Skip to main content
SpringerLink
Log in

The economic cost of the Arab Spring: the case of the Egyptian revolution

  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

This paper analyzes the effects that the Arab Spring and the subsequent revolution had on per capita real Gross Domestic Product in Egypt. The estimation procedure that we follow is the synthetic control method. After comparing the observed evolution of Egyptian real output in the period 2011–2017 with that of synthetic Egypt, our estimates show (i) an accumulated loss in the growth rate of per capita real Gross Domestic Product of 12.04% (a yearly average of 1.56%); (ii) an accumulated loss in the per capita real Gross Domestic Product of 6279.7 dollars (a yearly average of 897.1 dollars); and (iii) an accumulated loss in the aggregate real Gross Domestic Product of 582.5 billion dollars (a yearly average of 83.2 billion dollars).

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
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. One exception is Groizard et al. (2016) which studies foreign tourists’ demand for travel to countries experiencing Arab Spring episodes by using a gravity model of bilateral tourism flows for Egypt, Syria, Tunisia and Yemen.

  2. Matta et al. (2016) follow a similar approach where Tunisia is the case study.

  3. The data come from the World Travel & Tourism Council (https://www.wttc.org) [last accessed December 2018].

  4. The data source is the World Development Indicators Databank (http://databank.worldbank.org) [last accessed December 2018].

  5. The data come from different sources: Quality of Government Standard Dataset (http://qog.pol.gu.se) for education, unemployment and inflation data [last accessed December 2018]; Transparency International’s 2010 report (http://www.transparency.org) for corruption data [last accessed December 2018]; and World Development Indicators Databank (http://databank.worldbank.org) for poverty [last accessed December 2018].

  6. This heavily draws on Abadie et al. (2010, 2015).

  7. If the number of treated units was more than one, the method could be applied independently to each of the treated units or to an aggregate of all treated units.

  8. Note that the non-negative elements of matrix V can always be normalized to add up to, say, 1 as this does not affect the optimal choice for the vector of weights \(\mathbf {w}\).

  9. This is defined as \((T_{0}-T^{*})^{-1}\sum _{t=T^{*}+1}^{T_{0}}\left( Y_{1t}-\sum _{j=2}^{J+1}Y_{jt}w_{j}^{*}\right) ^{2}\). Intuitively, the cross-validation technique selects the matrix V that minimizes out-of-sample prediction errors.

  10. In particular, we use the R MSCMT package, version 1.3.3, which has proven to outperform other computational procedures implemented in R, Stata\(^{\copyright }\) and Matlab\(^{\copyright }\) in terms of computational time and accuracy (see Becker and Klößner 2017, 2018).

  11. Acemoglu et al. (2016) adopt a slightly more restrictive criterion as only control units with a Pre-MSPE less than or equal to \(\sqrt{3}\) times that of the treated unit are considered to test the statistical significance of the treatment effect.

  12. The suitability of introducing this discussion was kindly suggested to us by an anonymous referee.

  13. For the sake of space saving the corresponding counterpart to Table 2 has not been included in this paper, but it is available upon request from the authors.

References

Download references

Acknowledgements

We are deeply indebted to Javier Gardeazabal for his comments and suggestions on an earlier draft, to Martin Becker for his valuable help with the R code, and to the editor and two anonymous referees. The usual disclaimer applies.

Author information

Authors and Affiliations

  1. Departamento de Fundamentos del Análisis Económico II, University of the Basque Country UPV/EHU, Avda. Lehendakari Aguirre 83, 48015, Bilbao, Spain

    Cruz A. Echevarría

  2. Departamento de Economía Aplicada III (Econometría y Estadística), University of the Basque Country UPV/EHU, Avda. Lehendakari Aguirre 83, 48015, Bilbao, Spain

    Javier García-Enríquez

Authors
  1. Cruz A. Echevarría
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Javier García-Enríquez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cruz A. Echevarría.

Ethics declarations

Conflict of interest

Both authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

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

This study was funded by the Spanish Ministry of Economy and Competitiveness and the European Fund of Regional Development [Grant Numbers ECO2015-64467-R and ECO2016-76884-P (MINECO/FEDER)] and by the Basque Government (Grant Numbers DEUI-IT-793-13 and DEUI-IT-783-13).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Echevarría, C.A., García-Enríquez, J. The economic cost of the Arab Spring: the case of the Egyptian revolution. Empir Econ 59, 1453–1477 (2020). https://doi.org/10.1007/s00181-019-01684-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00181-019-01684-7

Keywords

Search

Navigation