Firebaugh and beck 1994

Does Economic Growth Benefit the Masses? Growth, Dependence, and Welfare in the Third
World
Author(s): Glenn Firebaugh and Frank D. Beck
Source: American Sociological Review, Vol. 59, No. 5 (Oct., 1994), pp. 631-653
Published by: American Sociological Association
Stable URL: http://www.jstor.org/stable/2096441
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DOES ECONOMIC GROWTH BENEFIT THE MASSES?
GROWTH, DEPENDENCE, AND WELFARE IN THE THIRD WORLD*
GLENN FIREBAUGH FRANK D. BECK
Pennsylvania State University Pennsylvania State University
Despite recent economic gains in much of the Third World, sociologists have paid
little attention to the possible national benefits of economic growth. Instead, they
have focused on the possible harm caused by the Third World's dependence on for-
eign investment and trade. Our analysis questions that focus. Based on data for 62
less-developed countries spanning two decades, we find that the effects of depen-
dence largely vanish when (1) the effects of economic growth are carefully specified,
and (2) the "semi-difference" models currently in vogue in cross-national research
are replaced by more appropriate difference or difference-of-logs (growth-rate) mod-
els. In light of the common claim that economic growth in the Third World benefits
only the rich, we employ measures of national welfare that the rich cannot readily
monopolize. The effects of economic growth on national welfare are large and ro-
bust, whereas the effects of dependence are hard to find. These findings contradict
earlier studies, which had concluded that the effects of dependence dwarf the effects
of economic growth.
"One truthis straightforward.Industrial-
ization is the only hopefor thepoor "
-C. R Snow (1963:30)
E conomic growth is a means to an end-
a better life for the masses. Unless eco-
nomic growthraises generalliving standards,
true "development"has not taken place. So-
ciologists, economists, and policymakers
agree that improved living standardsfor all
is the ultimate objective of economic policy.
Has economic growthbenefitedthe masses
in the Third World? Economic growth-an
increase in the total value of goods and ser-
vices produced per person-has been occur-
ring throughouttheThirdWorldover the past
few decades. But because goods andservices
can be concentrated in the hands of a few,
*
Directallcorrespondence
toGlennFirebaugh,
Departmentof Sociology, 206 OswaldTower,
Pennsylvania
StateUniversity,UniversityPark,
PA 16802 (internet:FIREBAUG@POP.PSU.EDU).
This study was supportedby NSF grantSBR-
9308505 to Firebaugh.Additionalsupportwas
providedby thePopulation
Research
Institute
of
thePennsylvania
StateUniversity,
whichhascore
support
fromNICHD(grant1-HD28263-01).
We
areindebtedto BradleyBullock,CliffordClogg,
theASREditor,andtheanonymous
ASRreview-
ers.[Reviewersacknowledged
by theauthors
are
Kenneth
Bollen,WilliamDixon,PeterEvans,and
Miles Simpson. -ED.]
economic growth need not raise the standard
of living for the masses. A recent cross-na-
tional study in sociology concluded thateco-
nomic growth has yielded little benefit for
the masses in the Third World (Wimberley
andBello 1992). "Themost unforgivablesin
of development planners is to become mes-
merized by high growth rates in the Gross
National Product and to forget the real ob-
jective of development"(Haq 1976:24).
To determinewhethernationalliving stan-
dards are improving or deteriorating, re-
searchersmust examine changes in phenom-
ena, like food consumption,that are not eas-
ily concentrated. In investigating returns to
economic growth, then, the key issue is
whether, and to what extent, the expansion
of goods and services in the ThirdWorldhas
improved measures that the rich cannot mo-
nopolize. To address that issue, we examine
the effects of economic growth on changes
in food consumption,infantsurvival,andlife
expectancy (at age 1), using data for 62 low-
income nations from 1965 to 1988.
THEORYAND LITERATUREREVIEW
TheEffects of Dependence
By conventional measures of material well-
being or quality of life, the masses in rich
AmericanSociological Review, 1994, Vol. 59 (October:631-653) 631

632 AMERICANSOCIOLOGICAL
REVIEW
nations tend to be better off than those in
poor nations. It does not follow, however,
that economic growth will necessarily im-
prove the quality of life of ordinarypeople
in poor countries. Revisionist literature in
development sociology argues that national
income growth based on a dependence on
foreign investment and trade scarcely ben-
efits the masses (and may even harmthem).
But this argumentflies in the face of conven-
tional economic wisdom. What is the evi-
dence for the revisionist view?
The search for dependence effects domi-
nateddevelopment studies in sociology dur-
ing the 1980s and into the 1990s (Bornschier
and Chase-Dunn 1985; Boswell and Dixon
1990; Evans and Timberlake 1980; Jaffee
1985; London 1987, 1988; London andRob-
inson 1989; London and Smith 1988; Lon-
don and Williams 1988, 1990; Stokes and
Jaffee 1982; Wimberley 1990, 1991; Wim-
berley andBello 1992). The basic premiseof
this researchis that"dependence"is the ma-
jor impedimentto developmentin poorcoun-
tries (Chase-Dunn 1975). Dependence usu-
ally refers to investment dependence (reli-
ance on transnationalcorporationsfor capi-
tal) or tradedependence (tradewith rich core
nations). Although, in principle, peripheral
nationscould dependon core nationsin a va-
riety of ways-militarily, politically, cultur-
ally-most researchin sociology has focused
on investment and trade.
Sociologists' concern with the effects of
dependence derive from the writings of neo-
Marxist scholars in the 1960s and 1970s,
who argued that poor nations remain poor
because of their inherently exploitative ex-
change relations with the United States and
other rich nations. Early versions of depen-
dency theory appear to claim that depen-
dence precludes economic growth (see
Gereffi 1983:chap. 1), but subsequent eco-
nomic growth in much of the Third World
has deflated that claim. Recent dependency
discussions concede thateconomic growthis
possible in dependent countries, but argue
that dependence depresses and distorts eco-
nomic growth in these countries (Bornschier
and Chase-Dunn 1985).
Empirical studies rarely distinguish be-
tween depressed economic growth and dis-
torted economic growth. The distinction is
crucial when analyzing the consequences of
economic growth for national welfare be-
cause depressed growth implies an additive
effect of dependence whereas distorted
growthimplies an interactioneffect. Briefly,
the depressed-growth thesis argues that in-
vestment dependence harms the masses in
less developed countries (LDCs)by slowing
income growth.A substantialliteraturein so-
ciology (see Firebaugh 1992 for citations)
has concluded that,over the long run,highly
dependent LDCs fare worse economically
than do less dependent LDCs. The implied
causal orderis greaterdependence -+ slower
economic growth-e reducedwelfare.
Distorted economic growth has a different
empirical pattern. Although highly depen-
dent nationsmay grow as fast as less depen-
dent nations, growth is uneven, dispropor-
tionatelybenefiting theprivileged (Bradshaw
1988). In otherwords, the strengthof the re-
lationshipbetween economic growthandim-
provementin overall welfare depends on the
level of dependence-a classic interaction
effect. However, no cross-national research
has employed the requisite interactionmod-
els to test the claim.
TheoreticalArgumentsfor the Adverse
Effects of Dependence
Dependency theorists arguethatdependence
on rich nations harms LDCeconomies, par-
ticularly trade dependence and investment
dependence.1
Trade dependence. Classical economists,
like Ricardo, saw tradeas benefiting all par-
ticipants by promotinginternationalspecial-
ization. However, tradehas produced disap-
pointing results as many poor nations re-
mained poor despite heavy involvement in
internationaltrade.One influential school of
thought holds that the disappointing effects
of tradein the ThirdWorldcan be traced to
whatdevelopmenteconomists call the "com-
modity problem": Gains from trade are bi-
ased against LDCsbecause LDCstend to ex-
change raw materials for processed goods
(Adams andBehrman 1982).
l Becauseconventionaleconomictheoryand
dependencytheoryboth warnThirdWorldna-
tionsagainstexcessivedebt,we do notexamine
theeffectof debtdependence.
Thedistinguishing
feature
of dependency
theoryis itsviewthattrade
andforeigninvestment
haveharmful
effects.

