social economic factors of marriage market in bulgaria
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Purpose: Investigate and analyze the marriages in Bulgaria, through a regression. The main purpose is to investigate how independent macro variables (social and economic) influence the number of marriages in the country through the last years.TRANSCRIPT
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 1
Social-Economic factors of marriage market in Bulgaria
A marriage market analysis, based on macro social-economic factors and secondary
information from other researches on the same topic
Hristo B. Kolev1
AUBG2, EMBA3 program
1 Corresponding Author – contact: [email protected] 2 American University in Bulgaria 3 Executive Master of Business Administration
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 2
Abstract
Purpose:
Investigate and analyze the marriages in Bulgaria, through a regression. The main
purpose is to investigate how independent macro variables (social and economic)
influence the number of marriages in the country through the last years.
Methodology/approach:
The paper and the final results are based on the regression made in this
investigation. The independent variables chosen for the regression are based on other
investigation made over the last years on the same/similar topics. Data is extracted
from the Bulgarian National Statistic Institute4, European Union official statistics
(Eurostats)5, and The World Bank6. There are 3 different set of variables, depending
on existing data (1960-2010; 1990-2010; and 1998-2010). 3 regressions have been
run including all relevant set of variables (see table further down).
4 http://www.nsi.bg 5 http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/ 6 www.worldbank.org
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 3
Variable (independent) Set Regression Divorces 1 1 Population 1 1 Live births
• BIM7 • BOM8
1 1
Previous marriages 2 2 GDP per habitant 2 2 Total GDP 2 2 Inflation 2 2 Unemployment
• Male • Female
3 3
Education • Male • Female
3 3
Findings:
Marriages in Bulgaria depend more on social than on economic variables. Number
of marriages doesn’t depend on punctual economic crashes like the 1996-1997 strong
inflation. Women participation in education and labor market is different from other
societies and independent variables related to this issues are not related to marriages
in Bulgaria, which is the main difference, compared with the 5 consulted researches
on the same topic.
7 BIM: births in marriage 8 BOM: births outside marriage
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 4
Introduction
Society is changing. The Marriage is a historical framework of society over the
world, no matter religion or political views. As a consequence of the change in
society a change in the framework is observed. In Bulgaria marriages have been
decreasing in a constant rate and now days represent 35% of marriages 50 years ago.
Today births outside marriage represent 54% of all births, and in 1960 were only 8%.
These changes occurred little by little in the society, there was not a drastic inversion.
Is there a logical explanation about this change? What happened in the society that led
to these changes? This paper is analyzing some social and economic variables that
explain part of what is occurring.
This paper is organized as follows. Part one is reviewing 5 previous researches
bout same/close topic. Part two presents a brief explication of the variables analyzed
in this research. Part three provides several regressions of the 3 SETs of variables.
Part four is a concluding section.
1. Theory of the Marriage Market:
This first part of the paper is a brief review of the recent works over Marriage
Market and its dependence of the social-economic factors. These works are the bases
of the independent variables used further down in this paper to explain the dependent
variable (Number of Marriages in Bulgaria).
Gary Becker (1971) in his work “The Economics of Discrimination”, models the
marriage market as a system, in which agents (men and women) have to maximize
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 5
their utility. They have to compare their utility functions based on two states: the first,
in which utility depends on the consumption and personal income of a single agent;
and, second, of marriage, where the utility depends on the sum of the man and
woman’s income. The agent will marry only if the marriage case utility is higher
compared on the single case utility. Becker’s model concludes that, because of this
direct connection of utility and income, couples may tend to be formed by agents with
similar income levels. Becker includes in his analysis the possibility of divorce. The
reason is that when an agent is searching for his/her best mate he/she collects
information. As this information is costly to find, the agent will marry when the
marginal utility from additional information equals the marginal cost of obtaining it.
The possibility of divorce is given in the long run, when married agents get more
information, which leads them to re-evaluate their marriage decision.
Blau, Kahn, Waldfogel, (2002) in their work “Understanding Young Woman’s
Marriage Decisions”, analyzed the labor market impact on the decisions of young
women. Their methodology consisted of two steps, the first is a regression where
Marriage is the dependent variable, and independent variables are personal
characteristics (ethnic of the agent and education level); and the second step is the
relation between results from the regression and the labor conditions. The final result
are: a) When the female labor market conditions are favorable (easy for wemen to
enter in the labor market, good salaries, etc.), then the marriages are decreasing; and
b) In contrast, when conditions of men's labor market are favorable, the marriage rate
is increasing.
