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Dep art men t o f E co n o mi c H i st o r y
M a s t e r Pr o gr a m m e i n E c o n o mi c D e mo gr a p h y
Fertility Transition and Regional Variation of Fertility in
Turkey: Panel Data Fixed Effects Estimation, 1975-2000
Alper AVSAR
EKHR01
Master’s thesis (15 credit points)
Spring 2010
Supervisor:
Maria Stanfors
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Table of Contents
Abstract
1. Introduction
1.1 Aim of the Thesis
1.2 Research Question
4
5
6
2. Background
6
2.1
2.2
2.3
2.4
2.5
7
9
11
14
16
General Overview of Turkey
Analysis of Fertility and Mortality Trends
Stages of Demographic Transition in Turkey
Regional Fertility Trends
Previous Research
3. Theoretical Considerations
3.1 Demographic Transition Theory
3.2 Economic Theories of Demographic Transition
3.3 Cultural Theory of Demographic Transition
3.4 Definitions of Variables and Hypothesis
4. Data and Method
4.1 Source Material
4.2 Statistical Method
5. Empirical Analysis
5.1 Statistical Results
5.2 Discussion
18
18
21
29
30
34
34
35
37
37
41
6. Conclusion
43
References
44
APPENDIX
48
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Abstract:
Turkey, similar to other least developed countries, entered into demographic transition process in
the second half of 20th century. However, the transition process was not experienced at the same
time and in the same way across different regions of the country. The aim of this study is to
reveal the determinants of fertility transition and regional fertility variation in Turkey. The period
under consideration is between 1975 and 2000 in other words the later part of transition.
Different from previous studies, this study covers longer period of fertility transition and applies
panel data fixed effects estimation method. The results indicate that education and income is
decisive in fertility transition. However, different factors gain importance in different regions.
Keywords: Demographic transition, fertility, regional variations in fertility rate, Turkey.
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1. Introduction
Turkey, similar to other developing countries, entered the demographic transition process during
the second half of 20th century. The pattern of this process was similar to that experienced in
Europe long before the last quarter of 19th century; first infant and child mortality rates decreased
and after some time, fertility rates followed this trend and reached replacement level. However,
transition process was not experienced at the same time and in the same way across regions of the
country. There exist variations in fertility rates among different regions especially between East
and West. For example, in West, total fertility rate decreased from 4.35 children in year 1960 to
1.73 in 2008. In East, total fertility rates have always been higher than West. In 1960, total
fertility rate was 8.27 children yet it decreased to 3.27 children in 2008*. Fertility in urban-rural
residence also varies in Turkey. Turkish Demographic and Health Survey 2008 (TDHS) indicates
that total fertility rate in urban residence is 2.00 children but in rural residence it increased and
reached 2.68 children. Statistical indicators show that West had completed fertility transition but
East is still experiencing the fertility decline.
Variations in fertility rates across different regions of Turkey indicate that families decide their
level of fertility by taking different factors peculiar to region into consideration. It is important to
reveal these factors because we can develop effective social and economic policies if we
understand how families reach a decision about the number of children.
Turkey offers excellent research opportunities with its unique modernization process and
multicultural fabric of society; though challenging because the country, similar to other
developing countries, lacks of longitudinal statistical record. Because of the data limitations, the
field of demography is newer and untouched in Turkey. However, it is important to know exact
number of population and its characteristics, especially fertility levels in order to make efficient
social and economic policies in future.
According to Easterlin’s relative cohort size theory, if the current fertility levels are high, a new
born exposes to overcrowding effect in three institutions namely; family, education, and labor
market (Macunovich 2000, 236). For example, in family institution, parents have to distribute
their limited income to more children if fertility levels are high. This means that each child is
made less human capital investment relative to former cohort. In education institutions, physical
and labor capital may not meet the demand of larger cohorts unless necessary investments are
made. Thus, quality of education decreases. Finally in labor markets, wages decreased and
unemployment rates increased if government does not meet employment of active labor force in
case of rise in cohort population. On the other hand, a decrease in current fertility also causes
problems. Lower fertility has contributed in a major way to population ageing, with economy
wide effects on labor supply, consumption patterns, old age security, and so forth (Dribe 2008,
65). Hence, demographic structure of any country should be investigated carefully in order to
prevent possible problems in the future.
