Rural Sociology 56(1), 1991, pp. 1-21Copyright © 1991 by the Rural Sociological Society

Female Labor Force Participation in Urban andRural China 1

Richard E. Barrett, William P. Bridges, Moshe Semyonov,* andXiaoyuan Gao*Deportment oj Sociology, University oj Tel Aviv, Tel Aviv, Israel andDepartment oj Sociology, University oj Illinois at Chicago,Chicago, Illinois 60680

ABSTRACT The objective of this study is to examine female labor forceparticipation and its determinants in rural and urban China. The socio­logical literature has demonstrated that participation tends to increase inurban and industrialized places where women have higher levels of edu­cation and fewer children, where more workers are engaged in servicepursuits, and where family structure is less traditional. With the use ofdata on counties and cities (N = 2,377) from the I-percent sample of the1982 census of the People's Republic of China, it was found that femalelabor force participation is likely to rise in areas with increased agriculturalemployment, educational levels, proportion of female-headed households,and higher male-to-female sex ratios. Both the size of the service sectorand the fertility rate had negligible effects on female labor force partici­pation. Although, on average, rural places have slightly higher levels offemale labor force participation, when other variables are controlled, ur­ban places have a higher rate of female participation. In addition, thefindings suggest that market factors (i.e., education) are more likely todetermine the rate of female labor force participation in urban areas;whereas demographic and social factors (i.e., sex ratio and householdstructure) playa more important role in explaining the female labor forceparticipation in rural counties.

Introduction

One of the most significant aspects of social change in the secondhalfof the twentieth century has been the dramatic increase in femalelabor force participation in almost all nations. Consequently, a con­siderable body of research has examined structural determinants offemale labor force participation. This literature clearly demonstratesthat participation is strongly influenced by level of industrialization,fertility rate, family structure, social composition, and spatial locationof the areal-social unit. These factors appeared to exert significanteffects on participation in large cities and small rural communities inboth developed and less developed countries (Cain and Dooley 1976;Durand 1975; Pampel and Tanaka 1986; Semyonov 1980, 1983;

I The authors gratefully acknowledge helpful comments from Xiangming Chen,computational assistance rendered by Ms. Betsy McEneany, and financial support pro­vided by the Campus Research Board, University of Illinois at Chicago.

2 Rural Sociology, Vol. 56, No.1, Spring 1991

Semyonov and Shenhav 1988; Ward 1983; Ward and Pampel 1985;Weiss et al. 1976).

While the literature on female labor force participation across andwithin nations is substantial, only a few studies have examined thistopic in China (Croll 1979; Johnson 1983; Parish and Whyte 1978;Stacey 1983; Thorborg 1978; Whyte and Parish 1984; Wolf 1985).There are several benefits to be expected from additional scrutinyof the Chinese case, particularly for those interested in examiningsocieties from the standpoint of rural-urban differences. First, thedevelopment model operant in China since the late 1940s, and es­pecially since the Great Leap Forward, has placed relatively strongemphasis on modernization of the agricultural sector and on maxi­mizing women's labor inputs in agriculture (Perkins and Yusuf 1984).This particular emphasis has not been present in the modernizationstrategies of most other developing nations in the socialist worldwhere investment in heavy industry has taken center stage. Thus,China provides an interesting test case for judging how much women'slevel of economic participation is influenced by political and ideolog­ical forces, on one side, and by general modernization trends on theother (Andors 1983).

A second reason for renewed efforts in examining women's laborforce participation in China is that existing studies, notwithstandingtheir importance, have used relatively small sample sizes, have tendedto focus on only one region, or have relied primarily on secondarysources (such as the Chinese press). In this paper, through the use ofthe l-percent sample of the 1982 Census of China, we can, for thefirst time, examine systematically the structural determinants of femalelabor force participation across urban and rural China. By carryingout a comparative ecological analysis of these census data, we are ableboth to describe patterns ofparticipation and to test theoretical prop­ositions developed in the literature. Indeed, our main purpose is tounderstand the structural factors that bring women into the casheconomy in rural and urban places in China.f Before turning to ouranalysis, we briefly review the literature on two issues: (1) What isknown about the relationship between modernization and femalelabor force participation in general?; and (2) What special consider­ations are likely to be operant in post-World War II China?

2 Because ofthe unique political economy ofChina where there are strong constraintsagainst migration and frequent direct assignment of individuals to specific jobs, we arenot concerned here with microeconomic, individual decision-making models. Thistopic, though interesting, is beyond the scope of this paper. In addition, though weuse the term "cash economy," many of the reasons why people work outside the home(housing subsidies, or, in some cases, for protection from political and economic mo­bilization campaigns) are very difficult to specify in Western monetary terms (Walder1986).

