This paper contributes to the literature in three ways. Our first contribution is calculating the marriage premium for Turkey. Our results suggest that married men earn 27 percent more than single men and married women earn 4 percent less than single women. Our second contribution is calculating the marriage premium for Turkey’s regions. For men, the wage difference is the smallest, 0.43, in Istanbul. The difference is highest in Akdeniz region. For women, the wage difference is smallest, -0.04, in Ege and the highest, 0.62, in Dogu Anadolu. Finally, we estimated the relationship between age and the marriage premium. We found that for men, at younger ages the difference is high. For women, in most of ages single women earn more than married women.marriage, earnings, marriage premium

Mercan, Murat A.

English

Research Papers in Economics

1 
 
 
 
 
 
Marriage Premium in Turkey 
 
 Murat Anil Mercan* 
Gebze Yüksek Teknoloji Enstitüsü 
 
 
 
 
 
 
 
 
 
 
 
 
 
*Gebze Yüksek Teknoloji Enstitüsü, Çayırova Kampüsü B Blok: 111 Çayırova/Gebze,Kocaeli 41400  
email:mamercan@gyte.edu.tr  
tel:0262 6051431 
 
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Abstract 
This paper contributes to the literature in three ways. Our first contribution is calculating the 
marriage premium for Turkey. Our results suggest that married men earn 27 percent more than 
single men and married women earn 4 percent less than single women. Our second contribution 
is calculating the marriage premium for Turkey’s regions. For men, the wage difference is the 
smallest, 0.43, in Istanbul. The difference is highest in Akdeniz region. For women, the wage 
difference  is  smallest,   0.04,  in  Ege  and  the  highest,  0.62,  in  Dogu  Anadolu.  Finally,  we 
estimated the relationship between age and the marriage premium. We found that for men, at 
younger ages the difference is high. For women, in most of ages single women earn more than 
married women. 
Keywords: marriage, earnings, marriage premium 
   3 
 
I Introduction 
Is there a marriage premium? It asks do married men earn more than single men. This question 
takes  a  lot  of  attention,  for  instance,  Leonard  and  Stanley  (2010)’s  meta regression  analysis 
depends on 50 studies which estimate the marriage premium.  
In  addition,  for  the  first  time,  we  used  Income  and  Living  Conditions  Survey  (ILCS)  2009  for  the 
marriage premium analysis. ILCS is a nationally representative dataset. When we look at the averages 
of wages, we see married men earn more than single men. For instance, in our 2009 sample on 
average single men earn 6,824 TL. On the other hand, on average married men earn 10,061 TL. 
It is sixty eight percent more than single men’s average. When we look at women’s earnings, we 
see a similar pattern. On average single women earn 6,738 TL and married women earn 7,628 
TL. 
This paper contributes to the literature in three ways. Our first contribution is calculating the 
marriage premium for Turkey. Our second contribution is calculating the marriage premium for 
Turkey’s regions. Finally, we estimated the relationship between age and the marriage premium. 
Our results suggest that married men earn 27 percent more than single men and married women 
earn  4  percent  less  than  single  women.  In  addition,  we  looked  at  the  marriage  premium  of 
Turkey’s regions. For men, the wage difference is the smallest, 0.43, in Istanbul. The difference 
is highest in Akdeniz region. For women, the wage difference is smallest,  0.04, in Ege and the 
highest, 0.62, in Dogu Anadolu. 
II Theoretical Background 
There are three main explanations why married men earn more than single men. First of all, 
married men might be more productive because they can specialize in non household production. 
Second  possibility  is  employers  discriminate  in  favor  of  married  men.  Finally,  married  men 
might have some unobservable characteristics which make them attractive in both labor market 
and marriage market. Antonovics and Town (2004) use a dataset which includes monozygotic 
twins. They found when they treated the data as a cross section the marriage premium is 19 
percent. However, when they look within monozygotic twins, they found the marriage premium 
increases to 26 percent. 
Schoeni (1990) uses Luxembourg Income Study and calculates the marriage premium for twelve 
different countries. He found that the marriage premium varies between 3 percent and 31 percent 
in the twelve countries. In addition, Schoeni (1990) investigates the relationship between age and 
the marriage premium. He found that the mean marriage premium for men ages 30 and 50 across 
twelve countries is 13.6 percent and 19.7 percent, respectively. 
Ozcan  et  al.  (2003)  investigate  wage  differences  by  gender,  wage  and  self  employment  in 
Istanbul.  They  use  the  1994  Household  Income  Survey  of  the  State  Institute  of  Statistics. 
According  to  Ozcan  et  al.  (2003)  in  Istanbul  the  mean  earnings  of  married  and  unmarried 4 
 
