Journal of Policy Modeling 35 (2013) 669683
Available online at www.sciencedirect.com
Economic growth in MENA countries: Is thereconvergence of per-capita GDPs?
M. Simona Andreano a, Lucio Laureti b, Paolo Postiglione c,a Universitas Mercatorum, Via Appia Pignatelli 62, 00178 Rome, Italy
b LUM Jean Monnet University SS 100 Casamassima (BA) and Jean Monnet Permanent Course EuropeanCommission, Italy
c G. dAnnunzio University of Chieti-Pescara, Department of Economic Studies, Viale Pindaro 42,65127 Pescara, Italy
Received 15 December 2011; received in revised form 3 July 2012; accepted 15 October 2012Available online 13 March 2013
In the last years a central issue in economic growth debate has been represented by the convergenceproblem. Many empirical economists have noticed that per-capita GDPs of poor regions tend to converge tothose of the richer ones. This tendency is more evident in the nineties when the globalization phenomenonwas born. In this paper we use a conditional -convergence approach to evaluate the economic growth ofthe Middle East and North Africa (MENA) countries. In particular, we use a set of state, environmental,and economic covariates as conditioning variables of the model. The MENA region is daily at the center ofeconomic and political debate, and this stylized fact represents a further source of interest. Our data set isconstituted by 26 countries, and ranges from 1950 to 2007. 2013 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.
JEL classification: C13; O47; O57; F11
Keywords: -Convergence; MENA countries; Determinants of growth
There are very large differences in per-capita GDPs across countries today. The richer countriesshow a per-capita GDP more than thirty times larger than that of the poorest countries in terms
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of Purchasing Power Parity (PPP) adjusted dollars.1 For example, in 2011 per-capita GDP in theUnited States (US) was $48,442 (valued at current international dollars, World Bank source),while it was $8442 in China, $3650 in India, $2532 in Nigeria, and much lower in some otherAfrican countries such as Chad, Ethiopia, and Mali. The gap is obviously larger when there isno PPP adjustment. It is worth noticing that high-income levels generally reflect high standardsof living. In fact, per-capita GDP is usually used as a proxy for the quality of life in differentcountries, but we are aware that material wealth is only one of many aspects of life that enhanceeconomic well being. For example, recent estimates suggest that longevity has been a quantita-tively important component in welfare in the US during the twentieth century (Nordhaus, 2003).So far, understanding the motivation of the presence of these persistent economic differencesamong countries represents one of the most important challenges facing social sciences.
During the last years, the analysis of economic growth has become increasingly popular inthe macroeconomic literature (Abramovitz, 1986; Barro & Sala-i-Martin, 1995). Many empiricaleconomists, in agreement with Solows neoclassical growth model (1956), have observed that per-capita GDPs of poor regions grow more quickly than those of the rich ones, in other words poorcountries tend to finally catch up rich ones (Barro & Sala-i-Martin, 1992). This phenomenon,known in literature as economic convergence, implies a long run tendency to equalization ofper-capita GDPs.2 The assessment of this empirical tendency represents a matter of primaryrelevance for policy makers (Islam, 2003). According to the classification originally proposedby Galor (1996), three different definitions of economic convergence can be identified: absoluteconvergence, conditional convergence, and convergence clubs. Absolute convergence is reachedwhen all economies converge toward the same steady-state (in terms of per-capita GDP growthrates). However, the steady-state may depend on features specific to each economy, in which caseconvergence will still take place, but not necessarily at the same levels. This is the case whenper-capita GDP depends on a series of determinants such as, for example, factor endowment orinstitutions, which can vary from one economy to another even in the long run. Convergence isthen said to be conditional. Finally, the concept of convergence clubs is linked to the existenceof multiple, locally stable, steady-state equilibrium to which economies with similar characteris-tics converge (Durlauf & Johnson, 1995). Recently, the interest of empirical researcher focuseson the investigation of the phenomenon at the regional level, namely the analysis of economicconvergence on intra-national scales. More recent studies introduce a spatial dimension into theformulation of the problem, see, for instance Rey and Montouri (1999) for an introduction ofthe problem, and Postiglione, Benedetti, and Lafratta (2010) and Postiglione, Andreano, andBenedetti (in press) for some very recent contributions to the debate.
Alternative definitions, as those based on the concept of stochastic convergence, have also beenintroduced in the literature (Evans & Karras, 1996). To overcome some problems linked with theanalysis of economic convergence, such as endogeneity, heterogeneity, and omitted variables,other techniques, like panel data (Islam, 1995; Laureti & Postiglione, 2005), and probabilitytransition matrices (Quah, 1997), have often been used.
The purpose of the present paper is to analyze the economic growth in the Middle East and NorthAfrica (MENA) countries, with particular emphasis on the convergence process in terms of long-term trend of per-capita GDPs. The economy of the region has been heavily influenced by peculiar
1 Per-capita GDP based on purchasing power parity is gross domestic product converted to international dollars usingpurchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has inthe United States. For an application to Mediterranean countries see Laureti (2001).
2 See Laureti (2008) for an analysis of economic convergence in Mediterranean countries.
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factors, such as energy sources, and demographic and institutional characteristics. Furthermore,this thematic paper aims to evidence the specific determinants of the growth process.
The term MENA covers a wide geographical area, extending from Morocco to Iran, includingthe majority of both the Middle Eastern and Maghreb countries. Following the definition ofWorld Bank, the MENA is: an economically heterogeneous region that includes both the oil-richeconomies in the Gulf and countries that are resource-scarce in relation to population, such asEgypt, Morocco, and Yemen. For the complete description of the countries in our sample data seeSection 3.3
Over the last fifteen years, the growth performance of the MENA region as a whole, despite itsnatural resources richness, has been unsatisfactory and not in line with other developing countries.In comparison with other regions in the world, growth rates in the MENA countries have beenremarkably volatile and lower than that of the poor-performing regions such as Sub-SaharanAfrica (SSA). This volatility is only partly due to political and social instability, to the wars or tothe marked fluctuations in oil prices that have characterized the history over the last century.
Besides, the area is subject to a peculiar process of development, which probably has no equalsworldwide. An example is the significant inter-regional migration flows, the consistent populationgrowth, the policy mis-management, and, finally, the strong interdependence between politics onone side, and the economic and social spheres on the other side.
Only a few empirical studies have dealt with the MENA region, largely due to lack of data.Abu-Qarn and Abu-Bader (2007) analyzed a period ranging from 1960 to 1998, and observed thataccumulation of capital seems to be the major determinant of economic growth. Adams and Page(2003) used cross-country data to analyze trends in poverty, inequality, and economic growth inthe MENA region. The analysis showed that international migration/remittances and public sectoremployment had a statistically significant impact on reducing the level and depth of poverty inthe MENA region. Ben Naceur and Ghazouani (2007) highlighted the idea of not significant rela-tionship between banking and stock market development and growth. Arouri, Youssef, Mhenni,and Rault (2012) investigated the relationship between carbon dioxide emissions, energy con-sumption, and real GDP for 12 MENA countries over the period 19812005. Finally, Guetatand Serranito (2007) tested the convergence hypothesis in the MENA region using unit roots inpanel data following Evans and Karras (1996) methodology. They concluded that the conditionalconvergence is not rejected for the majority of the MENA countries.
In a previous paper, Andreano and Savio (2012) analyzed the absolute -convergence forthe MENA countries. They observed that the large and heterogeneous region of MENA hasexperienced over the last sixty years a process of weak not significant convergence, with apparentinequalities in recent period. The consequent social and political tensions still constitute an elementof risk for the region, as evidenced by the recent events. In other words, the hypothesis of absolute-convergence does not seem to be confirmed by the data.
Compared to other studies, our analysis uses an enlarged definition of the MENA countriesand covers a more extensive sample period ranging from 1950 to 2007.
In the light of the recent events that characterized the Arabic spring, we re-examines theSummer-Heston data set in order to identify the conditioning factors of the growth in the area.The aim of the paper is to achieve a better understanding of the heterogeneous, interrelatedcharacteristics of the growth, ranging from economic and social, to demographic and governancefactors. The objective is to provide a proper interpretation of how these aspects, interacting with
3 Note that often the studies on the MENA countries are added and overlap with those of the Mediterranean countries.
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each other and at the same time with the initial conditions of development, have led to a given pathof growth in the area. These main determinants are analyzed in terms of conditional -convergence.
The layout of the paper is the following. Section 2 is devoted to a review of the main conceptsof -convergence. A description of data and some statistical measure are given in Section 3.Furthermore, Section 3 presents the empirical analysis of conditional -convergence approachfor our data sample. Finally, Section 4 concludes the paper and outlines the future research agenda.
2. A review of economic convergence approach
The economic convergence in per-capita GDPs across countries has been largely analyzedfrom both the theoretical and the empirical point of view (Barro & Sala-i-Martin, 1992). Themost popular approaches in the quantitative measurement of convergence are those based on theconcepts of -convergence and -convergence (Barro & Sala-i-Martin, 1995).
The -convergence approach is based on the study of the time trend of the variance of thelogarithms of per-capita GDP. If there is a decreasing long-term trend, then countries converge toa common growth rate, and so -convergence is satisfied. This approach is not justified by anyeconomic theory and, furthermore, the variance of logarithms is insensible to permutations, it doesnot allow discriminating between different geographical situations. However, the -convergenceis a widely used measure. For example, for some application in European Union see Monfort(2008).
So, the -convergence approach has been considered the more convincing under the theoret-ical viewpoint, as well as the more appealing, since it leads to a quantification of the speed ofconvergence. The concept of -convergence is directly related to the neoclassical Solow-Swanexogenous growth theory (Solow, 1956; Swan, 1956), assuming exogenous saving rates and aproduction function based on decreasing productivity of capital and constant returns. Accordingto this model we can write that:
Y (t) = F (K(t); L(t))
t= sf (k) pk
where Y(t) is the total production at time t, F(.) is a production function, homogenous of degreeone, K is the stock of physical capital, L is the labor force, k is the per-capita capital, k/t is thederivative of k with respect to time t, s is constant saving rate, f(k) is the per-capita production,and p is the populations growth rate.
On this basis Barro and Sala-i-Martin (1992), in order to measure absolute -convergence,suggest the following statistical model:
gi = + qi + i (2)where gi is the average growth rate of per-capita GDP across the time period under investiga-tion, is the intercept, qi = ln(yi0) is the natural logarithm of the initial level of per-capita GDP, = (1 eT)/T, is the speed of convergence which measures how fast economies will con-verge toward the steady state,4 T is the spanned time interval, and i is the error term and is theerror term which is assumed to be normally distributed (0, 2 ). In a cross-section of economies,
4 = ln (T+1)T
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there is absolute -convergence if we find a negative relation between the growth rate of per-capitaGDP and its initial level, i.e. if is negative and statistically different from 0. Note that throughthe absolute approach, the per-capita GDP growth rate is described as a function of only onecovariate (i.e. the natural logarithm of the initial level of per-capita GDP).
The use of absolute -convergence approach does not seem to be realistic, since it is implausibleto consider different economies identical for some structural characteristics as, for example: savingrates, population growth rates, preferences (Sala-i-Martin, 1996). The idea that economic growthis a composite function of a great number of interrelated factors has led some economists todevelop the idea of conditional economic convergence. The conditional approach is coherentwith the neoclassical framework, but it concerns the tendency of a cross-section of coun...