metadata: authors: 0: author: Agenor,Pierre-Richard
docna: 0: docna: Does globalization hurt the poor?
docty: Policy Research Working Paper
subtopic: Educational Sciences,International Trade and Trade Rules,Inflation,Inequality
teratopic: Poverty Reduction
abstracts: cdata!: Ag�or attempts to examine analytically
            and empirically the extent to which globalization affects
            the poor in low- and middle-income countries. He begins with
            a description of various channels through which trade
            openness and financial integration may have an adverse
            effect on poverty. However, the author also stresses the
            possible nonlinearities involved-possibilities that have
            seldom been recognized in the ongoing debate. Ag�or then
            presents cross-country regressions that relate measures of
            real and financial integration to poverty. The regressions
            control for changes in income per capita and output growth
            rates, as well as various other macroeconomic and structural
            variables, such as the inflation tax, changes in the real
            exchange rate and the terms of trade, health and schooling
            indicators, and macroeconomic volatility. The author uses
            not only individual indicators of trade and financial
            openness but also a "globalization index" based on
            principal components analysis, and tests for both linear and
            nonlinear effects. The results suggest the existence of a
            nonmonotonic, Laffer-type relationship between globalization
            and poverty. At low levels, globalization appears to hurt
            the poor; but beyond a certain threshold, it seems to reduce
            poverty-possibly because it brings with it renewed impetus
            for reform. So, globalization may hurt the poor not because
            it went too far, but rather because it did not go far enough.
repnme: repnme: Does globalization hurt the poor?
display_title: Does globalization hurt the poor
listing_relative_url: /research/2002/10/2054539/globalization-hurt-poor
topicv3: Education, Skills Development and Labor
            Market m1326135 1484,Poverty m1326687 695,Inflation m1326709 0870F4727ACED1CF8525815C00471347,Trade m1326924 698,Education m1327048 470
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Poverty Reduction
origu: WBIEP
no_of_pages: 64
author_keys: 0: author_key: 177753
model_extractions: I POLICY RESEARCH WORKING PAPER 2922

# Abstract

Agenor attempts to examine analytically and empirically the extent to which globalization affects the poor in lowand middle-income countries. He begins with a description of various channels through which trade openness and financial integration may have an adverse effect on poverty. However, the author also stresses the possible nonlinearities involved-possibilities that have seldom been recognized in the ongoing debate. Agenor then presents cross-country regressions that relate measures of real and financial integration to poverty. The regressions control for changes in income per capita and output growth rates, as well as various other macroeconomic and structural variables, such as the inflation tax, changes in the real exchange rate and the terms of trade, health and schooling indicators, and macroeconomic volatility. The author uses not only individual indicators of trade and financial openness but also a "globalization index" based on principal components analysis, and tests for both linear and nonlinear effects.

The results suggest the existence of a nonmonotonic, Laffer-type relationship between globalization and poverty. At low levels, globalization appears to hurt the poor; but beyond a certain threshold, it seems to reduce poverty-possibly because it brings with it renewed impetus for reform. So, globalization may hurt the poor not because it went too far, but rather because it did not go far enough.

This paper-a product of the Poverty Reduction and Economic Management<sup>Division,WorldBank Institute-ispart of</sup> a larger effort in the institute to study the impact of globalization on the poor<sup>in developing countries.Copies of the paper</sup> are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Maria<sup>Gosiengfiao,</sup> roomJ4-282, telephone 202-473-3363, fax 202-676-9810, email address mgosiengfiao@worldbank.org.<sup>Policy Research</sup> Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted<sup>at</sup> pagenor@worldbank.org. October 2002. (56 pages) _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage_<sup>_the exchange of ideas about_</sup> _development issues. An obiective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of_<sup>_theWorld Bank,its Executive Directors, or the_</sup> _countries they represent._ Produced by the Research Advisory Staff
# Does Globalization Hurt the Poor?

**Pierre-Richard Agenor*** The World Bank Washington DC 20433

***1** am grateful to Joshua Aizenman, Ramon<sup>Moreno,andMarkTaylor forhelpful discussions and</sup> comments on a preliminary draft, and<sup>toNihalBayraktarforexcellentresearchassistance.</sup>
# Table of Contents

- I. Introduction

- II. How Globalization may hurt the Poor

1. Trade Openness

2. Financial Integration 3. Nonlinearities

- Ill. Methodology

- Ill. Preliminary Empirical Evidence

- IV. A Poverty-Globalization Laffer Curve?

- V. Concluding Remarks

Appendix A: Country Names, Variable Definitions and Data Sources Appendix B: Calculation of Principal Components References Tables 1 to 5 Figure 1. The Poverty-Globalization Laffer Curve 2
# 1. INTRODUCTION

Globalization-defined as<sup>theprocess through whichgoodsandservices,</sup> capital, people, information<sup>andideas flowacrossborders andlead togreater</sup> integration of economies<sup>andsocieties-has madesubstantial advancesin recent</sup> decades and is viewed by<sup>manyasaninescapable featureof theworldtoday.</sup> There are, undoubtedly,<sup>significantpotentialbenefits toglobalization.For</sup> instance, it is now well recognized<sup>that opennessto foreigndirect investmentcan</sup> contribute to growth by stimulating<sup>domestic investment, improvingefficiency and</sup> productivity (as a result of greater<sup>access tonew technologies),orbyincreasing</sup> the "knowledge" applied<sup>toproduction. Oppnnesstocapitalflowsmayalso</sup> increase opportunities for<sup>portfoliorisk diversificationandconsumptionsmoothing</sup> through borrowing and lending;<sup>andproducerswhoare abletodiversifyriskson</sup> world capital markets may<sup>invest inmorerisky (andhigher-yield) projects,thereby</sup> raising the country's rate of<sup>economic growth(Obsffeld(1994)).Increasedaccess</sup> to the domestic financial system<sup>by foreignbanksmay raisetheefficiency of the</sup> intermediation process between<sup>saversandborrowers,therebyloweringmarkup</sup> rates in banking, as well<sup>asthecostofinvestment,andraisinggrowthrates</sup> (Baldwin and Forslid (2000)).<sup>Moredirectly,totheextent thatfinancialopenness</sup> helps to mitigate asymmetric<sup>information problems andtoreduce thefixedcosts</sup> associated with small-scale<sup>lending,itcanimprovethe opportunitiesfor thepoor</sup> to access the formal financial<sup>system.'</sup> Similarly, openness to trade<sup>maygeneratesignificant gains,bothstatic and</sup> dynamic. Satic economic<sup>gains, asemphasizedbyconventionaltradetheory,</sup>

> 1As discussed by Eichengreen (2001), however, although there is evidence suggesting that financial openness and financial<sup>developmentmayraisegrowth-asin Bekaert,Harveyand</sup> Lundblad (2002), Bosworth<sup>andCollins(2000),Jalilian andKirkpatrick(2002),andLevine(2000)-</sup> there is some debate as to<sup>the exactmagnitudeof theseeffects.KleinandOlivei(2001),for</sup> instance, analyzed the effects<sup>of capitalaccountliberalizationon growthand financialdepthfora</sup> cross-section of countries over<sup>theperiod1986-95.They found that countrieswithopencapital</sup> accounts experienced a<sup>larger increasein financial depththancountrieswithclosedcapital</sup> accounts, and through that<sup>channel, higherratesof economicgrowth. However,this positive effect</sup>

3
> refer to the fact that under greater openness to trade, productive resources tend to be reallocated toward activities where they are used with comparatively greater efficiency and away from less efficient activities (such as import-substitution

> industries or rent-seeking activities). In addition, the literature on endogenous

> growth has emphasized the existence of various mechanisms through which trade openness may generate dynamic gains and thereby affect the economy's rate of growth in the long run. In particular, it has been argued that trade openness may facilitate the acquisition of new inputs, less expensive or higher-quality intermediate goods, and improved technologies, which enhance the overall

> productivity of the economy. Romer (1994), for instance, has argued that in an

> economy subject to trade restrictions, only a narrow range of specialized intermediate goods or capital goods can be profitably produced and therefore the

> full range of technological possibilities, which rely on a potentially broader range of inputs, cannot be exploited effectively. In this model a greater variety of inputs does more for production than a greater quantity of a narrow range of inputs.

> Thus, access to a variety of foreign inputs at a lower cost shifts the economy-wide

> production possibility frontier outward, thereby raising productivity.<sup>2</sup> Moreover, the

> mechanism through which increased productivity and growth rates occur as economies become open to intemational trade is not limited to the adoption of

> more specialized intermediate inputs and machinery available from trading

> partners; there are many types of useful knowledge that are not embodied in

> material inputs (such as production engineering and information about changing product patterns), but can also be transferred as a result of trade with more advanced countries. As argued by Romer (1992), in practice, the transmission of

appears to be significant only for industrial countries, not for developing countries. Carkovic and Levine (2002) also failed to find a robust, independent effect of FDI on growth.

**2** Several other contributions have emphasized the role of the international diffusion and adoption of new technologies or new goods. Grossman and Helpman (1991) and Rivera-Batiz and Romer (1991), for instance, developed models in which technology is produced by profitmaximizing firms. They showed that openness to international markets can increase the growth rate of technology by increasing the size of the market available to technology producers and allowing those countries with a comparaffve advantage in technology production to specialize in that activity. International trade may also improve domestic productivity and economic growth by increasing knowledge spillovers from more advanced trading partners. Baldwin and Forslid (2000)

4
ideas may be as important,<sup>ifnot moreimportant, thanthetransmissionofnew</sup> inputs.