DOES ECONOMICGROWTHBENEFITTHEMASSES? 633
Why is specialization in the export of raw
materials bad for LDCs?One reason may be
a long-termseculardecline in tradetermsfor
raw materials (Prebisch 1950; Singer 1950).
A related argument is that the demand for
primaryproducts is fundamentallyinelastic,
so that markets for those goods grow too
slowly to fuel economic growth.Finally,eco-
nomic growth may be adversely affected by
volatility in the prices of raw materials (see
KnudsenandParnes 1975). These arguments
arehardto prove and aredismissed by many
development economists.
Dependency theorists most often argue
that: (1) primary production is "linkage-
weak," meaning that it does not lead to the
creationof new industries,and(2) theperiph-
ery-to-core exchange of unprocessedforpro-
cessed goods is inherentlyunequal.The link-
age-weak argument is central to Amin's
(1974, 1976) theory of "disarticulated"LDC
economies-economies characterized by
weak or missing links between sectors (Sica
1978; Stokes andAnderson 1990; see Smith
1980 for acritique).LDCsthattradewithcore
countries may also be exploited in the ex-
change itself, as "more value" is exchanged
for "less value."One version of unequal-ex-
change theory sees this inequality as labor-
based:"Unequalexchange ultimatelyderives
from the exchange of unequal quantities of
labor"(Mandel 1975:351; Emmanuel 1972).
Another version sees the inequality as com-
modity-based (i.e., LDCs' specialization in
the export of raw materials implies "unbal-
anced flows of energy and matter"[Bunker
1984:1018]). Whatever the source, unequal
exchange locks LDCsinto a subordinatesta-
tus in a polarized world economy.
Investmentdependence. During the 1980s,
the focus of dependency research shifted
from the effects of tradeto the effects of in-
vestment. This shift probably reflected dis-
enchantment with the mixed results from
studies of trade dependence (Rubinson and
Holtzman 1981). In 1985 Bornschier and
Chase-Dunn published an influential book
claiming evidence for a substantial adverse
effect of foreign investment on LDCsbased
on a new measure of foreign investment. A
spate of studies followed, all of which con-
cluded (using the new foreign investment
measure) that foreign investment harms
LDCs(Firebaugh 1992).
The theoreticalcase againstforeign invest-
ment argues that transnationalcorporations
lock LDCsinto an inferior status in the hier-
archical world system (Bornschier and
Chase-Dunn 1985). The interests of these
corporationsdiverge from those of their host
nations. Transnationalcorporations tend to
repatriate profits, to sell goods at reduced
prices to their subsidiaries in the core (to
avoid paying taxes to LDCs), to transplant
inappropriatecore technologies and organi-
zational forms, to stifle local businesses, and
so on. In addition, by juxtaposing a modern
export-orientedeconomy beside a traditional
economy, transnationalcorporationspromote
inequalityandcreate a sortof disjointed, hy-
brid economy. Because the two economies
remainseparate,the initial surgein aggregate
national product is misleading and is fol-
lowed by stagnation. Thus, peripheral na-
tions would fare betterin the long run to es-
chew investmentfrom core nations.
Followinganinitialgrowthspurtthis [foreign
investment]will createan industrialstructure
inwhichmonopolyis predominant,
laboris in-
sufficientlyabsorbed,andthereis underutili-
zationof the productive
forces.Thus,the pe-
ripheralcountriesthatadoptthis pathof un-
evendevelopment
basedon incomeinequality
and foreign capital importswill experience
economicstagnation. .. relativeto countries
thatareless penetrated
bytransnational
corpo-
rations.(Bornschier
andChase-Dunn
1985:39-
40)
To summarize, the answer to the question
"Does economic growth benefit the masses
in the Third World?"is more controversial
thanone might think.A huge dependencylit-
eratureclaims thatthe benefits to the masses
of aggregate economic growth may be
ephemeral in the Third World, because
growth based on imported capital and trade
with the core is short-lived andunevenly dis-
tributed. Over the long run, dependence
harms the masses in the Third World either
by suppressing economic expansion or by
distorting the salutary effects of economic
expansion.
TheoreticalArgumentsfor the Beneficial
Effects of Economic Growth
The case for economic growth's salutaryef-
fects for the masses is found in introductory

REVIEW
economics textbooks. Why do the rich and
powerful not reap all or most of the benefits
of growth?Why must owners sharethe fruits
of increased output with workers? The an-
swer is greed-greed drives capitalists in a
continual search for profits. To profit from
capital, capital must be invested, usually in
laborandequipment.A plantowner wants as
many workers as possible in order to maxi-
mize output.But because inputsbringdeclin-
ing marginal returns, at some point the in-
crease in production from an additional
workerwill equal the cost of that worker.At
this point no more workerswill be hired.
But what if productivity goes up as a re-
sult of increased investmentsin physical and
human capital? In a world with only one
profit-maximizing capitalist or with an un-
limited number of workers, wages would
not necessarily rise with increases in worker
productivity,because the capitalist could get
an adequate labor supply with subsistence-
level wages. But in the real world, many
capitalists usually compete for labor. In this
case, when productivity goes up, employers
want to hire more workers at the current
wage. But employers can take workersaway
from other employers only by raising the
wage. Because productivity per worker has
gone up, it is now worth it for the employer
to raise the wage to attract new workers.
Thus, some employers raise the wage to
where it equals the new marginalproductiv-
ity of labor. Once some employers do this,
owners who refuse to raise wages will lose
their workers to those who have raised their
wages. Thus, owners who want to remain in
business must raise their wage. In this way,
the entire market wage increases. This is
why productivity growth is disequilibrating,
raising the market wage to a new equilib-
rium. In principle, owners could collude to
keep wages low, but in practice the lure of
windfall profits for cheaters makes such car-
tels unstable.
Economists are often rightly criticized for
taking marginal productivity theory to ex-
tremes, as for example when they assume
thatwages perfectly reflect marginalproduc-
tion. To supportthe textbook explanation of
why owners must share the fruits of in-
creased output with workers, we need only
find that wages tend to be linked to produc-
tivity in the aggregate.
If wages are linked to workers' productiv-
ity, then there should be a positive cross-
country association between per capita GDP
(a measure of average productivity) and av-
erage income for the bottom half of the
population(which reflects prevailingwages).
Across 37 nations (rich and poor), GDPper
capitain 1985 is highly correlatedwith aver-
age income of the bottom 40 percent of the
population (r = .98) and the bottom 60 per-
cent of the population (r = .99; datafrom In-
ternationalBank for Reconstructionand De-
velopment 1990). Clearly, wages are tied to
averageproductivitycross-nationally.
The usual counterargumentis that depen-
dence increases inequality,so workersin de-
pendent nations do not benefit from eco-
nomic growth.The evidence consists largely
of cross-national regressions showing that
dependent nations tend to have greater in-
come inequality. However, in a growing
economy, workers can lose relatively while
gaining absolutely. Thus, the regressions
used in dependency research miss a critical
point: The issue is not whether dependence
increasesinequality,butwhetherthe increase
in inequality is so great that workers fail to
benefit from gains in productivity. If work-
ers in dependent nations fail to benefit from
productivitygains, thecross-countryassocia-
tion between GDP and workers' incomes
should be zero for those nations. However,
the evidence suggests otherwise: For the 18
(of the 37) nations with investment depen-
dence above the median, the correlation be-
tween average income and average produc-
tivity is far from zero (r = .96 for the bottom
40 percent of the population and .98 for the
bottom 60 percentof the population).
The apparentstrengthof the cross-national
link between wages and economic level sug-
gests substantial benefits from economic
growth.As wages rise, diets should improve
and infant mortalityshould decline.
Yet a recent cross-national study claimed
thatthereturnsto economic growthhavebeen
minimalfor the masses. Based on 1967-1985
data for 59 LDCs, Wimberley and Bello
(1992) concluded that "investment depen-
dence has an exceptionally strong harmful
effect on [food] consumption."This effect is
largelyindependentof growth-"[E]conomic
growth ... mediates very little of the effects
of dependence on consumption, signifying

