Only the Lonely? The Influence of Spouse on the Transition to Self- Employment Berkay Ozcan Center for Research on Inequalities and the Life Course, Sociology Department Yale University

Motivation 1.Scant research about self-employment in the family domain: Self-employed considered as a “lonely only” individual with strong assumptions about the exogeneity of external influences on the decision to become self-employed. When family is considered, it is often viewed from the intergenerational perspective. Spouses are treated as forgotten relatives.

Motivation 2. Major transformations around the family might have changed the distribution of advantages and disadvantages for SE across the households over the last three decades. i.e. decline in the co-residence in inter-generational households, rise in single-headed households; educational attainment and lfp of the married women, assortative mating. 3. Cross-sectional research shows that married individuals are overrepresented among the self-employed. Married self-employed have higher earnings than unmarried ones other things being equal. (Wong, 1986)

Motivation 4. Few existing studies that include marriage and spouses have important methodological shortcomings: Selected/Truncated Samples: i.e. only the married; the immigrants or solely women’s transition to self-employment Cross-sectional designs: i.e. absence of premarital work- history, simultaneous selection into the marriage and self- employment (i.e. assortative mating on observables)

Research Questions Does marriage matter for the transition to become self-employed? Does it affect women differently than men? What are the spousal characteristics that matter most for different types of self-employment transitions?

Outline 1.Theoretical background and hypotheses 2.Dependent variables 3.Data, Sample and Methods 4.Results 5.Conclusions

Theoretical Background 1.Marriage can be a risk-reducing institution. Also a wealth-enhancing institution. 2.Marriage and spouses influence ones’ labor force participation and labor market outcomes in general (i.e. occupational status, career mobility). 3.Most theories of entrepreneurship treated self-employment as an alternative way for career mobility. But it can also be a way to participate in the labor market.

Theoretical Background Spouses might improve each other’s resources, via skill and knowledge transfers, networks. i.e. help with job related exams, inform about job opportunities, use influence on connections..etc. Having a spouse -> positive effect on labor market outcomes. Marriage can lead an erosion in the job related human capital for the spouse that specializes in the domestic work. Having a spouse who is employed -> negative effect for one spouse and positive for the other.

Dependent Variables (SE Types) Previous literature focused on “Incorporated Businesses” and “Entrepreneurs” Incorporated business owners are likely to be men due to higher levels of career commitment (Budig 2006, Arum 2004). Additionally, I include “Unincorporated Businesses” Women are more prevalent in unincorporated business because they use self employment as a strategy for work and family life balance (Carr 1996, Budig 2006).

Table 1. Distribution of the Self-employed by Education and gender (2003). Unincorporated Self- employed Incorporated Self-employed TotalMenWomenTotalMenWomen Less than High School 10,612,77,34,95,14,4 High School 31,432,429,723,123,023,1 Some college 18,317,719,218,317,620,2 Associate degree 8,57,110,87,478,6 College graduates 18,917,920,528,428,528,2 Advance d Degree 12,312,212,517,918,815,5 Total 100 Source: Author's recalculations of the table 3 of Hipple (2004) which uses Current Population Survey (CPS) 2003

Table 2. The Incidence of the Self-Employed by Gender and Occupation.

Data and Sample Panel Study of Income Dynamics (PSID) between annual observations. Career history of all the individuals from the time that they enter the labor market until they realize a SE transition or become censored. Out of this risk set, I exclude individuals: a) who never became family head or wife b) who have unrecoverable attrition of more than one year c) who start immediately as self employed after formal schooling (only 11 individuals) Previous literature indicates the almost 40% of men by their early fifties have engaged self employment at least once in a life time. In my sample this rate is 34% when they reached 47.

Model Specification where: p is the complementary log-log function (other link functions also estimated) m denotes the dummy variable indicating whether individual is married in the previous year. r i defines the resources of the spouse ( i indicates the type of resources; 1) human capital 2) social resources and 3) financial resources) X represents the matrix of control variables t j stands for the intercepts for each of the time interval considered (i.e. baseline h. rate). I estimate different versions of the following basic specification

Explanatory and Control Variables 1.Explanatory Variables: Marital status : -Marriage and cohabitation treated equally. -Marriage enters in the model in the lagged form (i.e. temporal order) Spousal Resources : -Social Resources: Spouse employment status Spouse Education -Financial Resources: Spouse hourly wage

Explanatory and Control Variables 2.Control variables: - Individual characteristics: Education, race hourly wage, origin state of employment... -Father’s self employment status, parent’s SES status. -State-level SE rate. -Marriage duration, birth-event

MENWOMEN VariableNMeanSt. D.MinMaxNMeanSt D.MinMax Self-Emp- Corporation ,0060, ,0020,0401 Self-Emp- Unincorp. Bus ,0120, ,010,1101 Time ,766, ,846,80132 Time ,85177, ,17175, Race-Black ,310, ,380,4901 Race-Hispanic ,030, ,030,1701 Marriage Duration ,446, ,656,09032 Married(lagged) ,660, ,590,4901 Education ,120, ,130,3401 Education ,480, ,490,5001 Education ,190, ,200,4001 Education ,160, ,130,3401 Previous year not-work ,200, ,410,4901 Years of Not working ,301, ,523,30031 Lnhourly wage (lag) ,150,80010, ,770,87011,15 Parents' SES-Aver-Vary ,440, ,400,4901 Parents' SES-Well-off ,290, ,260,4401 Father Self-employed ,030, ,020,1501 State Self Emp. Rate ,150,030,020, ,150,030,020,30 Spouse Not working ,260, ,040,1901 Spouse Employed ,360, ,490,5001 Spouse Self-employed ,030, ,040,2101 Lnhourly wage _Sp(lag) ,111,1007, ,221,26010,12 _lag Spouse_edu~ ,030, ,030,1601 _lag Spouse_edu~ ,070, ,050,2201 _lag Spouse_edu~ ,320, ,270,4401 _lag Spouse_edu~ ,140, ,130,3401 _lag Spouse_edu~ ,090, ,100,3101

Results 1) The effect of Marriage and Individual Resources (only relevant estimates are reported) – Table 1- Corporate Business – Table 2- Unincorporated Business 2) Spousal Effects (only relevant estimates are reported) – Table 3-Corporate Business – Table 4-Unincorporated Business

Conclusions Marriage does not positively affect the likelihood of SE transitions of women when SE is a career advancement (Corporate business). Whereas it positively contributes to the likelihood of men’s starting up a corporate business. Once we control for marriage duration, being married in the previous period increases the likelihood of a transition to unincorporated business type of self employment both for men and women. Negative sign for the marriage duration means transition to SE becomes less likely as the time spent in the marriage.

Table 6: Determinants of Hazards of Transition to S.E.-Corporate Business (C-log-log ) Spouse Res. WOMENMEN modelaModelbmodelcmodeldmodelemodelfmodelgmodelhmodelimodelj Marriage Duration-Sq ** ** (0.025) (0.041)(0.025)(0.043)(0.024) (0.029)(0.024)(0.027) Education_ ***1.397** **1.106* (0.798)(0.805)(0.807)(0.806)(0.796)(0.638)(0.653)(0.772)(0.648) Trans. from not-work0.591**0.575** ** *-1.032** ** (0.284)(0.288)(0.392)(0.294)(0.392)(0.317) (0.413)(0.305)(0.395) ln-lagged(hourly wage) ***-0.608***-0.581***-0.600***-0.484** (0.104)(0.106)(0.190)(0.117)(0.189)(0.154)(0.148)(0.191)(0.148)(0.206) Parents SES-Aver-Vary **0.476*0.579*0.395*0.476* (0.348)(0.346)(0.404)(0.339)(0.401)(0.243)(0.244)(0.298)(0.235)(0.287) Parents SES- Well Off0.670*0.634*0.837**0.597*0.868**0.821***0.811***0.815***0.743***0.769*** (0.343)(0.340)(0.393)(0.332)(0.390)(0.242)(0.245)(0.297)(0.236)(0.285) SPOUSE SOCIAL RESOURCES Spouse Employment Status (Ref. Cat: Spouse Not Working) _ No spouse-0.881* *-0.933***-0.937**-0.828*** (0.517)(0.598)(0.718)(0.464)(0.346)(0.253)(0.308)(0.443)(0.285)(0.303) _ Spouse Salary Earner-0.985*-1.066**-1.270** (0.522)(0.526)(0.594) (0.173)(0.175)(0.234) _Spouse Self-Employed * (0.530)(0.532)(0.663) (0.345)(0.357)(0.495) Spouse Education (Ref. Cat: Highest Education) _lag Spouse Edu~ (0.545)(0.731)(0.545) _lag Spouse Edu~ **-0.999*-0.958** (0.684)(0.865)(0.670) (0.391)(0.570)(0.386) _lag Spouse Edu~ ***-0.513*-0.645*** (0.415)(0.518)(0.407) (0.233)(0.295)(0.227) _lag Spouse Edu~ * (0.366)(0.487)(0.365) (0.238)(0.283)(0.228) SPOUSE FINANCIAL RESOURCES Spouse ln-lagged(hourly wage) (0.145)(0.173) (0.137) (0.126) Ll chi2118.7***122.6***99.7**72.8***72.5***102.7***115.8***94.4***114.0***78.5*** N # of Events

Table 7: Determinants of Hazards of Transition to S.E.- Unincorporated Business (C-log-log Estimates) Spouse Resources WOMENMEN modelamodelbModelcmodeldmodelemodelfmodelgmodelhmodelimodelj Marriage Duration-Sq *** ***-0.044***-0.045***-0.041***-0.044***-0.057***-0.034***-0.051*** (0.011) (0.014)(0.011)(0.014)(0.013) (0.018)(0.013)(0.017) Black-0.666***-0.672***-0.677***-0.691***-0.694***-0.806***-0.794***-0.848***-0.804***-0.812*** (0.112)(0.113)(0.119)(0.112)(0.119)(0.131) (0.151)(0.127)(0.145) Education_50.564**0.551**0.604**0.577**0.607** (0.236)(0.253)(0.264)(0.252)(0.244)(0.235)(0.249)(0.286)(0.246)(0.272) ln-lagged(hourly wage)-0.375***-0.377***-0.477***-0.373***-0.478***-0.823***-0.819***-0.863***-0.824***-0.850*** (0.097)(0.098)(0.092)(0.098)(0.092)(0.088)(0.089)(0.111)(0.086)(0.109) Parents SES- Well Off 0.193*0.198*0.232*0.210*0.233* (0.117)(0.118)(0.126)(0.117)(0.125)(0.133) (0.153)(0.131)(0.148) State Self-Emp. Rate5.167***5.158***5.895***5.282***5.940***3.295**3.257** ** (1.424)(1.425)(1.502)(1.417)(1.508)(1.515) (1.814)(1.469)(1.764) SPOUSE SOCIAL RESOURCES Spouse Employment Status (Ref. Cat: Spouse Not Working) _ No spouse *-0.293*-0.464***-0.605***-0.489*-0.549*** (0.261)(0.314)(0.341)(0.190)(0.157)(0.160)(0.227)(0.288)(0.206)(0.192) _ Spouse Salary Earner (0.249)(0.258)(0.271) (0.119)(0.121)(0.176) _Spouse Self-Employed * * (0.291)(0.301)(0.331) (0.243)(0.245)(0.353) Spouse Education (Ref. Cat: Highest Education) _lag Spouse Edu~ (0.314)(0.341)(0.304) (0.332)(0.436)(0.306) _lag Spouse Edu~ (0.245)(0.276)(0.240) (0.290)(0.227) _lag Spouse Edu~ (0.166)(0.190)(0.164) (0.187)(0.215)(0.180) _lag Spouse Edu~ ** (0.171)(0.193)(0.170) (0.204)(0.238)(0.196) SPOUSE FINANCIAL RESOURCES Spouse ln-l-hourly wage (0.062) (0.060) (0.105) (0.092) Ll chi *** *** *** ***205.80*** *** *** *** *** *** Bic N # of Events

Conclusions Being in a couple affects men positively. It only affects women positively if men doesn’t work or he is self-employed. (No support for risk-pooling hypothesis) Wife’s human capital is the main spousal resource on the likelihood of men’s self-employment transition. Some evidence for the hypothesis that “women mostly seek SE as a strategy to find the work life balance”. Spousal social capital is an important contributor to the likelihood of their transition to unincorporated business. (A way to keep themselves in the labor market)

Main Caveats (Unobserved)Selection of individuals both into self employment and marriage. (other than educational assortative mating) Few events for women entrepreneurs for corporate business. Heterogeneity among the unincorporated business owners (skilled versus unskilled) NEXT STEP: -Competing risk model across for the outcomes of different types of SE - Different classification of SE: i.e. managerial/professional versus non-professional/ unskilled