Caucutt, Guner and Knowles (2001) in their analysis “Time of Births: A Marriage
Market Analysis”, state that one of the main independent variables when analyzing
the Marriage Market is the decision to have a babe. This is because while agents are
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 6
single and don’t have children, they have more possibilities to enter in the labor
market, and in contrast, having children leads to higher direct costs and opportunity
costs. The authors developed an equilibrium model based on marriage, divorces, and
human capital accumulation, which allows them to find different moments in time life
to have children. The model is analyzing the effects of a relative increase in wages of
women to wages of men and the increased the return rate on women's experience. The
study concludes that the decision of having children has an important role in
determining Marriages and Income differences.
Ermisch and Francesconi (2002) in their work “Intergenerational Social Mobility
and Assortative mating in Britain” investigated the relationship between
socioeconomic status of parents and children. The model defends that all agents have
a utility-maximizing behavior that requires the existence of two sub-problems: the
problem of the children, that is to select optimal mate in optimal time; an, the problem
of parents, which is to determine the optimal level of investment in education of their
children, to ensure its economic future. The results are: low intergenerational
elasticity; human capital (intergenerational), rather than the marriage market,
determines the social status that an agent can achieve; and finally, their results support
the idea that there are strong intergenerational rigidities because of the quality of
capital that children could inherit by reach parents.
Mercado, Leitón, Ríos (2004), in their research “The Marriage Market: a link
between Social Mobility and Labor Market” analyzed the elements that are behind the
low social mobility in Bolivia. The binding hypothesis follows that the marriage
market could be acting as a mechanism that reinforces the low social mobility.
Moreover, the marriage market is considered as an important link between social
mobility and the labor market. The result show an evident strong marriage market
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 7
segmentation that would slowdown the social mobility and, is a factor that leads to
misallocations in the labor market.
2. Analyzed variables
The preliminary independent variables are base on the works cited in the previous
part of this paper. Other macroeconomic variables are included, as GDP and Inflation.
The independent variables are classified in 3 sets (because of different available data).
Set 1 of variables includes those with most information from 1960/1961 to 2010. Set
2 of variables includes those with information from 1990 to 2010. And set 3 of
variables including time series from 1998 to 2010. The present paper will analyze 3
regressions in order to include all a priori important information.
Variables:
• Marriages: this is the dependent variable, expected to be explained.
The graph further down represents the marriages in Bulgaria since 1960 until
2010 (51 periods). Marriages have fallen from 69.000 in 1960 to 24.300 in 2010.
The regressions run in the next part of the paper will try to explain this decrease
with social-economic macro variables. The biggest decrease is from period 29
(1989) when the number of marriages was 63,263 to period 34 (1994) with 37,910
marriages. This period has a historical meaning, 1989 is a year of big social and
political changes in Bulgaria (change in the politic situation from Communism to
Democracy) and in the region (Union of the 2 German countries). Unfortunately
these changes won’t be captured by the regression.
• Divorces: independent variable (set 1 of independent variables)
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 8
There is data for this variable since 1961 to 2010. The variable was previously
analyzed as related to marriages by Gary Becker (1971) as possibility on the long run
to get more information about the other partner in the marriage and to reconsider the
utility function of the marriage. The graph show us that divorces increase form 8,549
in period 2 (1961) to 11,012 in period 51 (2010), but the relative weight increased
much more, from 13% of all marriages in 1961 to 45% in 2010.
• Population: independent variable (set 1 of independent variables)
This variable hasn’t been analyzed by previous researches, we will see if it is
relevant or not in the case of Bulgarian marriages. The population has stayed stable
over the years, as it only decreased by 300,000 people in 70 years (7,829,246 in
1960 to 7,563,710 in 2010).
• Live births in and outside marriage: independent variable (set 1 of
independent variables)
This variable is interesting because it is very close to the decision of having a
babe. The variable decision of having a babe was already examined by Caucutt,
Guner and Knowles (2001) with the conclusion that the kids suppose direct costs
and opportunity costs for their parents. Actually there are 2 variables: births in
marriage (BIM); and births outside marriage (BOM). On one hand the BIM have
been decreasing: 128,883 in 1960, representing 1,87 births per marriage to 34,663
or 1,43 births per marriage in 2010. On the other hand BOM have been increasing
from 11,199, representing 16% births per marriage in 1960 to 40,850 or 1,68 births
per marriage in 2010. Please note that both type of births (BIM AND BOM) are
related to the total number of marriages.
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 9
• Previous marriages or second time marriages (STM): independent variable
(set 2 of independent variables)
This variable collects the agents that got married more that once. The variable
hasn’t been analyzed in previous studies, but is an interesting social variable to
determine if it is relevant or not to marriages. In 1990 the number of second or
more time marriages were 7,181 or 12% of all marriages and in 2010 were 3,388
or 14%.