*
The information about regional total fertility rates for the year 1960 and 2008 belongs to the State Institute of
Statistics (1994) page 27, table 3.7 and Turkish Demographic and Health Survey (2010) page 62, table 4.2
respectively.
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In this study, I will contribute to the Turkish demographic researches by revealing determinants
of fertility transition and the causes of variation in fertility levels across five statistical regions of
Turkey.
1.1 Aim of the Thesis
The aim of my thesis is to identify the factors responsible for fertility transition and regional
fertility variation in Turkey between 1975 and 2000. According to State Institute of Statistics’
(SIS) classification, Turkey consists of five different statistical regions which differ in social,
economic and cultural background. These different characteristics of regions may play an
important role in fertility transition and cause variations in fertility at regional level. In order to
achieve my aim, I will benefit from panel data fixed effects estimation method by using
population census data belong to 1975, 1980, 1985, 1990, and 2000. I employed different theories
in order to determine independent variables. The theories that I used are classical, economic and
cultural theories of demographic transition. Using these theories allowed me to look at the
complete picture of fertility transition in Turkey. Solving regression equation and interpreting
results correctly will provide me to analyze factors effective in fertility transition and to find out
causes of regional fertility variation in Turkey. I will have specified the independent variable
which has the highest magnitude in explaining transition and regional differences.
Moreover, this study aims to make two important contributions to Turkish demography research.
First of all, due to lack of longitudinal data, past researches aim to show the determinants of
fertility transition and causes of regional variations in fertility, use either descriptive statistics or
cross sectional OLS regression. Although cross sectional method is a useful tool under data
limitations, it only provides a static view. By employing panel data fixed effects estimation, I
include the time aspect to my study which provides a dynamic picture of transition. Secondly,
when we look at researches conducted on regional variations of fertility in Turkey, we see that
they tend to explain fertility variation by adopting one of the demographic transition theories. For
example, either classical or cultural theory of transition is adopted. Rather than adopting one
theory, this study employs three fundamental theories of demographic transition to explain the
causes of variation in fertility levels. All in all, these contributions provide me to develop better
policy recommendations in order to close the gap.
However, a similar study was conducted by Yasıt (2007) between years 1980 and 2000. Different
from her study, I included population census for the year 1975. Fertility transition in Turkey was
started in 1950s. Including data belongs to 1975 allows me to cover a wider time span of
transition and thus to reach more accurate results. I also increased my observations which will
improve the precision of my estimators. Moreover, I selected more accurate proxies for testing
different theories of demographic transition. I concentrated on regional variation in fertility.
1.2 Research Question
In this study, I will try to answer two research questions namely; “What are the determinants of
fertility transition in Turkey?” and “What factors are important in explaining fertility variation
across different regions of Turkey?” The causes of fertility transition and regional variations of
fertility frequently studied topics in relevant fields. As I stated, Turkish demography field is
newer and mostly untouched. For this reason, my research questions deserve to be studied.
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In order to answer these questions, I developed hypothesis according to three fundamental
theories of demographic transition. These theories are; classical, economic and cultural theories.
Classical demographic transition theory accentuates that modernization process, through affecting
socioeconomic structure, is the real cause behind demographic transition. According to theory,
different levels of modernization i.e socioeconomic development in each region may be
responsible for fertility transition and cause regional fertility differences. To investigate the
relation between socioeconomic development and child women ratio, I employed infant mortality
rate, rurality, and employment in modern sectors of economy as independent variables. The
statistical method will help me to reveal direction, strength and statistical confidence of the
relationship between socioeconomic development variables and total fertility rate. I especially
answer the question of how economic development affects fertility transition by considering both
time and space effect.
Economic theories of fertility transition on the other hand adopt more micro approach and focus
on household level of decision. In modern industrialized countries, parent’s decision on the
number of children they want to have is claimed to be affected by income, market prices,
preferences, female employment and female education level. In the model, female non
agricultural labor force participation rate, rate of high school graduate women, rate of illiterate
women and gross provincial product variables represents economic theories of fertility transition.
Owing to the study, I will have revealed the effect of variables which show women’s position in
society such as illiterate women, high school graduate women and female non agricultural labor
force participation rate on fertility through time and across regions.