There is indeed some empirical<sup>evidencesuggestingthattradeintegration</sup> has beneficial effects on<sup>theleveland growthrateof output.StudiesbyFrankel</sup> and Romer (1999) and Irwin<sup>and Tervio (2002)have shown that countries that are</sup> more open to trade have<sup>higher incomes.In line withmorerecent theoriesof trade</sup> and growth, Klenow and<sup>Rodriguez-clare(1997) usedacomputablegeneral</sup> equilibrium framework<sup>thataccountsforproductvarietyeffectsthrougha</sup> production function in which<sup>a lower numberof intermediateinputvarieties results</sup> in productivity losses and<sup>lower output, despitethesame capital andlabor inputs.</sup> They found that accounting<sup>forsucheffectscanquadruplethestatic gainsfrom</sup> unilateral trade liberalization.<sup>Coe,Helpman,andHoffmaister(1997)foundthat</sup> trade flows provide a conduit<sup>through which advancedproductiontechniquesand</sup> technological knowledge<sup>are transmittedacrosscountries.3</sup> Wacziarg (1998) found that investment is<sup>themostimportant channel throughwhichopenness</sup> raises growth, accounting<sup>formorethan60percent of the totaleffect. Moreover,</sup> the empirical evidence<sup>alsosuggeststhat theleaming-by-doingandgrowth</sup> effects of these spillovers<sup>are largestin countries withhigher levels of education.</sup> Finally, a recent study by<sup>the WorldBank(2002)suggests that thecountries that</sup> have opened themselves<sup>themosttotradeinthelast twodecades(the"new</sup> globalizers") have, on average,<sup>grownthe fastest.Thesecountriesmanagedto</sup> reduce import tariffs, on average,<sup>by 34 percentagepointssince1980,compared</sup> with only 11 percentage points<sup>for thosedevelopingcountriesthat,onaverage,</sup> saw no growth in per capita<sup>incomesover theperiod.Because tradeisgoodfor</sup> growth, and growth is allegedly<sup>goodfor thepoor (on average,increasedgrowth</sup> raises the incomes of the<sup>poor inproportionto those of the population as claimed</sup> by Dollar and Kraay (2001))<sup>the study concludes thattrade(or,moregenerally,</sup> extend the Grossman-Helpman<sup>framework toaccountforimperfect competitionandscale</sup> economies in the research<sup>anddevelopment sector.</sup> 5
> intemational economic integration) is good for the poor. Nevertheless, as for financial integration, there is significant controversy as to the exact magnitude (if not direction) of the benefits associated with trade liberalization. In a detailed

> review of some the existing empirical studies, for instance, Rodriguez and Rodrik

> (1999) suggest a cautious assessment of their robustness.

Moreover, it is now increasingly recognized that the process of globalization entails significant risks and potentially large economic and social costly. Openness to global capital markets has brought greater volatility in domestic financial markets, particularly in countries whose financial systems were weak to begin with and economic policies lacked credibility. Large reversals in short-term capital flows (induced by the volatility of world capital markets) have led to severe financial crises and sharp increases in unemployment and poverty in the short run. Similarly, trade liberalization has led in some countries to reduced demand for unskilled labor and lower real wages in the short run; combined with a low degree of inter-sectoral labor mobility, job losses and income declines have often translated into higher poverty rates.<sup>4</sup> As a result, there have been growing concems about the negative effects of globalization, and an increasingly polarized debate on the plight of the world's poorest--namely, whether many of the 1.2 billion people who still live on less than $1 a day are sharing in the benefits of greater integration among economies and instead are disproportionately hit by short-run crises and economic downtums.

The main purpose of this paper is to try to assess, using cross-country econometric techniques, the extent to which globalization may indeed hurt the poor. Cross-country regressions--most notably in the context of empirical growth economics--have been the subject of criticism for their _ad hoc_ specification and the fragility of many of the results that they lead to (see Temple (1999)). They are,

> 3 As mentoned earlier, foreign direct investment provides another, perhaps more direct,

> route through which technology and advanced managerial and producton techniques can flow

> from industrial to developing countries.

6
nevertheless, useful<sup>toolswithsignificant advantagesover"event"or"case"</sup> studies. Such studies<sup>generally suffer from sampleselectivity biasandare unable</sup> to isolate with any<sup>degreeofprecisiontheindependenteffectofaparticular</sup> variable or set of variables<sup>(thatis,inthe present context,theimpactof</sup> globalization on poverty,<sup>asopposed todomesticfactors).Although the</sup> econometric methodology<sup>usedinthispaperdoesnot allowoneto takeafirm</sup> stand regarding issues such<sup>as causality,it providesausefulfirst step (subject to</sup> the caveats discussed<sup>below)inanattempttodisentangletheeffectsof</sup> globalization per se on poverty,<sup>while at the same timecontrolling for anumberof</sup> other determinants.

The paper is organized<sup>as follows.SectionII identifiesvariousmechanisms,</sup> related to both trade<sup>opennessandfinancialintegration, throughwhich</sup> globalization may hurt<sup>thepoor.This reviewis bynomeans exhaustive;my</sup> objective here is mainly<sup>toshowthatalthoughthereareverygood analytical</sup> arguments to suggest<sup>thatglobalizationmaybenefitthe poor(asdiscussed</sup> earlier), there are equally<sup>plausibleonesthatsupport the viewthattradeor</sup> financial integration may<sup>haveanadverse effectonpoverty.Byimplication,</sup> whether<sup>globalization is (onnet)"good"or "bad"for thepooris--as is</sup> determining often the case in economics--an<sup>empirical issue,not amatterof faith.Thisisby</sup> no means a claim to novelty<sup>but ratherareminderof apoint thathasoftenbeen</sup> "lost" by partisan views<sup>on both sides of the debate.I also emphasize the fact that</sup> the relationship between<sup>trade andfinancial opennessandpovertymaybenon-</sup> monotonic. This is also<sup>important,not onlybecause the possibility of anonlinear</sup> relationship has seldom<sup>been recognizedinthedebate,but also becauseithas</sup> implications for empirical<sup>tests.5SectionIIIdiscusses thebasic specification of the</sup>

> 41mperfect labor mobility<sup>across sectors seems indeed to have characterized severalrecent</sup> episodes of trade reform in<sup>developing countries (seeSeddon andWacziarg (2001)).</sup> 5 Edwards (2001) did<sup>pointoutthepossibilitythatcapital account opennessmaybe</sup> beneficial only once a certain<sup>levelofdevelopmentis reached.Similarly, Bekaert, Harvey and</sup> Lundblad (2002) found that<sup>the impactoffinancialliberalizatonongrowthdependsonthe</sup> country's level of secondary<sup>school enrollment.However,Arteta, Eichengreenand Wyplosz (2001)</sup> found that Edwards' results<sup>werenot robust;andBekaert,HarveyandLundbladfocused only on</sup> stock market liberalization.

7
regression model (including the choice of control variables) and explains the two dimensions through which globalization is measured. By necessity, my operational definition of "globalization" is narrower than what the concept usually involves (as defined earlier); I focus on measures of trade and financial openness (which indirectly captures technology transfers), but I do not capture the potentially important effects of labor and information flows. Section IV discusses some basic (linear) regression results. Section V extends the analysis to construct a "globalization index" based on principal components analysis. This index is then used to perform both linear and nonlinear regressions--using in the latter case the squared value of the index. I also discuss some robustness tests associated with these regressions. Section VI offers some concluding remarks and stresses the need for further empirical testing.

# 1. HOW GLOBALIZATION MAY HURT THE POOR

It is actually not very difficult to think of a number of channels through which the process of globalization may hurt the poor. Some of the most ardent "proglobalization" advocates would admit that, for instance, trade reform in developing countries may lead in the short run to higher unemployment and greater poverty, as a result of pervasive labor market distortions-such as a low degree of wage flexibility and imperfect labor mobility across sectors. In this section I want to emphasize, without trying to be exhaustive, the possibility that globalization may affect poverty adversely _in the long run_ as well. I first describe some possible channels through which trade liberalization may increase poverty, and then proceed to do the same for financial integration. I conclude this brief overview by stressing the importance of understanding the possible discontinuities and other nonlinearities that may arise in trying to assess the direction and strength of the link between globalization and poverty. Throughout the discussion, I will stress not only the possible direct effects of globalization on the poor, but also the indirect 8
effects that may operate<sup>throughtherateofeconomic growth--afairlywell-</sup> documented empirical regularity.

# 1. Trade Openness

Although, as noted in the<sup>introduction,therearesomegood arguments</sup> suggesting that trade liberalization<sup>may improveresourceallocationintheshort</sup> term or raise growth rates<sup>permanently(andthusbebeneficial to thepoor),there</sup> are a number of other arguments<sup>suggestingtheopposite.6Openingacountry's</sup> markets to foreign firms,<sup>forinstance,tendstoreducethemarketpowerof</sup> domestic firms and increase<sup>competitivepressuresonthem,eventually forcing</sup> (some of) them out of business.<sup>Inthe longerrun,the countrymaywell become</sup> more efficient in using its<sup>productiveresources,therebyenjoying highergrowth</sup> rates and lower poverty. But<sup>inthe shortterm,theinabilitytocompete,andthe</sup> presence of labor market<sup>rigidities(segmentationduetominimumwage</sup> legislation or wage-setting<sup>behavior by firmsor tradeunions,as well as imperfect</sup> mobility across sectors),<sup>may hamperthereallocationoflaborbetween</sup> nontradables and tradables<sup>thata reductionintariffs normallyentails(see,for</sup> instance, Agenor and Aizenman<sup>(1996)).Asaresult, bothunemploymentand</sup> poverty may increase and<sup>persist over time.</sup> Similarly, the effects of scale<sup>economiesandleaming-by-doingemphasized</sup> in the new theories of trade<sup>and growthtakeplacemostlyintheproductionof</sup> advanced manufactured<sup>products,suchashigh-technology goods.However,ifa</sup> country is "lagging behind"<sup>technologicallyandhasaninitialcomparative</sup> advantage in "non-dynamicn<sup>sectors,opennesstotradecanreducethegrowth</sup> rate (Matsuyama (1992)). Indeed,<sup>exportsof many developingcountriescontinue</sup> to consist of raw materials<sup>(includingenergyandagriculturalproducts)and</sup> relatively low-technology manufactured<sup>goods(suchastextiles).Eventhough</sup>

> 6See Winters (2002) for a detailed discussion of the linkages between trade policies and the poverty.

9
openness to trade (and capital flows) may help these countries to assimilate technologies and production techniques over time (thereby enabling them to shift eventually toward the production of goods and services that are characterized by dynamic gains) there may again be a 'transition period" during which globalization may have only a limited effect (if at all) on growth and poverty. It has also been argued that opening an economy to trade may discourage domestic research and development activities, for instance by inducing the poorer countries to allocate too much of their limited supply of skilled labor to the production of manufactured goods. In such conditions, paradoxically, restrictions on trade may accelerate growth.

> Trade liberalization may also lead to higher poverty by reducing the demand for unskilled labor and worsening income distribution. In a number of countries (particularly in Latin America), openness to trade during the 1980s and 1990s has coincided with an increase in the demand of, and the return to, skilled labor

> relative to unskilled labor, and a worsening of income distribution. An explanation of this phenomenon is that trade liberalization has been associated with the

> introduction of higher-level technology, the use of which requires skilled labor. The reason is that the cost of (imported) capital depends not only on the relative price of capital goods but also on tariffs that are incurred in purchasing a unit of capital goods abroad. To the extent that a fall in tariffs translates into a fall in the cost of capital (as the evidence suggests), a high degree of complementarity between skilled labor and capital, and a high degree of substitutability between unskilled

> labor and capital, would indeed entail an increase in the demand for skilled labor-thereby leading to a widening of the wage gap between skilled and unskilled labor.<sup>7</sup> The reduction in the demand for unskilled labor may translate into higher

> unemployment for that category of labor and increased poverty. Moreover, in the

> presence of imperfect credit markets (and following the logic of Galor and Zeira

> (1993)), the worsening of income distribution may hamper the ability of unskilled

10
workers to pledge collateral<sup>and borrow to finance the acquisitionof skills, thereby</sup> making an escape from<sup>the "povertytrap"moredifficult. There is strongempirical</sup> evidence suggesting that,<sup>indeed,humancapital accumulationindeveloping</sup> countries is subject tb credit<sup>market imperfections.</sup> The link between trade<sup>opennessand the accumulationof humancapitalis</sup> important to understand the<sup>long-run effects of globalization on poverty.Doopen</sup> trade regimes lead to high<sup>investmentin humancapitalin developing countries?</sup> Some theoretical models<sup>actually predict that free trade may lead to a</sup><sup>_decrease_in</sup> the accumulation of human<sup>capitalincountriesthatareinitially skills-scarce.</sup> Findlay and Kierzkowski<sup>(1983),forinstance,usinga modelinwhichcapital</sup> markets are perfect, showed<sup>that the accumulationof humancapital (andthus the</sup> supply of skilled labor)<sup>in countriesthatareinitiallyskills-scarcefallswhenthe</sup> rewards to education are<sup>reducedbytheavailabilityofcheaper,skills-intensive</sup> import goods. By contrast,<sup>Cartiglia(1997)showed that trade may actually</sup><sup>_reduce_</sup> initial differences in supplies<sup>of human capital. A key element of his analysis is the</sup> assumption that credit<sup>constraints(asmentioned earlier)limittheabilityof</sup> unskilled workers to finance<sup>the educationneededtobecomeskilled.In such</sup> conditions, capital market<sup>imperfectionsaffect thepattemofcomparative</sup> advantage and the impact<sup>oftrade liberalization.</sup> Because the argument<sup>is, I</sup> think, quite relevant for<sup>assessingthelinkbetweenglobalizationandpovertyin</sup> it<sup>is worth reviewingit in some detail.8</sup> developing countries, To begin with, consider a<sup>two-sectorsmall openeconomyin whichall</sup> workers (skilled and<sup>unskilled) live twoperiods.</sup> Two tradable goods<sup>are</sup> produced: a "high-tech"<sup>goodanda "low-tech"good(denotedby the subscripts H</sup> and L, respectively). Production<sup>oftheHgood,</sup><sup>_YH,_requires bothcapitaland</sup>

> 7For instance, Beyer, Rojas, and Vergara (1999) found that trade openness, as measured by the volume of trade<sup>overGDP,widened the-wagegapbetweenskilled andunskilled laborin</sup> Chile.

> 8Galor and Zeira (1996) present an altemative framework in which trade liberalization, by increasing the relative price<sup>ofgoodsproducedby skilledworkers, affectsthereturntohuman</sup> capital.
> skilled labor (in quantities _KH_ and _SH,_ respectively), whereas production of the L good, **_YL,_** requires capital and unskilled labor (in quantities _KL_ and U,

> respectively). Assuming the same Cobb-Douglas technology in both sectors,

> production is given by

> with the (constant) total stock of capital given by

> Let z denote the relative price of the H-good in terms of the L-good; because

> both goods are tradable, z is given on world markets. Assuming perfect mobility of

> capital across sectors and perfect competition, the rates of return on capital in

> each sector (that is, the marginal product of capital) must be equal:

Using (3) and (4), the equilibrium value of _KH_ is thus

> Wages of skilled and unskilled workers, ws and wu respectively, are determined from (1) and (2) by the marginal productivity of labor. Using the

> resulting expressions and (4), it can be established that

**12**
Thus, for z and the composition<sup>ofthelaborforce</sup><sup>_(SH_andU) given,the</sup> composition of production and<sup>factor retums areuniquely determined.</sup> As noted above, each Individual<sup>livestwoperiods.Inthefirstperiod,the</sup> individual can either go<sup>to school or workas anunskilled worker. Individuals who</sup> go to school in the first<sup>periodof theirlifeworkasskilledlaborinthesecond</sup> period; the others remain<sup>unskilled. At the endof the secondperiod, all individuals</sup> die and have one child.<sup>Thereisnopopulationgrowth,andthesizeofeach</sup> generation is normalized<sup>to one.At every pointin time, oneyoung generationand</sup> one old generation are alive,<sup>sothat the totalsizeof the populationis2.Inwhat</sup> follows, let et e (0,1) denote<sup>theproportion of (unskilled)individuals born in period</sup> t who go to school in period t.

Within each generation, individuals<sup>differintheownershipofcapital.,</sup> distribution<sup>of capitalwithin eachgeneration is assumedtobe</sup> Specifically, the constant over time and distributed<sup>uniformlyover theinterval</sup><sup>_(km_=</sup><sup>_a_+X+</sup><sup>_t,km:_</sup> _b + ,-t):_

# _n(k,) = n(k,; a, b,v, t)_ **_= Ikm,kM(kS),_**

where t 2 0, 'u Z 0, a Z _0, b_<sup>_>_a+2tand</sup><sup>_b_>0. The richest individuals own</sup><sup>_km = b_+</sup> u - t units of capital, whereas<sup>the poorest own</sup><sup>_km= a +_Mo</sup><sup>_+_tunits. Thus,of course</sup> _kM - km = b -_ a - 2t, which<sup>is positive giventherestrictionimposedon</sup><sup>_b._Let</sup><sup>_n(k8)'_</sup> denote the number of individuals<sup>who own</sup><sup>_ks_units of capital.</sup> The number of individuals in<sup>each generationis</sup>

**_-_** J **_f2 km=btv-tdks_** _= 1, b t_ **_k=a++t_**

13
> whereas the total stock of capital owned by each generation is

so that Thus, because in every period the total size of the population is 2, the size of the aggregate capital stock is a _+ b_ + _2u._

> The number of individuals in each generation whose stock of capital is at least as large as q is

> A quantity _SE_ of skilled workers are used to educate those individuals et who

> go to school in each period. Suppose, for simplicity, that the "production" of education is linear:

The supply of skilled workers at t is therefore equal to the number of individuals who went to school in the previous period, et-,, and is allocated between teachers and production of the H-good: which implies that, using (8): 14
_SHf = e,-i - yet._ (10) The supply of unskilled workers at t is the sum of those who chose not to go to school in the previous period, 1-et,,, and those who opted not to go to school in the current period: In the steady state, the number of individuals who become educated is the same in every generation (et = e); thus, equations (8) to (11) imply Suppose that the price of the H-good is high enough to ensure that the wage differential between wu and _ws_ is such that all individuals would prefer to be skilled, but that at the same time imperfections of the credit market (again, along the lines of Galor and Zeira (1993)) are such that the ability to invest in human capital in the first period of life depends on inherited wealth. Specifically, suppose that individual i will be able to attend school only if the income that he derives from its own capital, _rk 1,_ is as least as large as the cost of tuition, given by the wage of a (skilled) teacher, **_ws,_** multiplied by the teacher-students ratio, y. That is, Then, setting q = _ywslr_ and _nq =_ e in (7) yields 15
This equation gives the number of individuals in each generation that will be able to attend school, as a linear function of _wslr._ Inverting it yields Substituting the steady-state values of _SH_ and **U** from (12) and (13) in (5) and using (6) yields Equations (15) and (16) are two steady-state relations between e and **_w3Ir_** that determine the long-run general equilibrium of the economy. An interior solution is obtained for 0 < e < 1; otherwise, the economy either has no skilled labor and is specialized in the production of the L-good, or has only skilled labor and is specialized in the production of the H-good (e = 1).

To examine the effect of trade openness in this setting, consider an economy that is initially skills-scarce and whose comparative advantage<sup>in</sup> autarky (or prior to liberalization) is in the production of the L-good. When<sup>the</sup> economy is opened, the price of the H-good falls, and thus z falls as well.<sup>This,in</sup> tum, leads to a reduction in _ws,_ the return to the factor specific to the H-sector. The (equilibrium) number of individuals who attend school therefore increases. The reason is that when the price of the H-good falls, the wage of skilled workers falls as well, both because of the direct effect of the price change and because capital tends to move toward the L-good sector. Trade openness makes employment in the production of the H-good less profitable and induces skilled workers to switch away from production and into teaching; the fall in the cost of education that the reduction in ws entails makes credit constraints less binding 16
and more people can afford education. The supply of skilled labor therefore increases in equilibrium.

> The opposite happens in a country whose initial endowment of skilled labor

> is high and whose comparative advantage, prior to openness, is in the H-good.

> Trade increases the price of the H-good and induces skilled workers to switch

> from teaching toward production of the H-good. z rises and trade liberalization is associated with an increase in the demand for skilled labor relative to the demand for unskilled labor; the wage differential between labor categories widens. The

> cost of education rises and a smaller number of (unskilled) individuals are able to afford it. Put differently, trade liberalization increases the rewards of education in countries that are skills-abundant to begin with, and reduces the reward to education in countries that are skills-scarce initially. Capital market imperfections hinder the accumulation of human capital because the cost of education is a

> binding constraint. In initially skills-scarce countries, trade liberalization eases financing constraints (because the cost of education falls as _ws_ falls) and induces

> an increase in the accumulation of skills.<sup>9</sup>

Thus, in the presence of capital market imperfections that affect the ability of workers to borrow and invest in human capital, the impact of trade liberalization depends crucially on initial conditions, namely, the country's endowment of skilled labor. Suppose that one is considering a country characterized by a comparative advantage in the production of the L-good prior to trade liberalization (a fairly reasonable assumption for many low-income countries); does the model imply that poverty would fall as a result of trade openness? If one takes the unskilled wage as a measure of the poverty line and the ratio of unskilled workers to the total number of workers as an approximation to the "headcount" poverty index, the answer is yes. But if the poverty line is exogenous and the behavior of wages in the aftermath of liberalization is taken into account, the answer is ambiguous, for 17
two reasons. First, although the number of skilled<sup>workersrises,their wage falls.</sup> Second, as a result of gross complementarty<sup>betweenfactors,physicalcapital</sup> used in the production of the H-good rises (as<sup>canbe inferredfrom(1)) and falls in</sup> the L-sector; thus, although the fall in the supply<sup>of unskilled workers tends to put</sup> upward pressure on wages for that category of<sup>labor,the fall in the capital stock in</sup> the L-sector exerts an opposite effect, because<sup>ofitsimpactonthemarginal</sup> productivity of labor in that sector (as can be<sup>inferredfrom(2));thus,whether wu</sup> goes up or down cannot be established a<sup>_prior.10_Asa result, one cannot say for</sup> sure whether poverty rises or falls--it all depends<sup>onwhere thepoverty linestands</sup> with respect to the initial and post-liberalization<sup>levels of the unskilled wage.The</sup> point, nevertheless, is that poverty _may_<sup>increase,asaresultoftheinterplay</sup> between trade openness, the incentives that<sup>changesin factorretums createto</sup> accumulate human capital, and the borrowing<sup>constraintsthatindividualsmay</sup> face on the credit market when seeking to finance<sup>the acquisition of skills.</sup>

# **2. Financial Integration**

As noted earlier, although intemational financial<sup>market integrationmay</sup> bring significant benefits in the long term<sup>(andthereisindeedsomeevidence</sup> suggesting that this is the case), it is increasingly<sup>recognizedthat a high degreeof</sup> financial openness may entail significant short-term<sup>costs as well. The magnitude</sup> of the capital flows recorded by some developing<sup>countriesinrecent yearsand</sup> the abrupt reversals that such flows have<sup>displayedattimeshavebeen</sup> associated with deep financial instability, economic<sup>crises andsharp increasesin</sup> poverty rates-particularly in countries with imprudent sovereign debt management, improperly sequenced capital account<sup>liberalization,andpoorly</sup>

> 9Kim and Kim (2000) argued that education (or what they called 'general" human capital) may also help to increase the degree of _mobility_<sup>of workersacross sectors, thereby aftenuabngthe</sup> costs of trade reform (including a short-run<sup>increase in poverty) andraising growthrates.</sup> l<sup>0</sup> Moreover, note that the fact that the supply<sup>ofskilledlabor increasesinthe modelis</sup> entirely due to the assumpton that the cost of<sup>educationis proportional to</sup><sup>_wu;_if one assumes that</sup> tuition costs are exogenous, then the credit constraint<sup>wouldnotchange,possiblyleadingtono</sup> change in the equilibrium number of skilled workers.

18
regulated domestic financial systems. The recent crisis in East Asia is a case in point (see, for instance, Horton and Mazumdar (2001)).

A key problem associated with financial openness is that access to world capital markets tends to be _asymmetric._ Many developing countries (including some of the richer ones) are able to borrow on world capital markets only in "good" times, whereas in "bad" times they tend to face credit constraints. Access is thus pro-cyclical. Clearly, in such conditions, one of the alleged benefits of accessing world capital markets (the ability to borrow to smooth consumption in the face of temporary adverse shocks), is nothing but a fiction. Pro-cyclicality may, in fact, have a perverse effect and increase macroeconomic instability (see, for instance, Ag6nor (2001) and Dadush, Dasgupta, and Ratha (2000)): favorable shocks may attract large capital inflows and encourage consumption and spending at levels that are unsustainable in the longer term, forcing countries to over-adjust to adverse shocks as a result of abrupt capital reversals. The impact on poverty may thus be magnified.

In recent years, financial globalization in many transition and developing economies has taken the form of greater penetration of the domestic financial system by foreign banks. Unlike trade liberalization, which has often resulted from unilateral decisions by govemments to lower tariffs, this form of financial integration has often been less a matter of choice than a decision imposed by the country's situation-in several cases, the need to recapitalize domestic banks in the aftermath of a banking crisis (see Ag6nor (2001)). Although there are potentially large benefits associated with greater foreign penetration (such as enhanced quality of financial services, better techniques for credit analysis, and reduced risks of domestic financial instability), which may translate into higher growth rates and lower poverty, there are potentially adverse effects as well. Most importantly for the issue at stake, to the extent that foreign penetration is accompanied by a greater concentration of credit flows toward large firms producing tradables, and reduced access to loans by small and medium-size firms 19
(which tend to be more labor intensive than larger ones),<sup>it mayleadtoreduced</sup> levels of economic- activity, lower demand for labor,<sup>andpossiblytoagreater</sup> incidence of poverty. Evidence on this issue is still<sup>rather tenuous,butthe</sup> possibility cannot be dismissed.

Another channel through which financial openness<sup>mayhaveanadverse</sup> effect on the poor (at least in the short run) is the credit<sup>market.Asarguedby</sup> Agenor and Aizenman (1998, 1999)-in a framework that emphasizes<sup>thelinks</sup> between capital flows, the financial system, and the supply<sup>side of theeconomy,</sup> as well as the costly state verification approach pioneered<sup>by Townsend(1979)-</sup> the increased exposure to volatile shocks that is associated<sup>with financial</sup> openness may translate into higher domestic interest<sup>rates (becauseofthe</sup> increased risk of default), lower domestic output, and thus<sup>possibly higher poverty</sup> rates. The key reason is that increased volatility (of<sup>worldinterestrates,in</sup> particular) raises expected intermediation costs and<sup>leaddomesticfinancial</sup> institutions (whose ability to enforce loan contracts is<sup>limited)toeitherincrease</sup> domestic interest rates or to ration credit to maintain expected<sup>profits.Ofcourse,</sup> what this argument implies is that financial integration should<sup>beaccompaniedby</sup> adequate reforms of the domestic financial system to minimize<sup>the adverseeffects</sup> of volatility on output, employment, and poverty--not that<sup>financialopennessper</sup> se is undesirable.

But in addition to level effects associated with greater exposure<sup>to volatility, it</sup> has been argued that financial openness may also have<sup>adverseeffectson</sup> growth and, through that channel, on poverty. In particular,<sup>Devereuxand Smith</sup> (1994) studied the effects of intemational risk sharing (portfolio<sup>diversification) in a</sup> multi-country world in which growth is based upon the<sup>spillovereffects of human</sup> capital accumulation. They showed that when countries share<sup>endowmentrisk via</sup> international capital markets, the saving and growth rates<sup>canbelower thanin</sup> autarky. How they arrive at this conclusion is worth<sup>examiningin moredetail.</sup> 20
Consider a world consisting of N countries, each of them with a -stationary population. All countries produce a single homogeneous good, and there is an infinitely-lived, representative agent with constant relative risk aversion (CRRA) preferences, given by

> Production technology is also identical across countries. Specifically, output y't is given by

# _yit = Ok (Hitxit)_

where _kit_ is the firm's capital stock (and also country Is investment at t, assuming full depreciation within a period), _Hit_ the stock of knowledge (or human capital), and _xjt_ hours (supplied inelastically). In equilibrium, _Hit = Kit_ (the economy-wide capital stock), so that there are aggregate constant returns to scale in capital alone.

Each country faces idiosyncratic income risk but there is no aggregate uncertainty at the world level. More formally, there is a country-specific, random income shock, eSt, which is assumed to be proportional to the economy-wide capital stock in each country:

> where the distribution of the yit is assumed to be such that each country faces a zero-mean, i.i.d. process for its income risk over time and the aggregate world _N_ shock is zero in a symmetric equilibrium _E=I Yi:_ = 0

21
Agents choose consumption, investment, and asset holdings to maximize lifetime utility. Under "financial autarkyr, there are no markets that allow for intemational diversification of country-specific risk, and thus no trade in (statecontingent) assets between countries. Domestic saving must therefore be equal to domestic investment. Devereux and Smith show that the growth rate in this case, _A git_ ,is a random variable and is given by where ¢ can be shown to be a time-invariant function of the distribution of y. This expression shows that, because of the assumption of CRRA preferences (which implies positive third-order derivatives), an increase in country-specific income risk (as measured by a mean-preserving spread in the distribution of y,) will increase the economy's (average) growth rate through its positive impact on savings (which equals investment under autarky).

The expression in (18) is similar to (17), except that the y distribution does not appear."' By eliminating country-specific income risk, financial<sup>market</sup> integration eliminates the impact of this risk on savings, and therefore on economic growth. A comparison of (17) and (18) shows indeed that the average growth rate is lower under openness, because the elimination of income risk reduces world savings. Put differently, equilibrium growth rates in all countries are

> iiNote that to ensure positive growth requires imposing qO > 1.

22
lower under financial openness. The reason is that, as indicated above, with CRRA preferences riskier income leads to greater saving as a result of a precautionary motive. With full risk sharing, income risk is diversified away, reducing the equilibrium savings rate in each country. Lower saving in tum tends to lower the growth rate in each country.'<sup>2</sup> As shown by Devereux and Smith, the above result also holds if, instead of income-specific risk, countries differ in that they face specific productivity disturbances, Bit, provided that the distribution of productivity shocks satisfies again a "no aggregate uncertainty" condition and that a > 1 (the most relevant case empirically).1<sup>3</sup> However, it is sensitive to the assumption that there is only one investment technology available. As can be inferred from the results of Greenwood and Jovanovich (1990) and Obsffeld (1994), if there are many (risky) technologies available, financial openness may increase the equilibrium growth rate-even if it reduces savings rates, as a result of the precautionary motive alluded to eariier-by leading to a reallocation of savings to projects with high risk and return. Similarly, it should be noted that the above model takes the _depth_ of the financial system as given when assessing the impact of financial integration. However, it is possible that the two may be positively related beyond a certain level of income; in Agenor and Aizenman (1999), for instance, financial openness translates into lower interest rate markups and more efficient intermediation by domestic banks. In that case, intemational financial openness may bring additional benefits, which could mitigate the adverse impact of a greater opportunity for risk diversification on savings and growth. The point, nevertheless,

> 12They also show that If the gains from risk sharing under openness are more than offset by the losses associated with a reduced growth rate, welfare of each country may be lower than under financial autarky.

13Note that the assumpbon of time-separable, CRRA preferences is important for the argument but not crucial: as shown by Weil (1990), with generalized iso-elastic preferences that do not satisfy the axioms of expected utility and in which risk aversion is distinct from (the inverse of) intertemporal substitution, the response of savings to risk would depend in sign only on intertemporal substitution. Thus, in the Devereux-smith model, greater opportunities for risk sharing through intemational financial integrabon would therefore lead to lower savings and growth rates if the elasticity of intertemporal substitution is less than one (as is often the case in practce).

23
is that it is possible for financial globalization to hurt the poor (even in the long run), by lowering growth rates permanently.

# **2.** Nonlinearities

The foregoing discussion focused on the possibility of a linear, negative relationship between increased globalization and poverty. There are also, however, possible discontinuities (or threshold effects) and other nonlinearities that may come into play and alter the sign of the relationship between globalization and poverty. Understanding what causes these nonlinearities (which have seldom been acknowledged in the debate on the benefits and costs of globalization) is important not only from an analytical standpoint but also from the perspective of empirical analysis.

Consider the following example, which is described in more detail in Agenor (2002b).<sup>14</sup> Suppose that trade liberalization has two types of effects. The first is an _output_ effect, which translates into an increase in income per capita (as a result, for instance, of improved efficiency in the allocation of domestic resources). Suppose also that, in line with the evidence provided by Greenaway, Morgan and Wright (2002), this effect has a J-curve shape: at first, output falls (as output in import-competing industries drops) and then increases gradually (as the exportables sector expands). Assuming for simplicity a one-to-one, inverse relationship between income and poverty, this implies that globalization has an inverted J-curve effect on poverty.

The second effect of trade liberalization is a _relative wage_ effect, which is also assumed to be non-monotonic. Specifically, suppose that at first, the skilledunskilled wage differential increases with openness (as documented by Harrison and Hanson (1999), for instance), possibly because imports of capital goods 24
increase and firms substitute away from unskilled labor. Employment of that category of labor falls initially and poverty tends to increase. Over time, however, the initial widening in wage differentials may lead to investment in human capital and a gradual increase in the supply of skilled labor; this would tend to narrow the wage differential across skill categories, and higher degrees of liberalization may reduce poverty. This second effect may thus take the form of an inverted U-shape relation--which would depend, for instance, on whether there exists a subsidy to skills acquisition or not.

It is intuitively easy to see that, with both effects being nonlinear, multiple equilibria may emerge. However, for the purpose at hand, what is important to note is that the initial and longer-run effects of trade liberalization on poverty, operating either through output or relative wages, differ in sign: although poverty may rise in the short run, as output increases and investment in education rises, poverty begins to fall. Thus, not only does the sign of the relationship between globalization and poverty vary over time, the absolute value of the elasticity between these two variables is also not constant. Moreover, discontinuities may appear: the initial widening of the wage differential, for instance, may not be sufficiently large to translate into strong incentives to invest in skills; beyond a certain threshold; however, the impact.of the wage differential on the propensity to acquire human capital may change in a discrete fashion and may trigger a large increase in the supply of skilled labor. These discontinuities could lead, for instance, to a piece-wise linear relationship between globalization and poverty. Similar arguments can readily be developed to argue in favor of the existence of a nonlinear relationship between financial integration and poverty--as can be inferred, for instance, from the "threshold" effect, on the volatility of world interest rates discussed by Ag6nor and Aizenman (1999) in their analysis of the welfare benefits and costs of financial integration.

> 14 See for instance Albuquerque and Rebelo (2000) for another example of the nonlinear effect of trade reform. Their focus, however, is on changes in the industrial structure, rather than unemployment and poverty.

25.
The thrust of the foregoing discussion is thus twofold. First, although there are solid analytical arguments to suggest that globalization may improve the plight of the poor (in high- and low-income countries alike), there are also equallyconvincing reasons (at least to me) to suggest that the poor may not, after all, benefit much from trade and financial integration-at least without significant govemment interference. Assessing the net effects of globalization on the poor is therefore not a matter of faith, but rather an empirical issue. Second, there are important nonlinearties that may emerge in assessing the link between globalization and poverty. These nonlinearities are not mere theoretical curiosities; on the contrary, it can plausibly be argued that they may be very much at play in the real world. Ignoring them may seriously hamper the reliability of empirical results and may lead to misleading conclusions.

# Ill. METHODOLOGY

To assess the relationship between globalization and poverty I use a crosscountry regression framework, using unbalanced panel data for a group of developing countries for which I was able to collect sufficient data. The dependent variable is the poverty rate _(POV),_ measured by the headcount index for the population as a whole. In addition to measures of trade and financial integration, I include two sets of "control' variables, based on my previous results (see Agenor (2002a)): macroeconomic variables and structural indicators. Specifically, The set of explanatory variables used in the regressions are the following (see Appendix A for more precise definitions): _INFLTAX_ is the inflation tax rate, defined as the ratio of the inflation rate over one plus the inflation rate. This variable is conveniently bounded between zero and implies a concave relation between poverty and the inflation rate; 26
_TRANSGDP is_ the ratio of total subsidies and other current transfers over GDP, which aims at capturing the level effects associated _with_ changes<sup>in</sup> public spending; _LITY is_ the youth literacy rate in percent of the population aged 15-24, which aims to capture the level of education of the _labor_ force; _LHOSPITAL is_ the log of hospital beds per 1,000 persons, which measures overall health conditions; _GDPPC is_ GDP per capita at PPP exchange rates, which captures the<sup>level</sup> of economic development; _REALGR is_ the annual growth rate of GDP per capita, measured at PPP exchange rates, which can be viewed as either a proxy for the rate of return<sup>on</sup> physical investment, or as a measure of cyclical movements in output; _REALEX is_ the annual rate of change of the real effective exchange rate (defined such that an increase is a depreciation); _CTOT is_ the percentage change in the terms of trade; _VREALXL is_ a measure of macroeconomic volatility, which consists of rolling standard deviations of the real exchange rate.

I have discussed at length elsewhere the rationale for considering these variables (see Ag6nor (2002a, 2002b)), so only a brief justification is offered here. The inflation tax (which is levied on non-indexed assets, such<sup>ascurrency</sup> holdings) is expected to have a positive effect on poverty. Current transfers as a proportion of GDP has a priori an ambiguous effect. The effect of an across-theboard cut in transfers, for instance, may be to raise poverty; but to the<sup>extentthat</sup> 27
> it is accompanied by better targeting, poverty may fall. An increase in the literacy rate and an improvement in health (as measured by an increase in the number of hospital beds), are expected to reduce poverty. Both the level of GDP per capita and its rate of growth are also expected to be negatively correlated with the poverty rate. The effect of a real exchange rate depreciation is in general ambiguous; it may lead to a reduction in poverty if it benefits small farmers in the tradable sector (as is the case in many low-income developing countries), but if at the same time it brings about a significant increase in the cost-of-living index in urban areas, overall poverty may increase. An improvement in the terms of trade tends to reduce poverty if it represents an increase in the relative price of agricultural commodities (thereby benefiting small farmers in -rural areas) or a fall in the price of imported consumption goods (benefiting mostly households in urban areas). At the same time, however, a rise in import prices may have an adverse supply-side effect (because it raises the price of imported inputs) and

> may lower output, employment, and real wages, thereby increasing poverty. Finally, an increase in macroeconomic volatility (as measured by greater volatility of the real exchange rate) is expected to increase poverty, possibly through its adverse effect on investment and the propensity to save.

To measure globalization, even narrowly defined (as is the case in this study) to focus on trade and financial integration, is an arduous task. In particular, it is difficult to find an adequate measure of trade openness--which should ideally measure how open markets are to foreign competition. Proxies for openness that have been used include tariffs, nontariff barriers, effective rates of protection, trade liberalization, relative prices, import penetration, export intensity, and deviations of actual from predicted trade flows or volumes (see Edwards (1998), Harrison (1996), Harrison and Hanson (1999), and Rodriguez and Rodrik (1999)). Here, to measure trade globalization, I use two indicators: 28
_OPEN,_ the ratio of the sum of imports and exports of goods<sup>andservices in</sup> percent of GDP (referred to in what follows as the "trade<sup>opennessindicator"),</sup> which aims to capture exposure to extemal shocks; _TARIFF,_ the average tariff rate (that is, total tariff revenue<sup>dividedbythe</sup> value of imports).

The most common approach to examine the impact of financial<sup>opennessin</sup> cross-country studies is to build an index of capital account<sup>restrictionsonthe</sup> basis of the qualitative information reported in the<sup>IMF's</sup><sup>_AnnualReporton_</sup> _Exchange Arrangements and Restrictions._<sup>_15_</sup> The trouble<sup>withthis approachis that</sup> it provides no clue regarding the _intensity_ of capital restrictions--or,<sup>inversely,the</sup> effective degree of capital account liberalization. Here, I<sup>choseadifferentroute</sup> and opted for an "effective" measure of financial globalization,<sup>the ratioof foreign</sup> direct investment flows (FDI) to GDP. 16 If trade openness lowers poverty, the first variable should have a<sup>negative</sup> coefficient, whereas the second should have a positive<sup>coefficient.Similarly,if</sup> financial integration reduces poverty, the FDI-to-GDP ratio<sup>shouldhave anegative</sup> coefficient in the estimated regression.

It is important to acknowledge at the outset that all three<sup>oftheabove</sup> measures of globalization are problematic, because they<sup>captureonlyindirectly</sup> the process of trade and financial openness. For instance,<sup>thetradeopenness</sup>

> 15For instance, in their study on capital flows to transition economies, Garibaldi et al. (2002) constructed indices of restrictions on foreign direct investment<sup>andportfolio investment.The</sup> categories covered in the first index are approval requirements,<sup>the extentto whichprofitscanbe</sup> remitted abroad, ease in liquidating assets, and whether or<sup>notdirect investmentbenefitsfrom</sup> preferential treatment.

> 16A complementary measure of financial globalization,<sup>inlightofthegrowinginter-</sup> nationalization of banking, would be the share of assets<sup>of thedomestic financial systemheldby</sup> foreign banks. However, using the Bankscope database,<sup>Iwasunabletoobtainsufficient</sup> observations to include It in the regressions. Yet another<sup>approach would be to use the indicator of</sup> intensity of capital controls developed by Edison and<sup>Wamock(2001); however,their calculations</sup> pertain mostly to middle-income countries.

29
indicator (being calculated in nominal terms), is sensitive to short-run fluctuations in world commodity prices, whereas the average effective tariff rate does not capture non-tariff barriers--information on which is highly unreliable. Similarly, the ratio of FDI to GDP may show large fluctuations in specific years, reflecting specific operations, such as the privatization of a large public enterprise. To mitigate or "smooth out" the impact of year-on-year fluctuations in terms-of-trade changes on extemal openness and year-on-year fluctuations in FDI flows, I use in the regressions below averages over two and three years, in addition to the oneyear lagged value. I suspect that the "smoothing" effect associated with a threeyear average may be excessive and impart some bias in assessing the relationship between globalization indicators and poverty; nonetheless, I will report them for comparative purposes.

In addition to the problem of finding adequate indicators of trade and financial openness, there is a major data constraint relative to poverty rates and some of the other control variables defined earlier. I first started by compiling all the data on developing countries available on the poverty headcount index contained in the World Bank Live Database (LDB), which cover the period from the late 1980s to the late 1990s. This gives a sample of 57 countries, and a total number of observations equal to, at most, 91.17 However, due to the lack of available data on some of the control variables or globalization indicators (most notably government transfers as a share of GDP, average tariffs, and FDI), the "actual" sample size is at most 52 observations (for a total of 31 countries) in the initial set of regressions. After excluding the countries for which the number of observations is equal to one (Algeria, Brazil, Ecuador, Egypt, Ghana, Haiti, Kenya, Madagascar, Malawi, Malaysia, Mauritius, Nicaragua, Nigeria, Pakistan, Paraguay, Rwanda, Venezuela, Zimbabwe); I end up with a sample of 11 countries and at most 30 observations--6 countries for which the number of

> 17As is well known, there are serious conceptual and practical issues associated with the measurement of poverty, and the use of an 'international poverty line" for cross-country comparisons (see, for instance, Deaton (2001)). I will return to these measurement Issues in the concluding section.

30
observations is equal to two (Colombia,<sup>DominicanRepublic,India, Jordan,</sup> Thailand, Tunisia); 3 for which the number<sup>of observationsbeingequaltothree</sup> (Morocco, Peru, Sri Lanka); one for which<sup>fourobservationsareavailable(the</sup> Philippines); and one for which five observations<sup>available (Indonesia).</sup> The estimation method is OLS with fixed<sup>effects.Toaccount for simultaneity</sup> problems with the control varables, which<sup>from my previousstudies appear to be</sup> particularly important, for growth and GDP<sup>percapita,Iusedlaggedvaluesof</sup> these two variables; and as noted above,<sup>forthe globalization indicatorsIuse</sup> averages over two and three years, in addition<sup>to the one-yearlagged value.</sup>

# **IV. PRELIMINARY EVIDENCE**

Table 1 summarizes some preliminary results,<sup>basedonlinearregressions,</sup> for the two measures of trade integration<sup>describedearlier.Although inflationhas</sup> the correct (positive) sign in all cases,<sup>it is not significant. Changesin the terms of</sup> trade also have no significant effect on<sup>poverty when the trade opennessindicator</sup> is used, but it does appear to raise significantly<sup>the poverty rate when theaverage</sup> tariff rate is used as a measure of 'real'<sup>globalization.An increasein theshareof</sup> transfers to GDP is negatively associated<sup>withpoverty,but thevariableis</sup> significant again only when trade openness<sup>is measured by the average tariff rate.</sup> It is difficult to make much of the fact that public<sup>transfersandsubsidiesarenot</sup> significant in the first set of regressions; the<sup>reasonisthatthe variable doesnot</sup> measure very well what are the subsidies<sup>andtransfersthatactuallygotothe</sup> poor (it includes, for instance, transfers from<sup>the government toprivate andpublic</sup> enterprises). An increase in the rate of depreciation<sup>of the realexchangeratehas</sup> a strong, negative effect on poverty (possibly<sup>becauseimprovementsinthe</sup> relative price of tradables benefit to<sup>a</sup> significant<sup>extentfarmers producing</sup> exportables in the agricultural sector), whereas<sup>an increasein its volatility tends to</sup> 31
> increase significantly the proportion of the poor, as I found in an earlier study using a broader sample (see Agenor (2002a)). This latter effect may operate, as

> noted earlier, through and adverse effect of macroeconomic instability on the propensity to save and invest. The literacy rate has the correct sign and is highly significant in all the regressions shown in the table, whereas the health indicator

> (the number of hospital beds), despite being correctly signed in all cases, is statistically significant only when the average tariff rate is used. Both the level of real GDP per capita and its growth rate have the expected negative sign and are highly significant in all regressions involving the average tariff rate. By contrast,

> when trade integration is measured by the openness indicator, the level of real

> GDP per capita becomes statistically insignificant, despite the fact that its growth

> rate remains highly significant.

> Regarding the measures of globalization, the ratio of FDI-to-GDP does not appear to be robustly correlated with the behavior of poverty across countries. Neither is the trade openness indicator, although it is significant at a 10 percent

> level when either a one-year lag or a three-year average is used. By contrast, the

> (lagged) average tariff rate has a statistically significant negative effect on poverty, implying that trade integration (as measured by a fall in average tariffs) increases poverty--perhaps through some of the various channels identified earlier. This finding is robust to the various ways of averaging the tariff rate.

What should one draw from these results? As other researchers in the field have done, my inclination is to consider the results using the average tariff rates as more reliable than those using the trade openness indicator. I also view the results obtained with either a one-year lag or a two-year average as preferable, because a three-year lag may impart (as noted earlier) excessive "smoothing" to the underlying series. Thus, one would be tempted to conclude from these results (and particularly regressions (4) and (5)) that financial openness has no effect on poverty, whereas trade integration appears to have an adverse effect. However, this conclusion would be premature; the regression results shown in Table 1 32
assume the existence of<sup>alinear relationshipbetweenglobalizationandthepoor.</sup> But as discussed earlier, there<sup>aregoodreasonstobelievethat therelationship</sup> may be nonlinear.

# V. A POVERTY-GLOBALIZATION<sup>LAFFERCURVE?</sup>

To capture the possibility<sup>ofanonlinear relationshipbetweenglobalization</sup> and poverty, I proceed in<sup>twosteps.First,insteadof using severalindependent</sup> indicators as before, I derive<sup>a"composite"index of globalization(definedinsuch</sup> a way that an increase<sup>representsgreaterintegration)byusingprincipal</sup> components analysis. Second,<sup>Iintroducethesquaredvalueof theindexinthe</sup> regressions. In order to generate<sup>a"poverty-globalization"Laffer curve(withan</sup> inverted U shape), the coefficient<sup>of thelinear termshouldbepositive,whereas</sup> the coefficient of the squared<sup>termshould be negative.The peak of thequadratic</sup> equation would then identify<sup>the"threshold"levelof globalizationbeyondwhich</sup> further integration reduces<sup>poverty.</sup>

# 1. Principal Components Analysis

One option to construct<sup>acompositeindicatorof globalizationis toextend</sup> the methodology used for<sup>instancebyWacziarg(1998),andcombinevarious</sup> indicators of trade openness<sup>(suchasthoseusedabove) with measuresof</sup> financial openness.<sup>18</sup> A problem<sup>withthatapproach,however,isthedifficulty of</sup> defining relative weights<sup>inan objective manner.In this study,I tackle the problem</sup> differently. To derive a composite<sup>indicatorof tradeandfinancialglobalization,I</sup> use principal components<sup>analysis(PCA).Inessence,PCA aimstoreplacea</sup>

> 18 NWacziarg (1998) developed an index of trade policy by combining several Indicators, including average tariffs<sup>andanindicatorof non-tariff barriers.The weightsusedto constructthe</sup>

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> large set of variables by a smaller set that best "summarizes" the larger set. More formally, the principal components display the eigenvalue decomposition of the sample second moment of a group of series. The first principal component is computed as a linear combination of the series in the group with weights given by the first eigenvector, and so on. The higher the degree of co-movement existing

> among the original set of series, the fewer will be the number of principal components needed to explain a large portion of the variation of that set.

> Altematively, if all _n_ initial series are perfectly uncorrelated, it will take _n_ principal

> components to explain all of the variance in the original series; no advantage

> would be gained by looking at common factors, because none exists in the first place.<sup>19</sup>

In this study, I use the first principal component as a globalization index. That is, using either two or three of the previously-defined indicators of trade and financial openness (FDI and one minus the tariff rate; and both variables plus the trade openness indicator), I use PCA to construct one series, the first principal component, that explains as much of the variance of the original series as possible.<sup>20</sup> To see whether selecting only the first principal component is sufficient, I used a simple variant of the _scree_ test-essentially "eyeballing" a graph showing the proportion of the total variance (that is, the ratio of the first eigenvalue to the sum of all eigenvalues) that the component explains. Table 2 presents a summary of the results, for different lag-averaging procedures, and with and without the trade openness indicator. The results are based on standardized variables, to ensure that each series has a zero mean and a unit standard deviation (this standardization helps to ensure that all series receive uniform treatment and that the construction of the principal component measures is not

> combined index are determined from a regression of trade volumes (as a share of GDP) on these indicators plus some other '<sup>9</sup> Appendix B provides determinants.a brief technical discussion of PCA, as well as a description of my calculatons (which are based on the correlation matrix of the original matrix, instead of the vanance-covariance matrix). 20 use one minus the tariff rate, instead of the tariff rate itself, in order to ensure that an

> increase in any of the original series corresponds to greater integraton. I also performed all the calculations reported below with one over the tariff rate and obtained very similar results.

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influenced disproportionately<sup>by theseriesexhibitingthelargest variation).They</sup> indicate, for instance, that excluding<sup>thetradeopennessindicator andforatwo-</sup> lag average, the first principal<sup>component explains on averagealmost72percent</sup> of the variation in the original<sup>setofseries.I thereforeconcludethatthefirst</sup> principal component does a good<sup>job at'summarizing"theinformationcontained</sup> in the original series and can be<sup>used asa synthetic measureof globalization.</sup>

# 2. Estimation Results

The results of both linear and<sup>nonlinearregressionswiththeglobalization</sup> index are displayed in Tables<sup>3and4.Inbothtables, mostoftheprevious</sup> conclusions regarding the control<sup>variablescontinuetohold.Inparticular,the</sup> literacy remains highly significant.<sup>However,thenumberofhospitalbedsloses</sup> some of its significance, despite<sup>retaining the correct signinallcases.In addition,</sup> inflation becomes significant (when<sup>atwo-orthree-yearaveraging procedureis</sup> used) and so does the level of<sup>incomeper capita-regardlessof whether the trade</sup> openness indicator is used or<sup>notintheoriginalsetofseries usedtoperform</sup> PCA.<sup>21</sup> The degree of significance<sup>of therateof realexchangeratedepreciation</sup> varies significantly between Table<sup>3 and4:inthefirstcase,itfallssignificantly</sup> when the trade openness indicator<sup>is includedamong the seriesused to calculate</sup> the first principal component<sup>andwhenaone-yearlagisused,whereasinthe</sup> second it becomes insignificant,<sup>when either a two- or three-year averageis used</sup> and the trade openness indicator<sup>is excluded.</sup> The results shown in Table 3<sup>indicatethatglobalizationtendstohavean</sup> adverse effect on poverty, as<sup>shownindeedinTable1 whentheaveragetariff</sup> rate is used. However, this is<sup>notthewholestory.AsshowninTable4,the</sup> squared value of the globalization<sup>indexhasanegativeandhighly significant</sup>

> 21 In Table 4 the inflation tax rate and the share of transfers In GDP were excluded from some regressions, because they<sup>were incorrectly signed and (or)insignificant.</sup>

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> coefficient, regardless of whether one uses the trade openness indicator or not,

> and regardless of the number of lags used to average the original indicators of

> integration. This is true, in particular, of what I am tempted to regard the most

> "reliable" result-the regression in which the trade openness indicator is included

> and a two- or three-lag average is used. Indeed, these are the regressions for

> which the "best fit" (in the sense of the highest adjusted R-squared or the smallest standard error of the regression) is obtained in Table 4.

The implication of these results are clear: Given that the linear term has a positive coefficient, and the quadratic term a negative one, poverty at first increases when the index of globalization rises from low to moderate levels, and falls once globalization increases beyond a certain point. Put differently, although globalization at low levels may increase poverty, it may actually reduce it very significantly at higher levels.

# 1. Some Additional Sensitivity Tests

> To assess the sensitivity of the previous results (in addition to the standard diagnostic tests reported in the tables), I performed two exercises. First, I used a

> ratio of 0.6 for the proportion of variance explained by the first principal component as a cut-off point for including a country in the regressions. The results obtained (available upon request) very virtually identical to those reported in Tables 3 and 4. But of course, given the smaller sample size, these results are less efficient.

It may also be argued that, in line with the previous analytical discussion, globalization may have an indirect effect on poverty by a) raising the growth rate of output and the level of income per capita; b) by strengthening macroeconomic discipline, thereby leading to lower inflation and variability in the real exchange rate. In an attempt to account for these indirect effects, I used a two-step procedure. I first "purged" inflation, the level of income per capita, the growth rate 36
of real GDP, and the index of real<sup>exchangerate volatility by regressing themon</sup> the globalization index (assuming<sup>fixedeffectsin eachcase).I thenre-runthe</sup> regressions shown in Table 4<sup>usingthese"adjusted"variables.Theresultsare</sup> shown in Table 5 and are broadly<sup>similar to thoseshownin Table4, as far as the</sup> control variables are concerned.<sup>22They alsoindicate againthat the"best"results</sup> are obtained when the globalization<sup>indexis calculated witheither a two-or three-</sup> year average of the original series<sup>andwhenthetrade opennessindicatoris</sup> included.<sup>23</sup> Compared to Table 4,<sup>thelevelofsignificanceofthelinearterm</sup> involving the globalization index<sup>drops whena two-lag averageis used(it is now</sup> significant only at a 10 percent<sup>level);andthequadraticterm remains highly</sup> significant. Overall, therefore, this<sup>attempttocorrectfortheindirect impactof</sup> globalization on output and macroeconomic<sup>disciplineleadstoresultsthatare</sup> qualitatively similar to those obtained<sup>previouslywhenthetradeopenness</sup> indicator is included in the calculation<sup>ofthefirstprincipalcomponent.An</sup> important difference, however,<sup>is thedropinthe valueof the coefficientsof the</sup> linear term in the globalization index<sup>betweenTables 4 and 5. For instance, for the</sup> two-year average lag, and with the<sup>tradeopenness indicatorincluded,it falls from</sup> 0.027 to 0.015. At the same time,<sup>thecoefficientonthe quadratictermchanges</sup> relatively little (from -0.021 to -0.028).<sup>This isimportant because the shape of the</sup> poverty-globalization Laffer curve is<sup>very different dependingonthevalueof the</sup> coefficient of the linear term. To<sup>see this, let a>0be thecoefficient of thelinear</sup> term, and 3 < 0 the coefficient of the<sup>squared term;the thresholdvaluebeyond</sup> which globalization starts reducing<sup>poverty is -al2,B. With 1 being more or less the</sup> same under the one-step and two-step<sup>estimationresults,thevalue ofaplays a</sup> crucial role. Figure 1 illustrates the<sup>shape of thepoverty-globalizationLaffercurve</sup> for the two estimates of a obtained<sup>earlier(andfor,B =-0.02),underthe</sup> assumption that the constant term in<sup>the functional formsis the same.Clearly, the</sup>

> 22Note again that in Table 5 the<sup>inflation taxrateandthe literacyrate turnedouttobe</sup> incorrectly signed and (or) insignificant<sup>in some regressions, andwere thereforeexcluded.</sup> 23As noted earlier, again, using three-year<sup>averagesmay implyexcessive"smoothing of the</sup> underlying series.

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lower value of a under the two-step procedure implies _(cetens paribus)_ a significantly lower adverse effect of globalization on poverty.

# **VI.** CONCLUDING REMARKS

> Globalization, or the integration of economies and societies through trade,

> investment, finance, information and labor flows is, in the view of many, an

> inescapable feature of the world today. On the one hand, there is a considerable

> body of opinion arguing that globalization has led to substantial economic progress among rich and poor countries alike and, indeed, may be the principal

> mechanism for the intemational convergence of living standards. On the other,

> many point to the challenges that it poses for many countries as well as for the

> most vulnerable socio-economic groups within countries.

The purpose of this paper has been to examine the extent to which globalization affects the poor. Section II presented various arguments that may explain how trade and financial integration may hurt the poor. Two main points emerged from the discussion. The first is it is usually difficult to draw clear-cut theoretical conclusions regarding the effect of globalization on poverty as a result of conflicting effects, both in the short and the long run. Empirical studies are thus important to assess whether net effects are positive or negative. The second is that it is possible that nonlinearities may be involved in the relationship between globalization and poverty. Accounting for these effects is crucial for empirical testing.

> The second part presented some preliminary evidence, based on linear cross-country regressions linking various measures of real and financial integration to poverty. The regressions (performed over a group of 11 low- and

> middle-income countries and with data covering the late 1980s and the 1990s)

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control for changes in<sup>income percapitaandoutputgrowthrates,aswellas</sup> various other macroeconomic<sup>andstructural variables,such astheinflationtax,</sup> changes in the real exchange<sup>rate andthetermsoftrade,healthandschooling</sup> indicators, and macroeconomic<sup>volatility.The thirdpartextendedthe analysisto</sup> derive a "globalization<sup>index"basedonprincipalcomponentsanalysis(usingthe</sup> set of trade and financial<sup>opennessindicatorsdefinedinthepreliminary</sup> regressions) and tested<sup>forbothlinear andnonlinear effects. The resultsindicate</sup> that there appears<sup>tobeareasonably robust,non-monotonicLaffer-type</sup> relationship between poverty<sup>andglobalization(asmeasured by the first principal</sup> component): at low degrees<sup>ofglobalization, globalizationdoeshurtthepoor.</sup> However, at higher levels,<sup>globalization leads to a decline in poverty.</sup> What is the source of<sup>thisnonlinearity?At thisstage,andwithoutfurther</sup> empirical work, I can offer<sup>only conjectures, basedonmyanalyticalreviewof the</sup> links between globalization<sup>andpoverty.Onepossible explanationis that beyond</sup> a certain threshold a greater<sup>degreeof realand financial integration bringswithit</sup> (or induces governments<sup>to implement)far-reaching domesticinstitutional reforms</sup> that improve the ability<sup>ofprivate agentstosaveandinvest,strengthen the</sup> financial system and the<sup>regulationandsupervisionoffinancialintermediaries,</sup> and more generally improve<sup>the"socialandlegalinfrastructure"that is conducive</sup> to greater risk taking. Regardless<sup>of theexactmechanismthatmay beatplay,</sup> however, the striking<sup>implicationof thepoverty-globalizationLaffercurveisthat,</sup> paradoxically, globalization<sup>may hurtthepoorinsomecountriesnotbecauseit</sup> went too far but rather<sup>becauseitdidnotgofarenough.Put differently,by</sup> focusing on different<sup>portionsof thecurve,bothadvocatesandopponentsof</sup> globalization have been<sup>missing part of the story.</sup> I will conclude with the<sup>usualnoteof caution-theempirical resultsreported</sup> in this paper require further<sup>testing toassesstheir robustness.The existenceof</sup> nonlinearities could be<sup>furtherexploredbyusingsplinesandexploringtheir</sup> sensitivity to the choice<sup>of breakpoints.Altematively,one couldexploit techniques</sup> such as projection pursuit<sup>(asinFriedmanand Stuetzle(1981))or themethodof</sup> 39
altemating conditional expectations (Breiman and Friedman (1985)). More importantly perhaps, the sample size used in this study is small, mostly due to the lack of available data on poverty rates. The lack of a sufficient number of observations prevents the use of more advanced regression techniques, such as the GMM method used by Hansen and Tarp (2001) in a different context, which would allow to control at the same time for both unobserved country-specific characteristics and endogeneity. Moreover, the available data on both sides of the regression equation are not highly reliable. As is well known, the aggregate measure of poverty used in this study is based on survey data; but there are large differences across countries in measuring poverty from these micro data (related most notably to differences in definitions of income or consumption), which create potentially serious comparability problems. I have used 'effective' measures of trade and financial integration, but the data are not without problems. Using average import tariffs does not account for the existence of non-tariff barriers (which themselves are very difficult to measure with any degree of precision). An altemative option to measure trade openness might be to use the new index of trade restrictiveness compiled by the IMF, which is based on a variety of published and unpublished sources (see Lankes (2002)); and as noted earlier, the share of assets of the domestic financial system held by foreign banks could be a complementary measure of financial globalization. In both cases, however, the number of observations available remains an issue.

I also found that fixed effects (which were not reported here to save space) are important and statistically significant in many cases, suggesting that countryspecific factors are important in determining the behavior of poverty rates. There is therefore a risk of misspecification that may persist despite my effort to control adequately for various determinants of poverty. More generally, parameter heterogeneity is a key problem in the type of cross-country, growth-poverty regressions presented in this study. Indeed, an implicit assumption in this type of regressions is that the parameters are constant across countries, that is, that all countries follow the same underlying model relating growth and poverty. If one is 40
interested only in estimating parameter<sup>averages,thiscanbeweakenedslightly,</sup> by assuming only that parameters<sup>are distributedindependently of the variablesin</sup> the regression. Yet even this<sup>weakerassumptionis likely tobetoostrong. One</sup> can easily suggest examples of<sup>parametersthatarelikely tobe correlatedwith</sup> variables in the regression--for<sup>instance,macroeconomicinstabilitymaybe</sup> associated with both lower growth<sup>andalowerimpactofgrowthonpoverty,so</sup> that the coefficient on macroeconomic<sup>instability shouldideally be allowed to vary</sup> across countries. A sensible response to this<sup>istofindwaysofmodeling</sup> heterogeneity. For instance,<sup>inthe above example,it mightbepossible toreduce</sup> the extent of heterogeneity<sup>byintroducinganinteractiontermbetween</sup> macroeconomic instability and<sup>growth,andby usingheteroskedasticty-consistent</sup> standard errors for inference.<sup>Regardless,however,the regression model remains</sup> likely to embody restrictions on<sup>theparameters,which make usingthemodel at</sup> the individual country level problematic<sup>at best.Analtemative approach wouldbe</sup> to perform explicit tests<sup>explicitlyforpoolingandparameterheterogeneity.</sup> Unfortunately, the lack of observations<sup>remains a serious constraint.24</sup>

> 24To detect parameter heterogeneity (or the Opoolabiiity" of the data) one could use a twostep Chow test (as, for instance, in<sup>Evans,Green,and Murinde(2002)),ortheDutta-Leontest</sup> (see Dutta and Leon (1991)).<sup>Othermethods,basedonBayesiananalysis,are describedby</sup> Maddala and Wu (1996, 2000). However,<sup>none of these testscanbe implemented here because</sup> they all require sufficiently long time series<sup>for each individual country.</sup>

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