boom, bust, and the poor: poverty dynamics in the middle east and north africa, 1970–1999

The Quarterly Review of Economics and Finance46 (2007) 832–851

Boom, bust, and the poor: Poverty dynamics in theMiddle East and North Africa, 1970–1999�

John Page ∗The World Bank, United States

Received 15 September 2005; received in revised form 30 June 2006; accepted 28 July 2006Available online 13 November 2006

Abstract

This paper analyzes changes in poverty and inequality in the Middle East and North Africa. It finds that thestructural relationship between poverty reduction, income growth and distribution is the same for MENA andother developing economies. Prior to 1985 rapid growth sharply reduced poverty. After 1985, despite verylow income growth, a rising share of income accruing to the lowest quintile meant that the average incomeof the poor rose more rapidly than that of the non-poor. These unusual poverty dynamics were primarily dueto international migration. Remittances both increased per capita incomes in labor exporting countries andincreased the share of income accruing to the poor.© 2006 Published by Board of Trustees of the University of Illinois.

Keywords: Migration; Remittances; Oil; Poverty; Growth; Income redistribution: Public: MENA; Inequality

The low and middle income countries of the Middle East and North Africa (MENA) regionoffer a sharp contrast to much of the developing world in terms of both the overall incidenceof poverty and recent trends in poverty reduction.1 The oil boom of the 1970s and early 1980spermitted both oil exporters and non-oil exporters in the region to reduce poverty rapidly. Bythe mid-1990s, those living on less than US$ 1.00 per day in MENA had fallen to less than 2%of the region’s population, a point where, among developing countries, MENA trailed only theeconomies of Eastern Europe and Central Asia in terms of the incidence of extreme poverty.

� Paper contributed to a volume of essays in honor of Professor Heba Handoussa on the occasion of her retirement asManaging Director of the Economic Research Forum for the Arab Countries, Iran, and Turkey. The findings and viewsexpressed in this paper are those of the author. They do not represent the views of the World Bank, its Executive Directorsnor the countries that they represent.

∗ Tel.: +1 202 473 7461.E-mail address: [email protected].

1 Defined by the Millennium Development Goal (MDG) standard of US$ 1.00 per day at purchasing power parity.

1062-9769/$ – see front matter © 2006 Published by Board of Trustees of the University of Illinois.doi:10.1016/j.qref.2006.08.008

mailto:[email protected]

dx.doi.org/10.1016/j.qref.2006.08.008

J. Page / The Quarterly Review of Economics and Finance 46 (2007) 832–851 833

Yet, despite these enviable statistics, widespread concern emerged in the region during thelast decade of the twentieth century about the durability of MENAs success in reducing poverty.Economic growth and the pace of poverty reduction slowed sharply after 1985, and the share inthe population of both the extreme poor and of those living on US$ 2 per day rose at the end ofthe 1990s.

Throughout her professional life Heba Handoussa has been engaged in trying to improveour understanding of growth, equity, and poverty in MENA. As a researcher, she has writtenextensively about growth, employment, human development, and poverty issues in Egypt. AsManaging Director of the Economic Research Forum for the Arab Countries, Iran, and Turkey(ERF), she encouraged both country level and comparative empirical research into the extentof poverty in MENA and its determinants. And, she has worked throughout the region to makedata on poverty available to scholars. This paper builds on – and seeks to honor – that work byexplaining the poverty dynamics through “boom and bust” of the developing countries of theMiddle East and North Africa.2

Section 1 of the paper examines MENAs record of poverty reduction during the 30-yearboom and bust period of 1970–1999. Section 2 focuses on placing MENAs poverty dynamicsin international context, asking to what extent the patterns of growth, distributional change, andpoverty reduction observed in MENA differ from those of other developing regions. It finds thatin particular, the period after 1985 was unusual, because a rising share of income accruing to thelowest quintile of the income distribution meant that, despite very low rates of average incomegrowth, the average income of the poor rose more rapidly than that of the non-poor. Section3 tests the hypothesis that international migration and remittance income, together with publicemployment were largely responsible for the rising share of incomes accruing to poor in MENA.Section 4 concludes by asking if MENA can sustain its record of poverty reduction in the face ofcontinuing economic change.

Before beginning, it is important to highlight a major constraint facing those who attempt tounderstand poverty in the MENA region. The lack of accessible and comparable household budgetsurveys makes it difficult even to identify the extent of poverty in most Middle Eastern countries.3

For example, of the 15 Middle Eastern countries included in the Middle East and North AfricaRegion of the World Bank, only 9 appear in the largest international data set reporting on povertyand income inequality (Dollar & Kraay, 2002).4 Only four countries have nationally representativehousehold budget surveys that are openly accessible to the public, and of these none has openlyaccessible data for more than 1 year.5

1. Poverty and inequality in boom and bust, 1970–1999

The Middle East and North Africa began the last decade of the twentieth century with levelsof income poverty that were strikingly low by international standards. By 1990, only the non-

2 In this paper, the low and middle income countries – “developing countries” – of the region are defined as those forwhich we have both aggregate economic data and data on income distribution for at least one point in time. That set ofcountries consists of Algeria, Egypt, Iran, Iraq, Jordan, Morocco, Tunisia, and Yemen. Due to lack of information onincome distribution and to their fundamentally different level of development the GCC countries are omitted.

3 Throughout her tenure as Managing Director of the ERF Heba Handoussa campaigned for MENA governments tomake their surveys accessible to scholars in the region. Some progress is being made, but much remains to be accomplished.

4 These are the countries listed in footnote 1 plus Djibouti.5 The four economies which have openly accessible household surveys are: Morocco (1990/91), Egypt (1997), West

Bank and Gaza (1997), and Yemen (1998).

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market, socialist economies of the Eastern Bloc had succeeded in reducing the share of theincome poor in their populations below that of the MENA economies. In 1987 – the first year forwhich comparable international data exist – the Millennium Development Goal (MDG) povertyheadcount (US$ 1.00 per day) in MENA stood at 4.3% of the population; by 1990, it had declinedto 2.1%. The decade of the 1990’s, however, saw little additional progress in poverty reduction.Although the headcount index declined to a low of 1.9% of the population in 1993, by 2000 ithad risen to 2.8% (Table 1).

Using an income poverty measure based on US$ 2.00 per day, the trends in poverty reductionare similar.6 In 1987, about 30% of the region’s population lived below the poverty line. Theheadcount index declined to a low of 22.2% in 1996 – roughly similar to that of Eastern Europeand Central Asia – but rose between 1996 and 2000 to 24.4%, eliminating the gains of the previousdecade. Relative to other regions, however, the Middle East remained a low poverty region – evenat US$ 2.00 per day – trailing only the transitional economies of Europe and Central Asia.

What accounted for MENAs success in reducing poverty? Changes in headcount poverty canbe shown to be an outcome of changes in income (or consumption) and in its distribution amongincome classes.7 For any given distribution of income, rising income per capita will result in adecline in poverty. This is not to say, however, that average growth translates one for one intogrowth of the incomes of the poor.8 Growth associated with progressive distributional change willhave a greater impact in reducing poverty than growth, which leaves the distribution unchanged(Bourgignon, 2001). Regressive distributional change, on the other hand, can offset the benefitsof growth to the poor. There are two main reasons for this. The first is simply the direct, positiveimpact that progressive distributional change has on poverty reduction for any given rate ofgrowth. There is, however, a second, indirect and positive impact of a fall inequality. Reductionsin inequality increase the impact of future growth on poverty reduction.

Table 2 presents estimates of the average rate of per capita income growth, the rate of growth ofthe average income of the bottom quintile of the income distribution, and the poverty headcount atUS$ 1.00 or 2.00 per day for the developing countries of the Middle East and North Africa duringthe period 1970–1999. It also presents two measures of income distribution, the Gini coefficientand the share of income accruing to the bottom quintile of the population.

The impact of the boom and bust cycle of income growth on poverty reduction is apparent.The average per capita income growth for the region as a whole between 1975 and 1979 wasover 3.8%. This was sustained into the period 1980–1984 and followed by a sharp slowdown ingrowth in the period following 1985. Both parts of the cycle were linked to changes in the priceof oil.9 Growth was clearly good for the poor in MENA. The poverty headcount tracked incomegrowth, with the incidence of those living on less than US$ 1.00 per day falling rapidly between1975–1979 and 1990–1994, and then stabilizing at about 2% of the population. The pattern wasthe same for those living on less than US$ 2.00 per day. Substantial gains were recorded between1975 and 1985.

6 The MDG poverty target of US$ 1.00 per day (at purchasing power parity) has been criticized as inappropriately lowfor middle income countries and regions, such as MENA.

7 See, for example, Ravallion and Datt (1991), Bourgignon (2001), Cord, Lopez, and Page (2003).8 Ravallion (2001), for example, finds that, based on cross country evidence, the 95% confidence interval for a 1%

increase in average household income or consumption yields anything from a modest drop in the poverty rate of 0.6% toa more dramatic 3.5% decline.

9 See Page (1998) for an analysis of long run growth trends in the MENA region.

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Table 1Incidence of poverty in developing world using international standards of US$ 1.00 or 2.00 per day, 1987–2000

Region and income per capita, 2000 1987 1990 1996 2000

US$ 1.00 US$ 2.00 US$ 1.00 US$ 2.00 US$ 1.00 US$ 2.00 US$ 1.00 US$ 2.00

East Asia and Pacific (US$ 1030) 26.6 67.0 29.4 68.5 14.9 48.6 14.5 48.3Europe and Central Asia (US$ 2300) 0.2 3.6 1.4 6.8 5.1 19.9 4.2 21.3Latin America and the Caribbean (US$ 4035) 15.3 35.5 11.0 27.6 15.6 27.0 10.8 26.3Middle East and North Africa (US$ 1975) 4.3 30.0 2.1 21.0 2.2 22.2 2.8 24.4South Asia (US$ 450) 44.9 86.3 41.5 86.3 42.3 85.0 31.9 77.7Sub-Saharan Africa (US$ 515) 46.6 76.5 47.4 76.0 48.5 76.9 49.0 76.5World 28.3 61.0 28.3 60.8 24.5 56.1 21.6 53.6

Sources: Adams and Page (2003a), World Bank (2003).


Table 2Growth, distribution, and poverty reduction in developing MENA, 1975–2010

1975–1979 1980–1984 1985–1989 1990–1994 1995–1999 2000–2015 (projected)

Average growth ofincome per capita

3.83 2.68 1.37 1.39 2.23 1.70

Average Ginicoefficient

0.425 0.409 0.394 0.379 0.364 –

Average share ofbottom quintile

7.33 7.71 8.10 8.48 8.87 –

Average growth of percapita income oflowest quintile

3.76 3.31 1.94 1.48 3.65

Poverty headcount atUS$ 1 per day

12.4 10.1 4.3 2.2 2.5 1.2

Poverty headcount atUS$ 2 per day

57.3 44.1 30.0 21.5 23.0 10.2

Sources: Dollar and Kraay (2001), World Bank (2001), World Bank World Development Indicators Database, Author’sCalculations.

In contrast, the 1990s were a lost decade for economic growth and poverty reduction in thedeveloping economies of the MENA region. Real per capita incomes increased on average by lessthan 1.5% per year. Despite this slow growth, the MDG poverty headcount continued to declinemodestly until the mid-1990s when it reached a low of 1.9% of the population, but recent estimatesfor 2000 show an increase in the headcount index to 2.8% (World Bank, 2003). Given the severityof the economic “bust”, however, the fact that the region held the incidence of extreme povertyroughly constant over the decade was a substantial positive achievement.

Trends in income equality reinforced the positive impact of growth on the poor. Middle Easterneconomies entered their rapid growth period with income distributions that were becoming moreegalitarian, reflecting the political ideology, and policies of post-colonial governments. Theseregimes used both redistribution of assets – including agricultural land – and public expenditures– through public employment and consumer subsidies – to promote greater income equality withvarying degrees of success (Richards & Waterbury, 1990). On average for the region, however,the data in Table 2 show a very substantial reduction in income inequality between the mid-1970sand the late 1990s – the Gini coefficient declined by about 15% – driven by a substantial increasein the income share of the poorest quintile which grew by more than 21% over the same period.10

The impact of the slowdown in economic growth after 1985 was thus attenuated to some extentby continuing improvements in income distribution and in the share of income accruing to thepoorest quintile of the population. While the rate of growth of mean income slowed in responseto the slowdown in the overall growth rate, the rising income share of the lowest quintile servedto cushion the shock for those at the bottom of the income spectrum.

2. Growth, inequality, and poverty—is the Middle East exceptional?

Through boom and bust, both growth and progressive distributional change have played impor-tant roles in MENAs poverty dynamics. In particular, continued increases in the share of income

10 This is somewhat unusual in view of the large number of empirical studies suggesting that the Gini coefficient tendsto be quite stable over time (see Deininger & Squire, 1996; Foster & Szekely, 2000; Ravallion & Chen, 1997).


Fig. 1. (a) Gini coefficient by regions; (b) share of bottom 20%. Notes: EAP, East Asia and Pacific; ECA, Europe andCentral Asia; LAC, Latin America and Caribbean; SA, South Asia; SSA, Sub-Saharan Africa; MENA, Middle East andNorth Africa.

accruing to the lowest quintile of the distribution meant that the average income of the poor wasrising more rapidly than average income in the region as a whole (Table 2). This section exam-ines MENAs patterns of growth, change in inequality, and poverty reduction compared to otherdeveloping regions.

2.1. International trends in income distribution

Fig. 1(a) shows trends in average Gini coefficients for low and middle income countries insix regions for the period 1970–1999.11 These data, like other international comparisons, arefraught with comparability problems, but they do provide a broad comparison of changes inincome inequality over time.12 Two aspects of the dynamics of inequality are striking. First,although the MENA region began in 1970 with one of the higher average rates of income inequal-

11 The regional averages are calculated from the data of Dollar and Kraay (2001).12 The comparability problems are particularly acute for the period before 1985 when relatively few observations are

available in each region.


Fig. 2. Evolution of per capita income and income of the lowest quintile: developing countries.

ity in the world (Gini = 0.440), since that time it has recorded the largest improvement in incomedistribution. In fact, MENA is only one of two regions – Africa being the other – to show improve-ments in income inequality over the 30-year period. Second, because of these improvements, theMENA region now has one of the most equal income distributions in the developing world(Gini = 0.360).

Fig. 1(b) shows the regional pattern of change in the income share accruing to the bottomquintile for the period 1980–1999. In general, the regional changes reflect those observed in theGini coefficient, with MENA, Latin America, and Sub-Saharan Africa showing an increase inthe quintile share, and East Asia and Europe and Central Asia a deterioration. MENA shows themost sustained increase in the quintile share. At the midpoint of the period in 1990, the averageincome share going to the bottom quintile in MENA was equal to about 8%, which was roughlythe same as that for OECD countries (Gini = 0.310) and Eastern Europe and Central Asia. By theend of the period, MENAs quintile share had exceeded that for all other regions.

2.2. Regional patterns of growth and poverty reduction

The last three decades of the twentieth century witnessed quite different patterns of growthamong regional groupings of low and middle income countries. Fig. 2 plots the evolution of percapita income and per capita income of the lowest quintile for all developing countries in theDollar and Kraay (2001) sample over the period 1970–2000 (1970 = 100).13 Between 1970 and1990, the average income of the poorest 20% of the population in developing countries as a groupgrew at a similar pace to per capita income. The early 1990s, however, saw a fall in the averageincome levels of the poor (about 2% per year on average), while the second half of the 1990s wascharacterized by stagnation in the incomes of the lowest quintile in developing countries, despiterenewed average income growth.

Figs. 3–5 show the evolution of the income indices for the Middle East and North Africa,and for two comparators East Asia and the Pacific and Latin American and the Caribbean. Thepattern for MENA in Fig. 3 clearly shows both the impact of the boom on poverty reduction andthe cushioning effect of the rising income share of the poor on their incomes. Between 1975 and1985, the average income of the bottom quintile tracked average income growth and both rose

13 The indices in Figs. 2–5 were constructed on the basis of the median growth rate of the group in for each 5-year periodbetween 1970 and 2000.


Fig. 3. Evolution of per capita income and income of the lowest quintile: Middle East and North Africa.

Fig. 4. Evolution of per capita income and income of the lowest quintile: Latin America and the Caribbean.

substantially. After 1985, however, average per capita income was virtually stagnant, while theincome of the lowest quintile continued to rise. Over the 15-year period the income of the poorestquintile increased by nearly 40%.

In Latin America and the Caribbean (Fig. 4), the early 1980s were characterized by modestgrowth rates, but significant progressive distributional changes. The late 1980s, in contrast, sawa reversal in the income growth of the lowest quintile compared to the average income trend.

Fig. 5. Evolution of per capita income and income of the lowest quintile: East Asia and Pacific.


The 1990s present basically a repetition of the 1980s although the swings were somewhat lessdramatic. The early 1990s featured progressive distributional changes, while the late 1990s showeda reversal. East Asia (Fig. 5) is the mirror image of the pattern for MENA. Average incomes andthose of the poor rose in tandem through the 1980s. In the 1990s, there was a growing divergencebetween average income growth and that of the lowest quintile, reflecting a regressive change inthe income distribution.

Poverty headcount data – which are available only from the mid-1980s – however, indicatethat poverty has fallen in East Asia more than in the other two regions.14 This outcome illustratesthe powerful impact of very rapid growth on poverty reduction. While in East Asia the income ofthe lowest quintile increased in the late 1990s to 300% of the 1970 level, the income of the lowestquintile in the Middle East increased only to about 175% and in Latin America to about 125%.Thus, despite the deterioration in income distribution after 1990, growth in East Asia yielded thelargest income gains to the poor.

2.3. Growth, distribution, and poverty reduction: an empirical test

The patterns of growth of income presented above suggest that the experience of the MiddleEast and North Africa during the 1990s of “pro poor stagnation” was atypical of other developingregions. This section uses econometric estimates of the relationship between growth, inequality,and poverty reduction to test whether MENAs poverty dynamics between 1985 and 1999 arethe result of different structural relationships between income growth, inequality, and the povertyheadcount. It uses a new database due to Adams (2003), consisting of 101 observations on poverty,inequality, and the share of income accruing to the bottom quintile for 52 countries between 1985and 1999. The data also contain the computed mean income that would accrue to the lowestquintile of the population for each observation. The data are geographically representative andcontain 11 observations on 7 MENA economies.

Three specifications relating changes in poverty to growth and changes in inequality are pre-sented in Table 3. Eq. (1) shows the result of regressing changes in poverty on growth in theincome level of the lowest quintile of the population, which in turn depends on the evolutionof average income and of the share of average income of the lowest quintile. Econometricallythis model imposes the restriction that changes in inequality (as given by changes in the share ofincome of the lowest quintile of the population) and changes in average income have the sameimpact on poverty.

Eqs. (2) and (3) report the results of two frequently used specifications that include changesin inequality independently of growth of income.15 These equations do not restrict the impactof inequality to have any particular value (other than being constant across time periods). Twoalternative measures of inequality are considered. Eq. (2) uses changes in the (log) Gini. Eq. (3)uses changes in the log of the income share of the lowest quintile of the population. Eq. (3) is anunrestricted version of (1).

Table 3 reports the results of estimating these models for two different sub-samples, reflectingdiffering approaches to the use of the household survey and income data.16 The first sub-sampleconsiders all the spells – intervals between household surveys – in the database; this is the

14 See Ravallion (2001).15 See, for example, Ravallion (2001) and Adams (2003).16 In most of the empirical work on the income elasticity of poverty, individual observations are defined as spells—the

interval between two household surveys. Because surveys are undertaken at irregular intervals across countries this

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Table 3Poverty elasticity of growth and distribution

Dependent variable: change in log(headcount)

All spells Long spells

Eq. 1 Eq. 2 Eq. 3 Eq. 1 Eq. 2 Eq. 3

Change in log(y20) −3.96 (−6.33) −2.76 (−4.52)Change in log(y) −5.24 (−6.13) −5.33 (−6.08) −5.31 (−4.80) −5.82 (−5.18)Change in log(Gini) 5.80 (3.57) 4.16 (2.70)Change in log(share) −2.45 (−2.66) −1.28 (−1.74)MENA 0.08 (0.23) 0.16 (0.48) 0.04 (0.12) −0.14 (−0.51) −0.02 (−0.08) 0.09 (−0.46)Constant 0.05 (0.51) −0.014 (−0.16) 0.03 (0.36) 0.17 (1.87) 0.07 (0.81) 0.09 (1.03)Number of observations 101 101 101 52 52 52R-square 0.2902 0.3589 0.3239 0.3039 0.4672 0.4228Adjusted R-square 0.2757 0.3391 0.3030 0.2755 0.4399 0.3868F 20.03 18.10 15.49 10.70 14.03 11.72

Change in log(y20) −3.9 (−6.23) −2.71 (−4.43)Change in log(y) −5.21 (−6.04) −5.32 (−6.03) −5.32 (−4.62) −5.87 (−5.10)Change in log(Gini) 5.58 (3.35) 3.92 (2.41)Change in log(share) −2.33 (−2.51) −1.17 (−1.57)MENA 0.19 (0.53) 0.24 (0.66) 0.17 (0.47) 0.003 (0.01) 0.12 (0.40) 0.06 (0.22)MENA × y20 −9.56 (−1.19) −8.15 (−1.04)MENA × y −9.11 (−0.88) −9.53 (−0.89) −6.94 (−0.83) −6.49 (−0.73)MENA × Gini 9.10 (0.99) 8.05 (0.99)MENA × share −10.65 (−1.28) −9.20 (−1.23)Constant 0.05 (0.52) −0.01 (−0.13) 0.03 (0.37) 0.17 (1.88) 0.07 (0.83) 0.09 (1.01)Number of observations 101 101 101 52 52 52R-square 0.3004 0.367 0.336 0.3192 0.4791 0.4415Adjusted R-square 0.2788 0.3337 0.3010 0.2766 0.4224 0.3807F 13.89 11.02 9.61 7.50 8.46 7.27

Note: t-Values in parenthesis. Variables significant at more than the 0.05 level in bold.


approach used in much of the literature on poverty and growth. The second sub-sample takesa longer term perspective and only considers one spell per country spanning all periods betweenthe first and the last available survey. This transformation reduces the number of observationsto 52.

All coefficient estimates on the independent variables in Table 2 are of expected sign andare significant at conventional levels.17 Comparison of the corrected R2 between sub-samplessuggests that the length of growth–poverty spells is in fact relevant for evaluating the povertyreducing impact of growth and distributional change. The percentage of the variance explainedby Eqs. (2) and (3) increases moving from short growth–poverty spells to longer ones.18

Table 3 also reports the results of tests for structural differences in the econometric specifica-tions associated with the MENA economies. The first test consists of the introduction of a MENAspecific dummy variable in each specification. The second set of tests interacts the MENA dummyvariable with observations on the independent variables to test for significant differences in thecoefficient estimates.

The results of these tests are uniformly negative. The shift variable is not statistically differentfrom zero in any of the specifications. The interaction variables are of anticipated sign – suggestingthat the elasticity of poverty with respect to both income and inequality tends to be larger in MENAthan for the sample as a whole – but are not significant. These results hold for both sub-samples.Thus, the data indicate that the relationship between growth, inequality, and poverty reduction inMENA since 1985 is statistically similar to that for developing countries as a whole.

3. Holding the line—the role of migration and public employment

The cross country patterns of growth and poverty reduction presented above show that theeconomies of the Middle East and North Africa have been unusually successful in reducingpoverty and maintaining it at low levels despite a long period of economic stagnation. Yet, testsfor structural differences in the relationship between growth, inequality, and poverty indicatethat MENA is not exceptional. The elasticities of both income growth and changes in incomedistribution on poverty are statistically the same in MENA as in other developing countries.

Rather, it was the rapid rise in the share of income accruing to the bottom quintile of thedistribution that set MENA apart from other low and middle income regions, especially between1985 and 1999. This progressive distributional shift, when combined with even modest incomegrowth, was the engine behind MENAs unusual pattern of “pro-poor stagnation”. What are themechanisms by which this rising share of income accruing to the poor has been accomplished?In an earlier paper, Richard Adams and I argued that remittances deriving from internationalmigration and government employment have been the primary means of protecting the incomesof the poor in MENA (Adams & Page, 2003a).

Since the mid-1970s international migration has had a large impact on the MENA region. Asoil prices increased in the late 1970s, and the economies of the oil exporters boomed, people from

approach results in both an unbalanced panel of data in which some countries have multiple observations while othershave only a single spell and a relatively short-term focus, since the interval between household surveys in the majority ofcountries is often less than 5 years.17 Although the coefficient of the log share variable in Eq. (3) is only significant at the .10 level.18 This result does not hold for the first specification. However, in line with the results reported by Cord, Lopez, and

Page (2003), the income of the lowest quintile of the population performs well in tracking changes in absolute poverty,for both types of spells.


the Maghreb began seeking high-paying jobs in a variety of fields in Iraq, Kuwait, and SaudiArabia. At the same time, poor people from Algeria, Morocco, and Tunisia began seeking labor-intensive jobs in Western Europe. Although no comprehensive figures have ever been collectedon the number of migrants involved, the amount of money sent home by migrants from thesecountries was substantial.

Table 4 summarizes a new data set on international migration and remittances.19 It gives meanvalues for the relevant poverty, migration, and remittance variables in each of the six regions ofthe developing world – East Asia, Europe and Central Asia, Latin America and the Caribbean,Middle East and North Africa, South Asia and Sub-Saharan Africa – for the period 1985–1999.Mean values for the migration variable (migration as share of country population) are highestin two regions: Latin America and the Caribbean, and the Middle East and North Africa. Thisis particularly notable, given that the migration variable is estimated from partner country dataand the labor importing economies of the Gulf do not report such statistics. The mean values forthe remittance variable (official remittances as share of country GDP) are highest in the MiddleEast and North Africa, and South Asia. Again, substantial underreporting is likely, since the datareflect only officially recorded remittances flowing through the financial system and exclude allinformal and unofficial transfers.

Table 5 presents the distribution of remittances across quintile groups of countries ordered bytheir per capita incomes. The distribution for the whole sample and the distribution for MENAboth appear in the table. The contrast between the two is striking. For developing countries, as awhole the bulk of remittance income – more than 67.5% of the total – accrues to countries in thethird quintile of the global income distribution. The second and third quintiles together accountfor nearly 87% of official remittances received by all developing countries. Not surprisingly,world-wide migrants remit primarily to poor, but not the poorest countries.

The pattern for the developing MENA countries in the sample is markedly different. In MENAremittances accrue primarily to the richer countries; the share in remittances of the two highestquintiles combined exceeds 60% of total regional remittance income. But, while the largest shareof total regional remittances – 44.6% – accrues to countries in the top quintile of the regionalincome distribution, the second largest share – about 19.3% – accrues to the poorest countries inthe region.

These differences are likely due both to problems with the data and to differences in the patternsof migration in MENA in contrast to the rest of the developing world. Because the data reflect onlyofficial remittances, the large flows of unofficial remittances are not reflected in the distributions.20

There is no known evidence to suggest what the bias in the incidence of unofficial remittancesmay be, either world-wide or in MENA, but some of the observed difference in the distributionsmust reflect this omission. However, the structure of migration in MENA also differs from that inmuch of the rest of the developing world. In contrast to the prevailing pattern of migration fromdeveloping countries, there is a bimodal distribution of migrants from the Mashreq to the countriesof the Arab Gulf, consisting at one end of professional, managerial, and technical workers andat the other of unskilled laborers. Several higher income countries in MENA, notably Jordanand Lebanon, have traditionally produced large numbers of skilled migrants. These individualscommand substantial income premia in the Gulf and may also remit largely through officialchannels, thus contributing the observed pattern for the region.

19 For the definition of variables and sources see Adams and Page (2003b).20 One estimate of the possible volume of unrecorded remittances places it at US$ 10 billion per annum, El-Qorchi,

Maimbo, and Wilson (2002).

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Table 4Regional summary of mean values for poverty, inequality, migration, and remittances, 1985–1999

Region Poverty headcount (US$1 per person per day)

Gini coefficient Migration as share ofcountry population

Official remittances as share ofGDP (constant 1995 dollars)

Public employment asshare of total

East Asia 15.46 0.401 0.72 0.34 5.18Eastern Europe and Central Asia 2.49 0.306 0.54 0.09 15.21Latin America and the Caribbean 15.01 0.509 3.62 1.29 6.68Middle East and North Africa 2.51 0.382 1.91 9.60 12.07South Asia 34.67 0.324 0.50 2.59 7.77Sub-Saharan Africa 40.87 0.464 0.03 0.63 3.69Total 18.87 0.414 1.43 1.55 8.94

Note: All figures are mean values calculated from data in Adams and Page (2003a, 2003b).


Table 5Distribution of total official remittance income by income quintile of countries

Quintile Share of remittances

All developing countries1 7.972 19.373 67.524 2.085 3.06

Total 100

Middle East and North Africa1 19.292 13.783 5.904 16.465 44.57

Total 100

Source: Calculated from data in Adams and Page (2003a, 2003b).

A second factor explaining the low level of poverty in the MENA region may be governmentemployment. Since the early 1970s a number of MENA countries – for example, Egypt, Jordan,and Morocco – have used public sector employment (including government work) as a policyinstrument for providing income to an increasing proportion of the labor force. For example, thepublic sector currently employs about 33% and 38% of the total employed labor force in Egypt andJordan, respectively (Adams & Page, 2003a) These percentage figures are high by internationalstandards, and have led to substantial surplus labor throughout the public sector.

Table 4 also presents information on the share of the formal sector labor force engaged inpublic employment. Those classified as public employees consist of both employees in the publicadministration and (where available) estimates of employees of public and parastatal enterprises.Surprisingly, the data on public employment are even less complete than those on remittances,and the data set is limited to observations on 34 countries, including 6 in MENA. The transitioneconomies of Europe and Central Asia and the MENA economies have the highest shares ofpublic employment among developing regions. For the six MENA countries represented in thesample the average share of public employment exceeds 12%.

Virtually, all countries in the region also subsidized a range of consumer goods from basicfood stuffs to water and energy, beginning in the 1940s and continuing throughout the rest of thecentury (Page & Van Gelder, 2002). While these subsidies came under increasing fiscal pressureduring the 1990s and were reduced, they remained an important element of the social safety netunderpinning MENA households.

Consumer subsidies were (and continue to be) one reason why the poverty headcount at US$1.00 per day remained low during the period of economic stagnation. But while the programswere undoubtedly of value in reducing absolute poverty, their incidence has not been carefullydocumented, and partial evidence for Egypt, Jordan, Morocco, and Tunisia suggests that a numberof the most important commodity based programs benefited the upper quintiles of the incomedistribution disproportionately (Page & Van Gelder, 2002). If that is more broadly the case forthe region as a whole, consumer subsidies can help explain the dynamics of the head count indexbut not of the bottom quintile share.


3.1. Remittances, public employment, and poverty reduction: econometric results

This section combines the data on remittances and government employment described above,with the poverty and distribution data, to analyze the relationship between these two variables andpoverty in MENA.21 The econometric work seeks to explain the behavior of both the share andthe mean income of the lowest quintile of the distribution, the elements that drive the distinctivepoverty dynamics in MENA described above. The relationship to be estimated can be described by:

log S = α + β1 log μ + β2(x) + ε (1)

where S is the mean income of the bottom quintile (or the quintile income share), β1 the“elasticity of poverty” with respect to mean income per capita given by μ, β2 the coefficient ofthe income share variable with respect to variable x (remittances or government employment)and ε is an error term that includes errors in the poverty measure.

OLS estimates of Eq. (1) are presented in Table 6. The table first presents the results using thebasic specification (Eqs. 6(1) and 6(2)). It then presents tests for variations from the cross countryresults specific to the MENA region (Eqs. 6(3)–6(6)). Eq. 6(1) shows the relationship betweenper capita income, the share of remittances in national income, and the share of income accruingto the lowest quintile of the income distribution. Interestingly, the coefficient estimate for theelasticity of the quintile share with respect to per capita income is significant and negative. Thisimplies that in the data available for all developing countries there is a tendency for the incomeshare of the poorest to decline with rising incomes.22

Eq. 6(2) replaces the share of income accruing to the lowest quintile as the dependent variablewith the mean income of the lowest quintile. In this case, the coefficient on per capita incomeis positive and significant. This is not surprising. If the distribution remained unchanged acrosscountries as incomes rose, the predicted value of the coefficient would be one. The regressivechanges in distribution with rising income per person observed in the data offsets the income gainto the bottom quintile exactly to the extent of the estimated coefficient in Eq. 6(1). For the sampleas a whole, growth is good for the poor, but not as good as for the non-poor.

The coefficient on the share of remittances in national income is positive and significant (atthe 0.05 level) in both specifications. This result can be interpreted to indicate that remittanceshave an equalizing impact on income distribution and, controlling for the level of mean income,raise the incomes of those in the lowest quintile. The magnitude of the impact is small. At themean of the sample, controlling for the (significant) regressive impact of rising income per capitaon the share of income accruing to the poor, an increase of one percentage point in the share ofremittances in national income will result in an in increase in the share of income accruing to thelowest quintile of only 0.12%. But, remittances, also have a direct impact on the income of thelowest quintile through their contribution to per capita income. For the mean of the sample, thetotal impact of remittances is to raise the average income of the poor by 1.24%.

Eqs. 6(3)–6(6) report on the results of tests of the hypothesis that the structural relationshipbetween remittances and the income of the poor differs in MENA from the sample as a whole.When an intercept dummy is introduced into Eqs. 6(3) and 6(4) for the MENA observations it is

21 Comparable cross country data on consumer subsidies are not available. Thus, it is not possible to test econometricallyfor their impact on the poverty variables of interest.22 An attempt to test for a quadratic relationship between the income share variable and the level of income did not

produce statistically significant results.


Table 6Impact of the remittances on incomes of the poor

Variables Eq. 6(1) Eq. 6(2)

Dependent variable: log(share ofthe bottom 20%)

Dependent variable: log(meanincome of the bottom 20%)

Coefficient t-ratio Coefficient t-ratio

log(mean income) −0.28 −3.74 0.72 9.76Remittance 0.08 1.98 0.02 1.98Constant 2.95 9.01 −0.04 −0.13No. of observations 82 82R-square 0.1590 0.6024Adjusted R-square 0.1377 0.5924F 7.47 59.85





log(mean income) −0.27 −3.50 0.71 9.59Remittances 0.00 0.24 0.00 0.31MENA 0.35 2.35 0.34 2.31Constant 2.91 8.57 0.04 0.12No. of observations 82 82R-square 0.1595 0.6323Adjusted R-square 0.1271 0.6188F 4.93 47





log(mean income) −0.24 −3.21 0.74 10.03Remittances −0.01 −0.65 −0.01 −0.56MENA × remittance 0.04 1.82 0.04 1.76Constant 2.85 8.32 −0.02 −0.07No. of observations 82 82R-square 0.1364 0.6226Adjusted R-square 0.1032 0.6088F 4.11 45.09

positive and highly significant, and the coefficient of the remittance variable becomes insignificant.This means that, controlling for the level of income (and the impact of remittances), both theshare of income of the lowest quintile and the average income of the poor in the MENA regionare significantly above the level that would be predicted from the cross country relationship.However, the really interesting results in Table 6 relate to the interactive dummy variable forthe MENA region. The interactive variable (MENA dummy times remittances) is positive andstatistically significant at the 0.10 level, while the coefficient on the remittance variable is no longersignificant.


Table 7Impact of government employment on incomes of the poor





log(mean income) 0.02 0.19 1.02 8.04Government employment 0.03 1.78 0.03 1.78Constant 1.46 2.69 −1.53 −2.83No. of observations 34 34R-square 0.1456Adjusted R-square 0.0905 0.7878F 2.64 62.25





log(mean income x) 0.02 0.18 1.02 7.96Government employment 0.02 1.63 0.02 1.63MENA 0.10 0.49 0.10 0.49Constant 1.46 2.66 −1.54 −2.80No. of observations 34 34R-square 0.1523 0.8022Adjusted R-square 0.0675 0.7824F 1.80 40.56





log(mean income y) 0.01 0.09 1.02 7.80Government employment 0.03 1.85 0.03 1.85MENA × Govt emp. −0.01 −0.63 −0.01 −0.63Constant 1.50 2.71 −1.50 −2.72No. of observations 34 34R-square 0.1566 0.8032Adjusted R-square 0.0723 0.7835F 1.86 40.82

Taken together, these results suggest that the overall relationship between remittances and theincomes of the poor observed in the cross country data are primarily driven by the MENA region.The magnitude of the coefficient on remittances in MENA while larger than for the sampleas a whole remains small. The total impact of remittances on the incomes of the poor for theaverage MENA economy, however, is substantial. At the sample mean, the combined income anddistributional effect of remittances is to raise the average income of the lowest quintile in MENAby 9.17%.


Results of estimating Eq. (1) using government employment data are shown in Table 7. Asnoted, the sample size is severely restricted and less geographically representative than for theremittance data; only six MENA countries are included. For the full sample, the governmentemployment variable – expressed as a share of total employment – is positive and significantat the 0.10 level. This means that, controlling for the level of income, increases in the share ofgovernment employment increase the share of income accruing to the lowest income quintile.

Tests for structural differences between MENA and the whole sample are uniformly negative.Neither the coefficients of the intercept dummy nor the interactive dummy variable are signifi-cant. These results support the conclusion that in contrast to the results for remittances, MENAeconomies exhibit the same structural relationship between government employment and theincomes of the poor as developing countries in general. This does not imply that governmentemployment was unimportant for the poor in MENA, simply that the impact was of the samemagnitude as in other countries.

4. Conclusions

This paper has used a newly constructed cross country data set on growth, inequality, andpoverty to review and analyze trends in poverty reduction in developing Middle Eastern andNorth African countries. Six major findings emerge from the analysis.

First, compared to other developing areas, the Middle East has been unusual both for its lowincidence of poverty and for its ability to hold the line with respect to poverty reduction despitea boom and bust cycle of economic growth. As defined by the MDG goal of US$ 1.00 per day,there were very substantial reductions in poverty in MENA between 1970 and 1985, followed byrelative stability in the overall rate of extreme poverty from 1985 to 1999. The only other region ofthe developing world to achieve lower poverty headcounts than MENA – the countries of EasternEurope and Central Asia – experienced a sharp rise in poverty during the 1990s as a result of theireconomic transitions.

Second, during the 1980s and 1990s, the Middle East became one of the most equal regionsin the developing world in terms of income distribution. This progressive change in incomedistribution was driven in large measure by an increasing share of income going to the poorestquintile of the population.

Third, the Middle East and North Africa are not exceptional in terms of the sources of theirpoverty dynamics. They share with other developing economies similar elasticities of povertyreduction with respect to income growth and distribution. Because these elasticities are relativelyhigh, rapid GDP growth – combined with progressive distributional change – during the oil boomwas translated into rising incomes of the poor, as measured by the average income of the lowestincome quintile, and falling poverty headcounts. Between 1970 and 1985, the incomes of the poortracked mean income growth at a rate slightly exceeding one for one.

Fourth, during the slow growth period, continued progressive income redistribution resulted ina rising share of income accruing to the poorest quintile and to a growing divergence in averageincome growth between the poor and non-poor. This “pro-poor” bias to income growth cushionedthe impact of stagnant or declining per capita incomes on the poor during the last 15 years of thetwentieth century.

Fifth, an important source of the increase in the average income accruing to the poorest quintileof the population in MENA was international migration and remittances. Remittances had botha direct income effect, raising per capita incomes in the labor exporting countries of the region,and an indirect effect of increasing the share of income accruing to the poor.


Finally, while evidence on government employment is less conclusive, it suggests that thepublic sector may also have played a role in poverty reduction by acting as employer of last resortfor poor households, raising the share of income accruing to the lowest quintile.

The significant question not answered by these results is whether MENA can continue to fightpoverty successfully in the absence of accelerated growth. A number of factors suggest that itcannot. Because poverty in MENA responds to income growth and distribution in the same wayas in other countries, the incomes of the poor will only continue to rise in the face of stagnant percapita income growth if the share of income accruing to the poor continues to rise. But the drivingforces behind MENAs distributional dynamics – migration and public employment – may berunning out of steam. Migration, while still an important vehicle to raise the incomes of the pooris facing rising barriers and increasing competition from other labor exporting countries in bothof the region’s major labor importing destinations, the Arab Gulf, and the European Community.And, MENA governments facing fiscal constraints and pressures to privatize will increasinglyfind it difficult to provide public employment.23

The good news, however, is that given the relatively equal income distributions found in theregion, the poverty reduction payoff to even modest increases in growth will be substantial. Thechallenge for policy makers is therefore to find ways to accelerate growth while preserving to themaximum extent possible the distributional gains won by the poor in the last 30 years.

Acknowledgements

The author is indebted to Hyun Hwa Son for excellent research assistance and to RichardAdams for helpful discussions. The views and empirical findings presented in this paper are thoseof the author. They do not represent the views of the World Bank, its Executive Directors or thecountries they represent.

References

Adams, R. (2003). Economic Growth, Inequality and Poverty: Findings from a New Data Set Policy. Research WorkingPaper, 2972. Washington, DC: World Bank.

Adams, R., & Page, J. (2003a). Poverty, Inequality and Growth in Selected Middle East and North Africa Countries,1980–2000. World Development, 31, 2027–2048.

Adams, R., & Page, J. (2003b). International migration, remittances and poverty in developing countries. Washington,DC: World Bank.

Bourgignon, F. (2001). The growth elasticity of poverty reduction; explaining heterogeneity across countries and timeperiods. Paris: Delta, Mimeo.

Cord, L., Lopez, J. H., & Page, J. (2003). ‘When I use a word’—pro poor growth and poverty reduction. In M. Krakowski(Ed.), Attacking poverty: What makes growth pro-poor? Baden-Baden: Nomos Verlagellschatr.

Deininger, K., & Squire, L. (1996). A new data set measuring income inequality. The World Bank Economic Review, 10,565–591.

Dollar, D., & Kraay, A. (2001). Growth is good for the poor. Washington, DC: World Bank.Dollar, D., & Kraay, A. (2002). Growth is good for the poor. Journal of Economic Growth, 7, 195–225.El-Qorchi, M., Maimbo, S., & Wilson, J. (2002). The Hawala informal funds transfer system: An economic and regulatory

analysis. Washington, DC: International Monetary Fund.

23 In another contribution to this volume, Esfahani and Squire (2004) find evidence of increasing trade protection inMENA, beginning in the second half of the 1990s. They attribute this to an increase in the relative political power ofproducer interests. Given the size of the public industrial sector in MENA economies, this is also constant with an effortto maintain public employment in the face of increasing fiscal constraints.


Esfahani, H., & Squire, L. (2004). Explaining trade policy in the Middle East and North Africa.Foster, J., & Szekely, M. (2000). How good is growth? Asian Development Review, 18, 59–73.Page, J. (1998). From boom to bust and back? The crisis of growth in the Middle East and North Africa. In N. Shafik

(Ed.), Prospects for Middle Eastern and North African economies. London: MacMillan.Page, J., & Van Gelder, L. (2002). Globalization, growth and poverty reduction in the Middle East and North Africa,

1970–1999. Paper presented at the Fourth Mediterranean Development Forum: Amman, Jordan.Ravallion, M. (2001). Growth, inequality and poverty: Looking beyond averages. World Development, 29, 1803–1815.Ravallion, M., & Chen, S. (1997). What can new survey data tell us about recent changes in distribution and poverty? The

World Bank Economic Review, 11, 357–382.Ravallion, M., & Datt, G. (1991). Growth and redistribution components of changes in poverty measures: A decomposition

with applications to Brazil And India. Journal of Development Economics, 38, 273–295.Richards, A., & Waterbury, J. (1990). A political economy of the Middle East. Boulder, CO: Westview Press.World Bank. (2001). World development report 2000/2001: Attacking poverty. New York: Oxford University Press.World Bank. (2003). Global economic prospects and the developing countries. Washington, DC: World Bank.

boom, bust, and the poor: poverty dynamics in the middle east and north africa, 1970–1999

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