Female Labor Participation - Barrett et al. 3

Theoretical background

Research in developing and developed areas

Research on female labor force participation has traditionally oper­ated on the premise that participation is likely to increase with in­dustrial growth. Industrialization, and especially the rise of serviceindustries, generates greater demand and greater opportunities forwomen to join the cash economy (Bowen and Finegan 1969; Oppen­heimer 1970; Semyonov and Scott 1983; Wilensky 1968). Tertiaryindustries and, to some extent, manufacturing are female-demandingindustries and consequently create more opportunities for women toparticipate in the economically active labor force. Indeed, in theirlandmark treatise on labor force participation in the United States,Bowen and Finegan (1969) were able to demonstrate that city-to-cityvariation in labor force participation responded to the presence offemale-demanding industries.

In a similar vein, researchers expect participation to increase withcity size and to decrease with distance from the urban center (e.g.,Semyonov 1983; Tarver 1969). This expectation is rooted in the­idea that due to their more comprehensive division oflabor and morecomplex industrial and occupational structures, large urban centersprovide more opportunities for female employment in the cash econ­omy than do small towns and rural communities.

In addition to the industrial structure of the community, fertilityhas long been viewed as a major determinant of participation. Morespecifically, high fertility rates are likely to decrease female partici­pation in the cash economy. Demographers and sociologists haverepeatedly demonstrated in non-socialist and socialist nations (Galen­son 1973; Kasarda 1971; Ward 1983) that female labor force partic­ipation is negatively related to the fertility rate. Although the causaldirection of the relation between fertility and female labor forceparticipation is not completely established (Cramer 1980), social sci­entists agree that a higher fertility rate constitutes a constraint in­hibiting women from joining the economically active labor force andfrom developing professional careers.

Finally, several sociologists have suggested that regardless of thelevel of industrialization or of the fertility rate, family organizationis one of the most, if not the most, important determinants of femalelabor force participation (Collver and Langlois 1962; Youssef 1972).They argue that in systems characterized by fragile and unstablefamily structures, women must join the cash economy in order tobecome self-sufficient. By contrast, in systems characterized by stablefamilies, women are more likely to rely on husbands or kin for eco­nomic support. Several studies have consistently shown that familyinstability (as measured by the divorce rate or the prevalence of fe­male-headed households) is positively related to female labor force

4 Rural Sociology, Vol. 56, No.1, Spring 1991

participation (Collver and Langlois 1962; Kunzel 1974; Semyonov1980; Semyonov et al. 1987; Youssef 1972).

In sum, the process of industrialization and economic growthwas associated with considerable decrease in family size and with thetransition of the family from a producer to a consumer unit. Theseprocesses, coupled with rising educational opportunities for women,have generated, in turn, not only greater demand for female labor,but also a greater supply of women available for the cash economy.The goal of this research is to examine these hypotheses in the socialand political context of urban and rural China. A brief review ofprior studies on this issue in China seems in order.

Women's laborforce participation in China

In addition to the set of influences that are generally expected tooperate in most countries, there are some special characteristics ofthe Chinese labor force and its gender patterns which are worthnoting. First, in a nation without a free labor market and with verylimited job mobility (Goldstein and Goldstein 1984), the initial struc­tural characteristics of local areas might be expected to exert stronginfluences on female labor force participation. Thus, the administra­tive rather than market organization of Chinese labor markets meansthat the structural characteristics oflocal areas, such as their industrialcomposition, might be expected to affect their own female labor forceparticipation rates more directly because these characteristics will notinteract with labor market phenomena in surrounding localities (e.g.,Wolf 1985:79-111). In other words, labor shortages ofmajority malesin some localities would not necessarily draw in similar workers fromnearby regions because of the lack of wage effects on mobility in thebroader labor market. Thus, labor market adjustments might be moreautarkic and more tied to administrative decisions, structural char­acteristics, and perhaps even to local cultural predilections (such asareas with traditionally high rates of female employment; see Topley1975) than to broad market-based trends.

Another consideration is the official Chinese Communist ideologyon women's liberation (and women's labor force participation) sincethe Yenan period (early 1940s), which has "argued that general socialemancipation for women, including family reforms, was primarily,perhaps wholly, dependent on enlarging women's economic role out­side the family and changing their relationship to production" (John­son 1983:88). As Johnson points out, this Engelsian view puts theChinese Communist Party in the same boat (at least with regard toits assumptions about causal direction) as the modernization theoristsof the 1950s and early 1960s, who saw cultural forms changing rapidlyunder the impact of swift economic change. However, much of the

Female Labor Participation - Barrett et al. 5

recent feminist work on China (e.g., Croll 1978; Robinson 1985;Stacey 1983; Wolf 1985) questions the conclusion that egalitarianideologies have been put into practice to such an extent that olderpatterns have completely disappeared. Their research documents thatpatriarchy often survives under the guise of socialist industrial prin­ciples and that there have been significant swings in policy in responseto changes in ideology and to perceived economic problems, such asurban unemployment (Andors 1983).

The Chinese government has made the large-scale participation ofwomen in labor one of its explicit goals. To this end, it has investedheavily in the education of women at the primary school level. In1981, the ratio of female primary school students to all girls in theprimary school ages was 1.06, compared to a ratio of only 0.58 forother low-income nations (India excluded; see World Bank 1984:266).In general, it would be expected that local variations in state invest­ment in human capital should be linked to perceived benefits for thestate through increased labor force participation.

While there has been investment in primary school education forwomen in China, they are far less likely to be trained for technicaljobs, and there is frequent discrimination against women in the se­lection ofemployees by work units (Honig and Hershatter 1988:244­50). In the cities, they are less likely to move on to technical training.In the countryside, women are less likely to be trained for specializedoccupations because local officials fear that they will lose these em­ployees through marriage to a man from outside of their own village.Women who do gain skills often must revert to becoming unskilledagricultural laborers again when they enter their husbands' villagesas new brides (Wolf 1985:83). Because of these attitudes and a moregeneral residual prejudice against women's labor force participationin key 'occupational roles, women tend to be concentrated in unskilledagricultural labor.

The impact of fertility on female employment in China has de­creased with the advent of the fertility control programs of the 1970s,which culminated with the One-Child Policy promulgated in 1979(Banister 1987:147-296). However, only a very small proportion ofChinese women are completely childless, and nursery schools andkindergartens are much less available than is often supposed. Parishand Whyte found that in Guangdong villages in the early 1970s, lessthan 20 percent of families had access to such preschool facilities(1978:222-23). While child-care facilities are much more commonin towns and cities (Whyte and Parish 1984), fertility may still imposea significant impediment to the mobilization of the labor of motherswith young children (Honig and Hershatter 1988:247; Parish andWhyte 1978:224). In a recent empirical study, Poston and Gu (1987)have uncovered a substantial negative correlation at the provincial

6 Rural Sociology, Vol. 56, No.1, Spring 1991

level between fertility and women's employment in nonagriculturalactivities-a variable which is related to, but distinct from, total fe­male labor force participation.

Hypotheses

The literature on female labor force participation, on the one hand,and the research on Chinese society, on the other hand, have led usto a series of theoretical expectations. In general, we expect the rateof participation to be influenced by the industrial structure of givenareas, by fertility, and by the mode of family organization. First, weexpect that participation will rise with the level of industrialization,urbanization, and economic development. However, it was suggestedby Boserup (1970) that in developing and primarily agricultural so­cieties women's employment opportunities are likely to be primarilyin the agricultural sector-the sector in which women often firstreplace men. Thus, we expect participation in China to be affected,not only by the rise ofservice industries, but primarily by the presenceof agricultural employment.

The social composition of the locale is expected to affect partici­pation in several ways. Female labor force participation is likely toincrease where education is high. It is more difficult to predict whatthe effect of sex ratios will be on the level of female labor forceparticipation. If the ideological factors mentioned above are para­mount, we would predict that the relative availability ofmale workers,as indexed by the sex ratio, would have little impact on women'sparticipation. However, if economic necessity and labor demand playthe dominant role, we would predict that there would be a negativerelationship between the sex ratio and women's participation; that is,women work more in areas where the sex ratio is low (as a responseto chronic male labor shortages).

Furthermore, we expect the social organization of the family toplay a major role in the determination of the female labor forceparticipation rate. Places characterized by a less traditional system offamily organization, that is, places with large proportions of female­headed households are more likely to recruit women into the eco­nomically active labor force. While the existing literature would sug­gest a similar prediction about places with low fertility rates, thereare reasons to be cautious about making this forecast in the Chinesecase. As we have seen, fertility and the control of its consequences isan area of prime ideological importance in China. Here again, theresults ofour analysis will shed light on how the balance of ideologicaland more general social forces is tipped in this particular case.

In addition, locales are likely to differ in their ability to provideemployment to any adults, regardless of sex. That is, there may be

Female Labor Participation - Barrett et al. 7

some unmeasured variables that affect the general economic climateof these areas. To control for these effects, we introduce the rate ofmale labor force participation as an indicator of general employmentopportunities. Finally, because of the possibility ofcontaminating theeffects of different types of agricultural and industrial production indifferent regions of China, we examine the role of the precedingfactors with controls for region. This factor is represented by fiveregional dummy variables (North, East, Northeast, Central South,and Southwest).

Methodology

Data sources

The primary data source for this project is the recently releasedI-percent public use sample of the 1982 Census of China (ChinaStatistics Archive 1988). These tapes contain information on almost10,000,000 individuals in 2,000,000 domestic households and 225,000collective households (for details see China Statistics Archive 1988).Because we are pursuing an ecological approach in this paper, acritical decision in this research is identifying the proper units ofanalysis. In our investigation of the Chinese labor force, we haveaggregated the individual-level observations to the level of cities andcounties. Although more fine-grained geographic designations havebeen provided on the public use sample (e.g., "street code"), thereare several advantages to working at the county or county-equivalentlevel.

First, these units are large enough to provide for stable estimationof within-area population characteristics (e.g., proportion of the pop­ulation between the ages of20 and 24). Second, they are small enoughthat their internal variation on characteristics, such as urban versusrural residence, is meaningfully restricted. This would be less true ifdata were aggregated to the level of the province. Third, there maybe some rough correspondence between these areas, and the conceptof a "local labor market," especially in light of the fact that labormobility is relatively restricted in contemporary China.

In Appendix A, we have provided summary information on fourtypes of county-equivalent units. Column 1 provides data on the pop­ulation of all area units (N = 2,377) used in our subsequent analysis.In columns 2 through 5 parallel information is provided on largecities (N = 109), smaller cities (i.e., cities that are under the admin­istrative control of prefectures; N = 136), counties that are underthe administrative control oflarge cities (e.g., Beijing; N = 202), andrural counties (N = 1,930). In those parts of our subsequent analysiswhich analyze rural and urban units separately, the groups in columns

8 Rural Sociology, Vol. 56, No.1, Spring 1991

2 and 3 are combined to form an urban sector, while columns 4 and5 are combined to form a rural sector.s

I

Variables

As noted above, each of the variables included in our subsequentanalysis is measured at the level of one of 2,377 different ecologicalareas identified in the 1982 Census. To control for the fact that agestructures differ across areas of China, many of the variables havebeen adjusted using the technique of direct standardization (Shryockand Siegel 1971 :418--22). In all cases, the standard population usedwas the total population of China in 1982. However, for some vari­ables, such as rates of male and female labor force participation,standardization was accomplished using the sex-specific populationin five-year age intervals, while for other variables, such as femaleeducation, ten-year age intervals were employed. (In the discussionbelow we indicate whether or not each variable was standardized,and if it was, which age classification system was utilized.)

The dependent variable, female labor force participation, is definedas the number of women aged 15 through 64 who report their laborstatus as either "employed," "awaiting government job-assignment,"or "urban unemployed" divided by the total number of women inthe same age range in each area." Male labor force participation isdefined in a parallel manner. Both variables were age-standardizedusing five-year age intervals.

The ecological and industrial variables pertain to the entire pop­ulation of an area, not just females. Population density is entered asthe natural logarithm of persons per square kilometer and was codedfrom tabulations provided in the Population Atlas ofChina (PopulationCensus Office 1987). The industrial variables are proportions whichare standardized using ten-year age intervals. The first is the pro­portion of the total adult labor force employed in agriculture. Thesecond is the proportion of all nonagricultural workers who are em-

3 The label "urban county" may be confusing insofar as it suggests an area markedby a metropolitan rather than a rural way oflife. In China, some rural areas surroundinglarger cities are placed under the administrative control of the neighboring city gov­ernment, rather than being subordinated to the surrounding "prefectural" authorities.There is no strong parallel to this in U.S. political geography. The areas themselvesretain a decidedly rural flavor-the mean proportion employed in agriculture is 73percent which is much closer to the value of 82 percent found in so-called "rural"counties than it is to the 31 percent found in small cities and the 23 percent found inlarge cities.

4 Compared to the labor force of other countries, the Chinese classification includesvery few people in the categories corresponding to "unemployment," that is, awaitinggovernment job assignment or urban unemployed. The percentage of the adult pop­ulation in these categories is less than six-tenths ofone percent. Needless to say, Chineseand Western observers have estimated that the true rates ofunder- and unemploymentin China are far higher than those reported in the census (Emerson 1983; Taylor1988).

Female Labor Participation - Barrett et al. 9

ployed in service industries. The degree of traditionalism in familyorganization was measured by the proportion of households that areheaded by females. This variable is standardized using the age dis­tribution of women in ten-year age intervals. The modified generalfertility rate is the number of births in each area divided by thenumber of women between 20 and 39 years of age.

We have also included several social composition variables. Theeducational level of women is measured as an age-standardized meanyears of school completed derived by representing each of the sixeducational categories in the census by the appropriate midpoint ofits range and by calculating weighted averages (where the weightsare the age-standardized proportion of female adults in each edu­cational category). Again, ten-year age intervals were used for stan­dardization. In this analysis, the sex ratio is the total number of malepersons between 15 and 64 years ofage divided by the correspondingnumber of female persons and is standardized using the age distri­bution of the combined male and female population specified in five­year age intervals. Also included is the rate of male labor force par­ticipation in an area (standardized by five-year age intervals), whichmay be taken as an indicator of the availability of work opportunitiesin general.

In addition, five dummy variables are included to control for theeffect of the six geographical regions of China. These are (1) theNorth; (2) the Northeast; (3) the East; (4) the South Central; and (5)the Southwest." The excluded region is the Northwest, consisting ofShaanxi, Gansu, Qinghai, Ningxia, and Xinjiang provinces.

Findings

In Table 1, we present the means and standard deviation of variablesused in our analysis for the country as a whole (columns 1 and 2), forrural parts ofChina (columns 3 and 4), and for cities in China (columns5 and 6). It should be restated that the unit of analysis in rural areasis the county; in urban areas it is the city as a whole. The mostnoteworthy finding revealed in this table is that the typical area inChina has quite high female labor force participation rates, 70 percenton an age-standardized basis. Moreover, in contrast to what has beenobserved in most societies, the female labor force participation rateis slightly higher in rural areas than in urban areas (70% comparedto 68%).

There are some rather striking differences between rural and urbanplaces in other characteristics, most notably, fertility, family structure,

5 The provinces included in each region are as follows: North-Beijing (munici­pality); Tianjin (municipality); Hebei; Shanxi; Inner Mongolia. Northeast-Liaoning;Jilin; Heilongjiang. East-Shanghai (municipality); Jiangsu; Zhejiang; Anhui; Fujian;Jiangxi; Shandong. Central South-Henan; Hubei; Hunan; Guangdong; Guangxi.Southwest-Sichuan; Guizhou; Yunnan; Tibet.

Tab

le1.

Mea

nsan

dst

and

ard

devi

atio

nso

fva

riab

les

incl

uded

inth

ean

alys

isby

urb

an-r

ura

llo

cati

on

All

area

sR

ural

area

sU

rban

area

s

Mea

nSO

Mea

nSO

Mea

nSO

Fem

ale

labo

rfo

rce

part

icip

atio

n0.

700

0.15

00.

702

0.15

50.

680

0.08

6L

og

dens

ity

5.00

01.

653

4.81

91.

573

6.61

91.

457

Ru

ral-

urb

anar

ea(u

rban

=1)

0.10

10.

301

Per

cen

tag

ricu

ltur

alw

orke

rs0.

761

0.20

80.

816

0.12

20.

275

0.18

6P

erce

nt

nona

gric

ultu

ral

wor

kers

inse

rvic

ein

dust

ries

0.50

00.

192

0.51

90.

190

0.32

70.

107

Bir

thra

te0.

169

0.06

00.

175

0.05

90.

113

0.03

1P

erce

nt

fem

ale-

head

edho

useh

olds

0.18

10.

103

0.16

50.

087

0.32

00.

129

Mea

nye

ars

of

educ

atio

n5.

447

1.24

15.

221

1.06

17.

467

0.84

4Se

xra

tio

1.08

00.

098

1.07

30.

088

1.13

50.

146

Mal

ela

bor

forc

epa

rtic

ipat

ion

0.86

60.

037

0.87

00.

035

0.83

30.

032

No

rth

regi

on0.

154

0.36

10.

157

0.36

40.

126

0.33

3E

ast

regi

on0.

217

0.41

20.

213

0.41

00.

252

0.43

5N

orth

east

regi

on0.

077

0.26

70.

070

0.25

50.

143

0.35

1C

entr

alS

outh

regi

on0.

215

0.41

10.

211

0.40

80.

256

0.43

8S

outh

wes

tre

gion

0.20

10.

401

0.21

00.

408

0.11

30.

318

Nu

mb

ero

fca

ses

2,36

32,

125

238

~ C :::tJ ~ ~ .... V)

c (") c' .... ~ ~ ~ I.J

lSJ

'. ~ '"~

~ ""l

~.

~ \C \C ~

Female Labor Participation - Barrett et al. 11

Table 2. Correlations of independent variables with female laborforce participation by urban-rural location

All areasr

Rural areas Urban areasr r

0.254*

0.279*

0.0060.0320.471 *

-0.0700.0600.346*

-0.265*0.135*

-0.495*0.329*0.306*

0.026

0.490*

0.023-0.045*

0.316*

Log densityRural-urban area (urban = 1)Percent agricultural workersPercent nonagricultural workers in

service industries 0.265* 0.274*Birth rate 0.249* 0.254*Percent female-headed households 0.239* 0.286*Mean years of education -0.287* -0.326*Sex ratio -0.169* -0.195*Male labor force participation 0.346* 0.352*North region -0.202* -0.202*East region -0.064* -0.077*Northeast region -0.511 * -0.528*Central South region 0.210* 0.207*Southwest region 0.389* 0.393*

* Correlation coefficient significantly different from zero, p < .05.

education, and gender composition. Fertility, as captured by the gen­eral fertility rate, is higher in the countryside (.175 vs.. 113). House­hold structure also differs considerably in urban and rural places. Theaverage city has twice the relative number of female-headed house­holds compared to the average rural county (.320 vs..165). Notsurprisingly, the level of education, which is generally quite low inChina, is over two years higher in Chinese cities (7.5 vs. 5.2 years).Finally, probably as a result of differential migration, the age-stan­dardized sex ratio is considerably higher in urban places (1.135 vs.1.073).

In Table 2, correlations between the independent variables andfemale labor force participation are shown-first for the country asa whole and then separately for rural and urban areas. (Because ofthe large number of variables at issue in this analysis, we have notpresented the complete correlation matrix for the set of independentvariables. For readers interested in assessing the possibility that ourresults are affected by problems of multicollinearity, we address thatissue in Appendix B.) For the country as a whole, areas which havemore agricultural workers have higher female labor force partici­pation (r = .316), as do areas with many service workers (r = .265).The former is true within both counties and cities, but the latter istrue only for the countryside. Rural areas with fewer men (low sexratios) have higher rates offemale participation, but this phenomenondoes not appear to occur in cities. Surprisingly, rural areas havehigher female labor force participation if they have higher fertility.Fertility, however, is not related to participation in urban places.

Tab

le3.

Eco

logi

cal

mod

els

of

fem

ale

lab

or

forc

epa

rtic

ipat

ion

byu

rban

-ru

ral

loca

tion

All

area

sR

ural

area

sC

itie

s

bz-

rati

ob

r-ra

tio

bz-

rati

o

Inte

rcep

t0.

031

0.40

70.

095

1.16

9-0

.55

9-3

.76

8L

og

dens

ity

0.00

6*2.

823

0.00

20.

808

0.00

8*2.

260

Ru

ral-

urb

anar

ea(u

rban

=1)

0.10

9*7.

988

Per

cen

tag

ricu

ltur

alw

orke

rs0.

225*

9.35

40.

331

*11

.155

0.11

8*3.

705

Per

cen

tno

nagr

icul

tura

lw

orke

rsin

serv

ice

indu

stri

es0.

042*

2.38

3-0

.00

1-0

.07

00.

035

0.88

7B

irth

rate

0.06

51.

332

0.02

50.

487

0.0

69

0.46

5P

erce

nt

fem

ale-

head

edho

useh

olds

0.19

5*7.

091

0.23

2*7.

434

0.08

8*2.

022

Mea

nye

ars

of

educ

atio

n0.

007*

2.06

70.

006

1.75

60.

036*

4.58

1S

exra

tio

-0.1

77

*-7

.43

5-0

.19

1*

-6.9

02

-0.0

01

-0.0

32

Mal

ela

bor

forc

epa

rtic

ipat

ion

0.63

8*9.

257

0.53

6*7.

340

0.98

5*7.

355

No

rth

regi

on-0

.07

7*

-9.0

46

-0.0

79

*-8

.70

6-0

.05

0*

-3.0

51

Eas

tre

gion

-0.0

11

-1.2

92

-0.0

10

-1.0

11

0.03

5*2.

240

No

rth

east

regi

on-0

.19

5*

-17

.39

5-0

.21

6*

-17

.59

3-0

.05

6*

-3.1

28

Cen

tral

So

uth

regi

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Female Labor Participation - Barrett et al. 13

Finally, both town and country areas with many female-headed house­holds have elevated rates of participation, although the relationshipis considerably stronger in urban areas.

Since the explanatory variables are interrelated, at least in part, itis important to examine the independent effect of each on femalelabor force participation. Thus, in Table 3, we present the coefficientsand t-ratios from three regression equations in which female partic­ipation is estimated as a function of these social and economic vari­ables. These coefficients are presented first for the combined groupof urban and rural places (columns 1 and 2) and then separately forthe two types of areas (columns 3 through 6).

The parameters of the first regression equation in Table 3 providereasonably strong support for the "economic development" hypoth­esis. Places which are more densely settled have higher levels offemalelabor force participation. Interestingly, the effect of urban locationis positive and significant; that is, urban location increases femalelabor force participation. Apparently, the effect of urban location(observed earlier in Tables 1 and 2) was masked by its relationshipwith the other variables in the model; before such relationships werecontrolled, female participation appeared to be about 2 percent lowerin cities, but when they are taken into account, participation is re­vealed to be about 10 percent higher in urban places.

In part, this comes about because areas in which a higher propor­tion of all workers are engaged in agriculture have higher levels offemale labor force participation. This finding reflects, in part, thedeliberate efforts of the Chinese socialist regime to engage both wom­en and men in food production activities. It is also consistent withpatterns found in other developing societies, as we noted above. Lowlevels of mechanization in agriculture mean that almost all farm oc­cupations can be performed by individuals, regardless of vocationaltraining and skill. In any event, the level of female labor force par­ticipation in Chinese cities appears depressed not because of some­thing inherently different about urban life, but only because feweragricultural workers live there.

The results of equation 1 (in which urban and rural units werecombined) demonstrate that, in addition to the urban effect, partic­ipation is significantly influenced by both the industrial structure andthe social and demographic composition of places. Participation islikely to increase substantially with the presence of agricultural em­ployment, and, to a lesser extent, with the presence of service sectoremployment. Participation is likely to decline in places where theratio of men to women is high. Family structure was found to exerta strong influence on female employment. That is, participation tendsto rise in places characterized by a greater proportion of non-tradi­tional (female-headed) households. Finally, and somewhat surprising-

14 Rural Sociology, Vol. 56, No.1, Spring 1991

ly, fertility had no significant effect on female labor force participa­tion."

When comparing the models for rural areas (equation 2) and cities(equation 3), we find meaningful and interesting differences. First,the impact ofagricultural participation is considerably greater in ruralthan in urban places, while the effect of service employment is neg­ligible in both. Second, the influence of both family structure andsex ratio is more pronounced in rural areas than in cities. Third,female labor force participation is more strongly related to educa­tional level and to male labor force participation in urban than inrural places. We interpret this as consistent with a greater role ofmarket forces in cities. That is, educational level is frequently takenas a measure of labor supply and human capital, while the rate ofmale labor force participation is a reasonable indicator of the levelof labor demand. Apparently, female labor force participation is morelikely to be affected in rural places by the industrial structure and bysocial and demographic constraints, such as agricultural employment,the sex ratio, and household structure."

Conclusions

As Andors (1983) and others have shown, China has gone throughseveral distinct periods during which increasing women's rates ofemployment was either emphasized or de-emphasized. Our cross­sectional, areal-level analysis can only capture part of this process.Our findings show that there is a great deal of variation in femalelabor force participation between counties in rural areas and betweenmunicipalities throughout China. The point here is that the variabilitybetween counties and municipalities in female labor force partici-

6 A reviewer questions whether this result might have occurred because of our useof too narrow a measure of fertility; that is', specifically that the number of very youngchildren (those under one) may not capture well the variation between areas in women'stotal child-rearing activities, which do not end at a child's first birthday. In an earlieranalysis of these same data (Barrett et al. 1989), we report the coefficients for a morebroadly constructed variable-the ratio of the number of children under five to thenumber of women between the ages of 20 and 39. The results were similar to thoseshown here; between-place variation in fertility in China is not related to between­place variation in female labor force participation.

7 It is tempting- to ask how much of the lower level of female labor force participationin urban places is attributable to differences in the composition of urban places, (fewerworkers in urban places are engaged in agricultural pursuits, a factor which in Chinaencourages labor force participation among women) and how much is attributable tothe differences in the coefficients of the two equations in Table 3. The usual methodfor answering questions like this is regression decomposition (see Jones and Kelley1984). Application of this technique to our results does not shed much light on theunderlying processes, however. The results are unstable insofar as the relative sizes ofthe "means" coefficient and the "slopes" coefficient are very much dependent uponwhich population is taken as the reference group. At the same time, the largest com­ponent of the difference is the interaction component, which is about eight times largerthan the original difference.

Female Labor Participation - Barrett et al. 15

pation rates has seldom been mentioned in other accounts of theincrease in the proportion of working women in China. This suggeststhat either policies toward women's work have been applied differ­ently in various parts of China or else there are real social, economic,or cultural barriers to women's employment beyond the obvious ru­ral-urban differences.

Compared to other nations, especially to developing nations, Chinahas a high rate of female labor force participation. In fact, the femalelabor force participation rate is slightly higher in rural areas than incities, an unexpected finding for any country. However, when dif­ferences in industrial and social composition are controlled, the rateof female participation is significantly higher in urban places.

Besides the urban/rural distinction, female labor force participa­tion in China appears to be influenced by the industrial structure andby sociodemographic composition of places. First, participation islikely to be higher in locales characterized by agricultural employ­ment. This finding is consistent with the rationale suggested by Bose­rup (1970) in her work on women in less developed countries: womenreplace men in the agricultural sector as men seek jobs in the sec­ondary or tertiary sectors of the economy. On the other hand, servicesector employment has no effect on female labor force participation.In 1982, at least, China had, proportionally speaking, a very smallservice sector; its economic development policies consciously avoid­ed the wide-spread development of service industries (Whyte andParish 1984). This may be one reason why China diverges frompatterns observed in other nations. It is quite possible that the post­1979 economic reforms have had a major impact on the rapid de­velopment of service industries in China during the last decade andthe position of women in them.

As in other nations, participation tends to rise with women's ed­ucationallevels and with the proportion offemale-headed householdsin the area. Participation declines with a rising sex ratio and withdeclines in male labor force participation rates. Unlike many othernations, however, fertility has no effect on the female labor forceparticipation rate. This lack of influence may be a finding that isunique to the Chinese case and may not generalize to other ThirdWorld (or even First World) nations. The current family planningprogram began about 1972 and, with the advent of the One-ChildPolicy in 1979, had a major effect on all Chinese families (Banister1987). The remarkable finding here is how the fertility-unemploy­ment link was broken in rural areas, where there were few institu­tional supports (such as state-sponsored daycare or nurseries) to helpmothers return to work. This suggests that Chinese rural womenhave re-defined themselves as workers having careers, albeit ones inlargely unskilled agricultural jobs. How the shift towards family-basedfarming after 1979 and the rise in fertility since 1984 (Luther et al.1990) has affected this relationship is an interesting question.

16 Rural Sociology, Vol. 56, No.1, Spring 1991

Although the basic findings are similar for cities and rural areas,the magnitude of the effects of these determinants is quite different.Participation in urban places is most affected by educational levels ofwomen and the employment opportunities of men (as indicated bymale labor force participation rates). This finding is particularly cu­rious because most persons who leave school (whether male or female)in urban areas are assigned to jobs through an administrative mech­anism, not through the kind of individualistic job-search effort thatcharacterizes the labor market in capitalist economies. In contrast,participation in rural areas is more affected by the proportional sizeof the agricultural sector, the sex ratio, and the proportion of non­traditional households. Indeed, the urban-rural differences revealedby these models suggest that market factors play a more importantrole in female employment in urban China, while sociodemographicfactors are more significant in the rural sector. While our areal-levelanalysis cannot specify how these micro-level processes work, futurestudies may show if decisions made by brigade and production teamleaders (and now by family farmers) have had different aggregateimpacts on women workers than decisions made in nonagriculturalwork units.

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Appendix B

Procedures used to assess possible multicollinearityeffects

The type of data analyzed here are potentially characterized by rather strong in­tercorrelations among predictor variables raising the troubling possibility of multi­collinearity in regression results. To screen for the presence of collinearity problems,we employed the diagnostic procedure recommended by Belsey et al. (1980), which isavailable within the Statistical Analysis System (SAS Institute 1985:672). This proce­dure involves comparison of the "condition indices" ofthe independent variable matrixwith the proportion of variance of each independent variable associated with thatcondition index. Collinearity problems are likely when a "component associated witha high condition index contributes strongly to the variance of two or more variables"(SAS Institute 1985:672).

Inspection of the diagnostic results for the models shown in Table 3 revealed thefollowing: For the all-area regression there were only two components with conditionnumbers larger than 30 (except for that associated with the intercept), and neither ofthese contributed strongly to the variance of two or more variables. The same wastrue for the rural and urban regression. Nevertheless, for the sake of caution, we reraneach regression dropping the two variables associated with components that had con­dition numbers larger than 30. These results were then compared with those from the"full models" with special attention being paid to any instabilities in the standard errorsofthe regression coefficients (see Pindyck and Rubinfeld 1976:68). The standard errorsof the respective regression coefficients were virtually identical across the revised andoriginal models, strongly suggesting the absence of any serious collinearity artifacts.