workers  are  148.5  million  TL  and  63.2  million  TL,  respectively.  They  found  married  wage 
earner  men  earn  29  percent  more  than  unmarried  wage  earner  men.  In  addition,  they  found 
married wage earner women earn 27 percent less than unmarried wage earner women. 
Furthermore,  Muniz  and  Ruis Neto  (2011)  calculate  the  marriage  premium  for  Brazil.  They 
estimate the marriage premium among formally married, informally married, and single workers. 
Muniz  and  Ruis Neto  (2011)  find  the  wage  gap  is  largest  between  formally  and  informally 
married in Brazil. When they compare single  workers with formally  married and informally 
married workers, the gap is bigger with the formally married couples. 
In addition, Leonard and Stanley (2010) use a meta regression analysis which depends on 50 
studies.  According  to  them,  on  average,  these  50  studies  report  that  married  men  earn  15.5 
percent more than single men. The smallest wage premium reported is  0.39, and the maximum 
was  1.00.  Leonard  and  Stanley  (2010)  point  out  that  about  61  percent  of  the  estimates  are 
between 0.05 and 0.2. 
Besides, several studies investigate the wage gap between the genders. For instance, Blau and 
Kahn  (1996)  find  that  the  pay  gap  is  much  larger  for  married  workers  for  ten  countries. 
According to their estimates, the wage rate (women’s earnings over men’s earnings) is 0.55 and 
0.86 for married workers and single workers in the US.  
III Estimation Procedure and Data 
We used Oaxaca decomposition in this paper. According to Jann (2008), Oaxaca decomposition 
takes following form: 
        Y1 = X1b1 + e1 
        Y2 = X2b2 + e2 
for  some  outcome  variable  Y  in  two  groups  1  and  2.  As  long  as  E(e1)=E(e2)=0,  the  mean 
outcome difference between the two groups can be decomposed as 
        R = x1'b1   x2'b2 = (x1 x2)'b2 + x2'(b1 b2) + (x1 x2)'(b1 b2) = E + C+ CE 
where x1 and x2 are the vectors of means of the regressors. In addition, E stands for Endowment, 
C  stands  for  Coefficient,  and  CE  stands  for  Interaction  in  the  decomposition.  If  there  is  a 
selection, the model becomes 
        R_s = x1'b1   x2'b2   (s1bs1   s2bs2) 
where s1 and s2 are the means of selection variable (S) and bs1 and bs2 are the coefficients of S. 
In that case, our Oaxaca decomposition depends on the following regression: 
ln (wage) = α1  + β1 Educ + Ɵ1 Age + e1 5 
 
However, in our data set, age and education are not continuous variables. The age has 14 intervals and the 
education has seven intervals and Table 1 shows those intervals.   
IV Results 
Table 2 shows our OLS and selection model results from our Oaxaca decomposition. In our 
2009  sample,  the  mean  of  the  log  wages  is  8.96  for married  men  and  8.33  for  single  men, 
yielding a wage gap of 0.63.The first part reflects the mean increase in single men’s wages if 
they had the same characteristics as married men. The increase of 0.50 in the 2009 data indicates 
that differences in endowments account for about eighty percent of the wage gap. The second 
term quantifies the change in single men’s wages when applying the married men’s coefficients 
to  the  single  men’s  characteristics.  The  value  of  coefficients  is  0.79.  The  third  part  is  the 
interaction  term  that  measures  the  simultaneous  effect  of  differences  in  endowments  and 
coefficients. The value of interaction is  0.67. However, these results suffer from the selection 
bias. 
In our sample, we also corrected the selection bias. The second part shows those results. The first 
part reflects the mean increase in single men’s wages if they had the same characteristics as 
married men. The increase of 0.19 in the 2009 data indicates that differences in endowments 
account for about sixty five percent of the wage gap. In addition, the value of coefficients is 0.40 
and the value of interaction is  0.31. However, these results are not statistically significant. 
In addition, we calculated the wage gap for women. In our sample, the mean of the log wages is 
8.22 for married women and 8.27 for single women, yielding a wage gap of  0.05. . In addition, 
the value of coefficients is 0.12 and the value of interaction is  0.24. Furthermore, we corrected 
the selection bias. In that case, the wage gap becomes  0.04. These results suggest that married 
women earn less than single women in Turkey. 
Table 3 shows Oaxaca decomposition results for different regions in Turkey. For men, the wage 
difference is the smallest, 0.43, in Istanbul. The difference is highest in Akdeniz region. Other 
regions have pretty similar results which are around 0.60 For women, the wage difference is 
smallest,  0.04, in Ege and the highest, 0.62, in Dogu Anadolu.  
Table 4 shows the effect of age on marriage premium. For men, at younger ages, 15 24, the 
difference  is  high.  Then,  it  declines  to  zero.  After  that,  it  starts  to  increase.  There  is  one 
exception, 50 54, which is a negative number. For women, other than 55 59 age bracket, in all 
ages single women earn more than married women. 6 
 
VI Conclusion 
This study makes several contributions into the literature. First of all, we used a new dataset. Then, this 
dataset allows us to calculate the marriage premium for different regions in Turkey. Finally, we estimated 
the relationship between age and the marriage premium. 
For men, the  wage difference is the smallest,  0.43, in  Istanbul. The difference is highest in 
Akdeniz region. For women, the wage difference is smallest,  0.04, in Ege and the highest, 0.62, 
in Dogu Anadolu.When we look at the relationship between age and the marriage premium, we 
found that for men, at younger ages the difference is high. Then, it declines to zero. After that, it 
starts to increase. For women, other than 55 59 age bracket, in all ages single women earn more 
than married women. 
VII References  
Antonovics, Kate and Town,Robert (2004) “Are All the Good Men Married? Uncovering the 
Sources of the Marital Wage Premium,” American Economic Review, vol. 94(2), pages 317 321, 
May. 
Blau, Francine D. and Kahn, Lawrence M. (1996) “Wage Structure and Gender Earnings 
Differentials: An International Comparision.” Economica, 63, S29 S62. 
Jann, Ben (2008) “Blinder Oaxaca Decomposition for Linear Regression Models.” The Stata 
Journal, 8 (4): 453 479. 
Leonard, Megan and Stanley, T.D. (2010) “Is There a Male Marriage Wage Premium? A Meta 
Regression Analysis” Working Paper. 
Muniz, Jeronimo O. and Ruis Neto, Eduardo L. (2011) “Marriage Premium Among Men and 
Women in Brazil.” Working Paper. 
Ozcan, Yusuf Z., Ucdogruk, Senay, and Ozcan, Kivilcim M. (2003) “Wage Differences by 
Gender, Wage, and Self Employment in Urban Turkey.” Journal of Economic Cooperation, 24 
1, 1 24. 
Schoeni (1990) “The Earnings Effects of Marital Status: Results for Twelve Countries.” PSC 
Research Report No. 90 172. March 1990. 
 
