neighborhood social networks and female self-employment earnings in taiwan

Neighborhood social networks and femaleself-employment earnings in Taiwan

Ryuichiro Tsuchiya

Published online: 30 March 2010# Springer Science+Business Media, LLC 2010

Abstract Using the sample of Taiwanese female self-employed workers from theTaiwan Women and Family Survey (TWFS) conducted in 1989, this article exploresneighborhood social networks and female self-employment earnings. The evidencefrom linear regression and endogenous treatment effect models suggests that anindividual’s past provision of personalized assistance to adjacent neighborssignificantly increases current self-employment earnings, with corrections for self-selection into network participation. An individual’s past voluntary contributions tocommunity organizational activities also significantly increase current earnings, bothwith and without corrections for self-selection. However, there are negative self-selections into both cooperative neighborhood networks and community organiza-tional activities in the sense that female self-employed workers with high earningscapacity are less likely to choose to participate in these types of social networks.

Keywords Neighborhood social networks . Female self-employment .

Self-employment earnings . Community development

In most developing countries, and also in developed countries although to a lesserextent, unemployment, poor health, low-quality dwellings, criminal offences, andsocial exclusion are concentrated in disadvantaged local communities. One of themost widely used local development schemes are those involving the support of self-employment (Nolan 2003), since small businesses generate jobs (Birch 1987), andnew firm formation tends to foster regional employment growth (Audretsch andFritsch 2003). In particular, most countries operate local development programsspecifically designed to facilitate female entrepreneurship, and one of the commonfeatures of female-oriented business assistance is the stress on developing supportnetworks (Nolan 2003).

Int Entrep Manag J (2010) 6:143–161DOI 10.1007/s11365-010-0143-2

R. Tsuchiya (*)College of International Management, Ritsumeikan Asia Pacific University, 1-1, Jumonjibaru, Beppu,Oita 874 8577, Japane-mail: [email protected]

While most would agree on the importance of fostering female self-employmentfor local development, there is little agreement on whether local social networksaffect the performance of self-employment. Besser (1999) found a positiveassociation between business operators’ commitment to and support toward theircommunity and their perception of business success in the small town communitiesof Iowa. Based on the same data set, Kilkenny et al. (1999) found that the interactioneffect of an entrepreneur’s service to his/her community, reciprocated by thecommunity’s support of the business, is the single most significant determinant ofowners’ assessment of business success. By contrast, Bates (1994) found that inAsian immigrant-owned small businesses in the United States, the firms oriented toserving minority customers were less profitable and more failure prone than thosethat operated in a broader marketplace.

One important difference between the abovementioned studies lies in theirdefinitions of the community. In Besser (1999) and Kilkenny et al. (1999), the focalcommunity was at the level of a small town, while in Bates (1994), it was at the levelof minority groups. We adopt an approach that is consistent with these tworesearches but it focuses on a more micro-level unit. This paper aims to answer thefollowing question: Does past participation in cooperative networks with adjacentneighbors and voluntary contributions to community organizational activitiesenhance or diminish the performance of female self-employment activities? Sincespatial proximity affects the cost of social capital formation (Glaeser et al. 2002),people in local communities are more likely to communicate with their adjacentneighbors (Caplow and Forman 1950). Renzulli et al. (2000) found that the businessdiscussion networks of potential female startup founders included a higherproportion of kin and less heterogeneous contacts than in the case of male potentialstartup founders. Such disadvantages faced by female self-employed workers innetwork formation make the personal relationships formed in their neighborhoodsmore significant. The centerpiece of our analysis is a model that shows how the pastprovision of a variety of emotional aids in child rearing, elderly care, and socialsafety nets to neighbors affect female self-employment performance. Our model alsoshows how past contributions to community organizational activities affect self-employment earnings.

We employed models with corrections for the endogenous self-selection intonetwork participation, which neither of the previous researches applied in theirmodels. We predicted that with the correction for self-selection, past participation incooperative networks formed in neighborhoods will have a positive influence on theearnings derived from female self-employment activities. Another prediction is thatthose who have made voluntary contributions to community organizational activitieswill have higher earnings than those who have never done so, both with and withoutthe correction for self-selection. We also predicted that there will be negative self-selections into both neighborhood cooperative networks and community organiza-tional activities.

This paper is structured as follows. In the next section, theoretical insights aresummarized to focus on issues relating to neighborhood social networks. Led bytheoretical frameworks, two testable hypotheses are derived. Then, the data sourceand research methodology are described. Results from the multivariate regressionmodels are presented and the derived hypotheses are formally tested. In the final

144 Int Entrep Manag J (2010) 6:143–161

section, key findings and implications for policy makers, practitioners, andresearchers are presented.

Conceptual framework

The development of classical game theory allowed researchers to elaborateappropriate concepts for analyzing communities. The critical result comes fromrepeated game theory, which is known as a folk theorem (Fudenberg and Maskin1986). Under the condition of repeated encounters and perfect information,reputation effects and sanction mechanisms are at work and induce players toconsider the long-term consequences of their present actions.