the limited relevanceof earliercross-national
researchon growth"(p. 895). The effects of
economic growth are overshadowed by the
effects of investmentdependence:"Growth's
impact... is farsmallerthanthe directeffect
of TNC [transnationalcorporation]penetra-
tion" (p. 915). The authors concluded that
foreign investment, not lack of economic
growth,is the leading cause of "immiseration
in the noncore"(p. 915).
If these conclusions are true, they imply a
reorientation of development strategy from
the current focus on promoting economic
growthto a focus on reducinginvestmentde-
pendence. The conclusions imply some re-
thinkingof dependency theory as well: If the
pernicious effects of dependence are inde-
pendent of economic growth, the theory's
emphasis on depressed growth and distorted
growth is misplaced.
Yet there are reasons to be wary of the
Wimberley-Bello conclusions. First, why
should investment dependence have a direct
effect at all (let alone a dominant one)?
Wimberley and Bello's (1992:899) list of ar-
guments consists largely of reasons why for-
eign capital will affect growth (by reducing
aggregatedemand,by introducingcapital-in-
tensive technology that causes factor-price
distortions, etc.), not why it will operate in-
dependent of growth. Second, the finding
that the masses receive little benefit from
economic growth is hard to reconcile with
the strongcross-countryassociation between
wages andproductivity,andwith the findings
from case studies (e.g., Barrett and Whyte
1982 [on Taiwan]; Nee 1991 [on China]).
Third, the Wimberley-Bello analysis of
changes in welfare between 1967 and 1985
included no data on foreign investment after
1967. Thus, their claim that foreign invest-
ment has an "exceptionally strong"effect is
based on a model thatignores foreign invest-
ment over the period they studied.
Evidence FromDependency Studies Versus
Evidence From Reduced-FormModels
Reduced-form models indicate that foreign
investment's total effect on national welfare
is not negative. Currently, the dependency
literature suggests that foreign investment
harmsnationalwelfare indirectly-by reduc-
ing economic growth (Bornschier, Chase-
Dunn, and Rubinson 1978; Bornschier and
Chase-Dunn 1985; Wimberley and Bello
1992), anddirectly-by reducing welfare in-
dependentof the effects of economic growth
(Wimberleyand Bello 1992).
The puzzle of nonnegative total effects of
foreign investment in the face of putative
negative direct and indirect effects is solved
by close inspection of the methods used by
dependency researchersto estimate those di-
rect and indirect effects. The claim that for-
eign investment reduces national welfare by
retardingeconomic growth (indirect effect)
is based on a "stock and flow" model in
which the growth rate of the economy from
time 1 to time 2 is regressed on the level of
cumulatedforeign investment(stock) at time
1 andchange in thatlevel fromtime 1to time
2 (flow). Dependency researchersthen inter-
pret the negative slope obtained for capital
stock as indicating that foreign investment
harms LDCs' economies over the long run
(Bornschier and Chase-Dunn 1985).2
By this line of reasoning, however,domes-
tic investmentalso harmsThirdWorldecon-
omies over the long run, because the slope
for domestic stock at time 1 is also negative
(Firebaugh 1992). The problem is not the
negative coefficient for foreign stock in the
stock and flow model, but ratherthe inter-
pretationof the coefficient. The key indepen-
dent variables-foreign capital flow and for-
eign capital stock-are components of for-
eign investment rate: Investment rate is, in
effect, the ratio of capital flow to capital
stock (Firebaugh 1992). With flow held con-
stant, the greaterthe stock, the lower the ra-
tio of capital flow to stock. So if investment
boosts economic growth, then the greaterthe
stock (holding flow constant) the slower the
investment and therefore the slower the
growth. In short, a negative coefficient for
foreign stock indicates a beneficial effect of
foreign investmentin the dependency model.
Researchers have simply misconstrued the
effect of the denominator as a "dependence
effect."
The Wimberley-Bello finding that foreign
investment has an adverse direct effect on
2 Based on Bornschier, Chase-Dunn, and
Rubinson (1978), dependency researchers have
incorrectly assumed that the coefficient for stock
reflects long-run effects whereas the coefficient
for flow reflects short-runeffects.

REVIEW
welfare is also an artifact. The problem in-
volves the use of a semi-difference model
(i.e., a model in which some variables are
differenced and others are not). Because the
semi-difference model can often yield mis-
leading results in cross-national research,
we propose the difference model as the pre-
ferredalternative.
THE CASE FOR DIFFERENCEMODELS
IN CROSS-NATIONALRESEARCH
Because of its concern with the harmful
long-term effects of foreign investment, de-
pendency research's objective is to estimate
long-run effects. Because cross-sectional re-
lationships tend to reflect adjustments to
change over the long run(Kuh 1959), cross-
sectional data are appropriatefor estimating
long-run effects (Hu 1973:96-98). Until the
middle or late 1970s, most cross-national
studies in sociology used cross-sectional
data, but most studies now use two-wave
panel data. We argue that the use of panel
datais appropriatefor the questionsraisedby
dependency theory,butthe particularmethod
used in dependency researchis suspect.
Consider the following model for N na-
tions, measured first at time 1 and again at
some later time 2:
Y- = i Xilpi3 Zi'y1+Eni
i=1, 2,...N;(1)
Yi2=a2 +Xi2 +Ziy2+Ei2; (2)
whereX andZ arevectorsof causal variables,
andf3
and yare vectorsof parameters.If there
are p variables in vector X, then X has di-
mension 1 x p and f3has dimension p x 1;
similarly, for q variables in vector Z, Z is
1 x q and yis q x 1. Usually Y,X, and Z are
logged to reducethe influence of outliers, but
this has no bearingon our conclusions.3
3Fortheusualcase in whicha loggeddepen-
dentvariableis regressed
on loggedindependent
variables,let Y= log(Y), X = log(X'), andZ =
log(Z') in equations1 and2. This modification
implies a multiplicativemodel in the original
metric,butdoesnotalterourargument.
(Wemust
also assumethatthe logarithm
is definedforthe
variablesin the model,butthatusuallyis nota
problemin cross-nationalresearchbecause a
nation'slevels of GNP,foreigninvestment,ex-
portactivity,etc., arenevernegative.)
The distinction between X andZ is critical
to the argument.Z represents variables that
differ across nations but are constant for na-
tion i from time 1 to time 2 (there is no sec-
ond subscriptfor Z, because Zil = Z,2 = Zi),
whereasX denotes variablesthatdiffer across
nationsandarenot constantfor nationi from
time 1 to time 2. The variables oil and 6i2 are
randomdisturbances,and we assume:
E(eil lxil) = E(eil lXi2) =
E(e,1 IZi)
=Oforalli, (3)
E(CEi2IXi)
= E(Ei2 |Xi2) = E(Ei2ZiZ)
=O foralli. (4)
PI and yl can be estimated without bias by
least squares(regressYi1on Xi, andZi); simi-
larly,02 and y2can be estimated without bias
by least squares(regress Yi2on Xi2 andZi).
Summarizing, then: f3and y reflect long-
run effects under the usual econometric as-
sumptions. Because the objective of depen-
dency research is to estimate long-run ef-
fects, the general model given by equations
1 and 2 applies widely in cross-national re-
search. And the model can be estimated us-
ing least squares.In principle, then, the esti-
mationof long-runeffects is straightforward.
As a practical matter, however, there are
complications.
Bias Due to OmittedZ Variables
Enduring traits of individual units are hard
to measure and often remain unmeasured
(Liker,Augustyniak, and Duncan 1985). Al-
though the authors cited individual human
traits, like "taste,"to illustrate the difficulty
of measuring "constant" individual traits,
their point applies equally to nations. Na-
tions areunique, andit is not hardto thinkof
constant(or nearlyconstant)unmeasuredna-
tionalcharacteristicsthatcould have substan-
tial effects on the outcomes development so-
ciologists study.Examples include a nation's
location, topography,climate, rainfall, min-
eral resources, type and quality of soil, ac-
cess to seaports, history, culture, economic
system, political system, legal system, city
system, religious composition, relationship
with neighbors, and so on. The importance
of such national attributesdepends on the is-
sue studied,of course. The point here is that,

because enduringnationalattributesoften are
hard to quantify, they are rarely included in
the data used by development sociologists.
Thus, when enduring attributes are impor-
tant-as we suspect they often are-the re-
sults of quantitative cross-national research
can be seriously biased because the assump-
tions expressed in equations 3 and 4 in gen-
eral will not hold when Z (or some relevant
component of Z) is omitted.
Difference Models
A simple solution to the problem of unmea-
suredZ variablesis to use a differencemodel
(Allison 1990; Liker,Augustyniak,andDun-
can 1985; Rodgers 1989) formedby subtract-
ing equation 1 from equation 2:
Yi2- YiI = *
+ XiA - XiA + Zi 2
-Zi1y + E,
= a + (Xi2 - XiI)P2
+(02- P )Xil +E; (5)
where a* = a2 - a1, i = -i2 - eil, and (we
assume) yI = y2. Unless the effects of X
change from time 1 to time 2,1 PI 32 and
the model reduces to:
Yi2- Yi = (* +(x2 -Xil)A2 +.i (6)
There are three importantpoints aboutthe
difference model (also called the "first-dif-
ference" model [Liker, Augustyniak, and
Duncan 1985] or "fixed-effects" model [En-
gland, Farkas, Kilbourne, and Dou 1988]).
First, the effects of the Z variables are re-
moved even though the variables are not ac-
tually measured.This follows from the equi-
valence of yj and y2, so that Ziy2- Ziy1= 0
in equation 5 (this difference is approxi-
mately zero when yj = y2).Second, all vari-
ables are measured as change scores. This
feature distinguishes the "true" difference
4Isaac and Griffin (1989) discussed the issue
of "periodizing" data to get constant effects in
time-series models (short-runor medium-runef-
fects). With difference models, we can test the
assumption of constant effects by using equation
5 instead of equation 6. In any case, when using a
difference model we want the time interval to be
sufficiently long so that observed change is not
largely measurement error or transient fluctua-
tion.
model from the "semi-difference"model of
dependency research, in which some vari-
ables are measured as change scores and
some arenot. Third,underthe usual assump-
tions about the disturbances given by equa-
tions 3 and4, 13
can be estimatedwithoutbias
by an OLS regression of change in Y on
change in X, because:
E(e7 1Xi2)= E(Ei2Ixi2- E(ejj |Xi2)
= 0 foralli, and
E(e, 1Xil)= E(ei2 |Xil) - E(ejj 1X1j)
=0 foralli. (7)
Because log(Y2) - log(YI) = log(Y2/YI),
and log(Y2/YI)measures the growthrateof Y
(Jackman1980; Firebaugh1992:equation3),
the difference-of-logs model is a growth-rate
model.5Putdifferently,a difference model is
a growth-rate model if the variables are
logged. This featureof the difference model
bearsdirectly herebecause cross-nationalre-
gressions often employ variables in their
logged form.The difference-of-logs form has
three advantages:It tends to yield more ro-
bust results because outliers exert less influ-
ence; it avoids out-of-bounds estimates (al-
though it can give out-of-bounds estimates
for infant survivalprobability);and its coef-
ficients have a ready interpretationas the ef-
fect of one rateon another.
Semi-DifferenceModels
Cross-national research in sociology cur-
rently is dominatedby estimation models of
the form:
5Theterm"rate"
heremeansrateof changein
somequantity.Thus,for example,GNPgrowth
ratefromtime I to time t refersto the level of
GNPattimet relativeto its levelattimeI (simi-
larlyfor foreigninvestmentrateand the other
variablesusedhere).Percentage
change,defined
as 1OO(Yt
- Y1)/Y1,
is a simpleratemeasure.A
percentage
changedoesnottakeintoaccountthe
lengthof the time interval,however,so the an-
nualrateof change-defined as [tthrootof Y/Yf]
- 1 wheret is measured
in years-is oftenused
instead.Forcross-national
data,anannual
growth
rateis virtuallyequivalentto the difference-of-
logsmeasure
(r> .999betweenthetwomeasures
for the variablesused in this analysis).We use
thedifference-of-logs
measureherefor theoreti-
cal reasons,todifferenceoutZ (equation
5).