 
 
 7 
 
Table 1: Intervals 
Education 
0  Illiterate 
1  People who can read without holding a degree 
2  Elemantary School 
3  Middle School 
4  High School 
5  Vocational School 
6  College 
Age 
1  between 0 and 4 
2  between 5 and 11 
3  between 12 and 14 
4  between 15 and 19 
5  between 20 and 25 
6  between 25 and 29 
7  between 30 and 34 
8  between 35 and 39 
9  between 40 and 44 
10  between 45 and 49 
11  between 50 and 54 
12  between 55 and 59 
13  between 60 and 64 
14  65 or older 
   8 
 
Table 2: OLS and Selection Model Results 
A. Men 
(OLS) 
(SELECTION 
MODEL) 
Coeff.  s.e.  Coeff.  s.e. 
Mean 1  8.96  0.01  8.89  0.01 
Mean 2  8.33  0.03  8.62  5.41 
Difference  0.63  0.03  0.27  5.41 
Endowments  0.50  0.07  0.19  5.17 
Coefficients  0.79  0.03  0.40  5.41 
Interaction   0.67  0.07   0.31  5.17 
N  7674  7674 
B. Women  (OLS) 
(SELECTION 
MODEL) 
Coeff.  s.e.  Coeff.  s.e. 
Mean 1  8.22  0.04  8.13  0.04 
Mean 2  8.27  0.04  8.18  0.12 
Difference   0.05  0.06   0.04  0.13 
Endowments  0.06  0.04  0.04  0.10 
Coefficients  0.12  0.06  0.12  0.12 
Interaction   0.24  0.05   0.20  0.10 
N  2613  2613 
Note: Mean 1 is the mean of married (wo)men and Mean 2 is the mean of single (wo)men. 
 
   9 
 
Table 3: Regional Coefficients 
MEN  WOMEN 
Coeff.  se  N  Coeff.  se  N 
Istanbul  0.43  0.06  1080  0.05  0.09  408 
Marmara  0.61  0.07  1397  0.44  0.08  1124 
Ege  0.62  0.08  1045   0.04  0.14  461 
Ic Anadolu  0.69  0.07  1246  0.18  0.09  833 
Akdeniz  0.85  0.11  786  0.18  0.15  330 
Karadeniz  0.84  0.09  860  0.61  0.12  561 
Dogu Anadolu  0.65  0.09  1076  0.62  0.11  739 
Guney Anadolu  0.64  0.10  716   0.18  0.27  153 
Turkey  0.63  0.03  7674   0.04  0.13  2613 
 
   10 
 
Table 4: Age Coefficients 
MEN  WOMEN 
Coeff.  se  N  Coeff.  se  N 
15 19  0.49  0.26  598   0.66  0.27  251 
20 24  0.30  0.07  822   0.18  0.13  474 
25 29  0.01  0.05  1352   0.40  0.12  517 
30 34  0.10  0.09  1185   0.45  0.15  376 
35 39  0.30  0.18  1089   0.36  0.18  351 
40 44  0.14  0.23  982   0.33  0.19  286 
45 49  0.41  0.35  785   0.43  0.27  195 
50 54   0.11  0.32  498   0.24  0.31  98 
55 59  0.09  0.67  228  0.18  0.46  42 
60 64  1.11  0.45  90   0.75  1.43  11 
65+  1.63  0.95  45   0.29  0.82  12 
 
 

Are All the Good Men Married? Uncovering the Sources of

Blinder Oaxaca Decomposition for Linear Regression Models.”

Is There a Male Marriage Wage Premium? A Meta Regression Analysis” Working Paper.

Marriage Premium Among Men and Women in Brazil.” Working Paper.

The Earnings Effects of Marital Status: Results for Twelve Countries.”

Wage Differences by Gender, Wage, and Self Employment in Urban Turkey.”

Marriage Premium in Turkey

Marriage Premium in Turkey

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