The degree of assortative mating shows the degree of similarity within couples. Many papers try to calculate earnings correlations between husbands and wives. This paper tries to calculate the earnings correlations for Turkey and consider the effect of the sample selection. Our results show that there is a weak positive assortative mating in Turkey, and the bias from the selection is small. In addition, we look at the assortative mating coefficients in different regions in Turkey. Akdeniz region has the biggest correlation coefficient. Karadeniz has the lowest coefficient which is almost zero.assortative mating, marriage, earnings

Mercan, Murat A.

English

Research Papers in Economics

 
 
 
 
 
Assortative Mating and Turkish Marriage Market 
 
 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  
 
 
 
 
Assortative Mating and Turkish Marriage Market 
Abstract 
The degree of assortative mating shows the degree of similarity within couples. Many 
papers try to calculate earnings correlations between husbands and wives. This paper 
tries to calculate the earnings correlations for Turkey and consider the effect of the 
sample selection. Our results show that there is a weak positive assortative mating in 
Turkey, and the bias from the selection is small. In addition, we look at the assortative 
mating  coefficients  in  different  regions  in  Turkey.  Akdeniz  region  has  the  biggest 
correlation coefficient. Karadeniz has the lowest coefficient which is almost zero. 
JEL Codes: J12 
Keywords:  assortative mating, marriage, earnings  
 
I Introduction 
Assortative  mating  is  one  of  the  growing  topics  in  Economics.  The  degree  of 
assortative  mating  measures  the  degree  of  similarity  within  couples.  It  also  may 
measure similarities on education; for instance, Rose (2001), earnings; for instance, 
Zhang and Liu (2003); and so on.  According to Becker (1973 and 1974), knowing the 
relationship between husbands and wives is crucial to understanding the inequality of 
inheritable traits. It also helps us to understand the correlation between the traits of 
parents and children. Therefore, measuring assortative mating is crucial. 
Becker (1973) points out a negative correlation between husbands’ and wives’ wages 
maximizes total output because the gain from the division of labor is maximized. In 
addition, his analysis predicts that many women have a weak attachment to the labor 
force. The reason of that is husbands’ high wages discourage the wives who spend 
their times on the household production. Furthermore, his theory predicts a negative 
correlation  between  the  wage  rates,  if  we  hold  nonmarket  productivity  constant. 
However, he points out the sample selection leads to find a positive assortative mating. 
However,  Becker’s  theoretical  conclusion  about  assortative  mating  created  many 
controversies  in  literature.  Even  though  he  concluded  there  should  be  a  negative 
assortative mating on wages as a result of the sexual division of labor, the majority of 
studies found a strong positive assortative mating. There are a few exceptions, like 
Zhang and Liu (2003). They considered the effect of the selection bias and found a 
weak  negative  assortative  mating  for Taiwan.  In  addition,  Zimmer  (1996)  found  a 
negative coefficient for North American whites. 
There are several studies that tried to measure assortative mating for several different 
countries. This paper is separated from those by its methodological approach. It is the 
first time in the literature we calculated assortative mating for Turkey while we were 
considering the effect of the selection problem. There was just one previous study, 
Dayioglu and Baslevent (2006), for Turkey; however, they did not consider the effect 
of the selection problem. In addition, for the first time, we used Income and Living  
Conditions Survey (ILCS) 2006, 2007, and 2008 for the assortative mating analysis. 
ILCS  is  a  nationally  representative  dataset.  We  found  there  is  a  weak  positive 
assortative mating in Turkey, and the bias from the selection is small. 
II Turkish Marriage Market 
In this part, we are going to give some information about the Turkish marriage market. 
According to Turkish Statistical Institute (TUIK) data, in 2009, 47.5 percent of the 
population were married. In addition, there were 591,742 new marriages. 84, 667 of 
them were married in July. This is 14.3 percent of all Turkish marriages in 2009. The 
average marriage age is 28.3 and 24.3 for grooms and brides, respectively. 95 percent 
of grooms have never married before and 93.6 percent of brides have never married 
before. 
 In addition, the average age at the first marriage is 26.3 and 23.0 for grooms and 
brides, respectively. In 449,997 marriages, the groom is older than the bride. In 58.3 
percent of them, the age difference is less than six years. 45 percent of first time 
married grooms are between 25 and 29 years old.  40 percent of first time married 
brides are between 20 and 24 years old. 
Furthermore, 32.2 percent of illiterate grooms married a bride who was illiterate. 23.6 
percent  of  grooms  who  did  not  complete  any  school  married  a  bride  who  did  not 
complete any school. In addition, 42 percent of grooms who graduated from the high 
school married a bride who graduated from a high school. 33.9 percent of university 
graduate grooms married a bride who graduated from a university.  On the other hand, 
49  percent  of  university  graduate  brides  married  a  groom  who  graduated  from  a 
university.  
According to ISCO 88, there are nine different occupation groups in our survey. 14.92 
and  15.08  percent  of  couples  worked  in  the  same  occupation  in  2006  and  2007 
respectively. In addition, according to NACE REV 1.1, there are fourteen different 
groups for the firms’ economic activities in our survey.  17.64 and 18.67 percent of 
couples worked in firms which had the same economic activities in 2006 and 2007 
respectively. Agriculture, hunting and forestry is the largest group in both years.  
III Theoretical Background 
Becker (1974) points outs the method of selecting a mate as similar to the method of 
selecting any other consumer good designed to increase a person’s level of utility. . In 
addition, Becker (1974) points out the positive mating on wages exist when he include 
caring into the model. 
Lam (1988) expanded Becker's model and included household public goods into the 
model. Lam (1988) points out that there is positive assortative mating on spouses' 
wealth. After that simple analysis, he allowed for household public goods that are 
produced within the home instead of being purchased in the market. In that case, he 
found two opposite effects and the possibility of a negative assortative mating. 
Nakosteen and Zimmer (2001) use Panel Study of Income Dynamics (PSID) and find 
evidence  of  positive  assortative  mating  on  the  earnings  for  the  US.  In  addition, 
Nakosteen  et.  all  (2004)  use  a  Swedish  data  and  find  the  existence  of  positive 
assortative mating on earnings. 
To date, the negative assortative mating on wages has been obtained by few studies 
like  Zimmer  (1996),  with  a  negative  coefficient  for  North American  whites.  In 