Although entrepreneurial networks are typically construed as the fundamentalfactor of the process of new firm formation (Brüderl and Preisendörfer 1998; Bosmaet al. 2004), the reliance on networks is not restricted to the startup stage.Entrepreneurs continue to rely on networks for business information, advice, andproblem solving (Johannisson et al. 1994).

We now specify a hypothesis about the effect of cooperative network ties withadjacent neighbors on child rearing, elderly care, and social safety nets. It has beenargued that neighborhoods rich in social capital are positively associated with childwell-being (as reviewed by Leventhal and Brooks-Gunn 2000) and elderly care(Chan 1993), and local social capital helps establish social safety nets (Conning andKevane 2002). We expect that for female self-employed workers, participation insuch close-knit cooperative networks is positively associated with the level ofreputation for trustworthy behavior in the community. In the dense networks ofcooperation through which residents are interrelated, information on the participant’spast actions is extensively shared, while multilateral punishment or ostracization istriggered if a participant defects. Due to the transmission of reputation, the provisionof emotional aids to adjacent neighbors not only enhances the individual’s welfarederived from strengthening personal friendship ties but is also positively associatedwith the level of the individual’s perceived trustworthiness and reputation in thecommunity.

For female self-employed workers, their perceived reputation in the commu-nity is a specific asset that affects their businesses performance. Flora (1998)argued that social capital thrives when individuals interact with one another inmultiple roles over a period of time. The personal reputation and trustworthiness ofa female self-employed worker perceived by her neighbors is more closelyassociated with her position in terms of the establishment of a loyal customer baseand professional links in the community, largely due to the multiplicity of theindividual’s role-set in neighborhoods and, as Renzulli et al. (2000) found, due tothe disadvantages faced by female business owners in network formation. Thus, theindividual’s reputation building by way of repeated interactions as a result ofneighborhood cooperation is a specific capital that yields a stream of benefits overtime.

Reputation building in the community offers the following benefits. The localtransactions relating to female self-employment businesses are mainly a result ofloyal customers, stable suppliers of raw materials, subcontractors for goods and

Int Entrep Manag J (2010) 6:143–161 145145

services, long-term employees, and suppliers of physical and financial capital.Individuals are able to gain informational advantages in the preference of localconsumers and reduce local advertisement cost. By sharing information about badplayers in a decentralized manner, individuals can lower screening costs. Trust mayfacilitate the enforcement of contracts and mediate the circulation of reliableinformation about technology and market opportunities. In sum, we expect theformation of reputation through personalized cooperation with adjacent neighbors toenhance business performance. Considered together, these arguments imply thefollowing:

Hypothesis 1. For female self-employed workers, the past provision ofpersonalized assistance in child care, elderly care, and social safety nets to theiradjacent neighbors will be positively associated with their current self-employmentearnings.

We then specify a hypothesis about the effect of past voluntary contributions tocommunity organizational activities. We expect that the earnings will be higher forthose who have made personalized voluntary contributions to community organiza-tional activities than for those who lack such experience. The community solvesproblems that both states and markets are unable to address (Hayami 1999; Bowlesand Gintis 2002). Accordingly, community organizational activities mainly involvethe provision of local public goods such as neighborhood amenities, the offering ofinsurance and other risk-sharing opportunities, and the provision of financial supportto the poor who are excluded from credit markets. These activities also frequentlyserve a social purpose.

The goods and services that community organizational activities provide arepublic goods, in the sense that the benefits of these goods cannot be entirely derivedsolely by those who have contributed to the activity (Kilkenny et al. 1999). That is,others, who cannot be excluded, also receive benefits without making contributions.Agents engage in the provision of non-excludable public goods by making at least asmany unpaid contributions as others do, largely led by the concern for theirreputation as well as prompted by altruism (Palfrey and Prisbrey 1996). At the sametime, the free-riding problem becomes more severe when public goods are suppliedthrough the voluntary contribution mechanism.

Female self-employed workers who have made voluntary contributions tocommunity organizational activities even in such situations tend to acquire thebroad reputation of being trustworthy in the entire community. In sum, weexpect that female self-employed workers’ past voluntary and personalizedcontributions to community organizational activities will be positively asso-ciated with their level of reputation in the community, and this reputation willmediate the formation of a loyal customer base, the securing of stable resourcesupplies, and the circulation of reliable information. Thus, we propose thefollowing:

Hypothesis 2. For female self-employed workers, past personalized contributionsto community organization activities will be positively associated with theircurrent self-employment earnings.


Methodology

Data

Taiwan’s post-war economic growth has been spectacular and has attracted muchresearch interest. In addition, industrialization has successfully spread in rural areasin a decentralized manner (Ho 1979). Among others, Numazaki (1997) argued thatentrepreneurs have been playing a key role in the rapid economic growth of Taiwan.In addition, as reviewed by Park and Johnston (1995), one important reason forthe decentralized industrialization was the rapid rise of rural entrepreneurship in the1960s and 1970s. Thus, entrepreneurship has been playing a pivotal role in theprocess of Taiwan’s decentralized regional development.

The estimation of our model on the neighborhood social networks of Taiwanesefemale self-employed workers is a challenging task, requiring data on their socialinteractions with adjacent neighbors. Therefore, we decided to use the TaiwanWomen and Family Survey (TWFS), along with a supplemental data source—theIncome and Expenditure Survey (IES). We derived most of the covariates from theTWFS, while the self-employment earnings and the average incomes of otherhouseholds in the respondents’ neighborhood, which are defined later, were obtainedfrom the IES. The TWFS was conducted in 1989 by National Taiwan University incooperation with the Institute of Economics of the Academia Sinica, the Departmentof Statistics of the Ministry of the Interior, and the University of Chicago. It covered3,803 female participants aged between 25 and 59 years. Through retrospectiveinterviews, this survey obtained a vast amount of information on the participants,such as their social welfare activities, current and past occupational status, employmenthistory from the age of 15 to the time of the survey, and family background. Althoughthe data collected during the late 1980s obviously limits the generalizability of ourresults, it provides ample information that vastly improves our ability to address theendogeneity self-selection problem of social network participation and to obtainconsistent estimates of the effect of neighborhood social networks.

The subjects of the TWFS were randomly selected from across the country. Thesurvey was first randomly sampled from the administrative units that wereinterviewed for the IES in January 1988. The IES 1988—the other data sourceused in this study—was conducted by executive Yuan, the Directorate General ofBudget, Accounting, and Statistics (DGBAS), and covered over 16,434 householdsbelonging to 1,478 administrative units. After selecting 25 percent of theseadministrative units (501 units, inclusive of those for reservations), the TWFSselected one female member aged between 25 and 59 years from all the householdsin each unit. If a household had more than one female member, then one memberwas selected randomly. In this manner, 4,328 females were interviewed from Marchto May 1989, out of which 3,803 of them gave effective responses. See Yu (1996)for an introduction on the TWFS.

Sample selection

From among these effective respondents of the TWFS, we identified self-employedindividuals. The individuals who were classified as either the employer or self-


employed by both our data sources—the IES and TWFS—were specified (178observations). However, from among these identified self-employed individuals, 41observations had missing values with regard to the variables, which will be definedlater on the basis of the TWFS survey questions and responses; further, since we wereunable to recover the missing values, the observations corresponding to them wereeliminated. In addition, a minority of the self-employed females in our sample wereprofessionals (3 observations). They were excluded from the sample, since the earningsof professionals are usually distinctively higher than those of other self-employedindividuals (Evans and Leighton 1989); moreover, this influence could not be capturedby the use of a control variable due to their extremely small proportion of such womenin our sample. Consequently, 134 observations were available for the analysis.

Selection of the self-employment earnings indicator

We estimated our models in terms of net hourly earnings flows from self-employment activities. We believed that the use of hourly earnings as a performanceindicator would help us focus on cross-sectional variations in individuals’ socialcapital values at any point of time. As previously mentioned, self-employed businessearnings were obtained from the IES. With regard to self-employed workers, the IESprovided data on the yearly entrepreneurial earnings derived from self-employmentbusiness during the year 1988. The hourly earnings were computed by dividing theyearly earnings by yearly working hours (the average weekly working hoursmultiplied by 52). The logarithmic form of these hourly earnings was used as thedependent variable (hourly earnings).

Neighborhood social network variables

Among other things, the respondents of the TWFS were asked, “Have you evertaken care of your neighbors’ children; taken care of the aged, indisposed, orphysically disabled neighbors; or assisted your neighbors who were facing financialdifficulties?” The 0/1 indicator of participation in neighborhood cooperativenetworks was coded as 1 if an affirmative response was obtained to this question,and 0 if a negative response was obtained (neighborhood cooperative network).

In addition, in the TWFS, the respondents were also asked, “Have you everparticipated in volunteer work for service organizations within your community,such as community councils and friendly societies?” Community councils aregenerally responsible for providing local public goods to their members, whilefriendly societies provide voluntary mutual aid and social security, and often servethe purpose of fostering friendships among the members. The two organizationsexemplified in the question cooperatively administrate the non-market collectiveresources located in local communities. However, it was unclear as to what type of“community service organization” This raised a serious concern with regard tonetwork characteristics such as the collective purpose of these organizations andmembers’ incentives to participate. Despite these limitations, this variable is able tofunction as a comprehensive indicator of participation in community organizationalactivities. It was coded as 1 if an affirmative response was obtained, and 0 if anegative response was obtained (community organizational activity).


Control variables

We specify female self-employment earnings as a function of an extensive numberof additional factors that are likely to affect female self-employment activities. Thesefactors have been theorized extensively in previous researches. We begin with areview of some important individual-level predictors and then proceed to discuss theinfluence exerted by firm and neighborhood characteristics.

A large body of research investigates the link between various input factors andself-employment earnings (Evans and Leighton 1989; Hamilton 2000). The modelspresented below include business size as measured in terms of the number ofworkers. Since the TWFS does not contain numerical data on the number ofworkers, and only provides categorical data, we assigned one to businesses withoutany employee, three to businesses with two to four workers, and 12 to those withfive to nineteen workers. The logarithm of this approximated number of workers wasincluded in our model (business size). In addition, similar to Evans and Leighton(1989) and Hamilton (2000), our models also included the health limitationrepresented by a 0/1 indicator coded as one if the respondent’s health situation in1988 was “very bad” or “not good,” and zero if it was “average,” “good,” or “verygood” (health limitation).

Another important set of variables shown to positively affect self-employment isrelated to the human and social capital of the self-employed. The logarithm of theyears devoted to the current business was employed (tenure). With the increase inself-employment tenures, experience and social networks increase accordingly.Although previous researches have specified the quadratic function of self-employment tenures, we chose not to use a quadratic specification in our smallsample in order to minimize the effect of multicollinearity. However, it should benoted that using a quadratic specification does not significantly alter the results.

As included in the models of previous researches (Evans and Leighton 1989;Hamilton 2000), our model included a measure of career experience. This measurecaptured the overall wage employment experience over an individual’s entire careerby wage experience. This was not measured in terms of the number of years that hadpassed since graduation, but rather, in terms of the logarithm of the actual length ofwage employment. For this variable, too, we avoided using a quadratic specificationfor the same reason that we avoided using it for tenure; however, using a quadraticspecification does not significantly alter the results.

Another important human capital variable that we investigated is the number ofyears spent in education (education). Although the effect of increasing educationtends to be discontinuous across different educational qualifications, because of thesmall size of our sample, we avoided using multiple 0/1 indicators, and specified thecontinuous effect of education across the years. Intergenerational transfer ofentrepreneurial human capital is also a strong predictor of self-employment (Dunnand Holtz-Eakin 2000). In order to control for this, our model included a 0/1indicator coded as one if the respondent’s father was or had been self-employed(self-employed father), and zero if this was not the case. Many entrepreneurialstudies treat the spouse’s emotional support toward entrepreneurship as social capital(Brüderl and Preisendörfer 1998; Bosma et al. 2004). This emotional support towardentrepreneurship is likely to affect the division of household labor. We controlled for


this female-specific factor by including a 0/1 indicator coded as one if the husbandhelped the respondent with housework “considerably” or “to some extent,” and zeroif the response was “none” (i.e., no help from the husband; husbands’ help).

In addition to individual—and household-level predictors, important regionalfactors might also stimulate or impede female self-employed workers’ socialinteractions. In order to control for the regional disparity, our model included threedummies—city, town, and village—with the village as the reference (city, town, andvillage). Four industrial controls—relating to farming, forestry, and fishing (farming)as well as manufacturing (manufacturing), commerce (commerce), and service(service)—were utilized in our model with farming and other miscellaneouscategories as the reference.

In addition to regional and industrial factors, the conditions of neighborhoodhouseholds might also influence the formation of neighborhood social networks.Based on cross-county data, it has been found that the strength of trust and civicnorms are positively related to income level and negatively related to incomeequality (Knack and Keefer 1997). We associated the income level of neighborhoodswith the average household incomes of the respondents’ adjacent neighbors. Thiswas computed by averaging the sum of the yearly incomes of all other householdsthat responded to the TWFS and that were located in the same administrative unit asthat of the female self-employed worker (neighborhood income level). Theadministrative units were at the level of hamlets (cun) in the case of village areas,or neighborhoods (li) in the case of cities, city-districts, and township areas. Theseunits are subordinate to city-, city-district-, township-, and village-level units. Aspreviously mentioned, these administrative units were used for the sampling andinterviews that were conducted as part of the IES and TWFS. However, it should benoted that the households that did not have any female member were excluded fromthe computation, since as previously mentioned, the TWFS considered only thosehouseholds that had at least one female member.

Descriptive statistics

The descriptive statistics presented in Table 1 provide an overview of our sample.The average of the logarithm of hourly earnings was approximately 3.7. The logarithmof the number of workers was 0.19 on average; that of the logarithm of the weeklyworking hours, approximately 4 l; that of the logarithm of the years in the currentbusiness, approximately two; and that of the logarithm of the years of wageemployment, approximately 0.08. The years of education of the respondents were6.4 on average. The husbands of six out of every ten respondents offered their wivesemotional support in housework. Further, one in five female self-employed workershad some limitations with regard to their health. The logarithm of the average incomeof neighborhood households was approximately 13 on average. With regard to thesocial network covariate, four in ten respondents had participated in the provision ofpersonalized support to adjacent neighbors, whereas one in ten had participated involunteer work for community service organizations. The most common location ofself-employment businesses was the city area, and the most common industry wascommerce. Although not reported in Table 2, on average, the marriage rate of therespondents was approximately 93 percent. In addition, among the subsample of the


Tab

le1

Descriptiv

estatisticsandcorrelations

Variable

Mean

Standard

Deviatio

ns1

23

45

67

89

1011

1213

1416

1718

1Hourlyearnings

3.715

1.014

2Businesssize

0.195

0.505

0.212*

*

3Tenure

2.102

0.966

0.092

0.050

4Wageexperience

0.075

2.121

−0.149

*0.047

−0.359

****

5Educatio

n6.306

3.372

0.171*

*0.334*

***

−0.081

0.330*

***

6Self-em

ployed

father

0.642

0.481

−0.038

−0.084

0.043

−0.070

−0.085

7Husbands’

help

0.575

0.496

−0.001

−0.079

−0.076

0.092

0.110

−0.013

8Health

limitatio

ns0.201

0.403

0.031

−0.062

0.047

−0.141

−0.201

**

−0.129

−0.208

**

9City

0.537

0.500

0.169*

0.196*

*−0

.050

0.078

0.459*

***

−0.100

0.140

−0.056

10To

wn

0.239

0.428

−0.075

−0.026

−0.187

**

0.086

−0.166

*−0

.093

0.022

−0.063

−0.604

****

11Manufacturing

0.060

0.238

0.135

0.127

0.216*

*−0

.021

0.052

0.057

−0.102

0.031

0.044

−0.141

12Com

merce

0.657

0.477

−0.111

−0.261

***

−0.253

***

−0.010

−0.079

−0.114

0.046

−0.068

0.023

0.147*

−0.349

****

13Service

0.194

0.397

0.184*

*0.326*

***

−0.036

0.078

0.180*

*−0

.066

0.040

−0.011

0.153*

0.035

−0.124

−0.679

****

14Neighborhood

incomelevel

13.148

0.268

0.106

0.093

−0.035

0.144*

0.176*

*−0

.066

0.215*

*0.029

0.339*

***

−0.015

0.034

0.042

0.065

15Neighborhood

cooperative

networks

0.410

0.494

−0.108

−0.149

*0.073

0.121

0.145*

0.180*

*0.227*

**

−0.041

0.075

−0.005

0.046

−0.068

0.051

0.154*

16Com

munity

organizatio

nal

activ

ities

0.097

0.297

0.097

−0.127

−0.060

0.040

−0.045

−0.018

−0.024

0.087

−0.050

−0.006

0.130

−0.082

0.031

−0.048

0.290*

***

Significancelevel:

*<.10,

**<.05,

***<.01,

****<.001


observations who reported travel time to workplace (n=129), the average time takento travel to the workplace was 4.4 min. This implies that a majority of the self-employed females in our sample either did not have a separate workplace (i.e., theyworked from home) or their workplaces were located quite close to their places ofresidence.

Multivariate analysis

In addition to the ordinary least squares (OLS) model, the endogenous treatmenteffect model that was initially proposed by Heckman (1978) was used. It is likelythat some background variables were imperfectly measured or omitted from the

Table 2 Reduced-form probit models of the likelihood of participation in neighborhood cooperativenetworks and community organizational activitiesa

Variable Models

1b 2c

Controls

Business size −0.982**** (0.274) (Excluded)

Tenure 0.250** (0.122) −0.203 (0.188)

Wage experience 0.076 (0.058) 0.045 (0.083)

Education 0.077* (0.040) −0.040 (0.074)

Self-employed father 0.456 (0.288) 0.071 (0.306)

Husband’s help 0.632*** (0.233) 0.078 (0.308)

Health limitation 0.289 (0.272) 0.376 (0.355)

City 0.309 (0.401) −0.392 (0.546)

Town 0.326 (0.393) −0.315 (0.462)

Manufacturing −0.106 (0.611) 0.943 (0.815)

Commerce −0.146 (0.470) −0.148 (0.642)

Service 0.407 (0.547) 0.211 (0.690)

Neighborhood income level 0.156 (0.438) −0.275 (0.731)

Female’s attitude in neighborhoods 0.335 (0.754)

Political interest in neighborhoods 1.353** (0.625)

Constant −4.187 (5.717) 2.376 (9.325)

Model statistics

Log-pseudolikelihood −251.230 −217.704Number of female self-employed workersin the model

134 134

Joint statistics of χ2 37.610 56.640

Significance of χ2 0.001 0.000

a Huber-White robust standard errors are in parenthesesb Probit model of the likelihood of participation in neighborhood cooperative networksc Probit model of the likelihood of participation in community organizational activities

Significance level: * < .10, ** < .05, *** < .01, **** < .001


regressions, potentially leading to a selection bias. For instance, individuals withhigh or low abilities could select themselves into neighborhood cooperativenetworks. Since selection or self-selection was unobserved, the relative effectivenessof neighborhood social networks could be confounded with the unknownbackground of the participants. Thus, selection phenomena appear when observedor unobserved characteristics simultaneously influence the fact of being part ofneighborhood cooperative networks and community organizational activities.

While not strictly necessary from a mathematical viewpoint, credible implemen-tation requires an instrument (often reported as an exclusion restriction); that is, avariable included in the estimation of the participation equation that is excluded fromthe earnings equation. As Durlauf (2002) suggested, a necessary condition forsatisfying the exclusion restriction in the estimation of the causal effect of socialcapital is that there exists an individual-level variable that affects individualoutcomes but whose group-level average does not causally affect individualoutcomes. Thus, the valid instrument should be the group-level average that doesnot causally affect individual self-employment earnings.

The instrumental variable for neighborhood cooperative network used in ourmodel was measured by the average proportion of females with a positive attitudetoward housework and childcare within hamlet—or neighborhood-level administra-tive units. This was obtained by calculating the proportion of females who believedthat housework and childcare were “glorious, fulfilling, and gratifying tasks” to thetotal number of females in the units who revealed specific attitudes in response to thesurvey question (female attitude in neighborhoods). It is likely that in neighborhoodswith a high proportion of females having positive attitudes toward housework andchildcare, there will be more cooperative networks related to childcare. Further, it islikely that individuals in such neighborhoods will provide more support with regardto neighborhood childcare than they will in neighborhoods with a low proportion offemales with such an attitude. It would also be reasonable to assume that suchneighborhood conditions do not causally affect individuals’ self-employmentearnings. It would also be unlikely that individuals’ self-employed earnings wouldcausally affect neighboring females’ perception toward housework and childcare.

The instrumental variable for community organizational activity is the proportionof females who were familiar with the Female Political Participation Quota Systemto the total number of the female respondents living in hamlet—or neighborhood-level administrative units (political interest in neighborhoods). The Constitutionstipulates that there should be a gender quota of 10 percent for political participation,and some gender activists have persistently demanded an increase in the quota.Collective actions and political mobilizations in neighborhood communities areoften shaped by community organizational activities (Holzner 2004; Musso et al.2006). Thus, a high level of interest in politics among neighboring females may bepositively associated with individuals’ willingness to participate in communityorganizational activities and with the level of such activities in the community. It isalso quite likely that neither the average degree of political interest among thefemales in the same neighborhood causally affects the individuals’ self-employmentearnings, nor is it causally affected by the individuals’ earnings.

Although the estimation approach of endogenous treatment effect models includesboth two-step and maximum likelihood estimators, it is generally perceived that


maximum likelihood estimators are not susceptible to collinearity problems. Sinceour sample is small, maximum likelihood estimators were obtained for both models.

Table 2 provides the reduced-form probit equations of the endogenous treatmenteffect model for neighborhood cooperative network (model 1) and communityorganizational activity (model 2). In model 1, the effect of business size wasnegative and significant. As firms grew in size, the participation rate with regard tothe provision of support to adjacent neighbors decreased. With regard to the effect oftenure, it is noted that there was a positive association between long-tenuredindividuals and participation rates. We also found that the number of years ofeducation increased an individual’s rate of past participation. The estimate forhusbands’ help in housework revealed that the greater the husbands’ help, the greaterwas the rate of past participation.

In model 2, the control for business size was excluded from the specification,since there were very few individuals who hired employees among the participantsof community organizational activities. In this model, only the average degree offemales’ political interest in neighborhoods had a significant effect, revealing that inneighborhoods with females who have a high level of interest in politics, the rate ofpast participation in community organizational activities is higher.

Variance inflation factor (VIF) tests were conducted for the following linearregression models, and the results suggested that the models were not seriouslydistorted by multicollinearity.

Results

Table 3 shows our model estimates. Model 1, a baseline OLS model, includes all ourcontrols. The effect of the years of wage experience was significant and negative.Contrary to what was predicted, hourly earnings declined with increasing wageexperience. The estimate of education revealed that the higher the education, thegreater were the hourly earnings. All the industry controls exhibited significant effects.

In model 2, we tested hypothesis 1 by adding a neighborhood cooperative networkcovariate. Contrary to what was predicted, the effect of cooperative neighborhoodnetworks on self-employment earnings was negative but insignificant. Thus, pastparticipation in neighborhood social networks did not have a significant effect on self-employment earnings, when tested by the linear regression model. In model 3, wetested hypothesis 2 by adding a community organizational activity covariate as analternative. As expected, the effect of past contributions to work relating to communityorganizational activity on self-employment earnings was positive and significant (β=0.391; p<0.1). Thus, individuals who had made voluntary contributions tocommunity organizational activities were earning more than those who had neverdone so, even without the corrections for self-selectivity. This lends support to H1.

In model 4, we tested hypothesis 1 by means of an endogenous treatment effectmodel. With the correction for self-selectivity, the effect of cooperative neighbor-hood network on self-employment earnings was positive and significant (β=1.582;p<0.01). When controlling for individuals’ self-selection, female individuals’ pastparticipation in neighborhood cooperative networks significantly enhanced self-employment earnings.


The coefficient estimate of correlations of error terms of the participation equationand earnings equation was strongly negative (ρ=−0.915). The likelihood-ratio testrejected the null hypothesis of the absence of error correlations between equations(p<0.01). Therefore, the unobservable factors common to both equations diminishedself-employment performance, while they raised the likelihood of participation incooperative networks. This implies the presence of negative self-selection intoneighborhood cooperative networks, in the sense that those with high earningscapacity are less likely to self-select themselves into cooperative networks.

In model 5, we tested hypothesis 2 by means of an endogenous treatment effectmodel. As predicted, the effect of community service organizations on self-employment earnings was positive and significant (β=1.167; p<0.01). In addition,the coefficient estimate derived from model 5 was much greater than that obtainedfrom the linear regression model shown in model 3. Thus, with the corrections forself-selectivity, the difference between the earnings of those who had madecontributions to community organizational activities and those who had never doneso became more substantial.

The estimate of correlations of error terms between the participation equation andearnings equation was negative (ρ=−0.440), and the likelihood ratio test rejected thenull hypothesis that ρ equals zero (p<0.01). Therefore, the unobservable factorscommon to both equations diminished self-employment performance while raisingthe likelihood of participation in community organizational activities. This impliesthe presence of negative self-selection even in the case of community organizationalactivities.

Conclusion and implications

Key Findings

This study aimed to fill a gap in our understanding of neighborhood social networksof female self-employed workers. Linear regression and endogenous treatment effectmodels were utilized to explore the evidence from the TWFS relating to female self-employed workers’ past participation in neighborhood cooperative networks andcommunity organizational activities. Statistical evidence obtained by using the linearregression model did not lend support to the fact that neighborhood cooperativenetworks affect female self-employment earnings. However, the result from thelinear regression model supports the performance enhancement effect of pastvoluntary contributions to community organizational activities. The finding thatinvolvement in community organizational activities enhances business performanceis consistent with that of Besser (1999).

On the other hand, the evidence obtained by using the endogenous treatmenteffect model supports the enhancement effect of neighborhood cooperative networkson female self-employment earnings, with the correction for self-selectivity. Theevidence also suggests that past voluntary contributions to community organizationalactivities were more strongly associated with female self-employment earnings withthe correction for self-selectivity than when the estimation was carried out withoutthe correction.


Tab

le3

Ordinaryleastsquaresandendogenous

treatm

enteffect

modelsof

femaleself-employmentearnings

a

Variable

Model

1b2

34c

5

Controls

Businesssize

0.189

(0.189

)0.122

(0.182

)0.22

8(0.193

)0.553*

*(0.239

)0.23

1(0.183

)

Tenure

0.049

(0.082

)0.073

(0.085

)0.06

0(0.084

)−0

.078

(0.117

)0.08

2(0.090

)

Wageexperience

−0.099

**

(0.041

)−0

.091

**

(0.040

)−0

.100

**

(0.042

)−0

.139

**

(0.060

)−0

.105

**

(0.043

)

Edu

catio

n0.047*

(0.026

)0.054*

*(0.025

)0.04

7*(0.026

)0.008

(0.038

)0.05

0*(0.028

)

Self-em

ploy

edfather

0.025

(0.208

)0.088

(0.228

)0.03

2(0.208

)−0

.317

(0.225

)0.04

4(0.201

)

Husband

s’help

0.017

(0.174

)0.070

(0.170

)0.01

7(0.174

)−0

.269

(0.261

)0.00

8(0.170

)

Health

limitatio

ns0.125

(0.169)

0.146

(0.172)

0.104

(0.164)

0.013

(0.233)

0.059

(0.158)

City

−0.034

(0.247

)−0

.022

(0.243

)−0

.017

(0.249

)−0

.098

(0.340

)0.02

3(0.259

)

Town

−0.103

(0.250

)−0

.075

(0.250

)−0

.089

(0.247

)−0

.255

(0.334

)−0

.053

(0.244

)

Manufacturing

0.958*

**

(0.338

)1.004*

*(0.328

)0.86

5**

(0.352

)0.714

(0.559

)0.70

0*(0.401

)

Com

merce

0.548*

*(0.242

)0.559*

*(0.238

)0.54

3**

(0.238

)0.489

(0.418

)0.53

2**

(0.236

)

Service

0.885*

**

(0.325

)0.929*

**

(0.331

)0.84

7***

(0.319

)0.647

(0.479

)0.79

6**

(0.310

)

Neighbo

rhoo

dincomelevel

0.238

(0.305

)0.284

(0.322

)0.25

4(0.314

)−0

.009

(0.381

)0.29

0(0.326

)


Neigh

borhoo

dsocial

networks

Neighborhoodcooperativenetworks

−0.293

(0.199

)1.582*

**

(0.458

)

Com

munity

organizatio

nalactiv

ities

0.391*

(0.211)

1.16

7***

(0.431

)

Constant

−0.368

(4.032

)−1

.041

(4.275

)−0

.638

(4.147

)3.257

(4.914

)−1

.243

(4.290

)

Model

statistics

R2

0.155

0.171

0.16

7

F-value

3.890

3.800

3.74

0

Significanceof

F0.000

0.000

0.00

0

ρ−0

.915

−0.440

σ1.244

0.95

3

Likelihood-ratio

statisticsof

independence

ofequatio

ns10.100

7.170

Significanceof

Likelihood-ratio

statistics

0.002

0.00

7

Log-pseudolikelihood

−251

.230

−217

.704

Num

berof

femaleself-employed

workers

inthemodel

134

134

134

134

134

Jointstatisticsof

χ2

37.610

56.640

Significanceof

χ2

0.001

0.00

0

aHub

er-W

hite

robuststandard

errors

arein

parentheses

bModels1–3:

OrdinaryLeastSquares

Mod

elcMod

els4–

5:End

ogenou

sTreatmentEffectModel

Significancelevel:

*<.10,

**<.05,

***<.01,

****<.001


Our evidence also suggests that there is a strong negative self-selection into thepast provision of personalized support to adjacent neighbors. The presence of strongnegative self-selection is an important reason as to why the linear regression andendogenous treatment effect models obtained different results with regard to thesignificance of neighborhood cooperative networks. Further, the evidence suggeststhat there is also a negative self-selection into past voluntary contributions tocommunity organizational activities, although weaker than that found in neighbor-hood cooperative networks.

We interpret the finding that individuals with high earnings capacity are lesslikely to self-select themselves to participate in neighborhood social networks asfollows. Neighborhood social networks are regularly characterized by close spatialproximity, member homogeneity, and low network inclusiveness (Alesina and LaFerrara 2000; Bowles and Gintis 2002). If neighborhood networks have suchexclusive properties, then why do they include a considerable number of peoplehaving low earnings capacity? First, the close proximity of neighborhoodinteractions facilitates social capital formation with low communication costs, sinceas Glaeser et al. (2002) argued, physical distance has a deterring effect on socialcapital formation. Second, in their seminal study of immigrant groups, Portes andSensenbrenner (1993) discussed the notion of “bounded solidarity.” The solidarityamong community members leads to hostility toward outsiders, whereas assuggested by the “protected market hypothesis” in the study of immigrant groups(Aldrich et al. 1985; Evans 1989), the solidarity offers the group members anadvantage in terms of them being able to exploit local market opportunities, althoughthis is the case to a lesser extent in general residential communities than inimmigrant groups. Thus, it is likely that these properties lead more females with lowearnings capacity to self-select into neighborhood social networks or to be selectedby the community.

On the other hand, we also interpret the finding pertaining to negative selection asthe evasive behavior of those with high earnings capacity to avoid communitycontrol and enforcement. The control and enforcement capacity of neighborhoodcommunities have a constraining effect on the competitive advantages of those withhigh earnings capacity. For instance, in his in-depth case study of Caotun Townshipin Nantou county in central Taiwan, Skoggard (1996, p. 131) observed thefollowing: “Wealthy factory bosses are expected to contribute generously to templesto pay back the gods for their good fortune. Entrepreneurs do give, but they also tryto protect themselves from the traditional claims placed on wealth by family andcommunity.... The entrepreneur is running away from the shame of not fullyhonoring traditional obligations of reciprocity that have maintained communitycohesiveness and identity, preserving rural society over the generations.” In moregeneral terms, as suggested by Portes (1998) and Sandefur and Laumann (1998), ifthe community expects successful members to assist less successful ones, therearises substantial free riding on the success. Portes and Sensenbrenner (1993) alsosuggested that the solidarity and enforcement capacities that promote ethnic businessalso restrict the scope of individual expression and the extent of extracommunitycontacts. Thus, for female self-employed workers with high earnings capacity, thecosts of participating in the neighborhood community are likely to be high, althoughthe participation will offer certain benefits. In sum, even though neighborhood social


networks have an enhancement effect on self-employed females, the beneficiariesare confined to certain groups of individuals with low earnings capacity, because ofthe self-selection into network participation.

Implications for policy makers and practitioners

A key finding of this study was the observation that participation in neighborhoodsocial networks significantly increases female self-employment earnings, althoughthe networks are more likely to include those with low earnings capacity. Policymakers and practitioners who seek to reduce the difficulties faced by deprivedcommunities are encouraging female self-employment. Assistance can be providedfor the vitalization of neighborhood cooperative networks and communityorganizational activities, and open access for a large number of female self-employed workers can be provided.

However, despite the enhancement effect, the individuals with low earnings capacityself-select into neighborhood social networks. Assuming an interventionist approach,policy makers and practitioners may reduce some of the barriers impeding socialinteractions across and beyond neighborhood communities, encouraging neighborhoodsocial networks to be more inclusive. For instance, Woolcock (1998, p. 171) warns ofthe limitations of certain networks such as those based on close ties. He describes suchnetworks as “being characterized by an ‘excess of community’ built on such fierceloyalties and familial attachments that members are discouraged from advancingeconomically, moving geographically, and engaging in amicable dispute resolutionwith outsiders.” Individuals seeking to encourage local female business developmentin distressed communities need to be aware of the profiles of neighborhood networkmembers and then encourage the development of an inclusive network.

Implications for researchers

In the future, longitudinal studies are required to explore the behavior of localentrepreneurs and dynamic business capabilities. This study needs to be replicated usingmale samples and also in a variety of national, cultural, regional, and industrial settings.We argued that neighborhood social networks increase female self-employmentearnings mainly by helping in the establishment of a customer base, by making inputresources available, and by circulating information mediated by the formation ofreputation. However, further studies are required to determine which of these factors isdominant. Additional studies are required to directly measure the extent to which thenon-market contribution to the community is reciprocated by the community asdiscussed in Kilkenny et al. (1999), and the level of civic norms in the community.Qualitative studies, particularly multiple in-depth case studies involving the use of theparticipant–observer technique that follow the neighborhood network process overtime could provide further valuable insights into when and how neighborhood socialnetworks are mobilized to identify and exploit local market opportunities.

Acknowledgements This research is supported by a grant from the 21st Century Center of ExcellenceProgram at Hitotsubashi University for research on the topic “Normative Evaluations and Social Choice ofContemporary Economic Systems.” I am deeply indebted to my doctoral dissertation advisers, Shinkichi


Taniguchi and Hiroyuki Okamuro, for their advice and guidance. I am grateful to Ming-Wen Hu, NoriyukiDoi, and the audience at the 2007 International Council for Small Business World Conference, held at theTurku School of Economics, for their helpful comments.

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neighborhood social networks and female self-employment earnings in taiwan

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