REVIEW
Yi2= a +
3Y,1 +Xil'r+ Ei2, (8)
where ris a vector of parametersand X is a
vector of variables. Models of this form-in
which Yat time 2 is regressed on Yat time 1
and Xs at time 1-are so common in cross-
nationalresearch in sociology thatpractitio-
nersreferto them as "panelanalyses."6How-
ever, the termused in thatway is potentially
misleading, because it suggests that there is
only one way to analyze panel data. In any
case, the issue is whether the standard
"lagged-Y-regressor model" (equation 8)
yields reliable estimates of the long-run ef-
fects of the Xs (13
in equations 1 and2). Does
the inclusion of lagged Y on the right-hand
side of the equation tend to eliminate the ef-
fects of the Z variables, so that r approxi-
mates13?
The features of the model expressed by
equation 8 can best be appreciatedby noting
that the autoregression coefficient, 3, often
approximates1.0 in cross-nationalstudies. If
we estimate a lagged-Y-regressormodel with
fixed 3= 1, we have Yi2= a + Yia
+ Xil + ?E2,
or:
Yi2-Yil =a+Xpi +e1i2* (9)
In short, the "panel analysis" in vogue in
cross-national research is, for practical pur-
poses, a semi-difference model, because S =
1 in most instances. In fact, dependency re-
searchers sometimes justify their use of
"panelanalysis" on the groundthat it yields
the effect of the level of X (dependence) on
change in Y-an argumentthatimplicitly as-
sumes S= 1 (equation 9).
Because the semi-difference model fails to
difference all measuredvariables,equation 5
does not hold, so the model does not differ-
ence out the effects of the Z variables. As a
result, dependency research is vulnerable to
omitted-variables bias. The issue distills to
6 The meaningof "panelanalysis"appearsto
have broadenedover time in comparativere-
search-it now applies to virtuallyany model
with Y1as a regressor,includingthe stock-and-
flow model.Thecriticalpointhereis thatcross-
nationalresearchin sociologyhasbeenbasedon
a modelthatrelieson Y1to relieveomitted-vari-
ablesbias. This is fundamentally
differentfrom
the modelwe propose,in whichdifferencing
is
usedto reducethattypeof bias.
this: To avoid bias in semi-difference mod-
els, the unmeasured causes of Y must be
uncorrelated with the measured causes,
whereas difference models requireonly that
the unmeasuredcauses and their effects re-
main stable over the measurement interval.
This featureof difference models gives them
a significant edge over semi-difference mod-
els in cross-nationalresearch.
Furthermore,no one has yet made a con-
vincing theoretical case for semi-difference
models in dependency research (i.e., why
some variables should be differenced and
othersnot). Again, the use of "panelmodels"
is sometimes defended on the groundthat it
is the level of dependencethataffects change
in the dependent variable. But even this de-
fense can not withstand close scrutiny. The
"level-affects-change" model (equation 9)
implies:
Yi2 = a2 + YiI + Xil T + Ei2, (9a)
which, unless rchanges, implies:
Yii=--
Oa+YiO
+XioT+fils (9b)
Subtractingequation(9b) fromequation(9a)
yields:
Yi2- YiI= (a2 - al)+(YiI - YiO)
+(X il -Xo M) T + (Ei2 -Eil ) (9c)
Two points are evident, one methodologi-
cal and one theoretical. Methodologically, a
difference model (equation 9c) can be used
even if a researcherbegins with the premise
thatthe level of X affects change in Y(equa-
tion 9). Again, the rationale for using a dif-
ference model is to alleviate omitted-vari-
ables bias from enduring national character-
istics. The datarequirementsfor this particu-
lar difference model (equation 9c) are stiffer
than those for the simpler difference model
of equation 6 because equation 9c requires
observationsat threepoints in time.
Theoretically, if the level of X causes a
subsequent change in Y,as in the lagged-Y-
regressor model (equation 9), then the
change in X in one measurement interval
causes changein Yin the nextinterval.Equa-
tion 9c says that change in Y is caused by
change in X and Yduringthe previous inter-
val, thusassumingthatthe effects of changes

in X "lie dormant"until the next interval.Al-
though scholars can differ on whether the
dormancyperiod for the effects of tradeand
investment is one year, five years, or twenty
years, the interval in a simple difference
model can be extended beyond that dor-
mancy period. The important point is that
even if the level of X causes change in Y,that
is not a groundfor rejecting difference mod-
els because level -> change implies that
change - change.
Finally, single-equation models like stock-
and-flow models do not separatethe long-run
effects from the short-runeffects of depen-
dence. A single equationhas only one depen-
dent variable,not one reflecting short-runef-
fects andone reflecting long-runeffects. The
one dependent variablein a regression equa-
tion either has fully adjusted to changes in
the exogenous variablesor it has not, andthe
use of a semi-difference model provides no
special insight for making that determina-
tion.
MODELAND MEASUREMENT
To test the effects of economic growth and
dependence on changes in national welfare
in LDCs, we use data for 62 nations over a
23-year period, 1965-1988.7 Often in cross-
national research, variables are added willy-
nilly with little attentionpaid to the model's
overall coherence. We avoid such a patch-
work approachby employing consistent dif-
ference and difference-of-logs (growth-rate)
models throughout.
We estimate difference models for each of
four measures of a nation's welfare: caloric
consumption per capita (1965-1986), infant
survival probability (1965-1988), women's
7 The 62 nations areAlgeria, Argentina,Benin,
Bolivia, Brazil, Burundi, Cameroon, Central Af-
ricanRepublic, Chile, Colombia, Costa Rica, Do-
minican Republic, Ecuador, Egypt, El Salvador,
Ethiopia, Ghana,Greece, Guatemala,Haiti, Hon-
duras, India, Indonesia, Ivory Coast, Jamaica,
Kenya, Liberia, Madagascar, Malawi, Malaysia,
Mali, Mauritania, Mexico, Morocco, Niger, Ni-
geria, Pakistan, Papua New Guinea, Paraguay,
Peru,Philippines, Portugal,Rwanda,Senegal, Si-
erraLeone, Somalia, South Africa, South Korea,
Sri Lanka, Sudan, Syria, Tanzania, Thailand,
Togo, Trinidad and Tobago, Tunisia, Turkey,
Uganda, Uruguay, Venezuela, Zaire, and Zimba-
bwe.
life expectancy at age 1 (1965-1988), and
men's life expectancy at age 1 (1965-1988).
These measures are not easily monopolized
by the nation's rich. All measures are coded
so that regression results can be interpreted
without reversing the signs of the coeffi-
cients. Thus, for example, a positive slope
indicates a beneficial effect of dependence
on welfare, and a negative slope indicates an
adverse effect.
Our objective is to estimate the welfare
consequences of economic development in
poor nations. We measure economic devel-
opment as GNP(gross national product) per
person. To avoid spurious economic effects,
we also include a measure of investment in
humancapital (SCHOOL),
three measures of
dependence (INVEST,%EXPORT,
RAWEX-
PORT),and two terms to capture floor and
ceiling effects (GNPand WELFARE
level at
time 1). Using asterisks to denote logged
variables, the basic growth-ratemodel is:
WELFARE2 -WELFARE,
= JL
+#1,(GNP -GNP*)
+12 (SCHoOL2-SCHOOL,)
+13 (INVEST -INVEST1)
+14(%EXPONR RT)
+35 (RAWEXPORT2
- RAWEXPORT1)
+16(GNP*) + P7 (WELFARE*)+
+, (10)
where WELFARE
refers to one of the four
dependent variables (the subscripts "1" and
"2"refer to time 1 [1965] and time 2 [1988
for most variables]); GNPis gross national
product per capita; SCHOOLis secondary
school enrollmentas a percentageof eligible
population; INVESTis foreign capital stock
divided by gross domestic product(thus for-
eign investment is measured relative to the
size of the host nation's economy); %EX-
PORTis value of exports as a percentage of
gross domestic product;and RAWEXPORT
is
value of unprocessedexports as a percentage
of all merchandiseexports.
Equation 10 depicts a difference model
(i.e., all the measured variables are differ-
enced). We assume that P1I
= /32 (see equa-
tion 6)-that the effects of the Xs were the
same in 1988 as in 1965. However, because