addition, Becker (1993) cites two studies: unpublished negative coefficients obtained 
by Gregg Lewis, and a much weaker correlation obtained by Smith (1979). 
Furthermore, Zhang and Liu (2003), who found a weak negative assortative mating, 
have similarities with this study. They also calculated the direction of the selection 
bias. They found that the simple regression coefficient between spouses' wages is 1.03. 
When  they  control  the  selection  problem,  the  partial  regression  coefficient  may 
become negative ( 0.0004). 
In  addition,  there  is  just  one  previous  study  for  Turkey,  Dayioglu  and  Baslevent 
(2006).  They  used  the  2003  Household  Budget  Survey  (HBS)  in  their  analysis. 
Dayioglu  and  Baslevent  (2006)  found  that  the  correlation  coefficient  between  the 
husbands  and  the  wives  is  0.44.  However,  they  did  not  consider  the  effect  of  the 
sample selection. One common approach is to use Heckman's (1979) procedure to  
correct the model for potential selection bias. We also are going to pursue that method 
on this paper. 
IV Estimation Procedure and Data 
To obtain an estimate of the partial correlation between spouses' earnings when we are 
controlling for spouses' other characteristics, we use the following equation 
Earnings h  =  α0 + α1  Earnings w  +  α2  Age h  +  α3  Age w                        
                     +  α4  Education h  +  α5  Education w  + ε                         (1) 
where subscripts h and w represent husbands and wives respectively. Our analysis will 
depend on Equation 1. 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.  Therefore, we had to use dummy variables for those intervals. 
In that case, we have a total of 19 variables for age and education in the regression. 
Table 2 reports the summary statistics of our sample. There are 692 and 745 couples in 
2006 and 2007, respectively. In addition, there are 913 couples in 2008. For husbands, 
even though 2006 has higher the maximum earnings, the average earnings are higher in 
2007.  The  difference  between  averages  is  less  than  1,000TL.  Wives’  earnings  are 
significantly lower than husbands’ earnings. The wives’ earnings are about 65 percent 
of the husbands’ earnings in three years. 
In the survey, we observe ages in brackets. When we looked at the age, we realize that 
the ages are pretty close in those three years. However, the husbands are older than 
wives. The average age bracket is 8.2 for husbands.  The eight includes ages between 
35 and 39. Besides, the average age of wives is around 7.6. The age bracket seven 
includes age between 30 and 34. 
In  addition,  the  education  variable  also  has  intervals,  instead  of  having  the  actual 
number.  There  are  seven  brackets.  0  means  illiterate  and  6  means  graduated  from 
college or above. Husbands’ and wives’ averages are close, around 3, which means 
graduated from the middle school. It is like completing eight years of schooling.    
V Results 
In this section, we will present nine different results from three different methods we 
have used. Our regressions depend on Equation 1. Table 3 shows all those results.  
First of all, the partial correlation is shown in the first row of Table 3. Results are 
pretty similar for two different samples. The partial correlations are 0.20, 0.25, and 
0.36 for 2006, 2007, and 2008 samples, respectively. These results suggest that there is 
a weak positive assortative mating in Turkey. 
On the other hand, we also examined the effect of sample selection. To do so, firstly 
we estimated an OLS regression, then we used Heckman’s selection model to find the 
direction of the selection bias. The second row of Table 3 shows that the estimates are 
0.33, 0.29, and 0.39 for 2006, 2007, and 2008, respectively. The OLS results are also 
proving there is a weak positive relation between husbands’ and wives’ earnings. After 
OLS analysis, we focused on the selection problem. We ran a Heckman’s selection 
model  and  estimates  became  0.36,  0.33,  and  0.38  for  2006,  2007,  and  2008, 
respectively.  It  means  that  the  direction  of  the  bias  is  toward  zero.  However,  the 
possible bias is small. We also tried to use several different regression forms for the 
selection. All of those gave small biases and are available upon request. 
Furthermore, we also calculate the partial correlations for seven different regions in 
Turkey. For  that, we used Income and Living Conditions Survey (ILCS) 2008. Table 
4 shows those estimates. In addition, Akdeniz has the highest coefficient that is 0.61. 
Dogu and Guney Anadolu has the second highest coefficient. Both of those are higher 
than Turkey’s overall coefficient which is 0.36. In these two regions, there is a strong 
positive assortative mating. Karadeniz has the lowest coefficient which is almost zero. 
Istanbul and Ege have 0.34 which is close to the Turkey’s overall coefficient. 
Finally,  we  also  tried  to  replicate  Dayioglu  and  Baslevent  (2006)’s  results.  Our 
correlation coefficients are 0.49 and 0.53 for 2006 and 2007, respectively. Our results 
are slightly larger than their 0.44. 
VI Conclusion  
This  study  is  the  first  attempt  to  investigate  assortative  mating  and  the  selection 
problem simultaneously for Turkey. Our results reveal that assortative mating is small  
in Turkey. Even though we could not find a negative assortative mating, our results 
show that there is a weak positive assortative mating in Turkey. 
In addition, we also calculated regional assortative mating.  Akdeniz region has the 
biggest correlation coefficient. Karadeniz has the lowest coefficient which is almost 
zero. Istanbul and Ege have 0.34 which is close to the Turkey’s overall coefficient. 
    
VII References  
Becker, Gary S. (1973), “A Theory of Marriage: Part I,” Journal of Political Economy 
81(4):813 46, 
Becker, Gary S. (1974), “A Theory of Marriage: Part II,” Journal of Political Economy 
82(2):S11 S26, 
Becker, Gary S. (1993), A Treatise on the Family (Enlarged Edition), Cambridge and 
London: Harvard University Press. 
Dayioglu,  Meltem  and  Cem  Baslevent  (2006),  “Female  Employment,  Earnings 
Inequality  and  Household  Well being:  The  Case  of  Urban  Turkey”  unpublished 
working paper. 
Lam, David (1988), ‘Marriage Markets and Assortative Mating with Household Public 
Goods’, Journal of Human Resources, 23(4), 462–87. 
Nakosteen,  Robert  A.  and  Zimmer,  Michael  A.  (2001),  “Spouse  Selection  and 
Earnings: Evidence of Marital Sorting,” Economic Inquiry, vol. 39(2), pages 201 13. 
Nakosteen, Robert A., Westerlund, Olle, and Zimmer, Michael A. (2004), “Marital 
Matching and Earnings: Evidence from the Unmarried Population in Sweden,” Journal 
of Human Resources, vol. 39(4). 
Rose,  Elaina  (2001)  “Marriage  and  Assortative  Mating:  How  Have  the  Patterns 
Changed?” mimeo University of Washington 
Smith, James (1979), “The Distribution of Family Earnings,” The Journal of Political 
Economy, 87(5), 163–92. 
Zhang, Junsen, and Pak Wai Liu.( 2003), “Testing Becker's Prediction on Assortative 
Mating on Spouses' Wages,” Journal of Human Resources 38(1):99 110.  
Zimmer, Michael A. (1996), “Assortative Mating and Ethnicity in the Low Wage 
Population: An Examination of Spouses’ Earnings”, Applied Economics Letters, 3(5), 
311–15. 
    
 
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 
  
 
 
T
a
b
l
e
 
2
:
S
u
m
m
a
r
y
 
S
t
a
t
i
s
t
i
c
s
 
 
 
 
 
 
 
 
 
 
 
2
0
0
6
 
2
0
0
7
 
 
2
0
0
8
 
M
e
a
n
 
S
t
d
.
 
E
r
r
o
r
 
M
i
n
 
M
a
x
 
M
e
a
n
 
S
t
d
.
 
E
r
r
o
r
 
M
i
n
 
M
a
x
 
 
M
e
a
n
 
S
t
d
.
 
E
r
r
o
r
 
M
i
n
 
M
a
x
 
H
u
s
b
a
n
d
s
 
 
E
a
r
n
i
n
g
s
 
8
7
2
0
.
5
6
 
9
3
6
0
.
5
8
 
5
0
 
1
4
4
0
0
0
 
9
7
0
5
.
1
0
 
8
8
3
5
.
4
7
 
1
0
0
 
8
0
0
0
0
 
 
1
0
7
5
8
.
7
0
 
9
1
5
6
.
2
4
 
1
2
0
 
9
5
0
0
0
 
A
g
e
 
8
.
2
6
 
1
.
6
6
 
5
 
1
4
 
8
.
2
2
 
1
.
7
6
 
4
 
1
4
 
 
8
.
2
0
 
1
.
6
9
 
4
 
1
4
 
E
d
u
c
a
t
i
o
n
 
3
.
6
1
 
1
.
8
1
 
0
 
6
 
3
.
6
5
 
1
.
7
6
 
0
 
6
 
 
3
.
6
0
 
1
.
7
9
 
0
 
6
 
 
W
i
v
e
s
 
 
E
a
r
n
i
n
g
s
 
5
5
8
5
.
8
9
 
5
9
7
2
.
1
0
 
2
0
 
4
3
0
0
0
 
6
2
0
8
.
6
0
 
6
9
2
2
.
2
1
 
4
5
 
5
8
8
0
0
 
 
7
0
6
2
.
8
4
 
8
2
1
1
.
2
1
 
2
0
 
9
0
0
0
0
 
A
g
e
 
7
.
6
6
 
1
.
6
2
 
4
 
1
4
 
7
.
5
7
 
1
.
7
2
 
4
 
1
2
 
 
7
.
5
2
 
1
.
6
8
 
4
 
1
3
 
E
d
u
c
a
t
i
o
n
 
3
.
3
7
 
1
.
9
8
 
0
 
6
 
3
.
4
0
 
1
.
9
3
 
0
 
6
 
 
3
.
3
7
 
1
.
9
2
 
0
 
6
 
 
 
N
 
6
9
2
 
7
4
5
 
 
9
1
3
  
T
a
b
l
e
 
3
:
 
E
s
t
i
m
a
t
e
s
 
P
a
r
t
i
a
l
 
C
o
r
r
e
l
a
t
i
o
n
 
O
L
S
 
H
e
c
k
m
a
n
'
s
 
2
0
0
6
 
2
0
0
7
 
2
0
0
8
 
2
0
0
6
 
2
0
0
7
 
2
0
0
8
 
2
0
0
6
 
2
0
0
7
 
2
0
0
8
 
0
.
2
0
 
0
.
2
5
 
0
.
3
6
 
0
.
3
3
*
*
*
 
0
.
2
9
*
*
 
0
.
3
9
*
*
*
 
0
.
3
6
*
*
*
 
0
.
3
3
*
*
*
 
0
.
3
8
*
*
*
 
[
0
.
1
1
]
 
[
0
.
1
4
]
 
[
0
.
0
6
]
 
[
0
.
1
0
]
 
[
0
.
1
3
]
 
[
0
.
0
6
]
 
N
 
6
9
2
 
7
4
5
 
9
1
3
 
6
9
2
 
7
4
5
 
9
1
3
 
5
5
7
8
 
5
3
8
3
 
5
4
5
7
 
N
o
t
e
s
:
 
 
*
*
*
 
I
t
 
i
s
 
s
i
g
n
i
f
i
c
a
n
t
 
a
t
 
9
9
%
 
s
i
g
n
i
f
i
c
a
n
c
e
 
l
e
v
e
l
.
 
*
*
 
 
I
t
 
i
s
 
s
i
g
n
i
f
i
c
a
n
t
 
a
t
 
9
5
%
 
s
i
g
n
i
f
i
c
a
n
c
e
 
l
e
v
e
l
.
 
*
 
 
I
t
 
i
s
 
s
i
g
n
i
f
i
c
a
n
t
 
a
t
 
9
0
%
 
s
i
g
n
i
f
i
c
a
n
c
e
 
l
e
v
e
l
.
 
 
 
  
Table 4: The Partial Correlations 
Region  Coefficient 
Istanbul  0.34 
Marmara  0.22 
Ege  0.34 
Ic Anadolu  0.24 
Akdeniz  0.61 
Karadeniz  0.05 
Dogu and Guney Anadolu  0.52 
Turkey  0.36 
 

A Theory of Marriage: Part I,”

Assortative Mating and Ethnicity in the Low Wage Population: An Examination of Spouses’ Earnings”,

Female Employment, Earnings Inequality and Household Well being: The Case of Urban Turkey” unpublished working paper.

Marital Matching and Earnings: Evidence from the Unmarried Population in Sweden,”

Marriage and Assortative Mating: How Have the Patterns Changed?” mimeo University of Washington Smith,

Marriage Markets and Assortative Mating with Household Public Goods’,

Spouse Selection and Earnings:

Testing Becker's Prediction on Assortative Mating on Spouses'

Assortative mating and Turkish marriage market

Assortative mating and Turkish marriage market

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics