Is Middle East and North Africa different? A comparative analysis of growth and structural change in and outside MENA

Abstract

By using general method of moments-system estimation on a panel of developing countries over the period 1984–2011, we contrast the Middle East and North African (MENA) countries’ growth pattern with that of middle-income countries from other regions. Three complementary dimensions of growth driver are assessed: accumulation, structural change and institutions. Our comparative analysis shows that MENA economies sharply contrast with other middle-income emerging economies with respect to two main dimensions: (1) the sectoral structure of production and (2) the institutional environment. We show that, during the last three decades, the MENA region has exhibited a specific pattern of growth featuring a low pace of structural change and high corruption levels, which may have hindered highly productive job creation, and eventually bred massive discontent in the region. The assumption of the complementary effect of the accumulation, institutional and structural growth determinants is also supported by our empirical estimations.

Keywords:

• economic growth
• structural change
• institutions
• corruption
• MENA
• middle-income; developing countries
• comparative analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Malik and Awadallah (2011) have proposed a very complementary descriptive explanation of the economic underpinnings of the Arab Spring which focuses on various sources (weak trade integration, high dependence to natural resource rents, opportunity costs of reforms) of hindrance to the expansion of a dynamic private sector.

2. It should be noticed, however, that Turkey accounts for 80% of Brazilian TFP levels, and Morocco and some rare resource-rich and labor-importing countries such as Oman or Saudi Arabia have TFP levels akin to those of the dynamic East-Asian economies (Thailand, Malaysia and China) (World Bank, 2009).

3. Financial constraint remains also high, since State-owned banks averaging 60% of the total assets of banking systems tend to favour large private or public enterprises, leaving small businesses exposed to capital shortage (Battacharya & Wolde, 2010; Enders, 2007).

4. However, estimations show that these returns are higher for all education levels, with the exception of the university level. Actually, what young educated people look for is also the stability associated with these public jobs (Yousef, 2004, p. 18).

5. Most of them are also involved in activities not properly recorded in national income statistics, such as the running of social services (Veganzones-Varoudakis & Pissarides, 2007).

6. Population growth, Investment, GDP growth and levels are taken from the World Bank Development Indicators, except initial levels of Schooling that come from Barro and Lee (2000). Data definitions, sources and mean values are reported in Table A1 in Appendix.

7. We use the UNCTAD's indicator which is measured by a Herfindhal index of concentration. It means that a higher value of the index corresponds to a higher concentration, and therefore, a lower diversification of the export structure.

8. We use the ICRG indicator of corruption, which takes a higher value when perceived political corruption is lower.

9. Algeria, Argentine, Brazil, China, Chile, Egypt, India, Indonesia, Malaysia, Mexico, Morocco, Pakistan, Paraguay, Peru, Philippines, Thailand, Tunisia, Turkey, Uruguay and Venezuela.

10. Sargan/Hansen instruments' validity tests and Arellano and Bond (1991) first and second order autocorrelation tests are reported in the bottom panel of the tables.

11. Mean- and variance-difference tests on GDP, Schooling, Population, Investment, FDI, Agricultural share and Corruption show that the MENA sub-group exhibits systematically lower level and higher heterogeneity for all variables, except for Corruption whose level is significantly higher. The results are not reported in the paper, but they are available on request.

12. Yet, FDI is no longer significant once non-linear specifications are estimated as in Table 4's column 4 and in Table 5. To explain the weak impact of FDI on MENA growth, various explanations have been advanced: the lack of structural transformation (Nicet-Chenaf & Rougier, 2011), the competition between MENA economies to attract FDI (Nicet-Chenaf & Rougier, 2009b), or the sensibility of FDI to the MENA region to macroeconomic instabilities in source and host countries (Nicet-Chenaf & Rougier, 2014, 2016).

13. For a description of the failure of industrial policy to trigger structural change in MENA region in general and in the case of Morocco more specifically, see Piveteau and Rougier (2011).

14. For a discussion of this point, see Rougier (2016) and Cammett et al. (2015).