• GDP per habitant (GDPH): independent variable (set 2 of independent
variables)
This variable was previously analyzed and considered as relatively important by
Becker (1971); Caucutt, Guner and Knowles (2001); and Ermisch and Francesconi
(2002). The data available for Bulgaria is from 1990 to 2010. The expected (from the
cited previous researches) relation of this variable to the dependent one is as women
income increases marriages would decrease. In the present paper aggregate data will
be used (men + women). Separate data analysis have been discard due to few
available data (only 5 years series from 2006 to 2010). Income per habitant in euros in
Bulgaria has increased from 1,200 in 1990 to 4,800 in 2010.
• Total GDP in millions (TGDP): independent variable (set 2 of independent
variables)
This variable is another way to measure the income of the habitants. It is
supposed that if GDP of one country is getting higher, the social status of its
population is becoming better (the income per habitant is rising). If we suppose
that higher GDP means high income for women in the Bulgarian society, we could
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 10
expect fewer marriages. The regression will prove or reject this hypothesis. There
is available data for this variable from 1990 to 2010.
• Inflation, consumer prices (ICO): independent variable (set 2 of
independent variables)
This variable hasn’t been analyzed in the previous researches, mentioned in the
first part of the paper. Still the variable is close related to the consume power of the
agents as high inflation could mean that that income increase could be not
sufficient to increase consume power and increase poverty of population.
Information for this variable is available from 1990 to 2010.
• Unemployment male and female (UM and UF): independent variable (set 3
of independent variables)
This variable was deeply analyzed in Blau (2002) with the conclusion that the
most favorable are the conditions of the labor market for women less marriages we
would have and the most favorable labor conditions for men, more marriages we
would have. Available data for this variable is from 1998 to 2010. In the regression
2 variables are used: female unemployment, which is decreasing from189 in 1998
to 156.2 in 2010, with some fluctuations; and male unemployment, which is
relatively stable - 212.9 in 1998 and 211.3 in 2010, but with serious fluctuations
over the years.
• Education male and female (EM and EF): independent variable (set 3 of
independent variables)
This variable was previously analyzed by Blau (2002). The results were already
mentioned. It is supposed that higher rate of education for women means better labor
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 11
conditions and entry facilities in the labor market and as a consequence lower rate of
marriages. The variable education is composed of 2 variables: EF; and EM. For both
the data is 1998-2010 time series where only the highest level of education has been
considered: first and second stage of tertiary education (levels 5 and 6). The data
shows increase in male education from 101,784 in 1998 to 127,709 in 2010 and stable
rates for female education 158,703 in 1998 and 159,337 in 2010. The regression will
give us details if fluctuations in male and female education are relevant to marriages
in Bulgaria.
3. Regressions9
The first regression to be made is with the variables from SET_1 (1961-2010) as
follows:
• Dependent variable: Nº of Marriages in Bulgaria from 1961 to 2010
• Independent variables, all data from 1961 to 2010 for Bulgaria:
o Nº of Divorces
o Population
o Births in Marriages (BIM)
o Births outside of Marriages (BOM)
9 Please check regression matrix in the appendix
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 12
First analysis of the summary output indicates that the variable Population in not
statistically significant as it doesn´t pass the T test (0.49) and have too high P-value.
On the other hand, there is possibility of multicollinearity problem as the F test shows
that the regression is statistically significant. Let’s drop out the problematic
independent variable and run the regression again. The results are as follow:
In this regression we have correct the previous problem and now all the
independent variables pass the T test: Divorces 5.44; BIM 24.99; BOM -3.6. The T
test shows that the variables are significant at 5% level. The P-value, that gives us the
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 13
significant value in also ok, all variables are below 1%, that means that there is only
1% chance that the variables are not related to Marriages. The regression equation is
Marriages=10,904+0.916Divorces+0.43BIM-0.26BOM. The adjusted R2 tells us that
these variables explain 98% of the dependent variable. F test is also significant
1,2477E-42.
The regression with data variables from SET_1 mixes the findings from 2 different
researches: Gary Becker (1971) who states that the divorce is a consequence on the
long run of gathering more information about the maximizing of the utility function of
marriage; and Caucutt, Guner and Knowles (2001) who related the decision of having
babes to the marriages. The present regression goes further and separates the effect of
pregnancy of married and not married women.
The second regression is to be made with the significant independent variables
from SET_1 and variables from SET_2. For this regression the data series is from
(1990-2010). The independent variables are as follows:
o Nº of Divorces SET_1
o Births in Marriages (BIM) SET_1
o Births outside of Marriages (BOM) SET_1
o Second or more times Marriages (STM) SET_2
o Total GDP (TGDP) SET_2
o Inflation, consumer prices (ICP) SET_2
o GDP per habitant (GDPH) SET_2
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 14
From the summary output we can see that there are several variables that doesn’t
pass the T-test are not significant with the P-value and can present correlation
problems. As the idea is to add more significant variables to the previous regression
the only variable that is statistically significant from this SET_2 is STM. Let’s drop
out the other 3 variables TGDP, ICP and GDPH. The results of the adjusted
regression are as follows:
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 15
All independent variables pass the T-test, P-value, and the regression is significant
as F-test is 7.7E-12. The only variable that is a little bit less significant is Divorces as
there is 5% of probability that Divorces is not related to Marriages. The equation is
Marriages=12,810+0.63Divorces+0.3BIM-0.27BOM+1,799STM. These variables
explain 96% of the dependent variable as shows the R2.
This regression adds more information to the Marriages Market, as one additional
no previously studied variable gives us more information about the market. No one of
the 5 previously consulted studies had in mind this variable - the previous experience
of agents in this market (Marriage Market)
The third regression is to be made with the significant independent variables from
SET_1, SET_2 and variables from SET_3. For this regression the data series is from
(1998-2010). The independent variables are as follows:
o Nº of Divorces SET_1
o Births in Marriages (BIM) SET_1
o Births outside of Marriages (BOM) SET_1
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 16
o Second or more times Marriages (STM) SET_2
o Unemployment male (UM) SET_3
o Unemployment female (UF) SET_3
o Education male (EM) SET_3
o Education female (EF) SET_3
After the summary output analysis we see several problems with T-test and P-
value. To adjust the regression let’s drop out problematic variables from SET_3 EM
and EF:
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 17
In this regression there are still problems with independent variables Divorces and
BIM. Let’s adjust the regression dropping out these variables:
All independent variables pass the T-test and the P-value. When analyzing the
variable BOM, there is 10% possibility that this variable is not related to Marriages,
in the variable STM this probability is 5%. The equation is Marriages= 26,976 -
0.15BOM+1.12STM-154.85UM+211UF. The regression is significant as the F-test is
3,8E-5.
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 18
This regression gives us some more detail about how labor market is related to
Marriages and supports Blau, Kahn, Waldfogel, (2002) findings in “Understanding
Young Woman’s Marriage Decisions”.
4. Conclusions
Factors that intervene on Marriage Market are more social than economic. In the
present paper have been analyzed several macro variables and their relation with the
number of marriages in Bulgaria. The results are obvious: 6 out of 12 analyzed
variables are statistically significant to explain the number of marriages in Bulgaria:
Divorces; BIM; BOM; STM; UM; and UF. Only 2 from these 6 could be considered
economic variables: UM; and UF. Other 6 variable were dropped out from the
regression as not relevant: Population, GDPH; TGDP; ICP; EM; and EF. 3 of the
dropped out variables are macroeconomic: GDPH; TGDP; ICP.
After the present regression analysis it could be concluded that the high decrease in
marriages in Bulgaria from 1960 to 2010 is due on social changes in the society,
rather than in economic changes. Bulgaria’s GDP has been growing ever since, as
well as habitant’s income, but marriages kept falling down in a compound annual rate
of about 2%. This rate remained even in the years of strong inflation of 121% in 1996
and 1,058% in 1997. One difference is observed, compared with the previously
examined researches about the topic: in most researches the women emancipation of
men in strongly related to marriages, not in the Bulgaria’s case. This is because, on
one hand, in Bulgaria women has historically received good education, education’s
levels of women, opposite to other countries, are greater that men’s education level,
and on other hand, women has historically participated very actively in the labor
market – housewife rate is very low compared with other countries.
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 19
Interesting variables that haven’t been considered, because of lack of information
about them, are economic variables as women income and access to higher job
position. Probably this is the variable that would explain the very high rate of BOM in
the Bulgarian society (BOM in 2010 are 40,850 when BIM in 2010 are 34,663).
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 20
References:
Becker, G., 1971 “The Economics of Discrimination”. The university of Chicago Press, Chicago, IL
Blau F., Kahn L., Waldfogel J., 2002 “Understanding Young Women’s Marriage Decisions: The Role of Labor and marriage Market Conditions” National Bureau of Economic Research. Working paper 7510
Caucutt E., Guner N., Knowles J., 2001 “Time of Births: A Marriage Market Analysis” University of Pennsylvania
Ehrenberg, R. & Smith, 1991 “Modern Labor Economics. Theory and Public Policy”. Harper Collins Publishers Inc., Fourth Edition
Mercado, Leitón, Ríos, 2004 “The Marriage Market: a link between Social Mobility and Labor Market”, Instituto de Investigaciones Socio-Económicas, Universidad Católica Boliviana
Bulgarian National Statistic Institute: http://www.nsi.bg
European Union official statistics (Eurostats): http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/
The World Bank : www.worldbank.org
SOCIAL-ECONOMIC FACTORS OF MARRIAGE MARKET IN BULGARIA 21
APPENDIX
Regression Matrix including all data sets: