Marriage and WagesFinal Paper Presentation

Online Micro-econometrics: Fall 2015

Xuefeng Xing (xxing@jhu.edu)Assel Dykanbayeva (adykanb2@jhu.edu)

The Effect of Marriage on Earnings of men• It is well-known fact in the labor economics that married men on

average earn more than unmarried men. • The difference between wages of men, which can be related to the

marital status, is called the marital (marriage) premium. • Most studies find that the marriage premium is between ten and forty

percent.• Although the existence of the marital premium is almost universally

accepted, there is much less agreement on its’ source.

What is the source of the Marital Premium?• The productivity approach explains that the marital premium exists

because the marriage makes men more productive.• The selection approach states that the marital premium is paid

because married men have some unobservable characteristics, which made them more attractive both for marriage and labor market.• The specialization approach implies that due to the marriage men

have opportunity to concentrate their efforts on career and devote less time to housework. This results in more earnings of married men.

Purpose of the study• The main purpose of our study is to analyze the effect of the marital status

of men on their earnings in government and private sector. • We consider that there can be a significant difference in the effect of marital

status on earnings in the private versus governmental sector.• This hypothesis is based on the assumption that civil service requires special

characteristics of an employee and a higher appreciation of traditional family values. • To some extent the hypothesis supports the selection approach in explaining

marital premium for men (existence of unobservable characteristics of men, which made them more attractive both for employee and for marriage).

Data and Empirical Specifications

• We utilized 2011 data from the Current Population Survey (CPS). • The dataset includes working men in the age range between 17 and 66,

excluding those who are either unemployed or employed in the military.

Married68%

Divorced/Widowed

9%

Not Married

23%

Married Divorced/WidowedNot Married

We also exclude from the dataset men whose information on wage was missing or with wages less than the minimal wage.There are 40,509 men in the sample.

Mean Wages of Men of different age groups, $

18-24 25-34 35-44 45-54 55-65 Total0

1000020000300004000050000600007000080000

1.Married 2.Divorced/Widowed 3.Not Married

We observe significantly higher wages of married men – on average, it is 62% or $25,970 higher than the average wage of single men.

Mean Wages of Men occupied in different industries, $

Agricultu

re & mining

Constructi

on

Manufacturin

gTrade

Transp

ortation

Informati

on

Finance

Professional se

rvices

Servi

ce0

20000

40000

60000

80000

100000

Married Divorced/Widowed Not Married

Mean Wages of Men by Races and Marital Status, $

White Black Hispanic Others0

1000020000300004000050000600007000080000

Married Divorced/Widowed Unmarried

The Model for estimating marital premium

• In the analysis of the relationship between marital status and wages the dependent variable is wages (P_EARN_VAL). Independent variables are an education, an experience and its square (EXSQ), dummies for marital status, dummy on type of occupation (1 – government, 0 – private), dummies for industry (variables AGRICULTURE, CONSTRUCTION, MANUFACTURING, TRANSPORTATION, INFORMATION, FINANCE, PROFESSIONAL SERVICES AND SERVICE), dummies on race. • The base group is white single men, working in a private company in

the trade industry.

Results• The coefficient of interest on the dummy Married is equal 0.206 with

SE 0.008 and p-value 26.56. • It implies that holding other variables constant, the predicted wage of

married men is 20.6% higher than never-married men.• The F-test value are high (1059.8), which means that coefficients in

the model are jointly statistically significant.• R-squared is 0.3079• The estimates of other variables have the expected signs, and all of

the estimates are statistically significant at the 1% level.

Does the Government pay more marital premium?

• We run the second regression, which additionally includes interaction term between dummies MARRIED and GOVERNMENT. • As a result, we obtain small changes in the coefficients’ estimates on

MARRIED and GOVERNMENT, and both statistically significant and significant in magnitude estimated coefficient on the interaction term with negative sign (β=- 0.1061, SE=0.0182). • These results imply that a marriage premium, paid by governmental

employer is less than those, obtained by the private-sector employee.

Conclusion• In our research, based on the CPS 2011 data, we discovered a marital

premium for men 20.6%. The hypothesis of bigger marital premium for men from governmental employers is rejected at 1% confidence level. • More than likely that the male marital wage premium is a result of

multiple factors. We suppose that a considerable part of the marriage premium stems from ability bias. Men who marry are just more conscientious, ambitious, and cooperative, and the CPS data lacks good measures of these traits.

Variables Model 1 Std. Err. Model 2 Std. Err.education 0.101 0.001 0.101 0.001experience 0.037 0.001 0.037 0.001experience squared -0.001 0.000 -0.001 0.000married 0.206 0.008 0.219 0.008divorced 0.048 0.012 0.045 0.012government 0.021 0.009 0.097 0.016agriculture 0.152 0.017 0.151 0.017construction 0.035 0.011 0.034 0.011manufacturing 0.124 0.011 0.123 0.011transportation 0.102 0.013 0.102 0.013information 0.219 0.019 0.219 0.019finance 0.253 0.014 0.252 0.014professional_services 0.076 0.010 0.076 0.010service -0.022 0.011 -0.021 0.011black -0.200 0.011 -0.201 0.011hispanic -0.131 0.008 -0.131 0.008others -0.095 0.010 -0.096 0.010gov_mar - - -0.106 0.018_cons 8.730 0.021 8.724 0.021

Appendix. Estimated coefficients