, Cairo

  • Krafft C, Assaad R (2017) Employment’s role in enabling and constraining marriage in the Middle East and North Africa. Economic Research Forum working paper series no. 1080. Cairo, Egypt

  • Krafft C, Assaad R, Keo C (2019) The evolution of labor supply in Egypt from 1988–2018: a gendered analysis. Economic Research Forum working paper series no. 1358. Cairo, Egypt

  • Kye B (2012) Cohort effects or period effects? Fertility decline in South Korea in the twentieth century. Popul Res Policy Rev 31:387–415

    Google Scholar 

  • Martínez DF, Iza A (2004) Skill premium effects on fertility and female labor force supply. J Popul Econ 17(1):1–16

    Google Scholar 

  • Ministry of Health and Population, El-Zanaty and Associates, ICF International (2015) Egypt demographic and health survey. Ministry of Health and Population and ICF International, Cairo

  • Mukhopadhyay SK (1994) Adapting household behavior to agricultural technology in West Bengal, India: wage labor, fertility, and child schooling determinants. Econ Dev Cult Chang 43(1):91-155

  • Nassar H (2003) Egypt: structural adjustment and women’s employment. In: Doumato EA, Posusney MP (eds) Women and globalization in the Arab Middle East: gender, economy, and society (pp. 95-118). Lynne Rienner Publishers, Boulder

  • Ní Bhrolcháin M (1992) Period paramount? A critique of the cohort approach to fertility. Popul Dev Rev 18(4):599–629

    Google Scholar 

  • Olmsted J (2003) Reexamining the fertility puzzle in MENA. In: Doumato EA, Posusney MP (eds) Women and globalization in the Arab Middle East: gender, economy, and society (pp. 73–94). Lynne Rienner Publishers, Boulder

  • Palmore JA, Gardner RW (1994) Measuring mortality, fertility, and natural increase: a self-teaching guide to elementary measures, 5th edn. East-West Center, Honolulu

    Google Scholar 

  • Radovich E, El-Shitany A, Sholkamy H, Benova L (2018) Rising up: fertility trends in Egypt before and after the revolution. PLoS One 13(1):1–14

    Google Scholar 

  • Retherford R, Ogawa N, Matsukura R, Eini-Zinab H (2010) Multivariate analysis of parity progression-based measure of total fertility rate and its components. Demography 47(1):97–124

    Google Scholar 

  • Rosenzweig MR, Evenson R (1977) Fertility, schooling, and the economic contribution of children in rural India: an econometric analysis. Econometrica 45(5):1,065–1,079

    Google Scholar 

  • Salem R (2015) Changes in the institution of marriage in Egypt from 1998 to 2012. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 162–181

    Google Scholar 

  • Schultz TW (1973) The value of children: an economic perspective. J Polit Econ 81(2):S2–S13

    Google Scholar 

  • Schultz TP (1985) Changing world prices, women’s wages, and the fertility transition: Sweden, 1860-1910. J Polit Econ 93(6):1126–1154

    Google Scholar 

  • Schultz TP (1997) Demand for children in low income countries. In: Rosenzweig MR, Stark O (eds) Handbook of population and family economics (1A:349–430). Elsevier Science B.V., Amsterdam

  • Schultz TP (2008) Population policies, fertility, women’s human capital, and child quality. Handb Dev Econ 4(07):3249–3303

    Google Scholar 

  • Selwaness I, Krafft C (2018) The dynamics of family formation and women’s work: what facilitates and hinders female employment in the Middle East and North Africa? Economic Research Forum working paper series no. 1192. Cairo, Egypt

  • Sieverding M, Hassan R (2016) “Her future is marriage”: young People’s attitudes towards gender roles and the gender gap in Egypt. Population Council, Cairo

    Google Scholar 

  • Social Research Center - The American University in Cairo (2012) Policies to address fertility plateau in Egypt: final report. The American University in Cairo and UNFPA, Cairo

    Google Scholar 

  • Strulik H, Vollmer S (2015) The fertility transition around the world. J Popul Econ 28(1):31–44

    Google Scholar 

  • Terza JV, Basu A, Rathouz PJ (2008a) Two-stage residual inclusion estimation: addressing endogeneity in health econometric modeling. J Health Econ 27(3):531–543

    Google Scholar 

  • Terza JV, Bradford WD, Dismuke CE (2008b) The use of linear instrumental variables methods in health services research and health economics: a cautionary note. Health Serv Res 43(3):1102–1120

    Google Scholar 

  • UNDP, Institute of National Planning (2003) Egypt human development report 2003. Cairo, Egypt

  • UNDP, Institute of National Planning (2005) Egypt human development report 2005. Cairo, Egypt

  • UNDP, Institute of National Planning (2008) Egypt human development report 2008: Egypt’s social contract: the role of civil society. Egypt

  • UNDP, Institute of National Planning (2010) Egypt human development report 2010. Egypt

  • UNDP, Institute of National Planning Egypt (2004) Egypt human development report 2004. Cairo, Egypt

  • USAID (2011) Egypt health and population legacy review (Vol. 1). USAID, Washington, DC

  • Van Hook J, Altman CE (2013) Using discrete-time event history fertility models to simulate total fertility rates and other fertility measures. Popul Res Policy Rev 32(4):585–610

    Google Scholar 

  • Vignoli D (2006) Fertility change in Egypt: from second to third birth. Demogr Res 15(18):499–516

    Google Scholar 

  • Weeks JR (1970) Urban and rural natural increase in Chile. The Milbank Memorial Fund Quarterly 48(1):71–89

    Google Scholar 

  • Willis RJ (1973) A new approach to the economic theory of fertility behavior. J Polit Econ 81(2):S14–S64

    Google Scholar 

  • Winship C, Radbill L (1994) Sampling weights and regression analysis. Sociol Methods Res 23(2):230–257

    Google Scholar 

  • Wooldridge JM (2002) Econometric analysis of cross section and panel data. The MIT Press, Cambridge

    Google Scholar 

  • Wooldridge JM (2014) Quasi-maximum likelihood estimation and testing for nonlinear models with endogenous explanatory variables. J Econ 182(1):226–234

    Google Scholar 

  • Wooldridge JM (2015) Control function methods in applied econometrics. J Hum Resour 50(2):421–445

    Google Scholar 

  • World Bank (2013) World development indicators. World Bank Databank. Retrieved from http://databank.worldbank.org/data/home.aspx

  • Yassine C (2015) Job accession, separation and mobility in the Egyptian labor market over the past decade. In: Assaad R, Krafft C (eds) The Egyptian labor market in an era of revolution. Oxford University Press, Oxford, pp 218–240

    Google Scholar 

  • Yount KM, Langsten R, Hill K (2000) The effect of gender preference on contraceptive use and fertility in rural Egypt. Stud Fam Plan 31(4):290–300

    Google Scholar 

  • Youssef H, Osman M, Roudi-Fahimi F (2014) Responding to rapid population growth in Egypt. Population Reference Bureau policy brief. Washington, DC

Download references

Acknowledgments

I thank Ragui Assaad, Marc Bellemare, Paul Glewwe, Deborah Levison, Djavad Salehi-Isfahani, Maia Sieverding, seminar participants at the University of Minnesota, conference participants at the Population Association of America 2014 annual conference, and conference participants at the Economic Research Forum 2016 annual conference for helpful questions and comments. The comments of anonymous referees substantially improved the paper and are much appreciated.

Funding

The author gratefully acknowledges support from the Minnesota Population Center at the University of Minnesota funded through the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD) of the NIH under award number R24HD041023.

Author information

Author notes

  1. Caroline Krafft

    Present address: Department of Economics and Political Science, St. Catherine University, 2004 Randolph Hall, St. Paul, MN, 55105, USA

Authors and Affiliations

  1. Department of Applied Economics, University of Minnesota, Ruttan Hall, 1994 Buford Avenue, St. Paul, MN, 55108, USA

    Caroline Krafft

Authors
  1. Caroline Krafft
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Caroline Krafft.

Ethics declarations

Conflict of interest

The author declares that she has no conflicts of interest.

Additional information

Responsible editor: Klaus F. Zimmermann

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1. Descriptive statistics and models

Table 6 Sample characteristics
Full size table
Table 7 Age-specific fertility rates (births per 1000 women), 1980–2014
Full size table
Table 8 Percentage of population employed in the public sector, 1991–2011, by sex, ages 25–39
Full size table
Table 9 Employment rate (percentage) and percentage of the population employed in the public sector by education and age, women aged 15–64, 1998, 2006, and 2012
Full size table
Table 10 Hazards for discrete-time survival analysis model for births, age groups and grouped calendar years model, full 1990–2011 sample. Dependent variable: hazard (in year) of a birth. Coefficients have been transformed into hazards. Standard errors in parentheses
Full size table

Appendix 2. Models incorporating spouse characteristics

A series of additional analyses are conducted controlling for spouse characteristics. Spouse data are not available for all women, as the husband may not be present due to death, migration, separation, or divorce. Approximately 89% of women included in the sample have a spouse present in the household at the time of the survey. The age group of the spouse at each year, his education (categorically, as with women), and his time-varying employment in the public sector (based on his retrospective labor market history data) are incorporated as controls in this subset of regressions. The regressions with these additional controls can help test the possibility that there are substantial fertility preference differentials among individuals and households who work in the public sector. The results are presented in Table 11. Importantly, the impact of women’s public sector work persists with odds ratios across births that are similar to Table 2. The impact on moving from the second to the third birth and the third birth to the fourth birth remains statistically significant. The spouse being employed in the public sector is not statistically significant.Footnote 18

Table 11 Discrete-time survival analysis model (logit) for births including spouse characteristics. Dependent variable: hazard (in year) of a birth. Coefficients have been transformed into odds ratios. Standard errors in parentheses
Full size table

Appendix 3. Models incorporating interactions between having a son, public sector, and parity

As well as decisions about fertility depending on how many children the family already has, whether or not the family has a son is an important part of fertility decisions (Sieverding and Hassan 2016; Yount et al. 2000). There may be more discretion for women to not have third, fourth, or fifth children due to the pull of public sector work if they have already had a son. Table 12 presents an exploration of the potential relationship between public sector work, child sex composition, and parity. Models are presented both without fixed effects (akin to specification 3 in Table 2) and with fixed effects (similar to specification 4 in Table 4). Interactions between public sector work and parity, as well as parity and having a son, along with the three-way interaction between public sector work, parity, and having a son are all presented.

First, as the literature suggests and was true in the other models, having a son reduces the odds of a subsequent birth. The effect is significant for all parities, and increasingly so, suggesting that once they have several children, if women have a son childbearing is more likely to slow or stop. For the main effects of public sector work interacted with parity (the main effects being in the case with no son yet), there are not significant effects and in the model without fixed effects, odds ratios even lose the pattern of decreasing in later parities when the woman is in the public sector. However, for those women who have a son, the impact of public sector work on later births is large, a significant odds ratio of 0.452 for going from the third to fourth birth in the model without fixed effects, and a similar but insignificant odds ratio (p = 0.158) in the fixed effects model. Essentially, the relationship between public sector work and fertility depends on having already had a few children, including a male child. Since 69% of women have three children and 87% of women with a third child have a son, the majority of women have the potential to have their fertility influenced by work.

Table 12 Discrete-time survival analysis models for births with interactions between having a son, public sector, and parity. Dependent variable: hazard (in year) of a birth. Coefficients have been transformed into odds ratios. Standard errors in parentheses
Full size table

Appendix 4. Variation in local employment opportunities

Figure 10 provides examples of the estimated variation in local employment opportunities over time for eight combinations of governorate and urban/rural. There is a substantial amount of variation in the estimated local employment opportunities over time. Although there is some consistency in overall trends, there are also clearly differences by location. This variation may be caused by where government jobs are allocated across a variety of different ministries and programs, such as the Social Fund for Development, which targets poor areas (with mixed success), or the national Youth Employment Program (Abou-Ali et al. 2010; De Gobbi and Nesporova 2005).

Fig. 10
figure 10

Example urban/rural and governorate level trends in percentage of 25–39-year olds with public sector employment. Source: Author’s calculations based on ELMPS 1998, 2006, and 2012. Note: Age 25–39 sample is for the year in question, not necessarily the age in survey year

Full size image

Appendix 5. First stage of 3SRI model

Table 13 Probit marginal effects (first stage) for employment in public sector in year. Dependent variable: probability (in year) of public sector employment
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krafft, C. Why is fertility on the rise in Egypt? The role of women’s employment opportunities. J Popul Econ 33, 1173–1218 (2020). https://doi.org/10.1007/s00148-020-00770-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00148-020-00770-w

Keywords

JEL classifications

Search

Navigation