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Demographics in MENA Countries: A Major Driver for Economic Growth

Abstract

MENA region is undergoing rapid demographic transition, where 50% of the population is under the age 25 and high youth unemployment rates are argued to be one of the main sources of political instability. In this paper we evaluate the economic impact of the demographic transition for selected MENA countries, namely: Iran, Morocco and Egypt who experience different speeds of transition. We have developed a general equilibrium overlapping generations model with a cost of capital mobilisation as a proxy for financial markets’ efficiency and simulated the demographic trends in each country. We find that the demographic shift will be an important driver for growth in the upcoming decades. Furthermore, our results show that a more efficient financial sector leads to better economic performance. Specifically, youth are the primary beneficiaries: an increase in the financial sector efficiency can reduce up to 8 percentage points of the the unemployment rate for the youngest age group.

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Fig. 1

Source: Authors

Fig. 2

Source: Authors’ calculations

Fig. 3

Source: Authors’ calculations

Notes

  1. 1.

    Unemployment rate for ages between 12 and 24, are given by national statistics.

  2. 2.

    Generalized method of moments.

  3. 3.

    The pension schemes are not very well developed in the region and many elderly stay in the labor market or depend on their children.

  4. 4.

    Considering migration is beyond the scope of this paper.

  5. 5.

    The classical contributions are introduced in Diamond (1981), Pissarides (1985) and Mortensen and Pissarides (1994).

  6. 6.

    TFP is set to 21, 18.9 and 19.5 in Iran, Morocco and Egypt respectively.

  7. 7.

    Age-productivity profile is estimated almost always by wage differentials, which is quite debatable as the rewards to the seniors maybe due to loyalty or past achievements rather than current productivity, on the other hand older workers importance to the companies is difficult to measure since it can be due to wider networks, knowing better how to deal with problems with lower frequencies etc. Hence, although wage differentials are not the ideal measures for productivity, they are considered one of the best so far.

  8. 8.

    In order to verify that our results are not simply a response to the calibration of the human capital we perform a robustness check (see in “Appendix 3”) where we set the human capital constant among different age groups.

  9. 9.

    10.2% for Morocco, 13% for Egypt and 12.8% for Iran in 2014.

  10. 10.

    United Nations, Department of Economic and Social Affairs, Population Division (2015), custom data acquired via website.

  11. 11.

    The main focus of this paper is on the efficiency of the financial sector and not its size.The literature on the impact of the financial sector on economic growth is very well developed (see Arcand et al. 2015).

  12. 12.

    In this model, like any other overlapping generation settings with perfect foresight the savings is 0 for the oldest age group.

  13. 13.

    The evolution of other variables such as consumption, wages, capital, interest rate and productivity are available upon request.

  14. 14.

    We can perform the same exercise for Morocco and Egypt, the results remain the same.

  15. 15.

    We can perform the same exercise for Iran or Egypt the results remain the same.

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Author information

Correspondence to Hippolyte d’Albis.

Additional information

Publisher's Note

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

This research has benefited from financial support by PSL Research University, Programme d’Investissements d’avenir, ANR-10-IDEX-0001-02 PSL.

We thank the anonymous reviewers for their careful reading of our manuscript and their insightful suggestions and comments. we also thank the participants of the MCD seminar at International Monetary Fund, specially Hossein Samiei for their helpful remarks and comments. All remaining errors are ours.

Appendices

Appendix 1: The Demographic Shift Parameters

See Fig. 4, Table 5.

Table 5 Demographic parameters.
Fig. 4
figure4

Population dynamics by age group and total. Note: Population of each age group is represented as its share in the total active population (Authors based on UN data set)

The growth rate of the population, Fig. 5, is a decreasing function, although for Iran and Morocco we observe a slight take off in the final periods of the simulation.

Fig. 5
figure5

Source: Authors based on UN data set

Active population growth rate.

Appendix 2: Robustness Check for Cost of Investment

In this appendix we show that our results are robust to the initial value of \((1-\varphi )\). In order to do so, we suppose the initial value of \((1-\varphi )\) to be 0.1 instead of 0.2, which means that the cost of allocating capital is 10% in our baseline scenario, the definition of High and Low scenario remains the same, the value of \((1-\varphi )\) in each case is reported in Table 6.

Table 6 The value of \((1-\varphi )\) or the cost of capital accumulation under different scenarios.

The results qualitatively, remain the same, although the initial steady state changes slightly since the initial cost of capital is not the same. The simulation results for Iran are reported in Figs. 6, 7, 8 and 9.Footnote 14

Fig. 6
figure6

Source: Authors

GDP level (percentage deviation from the initial steady state) for Iran.

Fig. 7
figure7

Source: Authors

GDP per capita (percentage deviation from the initial steady state) for Iran.

Fig. 8
figure8

Source: Authors

Unemployment rate evolution by age after the demographic shift (baseline) for Iran.

Fig. 9
figure9

Source: Authors

Savings per capita evolution by age for Iran. Note: Savings per capita for different age groups, according to model’s assumptions, the savings is nul for the last age group (55–64).

Appendix 3: Robustness Check, Constant Human Capital

One may argue that our results are merely a mechanical response to the different age-specific human capital, reported in Table 1.

In this appendix we perform the simulations for Morocco, and suppose a constant human capital for all age groups, i.e. \(h_i=2.5 \quad \forall i=1,\ldots,4\) The simulation results are reported in Figs. 10, 11, 12 and 13.Footnote 15

Fig. 10
figure10

Source: Authors

GDP level (percentage deviation from the initial steady state).

Fig. 11
figure11

Source: Authors

GDP per capita evolution (percentage deviation from the initial steady state).

Fig. 12
figure12

Source: Authors

Unemployment rate evolution by age after the demographic shift.

Fig. 13
figure13

Source: Authors

Savings per capita evolution by age for Morocco.

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Forouheshfar, Y., El Mekkaoui, N. & d’Albis, H. Demographics in MENA Countries: A Major Driver for Economic Growth. De Economist (2020). https://doi.org/10.1007/s10645-020-09357-y

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Keywords

  • Development
  • MENA region
  • Financial efficiency
  • OLG model
  • Demographic transition

JEL Classification

  • J11
  • E17
  • O16