REVIEW
preliminary analysis strongly suggested the
possibility of floor effects associated with
GNP, we include GNP*, as a separate vari-
able to test the constant-effects assumption.
The final regressor in equation 10, WEL-
FARE*,, is included because our welfare
measures have ceilings (infant survival
probability, for example, cannot exceed
1.0). We include Y1(WELFARE,) as a re-
gressor in order to capture ceiling effects,
not to reduce the biasing effects of omitted
variables.8
Dependent Variable:
Measures of National Welfare
Peering throughthe lens of affluence, West-
ern social scientists often fail to see grada-
tions in living standardsamong the peoples
of poor countries. Yet clearly there are gra-
dations in importantthings, like life expect-
ancy. Efforts to collect reliable data on life
expectancy and other indicatorsof a nation's
welfare have intensified in recent decades,
and we now have bettermeasures and wider
coverage than were availablepreviously.
We use welfare measures (1) that the rich
cannot readily monopolize (Hibbs 1973) and
(2) that are not ethnocentric.Avoiding mea-
sures that the rich can monopolize is critical
in light of the popular view (in sociology)
thatforeign investmenttends to dramatically
increase inequality in the Third World(i.e.,
it tends to benefit the rich and hurtthe poor).
To avoid ethnocentrism, we base our mea-
sures on a set of what we consider to be
minimal valuejudgments: Long life is good,
hunger is bad, and infant deaths are bad. "It
seems to me better that people should live
ratherthan die: that they shouldn't be hun-
gry: that they shouldn't have to watch their
children die" (Snow 1963:78).
Our measure of the absence of hunger is
caloric consumption per person per day,
1965-1986. We use infant survival prob-
ability, 1965-1988, ratherthan the more fa-
miliar infant mortality ratebecause we want
8 Ceiling effects imply 37 < 0 in equation 10. If
we isolate WELFARE*2on the left-hand side of
equation 10, the coefficient for WELFARE*,be-
comes (1 + 17). Thus, ceiling effects imply that
the autoregression slope is less than 1 (see
Firebaugh 1983 for examples of theories predict-
ing ceiling effects for economic growth).
to code all welfare measures in the positive
direction. We define the infant survival
probability as the probability that an infant
survives to age 1:
Infantsurvivalprobability=
1 - (Infantmortalityrate/1000).
Ourmeasureof length of life is life expect-
ancy at age 1, 1965-1988, calculated sepa-
rately for men and women. We use Morris's
(1979) equations to estimate life expectancy
at age 1. (We use age 1 to avoid redundancy
with the infant survivalprobability.)
Caloricconsumptionpercapita,infant sur-
vival, and life expectancy improved in most
LDCs over the years studied here (Interna-
tional Bankfor ReconstructionandDevelop-
ment 1990; Bradshaw, Noonan, Gash, and
Sershen 1993:table 2). Moreover, it is clear
from the aggregate figures that these in-
creases could not have benefited only the
rich: Averages for the 62 nations increased
nearly a standard deviation in less than a
quartercentury (Appendix Table A). If by
"the masses" we mean, for example, the
pooresttwo-thirdsof thepopulation,then the
masses must have received some benefit. If
benefits accruedonly to the richest one-third
of the population, then those privileged
people now areconsuming 774 morecalories
per day than they were two decades ago
(when they were doubtless already consum-
ing morethanthe average);their life expect-
ancies haveincreasedby 20 yearsinjust over
two decades; and their infants have more
thana 1.0 probabilityof surviving!
Exogenous Variables
Gross national product per capita. We use
the World Bank's GNP estimates (Interna-
tional Bankfor ReconstructionandDevelop-
ment 1990), 1965-1988 (1965 and 1986
when caloric consumption is the dependent
variable). This period subsumes the 1965-
1977 period used in the Bornschier and
Chase-Dunn(1985) dataset.
Investment dependence. Consistent with
dependency studies, we use the Ballmer-Cao
and Scheiddegger (1979) data on foreign in-
vestment, updated by United Nations data
(United Nations Centre on Transnational
Corporations 1983). Consistent with Cren-

shaw (1991), we use the period 1967-1978
(a choice dictated by data availability),
which is almost twice as long as the 1967-
1973 intervaltypical of dependency studies.
Export dependence. We follow prior stud-
ies in distinguishing quantityandtype of ex-
port. Nations areexport-dependentto the ex-
tent that (1) exports constitute a significant
fractionof theirnationalproduct,thusorient-
ing theireconomies towardthe productionof
goods for export; and (2) raw goods are ex-
portedfor processing elsewhere, thus depriv-
ing the exporter of the value added by pro-
cessing, as well as reinforcing the exporter's
supplierstatus.The firstformof dependence,
%EXPORTS,is measured by the value of
merchandiseexportsrelativeto gross domes-
tic product. The second, RAWEXPORTS,
is
the value of unprocessed goods (nonfuel, to
be consistent with Wimberley and Bello
1992) as a percentage of all merchandiseex-
ports.
Human capital investment.The "new neo-
classical theory of development,"an emerg-
ing paradigmin economics, stresses the im-
portance of knowledge and education for a
nation's development (Barro and Becker
1989; Lucas 1988; Romer 1990). For most
LDCs,investmentin educationrepresentsthe
most significant outlay for human capital.
Enrollment estimates for primary and sec-
ondary school are available for nearly all
LDCs. Primary schooling became virtually
universal in many LDCs during the years
studied here, posing problems of ceiling ef-
fects, so we use secondary enrollment as a
percentage of the population of secondary
school age children.
THEEFFECTSOFECONOMICGROWTH
ON NATIONALWELFARE
Estimates Based on Difference Models
Table 1 reports the estimated effect of eco-
nomic growth on change in a nation's wel-
fare for each of the fourmeasuresof welfare.
These estimates are based on difference
models, as opposed to the semi-difference
models used in previous research. In a nut-
shell, we find strong effects of economic
growth and weak effects of dependence.
Because results for the difference models
deviate sharply from those usually found by
sociologists (but not economists), we take
care to ensure thatour results are robust.We
first estimate the basic equation using both
the logged variables (the difference-of-log
model) and "raw"metric forms (difference
model) of the variables.Wepreferthe logged
form, because its results are less vulnerable
to outliers, as a comparison of the skewness
values makes clear.In the logged form, most
of the regressors have skewness levels close
to zero (no skew), and in no instance does
skewness exceed 1.0 in absolute value. In the
unlogged model, by contrast, four of the
seven regressors are substantially skewed to
the right(skewness > 1.0), andone is skewed
to the left (skewness < -1.0). More impor-
tant, economic growth and foreign invest-
ment are both skewed to the right-invest-
ment severely so (skewness = 4.24) in the
unlogged model. These skewness levels sug-
gest thatthe results might be inordinatelyin-
fluenced by a few nations. To safeguard
against such outliers, we employed the usual
diagnostic checks.9 However, we rely on the
differences-of-logs results and use the un-
logged results as supplementary.
In sharp contrastto Wimberley and Bello
(1992), the effect of economic growthdwarfs
the effects of dependence in determiningthe
welfare of the masses in these Third World
countries. The coefficient for economic
growth is statistically significantly for all
four of the dependent variables, whereas
only three of the 12 coefficients for the de-
pendence variables attain statistical signifi-
cance. The slope for foreign investment
never attains statistical significance, al-
though we would conclude that foreign in-
vestment has a significant positive effect on
9 After identifying the countries that had the
strongest influence on our results for the two key
variables-economic growth and foreign invest-
ment-we re-estimatedour coefficients for Table
1 omitting those nations. We relied on the
DFBETA statistic to identify influential nations
(Belsley, Kuh, and Welsch 1980; Bollen and
Jackman1985). Again we find positive effects for
economic growth andweak or nonexistent effects
for foreign investment.
10Our62 nations are not a probability sample,
so conventional probabilityinterpretationsarenot
appropriate.The tests nonetheless provide a uni-
form criterion for evaluating the fragility of esti-
mates in cross-national research.

REVIEW
Table 1. Estimated Metric Slopes for Regressions of Four Measures of National Welfare on Economic Growth,
Human Capital, and Foreign Dependence: Difference-of-Logs Model and Difference Model, 62 Less
Developed Countries, 1965 to 1988
Dependent Variable
Infant Life Expectancy at Age 1
Model and Caloric Survival
IndependentVariable Consumption Probability Women Men
DIFFERENCE-OF-LOGSMODEL (GROWTHRATE MODEL)
GNP per capita .135** .019** .061** .065**
[skewness = .11] (3.45) (3.01) (3.67) (3.73)
Percentenrolled in secondary school -.023 -.001 -.004 -.001
[skewness = .71] (-.88) (-.27) (-.31) (-.10)
Foreign investment as percent of GDP -.008 -.003 .012 .011
[skewness =-.05] (-.41) (-.85) (1.57) (1.42)
Exports as percent of GDP -.0002 -.0002 -.015* -.021**
[skewness = .42] (-.01) (-.08) (-2.13) (-2.82)
Raw materialexports as percent of all -0.04* -.003 -.006 -.004
exports [skewness =-.14] (-2.11) (-1.16) (-.86) (-.57)
Ceiling/Floor Effects
1965 level of dependent variable -.401** -.384** -.385** -.402**
(-3.60) (-6.27) (-6.11) (-6.24)
1965 GNP per capita .050* .010** .029** .025**
[skewness = .20] (2.65) (2.82) (3.13) (2.76)
Largest variance inflation factor 1.51 2.48 3.11 3.09
Adjusted R2 .41 .45 .47 .50
DIFFERENCEMODEL
GNP per capita .279** .000 .002* .001*
[skewness = 2.20] (4.01) (.05) (2.11) (2.14)
Percent enrolled in secondary school 3.83 .0003 .078** .076**
[skewness = 1.14] (1.45) (1.63) (2.73) (2.84)
Foreign investment as percent of GDP 22.56 -.0004 .341 .230
[skewness = 4.24] (.37) (-.12) (.54) (.38)
Exports as percent of GDP -.925 .0002 -.033 -.045*
[skewness =-1.48] (-.45) (1.28) (-1.55) (-2.23)
Raw materialexports as percent of all -2.61 -.0002 -.022 -.014
exports [skewness = .52] (-1.92) (-1.95) (-1.55) (-1.05)
1965 level of dependent variable -.360** -.248** -.232** -.251 **
(-2.72) (-4.04) (-3.68) (-4.09)
1965 GNP per capita .022 .000 -.0003 -.001
[skewness = 2.25] (.35) (.32) (-.39) (-1.10)
Adjusted R2 .36 .30 .27 .32
p <.05 **p< .01 (two-tailed tests)
Note: Skewness is .40, .16, .08, and -.07, respectively, for 1965 calories, infant survival, women's life expect-
ancy, and men's life expectancy in the difference-of-logs model. Skewness is .82, .25, .31, and .18, respectively,
for 1965 calories, infant survival, women's life expectancy, and men's life expectancy in the difference model.
Results for infant survival probability in the difference model should be interpreted cautiously because of the
possibility of out-of-bounds estimates. Numbers in parenthesesare t-statistics.

women's and men's life expectancies if we
predicted such an effect and used the gener-
ous a-levels common in dependence re-
search.II
Estimates employing the unlogged differ-
ence model (Table 1) tell basically the same
story about the effects of economic growth
and dependence: Three of the four coeffi-
cients for economic growth are significant,
whereas only one of the 12 coefficients for
the dependence variables is significant. Re-
sults for the control variables change some-
what:The GNP floor effect is no longer sig-
nificant and the effect of the school enroll-
ment variableis now positive.
Floor/Ceiling Effectsfor Dependence
Variables
Concerningthe failureto find harmfuleffects
for foreign investment, an anonymous re-
viewer argued that "a country where the
transnationalshare is minuscule but rapidly
growing is unlikely to be much affected [by
the foreign investmentrate]. .. ."To find out
if floor effects suppressthe effects of depen-
dence, we re-estimatedthe difference-of-logs
models of Table 1, adding terms to capture
the effects of initial levels of foreign invest-
ment stock, export volume, and unprocessed
exports. By adding terms for the initial lev-
els of these variables, we in effect relax the
constancy-of-effects requirement (l1 = 02,
see equation 5) for investment dependence
and tradedependence.
Results remain the same after controlling
for initial levels of the dependence variables
(Table 2). Economic growth consistently af-
fects the four welfare measures; the depen-
dence variables do not (only one of the 12
coefficients is significant, and it is positive).
If dependence on foreign investment has a
devastating effect, that effect should be evi-
dent because we are examining an era when
foreign investment in the Third World was
substantial (Gillis, Perkins, Rolmer, and
Snodgrass 1983:table 14.1). Yet we find no
evidence of a pernicious effect of foreign in-
II One-tailed tests, a = .10, are popular(Wim-
berley and Bello 1992), as are two-tailed tests
based on It I> 1.5 (London 1987, 1988; London
and Smith 1988; London and Williams 1990),
which corresponds roughly to a = .13.
vestment in these data: Whether or not the
initial level of foreign investment is con-
trolledfor, foreign investmentexhibits no di-
rect effect on national welfare growth.
Table 2 could be objected to on the
grounds that, if dimensions of dependence
are interrelated, including six measures of
dependence in the same equation inflates the
standarderrors (note the larger variance in-
flation factors for Table 2) and thus reduces
the likelihood of statistically significant re-
sults. The inflationof standarderrorsis more
likely to be a problemwith initial levels than
with rates, because levels tend to be more
highly correlated. To address this concern,
we re-estimated Table 2 using all combina-
tions of the three level-of-dependence vari-
ables. Since there are seven combinations
and four dependent variables, we estimated
28 models in all. Briefly, the resultsreinforce
those of Tables 1 and 2: Economic growth
has a positive, statistically significant effect
(p < .05, two-tailed tests) in all 28 regres-
sions, andthe slope for foreign investment is
never statistically significant. The slope for
initial level of foreign investment is signifi-
cant only twice (negative in both instances),
and initial level of trade dependence never
has a significant negative effect while in 13
instances the coefficient is statistically sig-
nificant andpositive.
Resultsfor SimultaneousEquation Models
Simultaneity bias is anotherpotential prob-
lem in our analysis. A literaturein develop-
ment economics is based on the premise that
improvement in national welfare can fuel
economic expansion. This "basic needs" ap-
proach(Hicks andStreeten 1979; Streetenet.
al. 1981) turns on its head the popular as-
sumption (among economists) that countries
can best alleviate poverty by focusing on
economic growth. In the basic needs ap-
proach, development programsare designed
explicitly to meet the needs of the masses for
food, shelter,clothing, elementarysanitation,
and access to potable water.To the conven-
tional argumentin economics thatsuch "con-
sumption expenditures"could lower invest-
ment and thus sacrifice long-run economic
gain at the altarof fleeting welfare improve-
ment, proponents reply that in the Third
World the provision of basic needs to the

REVIEW
Table 2. Estimated Metric Slopes for Regressions of Four Measures of National Welfare on Economic Growth,
Human Capital, and Foreign Dependence: Difference-of-Logs Model Controlling for Initial Levels of
Dependence, 62 Less Developed Countries, 1965 to 1988
Dependent Variable
Caloric Survival
GNP per capita .110 * .018** .053** .056**
(2.92) (2.99) (3.28) (3.34)
Percentenrolled in secondary school -.009 -.002 -.002 -.001
(-.36) (-.57) (-.22) (-.05)
Foreign investment as percent of GDP -.008 -.003 .011 .010
(-.43) (-1.20) (1.53) (1.34)
Exports as percent of GDP .053 .011* .009 .008
(1.86) (2.57) (.81) (.69)
Raw materialexports as percent of all -.034 -.003 -.008 -.006
exports (-1.80) (-1.08) (-1.05) (-.88)
(-4.11) (-7.04) (-6.33) (-6.55)
1965 GNP per capita .066** .01I** .030** .025*
(2.88) (2.78) (2.78) (2.38)
Adjusted R2 .48 .52 .52 .57
Up< .05 *p < .01 (two-tailed tests)
Note: Numbers in parentheses are t-statistics.
masses is a formof humancapitalinvestment
(especially in health, which affects individu-
als' productive capabilities) that pays off in
more rapideconomic growth. In short, there
is no necessary trade-off of short-termwel-
fare for long-run economic gains; countries
can have both (Hicks 1979).
Many economists remain skeptical of this
claim. In a recent survey of the basic needs
literature, Afxentiou (1990:241) concluded
that claims that fulfillment of basic needs
promotes growth "remain unsubstantiated."
Such skepticism among economists notwith-
standing, the basic needs approach has at-
tracted attention in sociology and political
science (Bullock 1986; Moon 1991; Moon
and Dixon 1992; Thomson and Newman
1988), where it has been accordeda more fa-
vorable reception.
For our purposes, the important point is
that the basic needs approachpoints to the
possibility of welfare affecting economic
growth, thus possibly producing simultane-
ity bias in our estimates of the effects of
economic growth on welfare. Lagging one
of the endogenous variables (as in standard
"panelanalysis") is not a foolproof solution.
Lagging may serve only to hide the prob-
lem, not solve it. To see why, consider again
the effects of the Zi, the unmeasuredendur-
ing causes. Because Z affects Y,if there are
reciprocaleffects from Yto X, Z will affect
X indirectly through Y.In this way, the un-
measured Zi will be correlated with the
measured causes in the standard "panel
model" (equation 8), resulting in biased es-
timates (Heise 1970:fig. 3). Although the X
variables might have been correlated with
the Z variables even without reciprocal ef-
fects from Yto X, reciprocal effects can in-
flate the correlation.
Therefore, we re-estimated the welfare
benefits of economic growth using a simul-
taneousequationmodel thatallows for recip-
rocal effects between national welfare and
economic growth. This requires two equa-
tions-one for economic growth and one for
welfare growth. Domestic investment is a
critical determinant of economic growth
(Firebaugh1992), so we addedit as an exog-

Table 3. EstimatedMetric Slopes for Regressions of FourMeasuresof National Welfare on Selected Independent
Variables: Two-Stage Least Squares Estimates for Simultaneous Equation Models, 62 Less Developed
Countries, 1965 to 1988
Dependent Variable
Caloric Survival
GNP per capita .228** .017* .077** .073**
(4.44) (2.05) (3.21) (2.88)
Percent enrolled in secondary school -.010 -.001 -.006 -.004
(-.36) (-.24) (-.52) (-.30)
(-3.76) (-5.80) (-5.30) (-5.14)
1965 GNP per capita .058** .010** .031** .025*
(3.03) (2.92) (2.86) (2.28)
.p< 05 * < .01 (two-tailed tests)
Note: Predictors of economic growth (in addition to change in welfare) are: domestic investment, foreign in-
vestment, school enrollment, and initial level of GNP. Numbers in parentheses are t-statistics.
enous variable. To identify the model, we
imposed two restrictions, both in line with
those imposed by some studies in the eco-
nomic growth/ basic needs "trade-off' litera-
ture. First, consistent with Moon and Dixon
(1992), we assume thatcapital investment-
mostly in plants and machinery-affects na-
tional welfare only throughits effect on eco-
nomic growth. (We allow for a direct effect
from school enrollmentto welfare, however,
because schooling can increase knowledge
abouthealth andnutrition.)Oursecond iden-
tifying assumption is that the initial level of
a welfare variable affects economic growth
only throughits effect on change in welfare.
The initial level of a welfare variablewas in-
cluded in the welfare equationsto capturethe
ceiling effect. Aside from that, there is no
good reason to suppose that 1965 welfare
levels affect 1965-1988 economic growth.
Table 3 reportsthe two-stage least squares
(2SLS) estimates of economic growthon na-
tional welfare for the simultaneous equation
model just described.'2Results are the same
12 Because we are investigating the determi-
nants of welfare growth, we do not report 2SLS
results for the equations predicting economic
growth (available from the authors on request).
Briefly, our results are in line with theory and
earlier studies: We find statistically significant
effects of investment in the expected positive di-
as those from the single-equation model:
Economic growthhas a positive effect on all
four indicatorsof welfare.
THEEFFECTSOFDEPENDENCE
Resultsfor Reduced-FormModels
The disappointingperformanceof the depen-
dence variables-especially foreign invest-
ment-in the difference model suggests that
priorresearchmayhaveexaggeratedtheirto-
tal effects (directandindirect)on welfare. To
find out, we re-estimated the difference-of-
logs models without the intervening eco-
nomic variables. Table 4 reports the results
for this reduced-formmodel. Of the 12 coef-
ficients for the dependencevariables,five are
statistically significant: two for foreign in-
vestment (both positive), and three for raw
materials exports (all negative). Based on
these findings, it would be prematureto con-
clude that adverse effects of dependence
don't exist. But these results-and the results
of dozens of other models we estimated, not
reportedhere-all tell the same story: There
is no credible cross-national evidence that
foreign investmentis the leading cause of the
"immiseration"of the world's poor.
rection,andsignificantreciprocal
effects for in-
fantsurvivalprobability
andlife expectancy.

REVIEW
Table 4. Estimated Metric Slopes for Regressions of FourMeasures of National Welfare: Reduced-Form Depen-
dence Models, 62 Less Developed Countries, 1965 to 1988
Dependent Variable
Caloric SuvIvnfant Life Expectancy at Age 1
Foreign investment as percent of GDP .002 -.002 .018* .018*
(.08) (-.65) (2.25) (2.23)
Exports as percent of GDP .014 .003 -.007 -.013
(.70) (1.05) (-.97) (-1.67)
Raw materialexports as percent of all -.067** -.007** -.014* -.011
exports (-3.74) (-2.68) (-2.05) (-1.57)
1965 level of dependent variable -.236* -.240** -.215** -.251**
(-2.17) (-5.65) (-5.28) (-5.91)
Adjusted R2 .21 .36 .35 .39
<.05 *p < .01 (two-tailed tests)
Note: Numbers in parentheses are t-statistics.
Testingthe Distorted-GrowthHypothesis:
Are Returns-to-GrowthLower in More
Dependent LDCs?
In the distorted-growth version of depen-
dency theory,more dependentnationscould,
on average, grow as fast as less dependent
nations, but the payoff in national welfare
will be nonexistent (or smaller) for the more
dependent nations. To determine if welfare
benefits in the Third World are conditional
on a nation's level of dependence, we re-es-
timatedthe coefficients for growth, using an
interaction design. If the distorted-growth
thesis has merit-and if dependence has the
paramounteffect dependency researchersat-
tributeto it-that effect should be detectable
when more dependent nations and less de-
pendent nations arecompared.
We use the median to classify the LDCson
dependence (high versus low),13 andestimate
13 Anycutoffpointis somewhatarbitrary,
but
the medianis attractive
becauseit yields equal-
size groups-an important
consideration
hereas
there are only 62 nations.Simply multiplying
economicgrowthby the level of dependence-
whendependence
is on anintervalscale-won't
do when N = 62, owing to severe multicollin-
earityproblems.
Usingthemediantoclassifythe
62 nationsas "moredependent"
and"lessdepen-
dent"producesgroupssharplydifferentwithre-
gardto dependence(e.g., annualforeigninvest-
the interaction effect separately for invest-
ment dependence and tradedependence. (To
rankthe LDCson tradedependence, we stan-
dardized and summed the two measures of
exportdependence.) In the strong version of
the distorted-growththesis, economic growth
does not benefit the masses at all in depen-
dent nations. In the weak version, economic
.growth has a positive effect, but the effect is
smaller thanit is in less dependent nations.
To search for strong and weak distorted-
growth dependence effects, for each of the
indicators of national welfare we estimate a
model with two termsfor the benefits of eco-
nomic growth-one term for high depen-
dence nations,andone termfor thedifference
in benefits between moredependentand less
dependent nations. The latter is an interac-
tion term,economic growthmultiplied by D,
whereD is adummyvariablecoded 1for less
dependent nations. By coding this way, the
estimated benefits to economic growth are:
Ph
GNPGROWTH
+ 12(GNPGROWTH
x D) =
(pi + 12) for low dependence nations;
P3I
for high dependence nations.
mentrateaverages12.9percentforthemorede-
pendentgroupof nationsversus2.8 percentfor
theless dependent
group).

Table 5. Effects of Economic Growth for More Dependent Versus Less Dependent LDCs
Effect of Economic Growth
More Dependent Less Dependent
Welfare Measure and LDC's (pi) LDC's Difference (12)
Type of Dependence (1) (2) (3)
Caloric Consumptionper Capita
Investment dependence .111* .266** .156*
Tradedependence .110* .232** .122
InfantSurvival Probability
Investment dependence .011 .036** .025*
Tradedependence .021** .019* -.002
Women'sLife Expectancy at Age I
Investment dependence .070** .059* -.010
Tradedependence .054** .080** .026
Men's Life Expectancy at Age I
Investment dependence .060** .064* .003
Tradedependence .054** .076** .022
p <.05 **p< .01 (two-tailed tests)
Thus, fPI
represents the welfare returnsto
economic growthin moredependentnations,
and 12is the difference in those returns,less
dependentnationsminus moredependentna-
tions. The test for distorted-growththeory is
straightforward:We test f3A
= 0 (strong ver-
sion of the theory)andP2> 0 (weak ver-
sion). 14
Table 5 indicates thatthe strong version of
distorted-growth theory receives little sup-
port: P3I
is positive in all eight regressions
andattainsstatistical significance in seven of
the eight (column 1). Apparently,the masses
benefit fromeconomic growtheven in highly
dependent LDCs. The weak version of the
theory does somewhat better: 12 is positive
14Thecontrolvariables
areD,thedummy
vari-
able indicatingmoredependentversusless de-
pendentnations(to allowfordifferentintercepts
formoreandless dependent
nations),schoolen-
rollment,andthe two ceiling/flooreffectsterms
(initial level of the welfarevariableandinitial
GNP).We do not enterinvestmentdependence
and tradedependenceas (continuous)control
variablesbecause we are testing the distorted
growththeory,notthe depressedgrowththeory.
Finally,to determineif economicgrowthhas a
statisticallysignificanteffect for less dependent
nationsin Table5, we reversedthecodingof D
andre-estimated
usingtherevisedcoding.
and statistically significant (as predicted) in
two of the eight regressions (column 3). In
both instances, it is investment dependence,
not trade dependence, that reduces the wel-
fare benefits of economic growth. Though
scarcely a ringing endorsement of general
dependency theory, these results offer some
tantalizing supportfor a weak version of the
theory. Perhaps reliance on foreign invest-
mentdoes reducethe welfare benefits of eco-
nomic growth in the ThirdWorld.Yet if that
is all thereis to dependencytheory,why does
it captivate sociologists? The view that im-
ported capital may not be as beneficial as
domestic capital is hardlya startling revela-
tion to development scholars.
CONCLUSIONS
The role of economic growthin betteringthe
human condition is a defining issue of our
era. Yet that issue is relatively neglected in
comparative sociology, where it is most of-
ten assumedthatdependence-not economic
growth-is the ascendantforce affecting na-
tional welfare. Based on data for 62 LDCs
over two decades, we estimated the effects
of economic growth anddependenceon food
consumption, infant survival, and life ex-
pectancy.Thereare three majorconclusions.

REVIEW
TheImportanceof Modeling in Cross-
National Research
Our data and measures are the same as, or
similar to, those used by dependency re-
searchers, yet our conclusions diverge
sharply.Why? In a word, modeling. We use
a difference model in place of the semi-dif-
ference model (including the stock-and-flow
model) that is standard in dependency re-
search.
While the difference model is not a pana-
cea, there are serious deficiencies in the
models used in dependency researchthatun-
dermine the credibility of thatresearch:
(1) The use of rates and rate components
(stock and flow) in the same model.
This, combined with the assumptionthat
the coefficient for capital stock attime 1
reflects long-rundependence effects, re-
sulted in a researchliteraturebased on a
statistical artifact.
(2) Inattention to the possible confounding
effects of unmeasuredenduringnational
characteristics.
(3) The tendency to treata model as a mot-
ley collection of variables-some
logged, some not; some differenced,
some not-without considering suffi-
ciently the problems of interpretingthe
coefficients for such a model.
The Centralityof Economic Growth
Ourresults assert the primacy of indigenous
conditions for nationaldevelopment(see also
Lenski and Nolan 1984; Nolan and Lenski
1985) rather than asymmetric international
exchange. Economic growth has demon-
strable benefits on national welfare in the
Third World. Economic growth is the only
variable (aside from the ceiling effect term)
that shows consistent, nontrivial effects on
all four indicatorsof nationalwelfare. These
beneficial effects of economic growthremain
after controlling for investmentdependence,
exportdependence, and schooling.
This finding, combined with the earlier
finding that dependency researchers have
unwittingly shown that foreign investment
tends to boost growth (Firebaugh 1992),
suggests that sociologists should reconsider
theirpreoccupation with dependency theory.
To inform development policy, we need fur-
ther research on the size of welfare returns
to economic growth and the conditions that
maximize those returns. Comparative re-
search in sociology should examine the ef-
fects of rising income on living standardsin
the ThirdWorldbecause that issue bears on
the daily experience of billions of people.
Moreover, a naturaldivision of labor exists
between development economists and devel-
opment sociologists: Economists study the
causes of economic growth; sociologists
study the consequences of economic growth
for national welfare. Policymakers and
economists frequently fail to consider wel-
fare consequences because economic policy
often merely assumes that economic growth
has salutaryeffects. Sociologists are less in-
clined to make such an assumption, yet de-
velopment sociologists rarely estimate the
effects of economic growth in the Third
World.
The belief that economic growth benefits
most people is the bedrock assumption of
much development policy. Until there is
credible cross-national evidence that eco-
nomic growthis irrelevantto welfare, devel-
opment specialists will remain skeptical of
resultsfromsociological analyses of national
welfare that fail to consider fully the effects
of economic growth.
TheExaggerated Effects of Dependence
Recent workin sociology puts forththe revi-
sionist view that foreign dependence, not
economic growth, is what matters for the
poor in LDCs. Foreign investment "has an
exceptionally strong harmful effect on con-
sumption . . . [resulting in] immiseration in
the non-core" (Wimberley and Bello 1992:
895, 915). London (1988) wrote thatforeign
investment "clearly distorts development in
ways that impede fertility decline" (p. 615).
Boswell and Dixon (1990) concluded that
dependence"gives rise to rebellion"(p. 555).
And so on.
This claim of the devastatingeffects of de-
pendence is feckless. Though some types of
foreign investmentandtrademay harmLDCs
under certain circumstances, robust depen-
dence effects are hardto find in the empiri-
cal cross-national record. Whether the de-
pressed-growth, distorted-growth, or inde-

pendent-of-growth versions of dependency
theory are examined, the empirical support
is spotty at best.
(1) Depressed-growth version. In this ver-
sion, dependence immiserates the poor by
reducing the size of the economic.pie or
slowing economic growth. Evidence for de-
pressed-growthconsists of interpretationsof
a denominatoreffect as a dependence effect
in a stock-and-flow model. Correctionof this
errorleads to the conclusion thatforeign in-
vestment boosts economic growth.
(2) Distorted-growth version. In this ver-
sion, dependence immiserates the poor by
reducing the welfare benefits of economic
growth-but it does not reduce economic
growth. We test this thesis with models that
are true to the thesis (i.e., interaction mod-
els). Because our findings are mixed, we
withhold judgment on the distorted-growth
thesis pending furtherresearch. Of the three
versions of dependencytheory,this one holds
the most promise.
(3) Independent-of-growthversion. In this
version, dependence immiseratesthe poor by
reducing the amountof the economic pie go-
ing to the masses, independentof changes in
the size of the pie. Wimberley and Bello
(1992) claimed that foreign investment pro-
duces this effect, but we failed to replicate
their finding when we replacetheirsemi-dif-
ference model with a difference model.
By using terms like "immiserate,"depen-
dency researchers suggest that dependence
causes the lot of the masses to deterioratein
absolute as well as relative terms. During
periods of economic growth, then, depen-
dence must cause inequality to increase so
severely that the masses lose in absolute as
well as in relative terms. Yet there is no
credible cross-national evidence for such a
claim. Even in the most dependent LDCs,
the masses tend to benefit from economic
growth.
GLENN FIREBAUGH is Professor of Sociology at
The Pennsylvania State University and Senior
Scientist at the University's Population Research
Institute. His principal interest is in social
change: In addition to using cross-national data
to study change in the Third World,he uses sur-
vey data to study cohort replacement's contribu-
tion to change in the United States. Current
projects include a studyof the enduringeffects of
women'spre-1920 disenfranchisementin the U.S.
(forthcoming in the American
Journal
of Sociol-
ogy) and a study of democratization and market
values in Romania.
FRANK D. BECK is a Ph.D. candidate in the De-
partmentof Sociology at The Pennsylvania State
University. His current workfocuses on the con-
sequences of economic restructuringfor state au-
tonomy,communitydevelopment,and social well-
being. His dissertation research on the practical
and theoretical significance of state-designated
enterprise zones has beenfunded by the Depart-
ment of Housing and UrbanDevelopment and by
the National Science Foundation.
Appendix Table A. Initial Levels of Four Measures of National Welfare and Change, 1965 to 1988: 62 Less De-
veloped Countries
Standard Mean
Mean Deviation Change
Variable (1965) (1965) (1965-1988)a
Caloric consumption per capita 2200.40 314.98 257.68
Infantsurvival probability .87 .05 .05
Life Expectancy at Age I
Women 57.75 8.17 7.44
Men 54.37 7.66 6.66
aIntervalis 1965-1986 for caloric consumption per capita.

REVIEW
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