Cultural theories of fertility transition assert that transformation of traditional society into
modern, urban society through changing preferences of parents about number of children is the
cause of decrease in fertility levels. Theories also suggest that spread of information about
modern contraceptive methods via mass media and education institutions further contribute
fertility decline. In the model, education level, rurality, employment in modern sectors of
economy and number of public libraries variables represent cultural theories. As a result of the
study, I will have showed how decrease in rurality, transformation of agricultural economy into
modern and spread of information through written media affect fertility.
2. Background
In this section, the main aim is to provide information about demographic structure of Turkey
from a historical point of view. In section 2.1, I will give information about Turkish geography,
history, economy and five geographical regions. In section 2.2, I will introduce population trends
by focusing on mortality, fertility and population growth in Turkey from 1920s until today. In
section 2.3, I will discuss the stages of Turkish demographic transition. In section 2.4, I will focus
on the causes of variation in fertility rates among regions of Turkey. Finally, in section 2.5, I will
analyze previous research on Turkish case. Appendix A. shows five statistical regions of Turkey
and Appendix B indicates provinces situated in each of these regions.
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2.1 General Overview of Turkey
Turkey is situated in geopolitically important area called as Anatolian Peninsula. In the
northwest, she has borders with Southeastern Europe, in the northeast Caucasus and in the
southeast Middle East. Turkey has coasts to three seas; in the North, Black Sea, in the West,
Aegean Sea and in the South, Mediterranean Sea. Having borders to three continents and access
to different sea routes open Turkey to political, social and economic changes coming from these
regions. Thus, Turkey can be seen as a social laboratory in which the effects of different social
phenomena can be observed at the same time. This unique structure of the country provides
excellent research opportunities for social scientists, especially for sociologists and
demographers.
Anatolia was dominated by the Seljuqs for almost two centuries (1055-1243) and afterwards she
became the core of Ottoman Empire, which ruled also in the Europe, Middle East and Africa for
almost six centuries (TDHS 2003, 1). After the collapse of Ottoman Empire by the end of The
First World War and following The War of Independence, a new Turkish state was established
from the ashes of empire. This new Turkish state was proclaimed as a republic in 29 October
1923. With the leadership of Kemal Ataturk, the country entered into a modernization process.
The reformation of Ataturk marked a dramatic turning point in the westernization process that
had already started before and the country broke up with almost all its traditional past and began
to be transformed into a modern republic. The founding principles of Turkish Republic represent
a radical shift from Ottoman traditions.
The modernization efforts taken by founding cadres of Turkish republic must be legitimize at
international level to maintain the sustainability of new system. Thus, Turkey established a close
relationship with Western countries, especially United States of America and Europe. Turkey is a
member of the United Nations, the Council of Europe and the North Atlantic Treaty Organization
(NATO) and an associate member of the European Union (TDHS 2008, 2).
Economic policies of Turkish Republic show differences in accordance with the necessities of the
era. When we look at the situation in 1920s, we see that Turkish economy went bankrupt as a
result of The First World War and The War of Independence. The country was poor and
undeveloped even though the land and resources were plentiful. The problem was that lack of
education, political and economic institutions and capital. The main economic activity was
primitive agriculture. Throughout the 1920s liberal policies were implemented; the government
promoted the development of industry through private enterprise, encouraged and assisted by
favorable legislation and the introduction of credit facilities (TDHS 2008, 4). The outcome of
liberal economic policies was not amazing but a moderate improvement in economy was
observed and Turkish agriculture was started to be mechanized.
The 1930s were important for Turkish economy because the origin of modern industrialization
was laid down in this decade. Industrialization was started in big cities especially Istanbul and
Izmir then spread to productive agricultural areas such as Menderes and Cukurova plains. The
economic policy of the Republic was changed radically in 1930s as a reaction to Great
Depression of 1929. Turkish economy implemented étatist economic policies which mean that
the key industries were owned by the state.
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Despite Turkey did not engage in Second World War actively, the country faced with heavy
restraints on economy (TDHS 2008). Turkish republic returned to apply liberal economic policies
with transition to multi party regime in 1950. On the one hand, country encouraged private
initiatives on the other hand government business enterprises were also supported. Import
substitution policy was adopted as main economic policy until 1980s. After the 1980 coup d’etat,
Turkey initiated to privatize all state initiatives and fully transformed into open market economy.
Turkey is a middle income country at the beginning of 2000s (TDHS 2003, 5).
According to SIS classification, Turkey is composed of five different regions namely, West,
South, Center, North and East which differ culturally, economically and historically. These
different characteristics of regions affect demographic structure especially fertility levels.
The West region is the most densely settled, the most industrialized and the most
socioeconomically advanced region of the country (TDHS 2008, 6). Istanbul and Izmir;
economic and cultural capitals of Turkey, are situated in this region. The coastal line as well as
inland is highly urbanized due to high inflow of migration. The main economic activities are
industry, agriculture and tourism.
The South region is a developing region of Turkey. It has a great industrial potential. However,
agriculture and tourism are the fundamental source of income in this region currently. An
important amount of citrus and cotton which are exported are grown in this region. The South
region has witnessed an industrial boom and an inflow of migrants, especially from the East and
Southeastern provinces (TDHS 2008, 6).
The Center is another developing region of Turkey. It characterized by less fertile lands and low
industry. Industrial production in the region is rising modestly as minor city centers rapidly
developed, and Kayseri is the best example of this (TDHS 2008, 6). Cereal, furniture and marble
production are the main industrial activities.
The North region has fertile lands but the cultivable amount is limited due to mountains structure
of terrain. Mining, tea and hazelnut production are the sources of income in this region. On the
other hand, Zonguldak, a western province has extensive coal mine reserves and is a center for
coal mining and steel industry (TDHS 2008, 6). There are some infrastructure problems in the
region yet larger amount of public (except some of those living in mountain villages) benefit
from basic education and health care services.
The East region is the least developed region of Turkey. The geographic situation and climate of
region renders agricultural activity difficult. However, the region is suitable for husbandry.
Moreover, armed conflict between Kurdish separatists and Turkish armed forces also prevent the
development of region. The level of urbanization is low, infrastructure is problematic. In general
public faces difficulties to benefit from basic education and health care services. Thus, East
region is the most migration giving region of Turkey.
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2.2 Analysis of Fertility and Mortality Trends
Central Statistical Office of Turkey conducted first population census of the republic in 1927. At
that time, population of Turkey was 14 million†. After 1935, population censuses were updated
every five years. The results of first censuses carry the marks of a history of wars, catastrophes
and population exchanges (Shorter 1968, 4). Shorter (1985) estimates that 2.14 million Turkish
were died in the first decade of 20th cc. by using reverse population projection method. Among
these deaths, a considerable number was working age (15-64 years old) men. Naturally, number
of widows and hectares of idle agricultural land were increased. Shortage of men and large
number of widows led to a decrease in number of births. Underuse of agricultural land
deteriorated living standards and resulted in high infant and child mortality. The normal process
of population renewal had been thwarted by both depressed fertility and high infant and early
childhood mortality during many years before 1923 (Shorter 1995, 9).
Population of Turkey started to increase in peace that came with the proclamation of republic in
1923 and subsequent reform process. The reforms were realized in the area of secularization, law,
emancipation of women and education. Industrialization of country was started and basic
infrastructure and health services laid foundation. The position of women in society was
strengthened through laws. Their education and labor force participation was supported. The
unification of education in 1924 and the acceptance of new Turkish (Latin) alphabet in 1928
increased the level of literates in society.
The fundamental population policy of the early republican period (1927-1950) was to recover the
population by increasing number of births. For this reason, abortion was declared as illegal in
1926, importation, production and sales of contraceptives were prohibited in 1930 (condom was
exempted to prevent the spread of venereal diseases) and finally sterilization was prohibited in
1936 (Shorter 2000). General public were also side with the government. Political stability,
extension of health protection, spread of education, and improving economic conditions brought
about gradual increase in population (Taeuber 1958, 103).
Pro-natalist policies of early republican period as well as peace and reformation process were
quickly felt as rising fertility and population growth rates. Shorter (1985) estimated total fertility
rate as 5.4 children in 1923. It reached to 6.66 children between the years 1935 and 1940. Annual
growth rate of population was 1.24 percent in 1927. It also reached 1.70 percent in that period.
†
The information about number of population in Turkey in 1927 comes from Shorter (1985)
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Table 2.2 Total Fertility and Infant Mortality Rate: 1935-2005
Periods
Total Fertility Rate Infant Mortality Rate
1935-1940
6.66
273
1940-1945
6.55
306
1945-1950
6.85
260
1950-1955
6.90
233
1955-1960
6.60
203
1960-1965
6.19
176
1965-1970
5.70
153
1970-1975
5.30
138
1975-1980
4.72
115
1980-1985
4.15
93
1985-1990
3.28
70
1990-1995
2.90
54
1995-2000
2.57
40
2000-2005
2.23
31
Source:Yavuz(2008:7,Table:5)
However, every segment of society could not benefit from improvements in health and education
equally. The conditions in rural areas were worse than urban areas. Throughout the period from
1927 to 1950, villages included about three fourths of population in Turkey (Taeuber 1958, 104).
Improvement in health and nutrition took place gradually. Thus, infant mortality rate was still
high, 273 per thousand births between 1935 and 1940.
The recovery of these key population parameters were interrupted by the Second World War.
Turkish armed forces recruited working age men to military against the threat of war. Total
fertility rate decreased to 6.55 children due to sexual abstinence in the period between 1940 and
1945. Shortage of men caused to decrease in agricultural production and deteriorated living
standards. Infant mortality rate further increased and reached 306 per thousand births. As a
consequence of the increased death rates during the war period, the population’s growth rate fell
from more than 2.0 percent per year beforehand to 1.7 percent in 1940 and 1.1 percent by 1945
(Shorter 2000, 121). Demobilization after the year 1945 showed its positive effect quickly. Total
fertility and population growth rate began to increase. Infant mortality rate continued to decrease
without interruption until today. The two subsequent periods witnessed the highest growth rate of
the republic’s history. Total fertility rate reached the highest point, 6.90 children between 1950
and 1955 and annual growth rate of population achieved the highest point, 2.85 percent between
1955 and 1960.
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Graph 2.2 Annual Growth Rate of Population: 1927-2000
Source: Turkish Statistical Institute (2009: 28, table: 3.1)
The demographic pressure of decrease in infant mortality rates was felt quickly among families
especially those located in urban areas and hence, fertility rates were begun to decrease from
1950s onwards. However, fertility and annual growth rate of population was thought to be high in
the1960s. Hence, Turkish state enacted the first population planning Law in 1965 which legalize
sale and use of contraceptives. The policy allowed the importation of modern contraceptive
methods, provided services at state health institutions free of charge and supported health
education for couples (TDHS 2004, 7). Total fertility decreased from 6.19 children in 1960s to
4.15 children in 1980s. In 1983, the abortion was also legalized which ended pro-natalist policies
of republic. According to latest census undertaken in 2000, total fertility rate decreased 2.5 per
women.
2.3 Stages of Demographic Transition in Turkey
The beginning of fertility transition in Turkey varies across different regions. Fertility levels in
the capital of Ottoman Empire, Istanbul and the most important port city, Izmir were started to
decline as early as 19th cc. However, rest of the Anatolia was characterized by higher fertility and
mortality rates. Turkey experienced fertility transition in its entire regions from 1960’s onwards.
In this section, I will analyze fertility transition in three stages.
2.3.1 First Stage of Demographic Transition
The first stage of demographic transition in Turkey took place in the period between 1923 and
1955. The characteristics of this period are that rise in fertility rates and decrease in mortality
rates due to peace and reformation process. The positive trend in these population parameters
reversed only for a short time during the mobilization for Second World War.
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Turkey’s particular demographic and socioeconomic history prior to, and during, this first period
was responsible for the increase in fertility (SIS 1994, 4). Wars, population exchanges, poor
economic conditions and diseases led to shortage of working age men. In order to rebuild family
and social life and to overcome the shortages of labor force, particularly in agriculture, both the
civil society and the state considered high fertility to be necessary (SIS 1994, 5). As a result of
stable political environment and normalization of economy fertility rate increased from 5.4
children in 1923 to 6.6 children in the period 1935-1940. It fluctuated between 6.66 and 6.85
children until 1950.
A decrease in mortality rate in parallel with an increase in fertility rate brought about increase in
population growth rate. Annual growth rate of population rose to 2.77 percent in 1955 from its
initial level of 2.11 percent in 1931. Population of Turkey increased from 13 million in 1927 to
24 million in 1925. Thus, the population had been doubled in that period.
The first stage of Turkish demographic transition was ended in mid 1950s with the beginning of
decline in fertility rates.
2.3.2 Second Stage of Demographic Transition
Turkey experienced the second stage of demographic transition between 1955 and 1985. The
most important characteristics of this period is that the beginning of irreversible decline in
fertility rates. The decline in fertility started in 1955 and continued throughout this period.
Moreover, annual growth rate of population achieved its highest level of all time, 2.85 percent.
The main reason behind high population growth rate is the improvements in public health which
caused decrease in mortality rate and increase in life expectancy at birth. The population of
Turkey increased from 24 million in 1955 to 51 million in 1985. Thus, the population had been
doubled again in this period.
The other important development in this period is rapid urbanization. The increasing number of
factories in urban areas resulted in increasing number of jobs. The proportion urban rose from
22.5 percent in 1955 to 51.1 percent in 1985 (SIS 1994, 5). The urban life altered fertility
behavior of migrants from rural areas. They chose to have low levels of fertility. In fact, part of
the motivation for moving was to lead family lives less oriented to large families and more
oriented to the economic, educational and consumption opportunities of the cities (SIS 1994, 5).
In this new environment, couples had changed their preferences away from children to new
opportunities of urban life. The economic transformation that was in progress at the same time
reduced the emphasis on family employment and increased the importance of qualifying for jobs
in an industrial labor market (SIS 1994, 5). The urban families chose to invest on quality; health
and education of their children than quantity. As a result, in the second stage of Turkish fertility
transition, urbanization emerged as an important factor that leads to decrease in fertility rates.
2.3.3 Third Stage of Demographic Transition
Turkey entered into third stage of demographic transition in the mid 1980s however; this stage
has not been completed yet. The characteristic of third stage of Turkish demographic transition is
the irreversible decline in population growth. Annual growth rate of population declined from
1980-1985 level of 2.49 percent to 1990-2000 level of 1.83. Fertility and mortality rates also
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continued to decline in this period.
The third stage of Turkish demographic transition is expected to be completed when two things
happen. First, fertility declines to a level that new generation nearly replace parent generation.
Second annual growth rate of population becomes zero. Indeed, current fertility levels decreased
to replacement level yet population still continue to grow.
Although fertility decline started in 1950s, annual growth rate of population continued to increase
until the mid 1980s due to population momentum effect. Since total fertility rate was above
replacement level for many years, number of women who were in reproductive ages was also
high. Even fertility rates continued to decrease throughout 1970s and 1980s, annual growth rate
of population navigated between 2.85 percent and 2.48 percent from 1960s to 1980s. The other
reason why the population keeps on growing is that people get older without dying (Shorter
1995). The improvement in public health services and increase in education level of mother
resulted in decrease in infant and child mortality rates. Thus, life expectancy at birth for both
sexes increased continuously except from mobilization period until today. Death rates
concentrated on higher ages. Thus, population of old and adult ages increased.
There are two important consequences of high population growth rate. First of all, number of
young population has been growing in Turkey since 1960s. New generations experience
difficulties in educational institutions and labor market. The capacity as well as the scale of
educational institutions should be increased. Necessary investment should be made to increase
productive capacity of economy. Thus, the unemployment problem of larger cohorts can be
solved. Moreover, increase in old age population increases the number of old age dependents.
The state should adjust pension system by considering increasing number of old age population.
Table 2.3: Projections for key population parameters
Total Fertility Rate
(per women)
Population Increase Rate
(%)
Expectation of Life at
Birth (year)
2005
2010
2010
2015
2015
2020
2020
2025
2025
2030
2030
2035
2035
2040
2.33
2.18
2.10
2.10
2.10
2.10
2.10
1.35
1.11
0.96
0.86
0.76
0.64
0.48
69.33
70.06
70.90
71.73
72.61
73.41
73.41
Source: Turkey’s Statistical Yearbook (2004: 74: table 4.13)
Table 2.3 shows projections for key population parameters in Turkey. Total fertility rate is
expected to decrease until 2020. It will have reached 2.1 children in the period between 2015 and
2020 and stayed constant through out 2030s. It indicates that population of young age people will
continue to decrease through the mid 21st c.c. Population growth rate will also slow down and
reach approximately zero in 2050s. Thus, we can say that, third stage of demographic transition
will be completed in the mid 21st c.c. Expectation of life at birth for both sexes is anticipated to
increase continuously and to reach 73.41 between 2035 and 2040. Death rates will further be
concentrated on high ages. As a result of increasing life expectancy and decreasing fertility rates,
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population of Turkey will become older. Turkish population is expected to reach a number
between 95 and 98 million by the mid 21st c.c. thus demographic transition in Turkey will
multiply the original (1923) population about 7.5 times by the time the transition is completed
(SIS 1994).
2.4 Regional Fertility Trends
According to Turkish Statistical Institute’s classification, Turkey composes of five statistical
regions; west, south, central, north and east which have different historical, cultural, social and
economic background. These differences across regions are also reflected to demographic
characteristics. Each region initiated the demographic transition in different times which resulted
in being different stages of transition thus variation of key population parameters such as fertility.
Total fertility rate decreased between 0.33 and 1.47 children on regional level and 0.88 children
on national level from 1980 to 2000 (Özgür 2004, 5). The numbers indicate that there exists
considerable variation in fertility rates in Turkey.
Table 2.4 shows total fertility rates for five regions of Turkey between the years 1960 and 2003. It
can be seen from the table that there exist clear pattern of decreasing fertility. All regions
experienced fertility transition from 1970s onwards although some regions such as west entered
into transition in 1950s or leading cities Istanbul and Izmir had been in process since the last
decade of the 19th c.c. However, each region contributes to fertility decline but the amount of
contribution varies.
There is an unchanging characteristic in Turkish demographic history that fertility rate increase
from west to east fractionally and they have always been lower in west whereas higher in east.
Table 2.4 Total Fertility Rates for Five Regions 1960-2003
Census Based Measures TFR West South Central North East
1960‡
4.35 6.71
6.56
6.56 8.27
1978
3.53 4.75
4.64
4.98 6.94
1983
2.97 4.32
3.95
4.39 6.72
1988
2.34 3.29
3.06
3.39 5.56
2000
1.92 2.43
2.29
2.28 4.02
Surveys
1989
2.60 3.00
3.10
3.50 5.70
1993
2.00 2.40
2.40
3.20 4.40
1998
2.03 2.55
2.56
2.68 4.19
2003
1.88 2.30
1.86
1.94 3.65
Source: SIS (1994:27, Table 3.7)
1998 Turkish Population and Health Surveys (1998:37, Table 3.2)
2000 Özgür (2004:6, Table 1)
2003 Turkish Population and Health Surveys (2003: 48, Table 4.2)
‡
TFR values belong to 1960, 1978, 1983 and 1988 are census based predictions.
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Total fertility rates are high in all regions in 1960. In west, it is 4.35 children yet in east; it is
almost double the value of west, 8.27 children. When we come to 2003, we see that fertility
reached to a level that is more than half of its 1960 level in each region. In west, central and
north, total fertility decreased to 1.88, 1.86, 1.94 children respectively. This indicates that these
regions have below replacement level fertility. In south, fertility is near replacement level 2.30
children but east has above replacement level, 3.65 children and seems to be late in fertility
transition. Although fertility also declines in east part of Turkey, the speed of decline is slow and
it needs more time to converge with other regions. Thus, east and the rest of Turkey exhibits
different patterns in fertility transition and east constitute a special case.
Regional variation of fertility is not a unique phenomenon for Turkey. In other developing
countries as well as in transitional Europe, regional fertility variations can be observed in
different stages of demographic transition. Thus, the question “why the timing and speed of
transition differ across regions within the same country?” has always been an interesting research
topic. In order to answer the question, some researchers adopt a socioeconomic perspective which
relates differences in fertility rates across regions to different levels of socioeconomic
development. On the other hand, the other researchers emphasize cultural differences among
regions as a cause of regional variation in fertility rate.
In order to reveal the causes of variation in fertility rates across regions of Turkey, Özgür (2004)
and Işık and Pınarcıoglu (2006) adopt a socioeconomic development perspective. According to
this approach, variables which are closely related with the status of women such as female labor
force participation, female education level and income can be accepted as determinants of level
of fertility and changing percentages of these variables among regions are presented as causes of
regional fertility variation.
Table 2.5 Key Socioeconomic Indicators, Turkey, 2000
WEST
NORTH
SOUTH
CENTER
EAST
Regions
Marmara
Aegean
Black Sea
Mediterranean
Central Anatolia
East Anatolia
Southeast Anatolia
Turkey
Female Non-Agricultural
Employment (%)
51.4
25.3
10.8
18.7
23.8
6.6
8.1
Illiterate
Women (%)
6
8
10
12
7
29
39
GDP per
capita ($)
4026
2952
2256
2534
2423
1299
1511
24.4
12
2941
Source: Özgür (2004:8,9,10)
Table 2.5 shows the percentage of female non agricultural employment, illiterate women and
GDP per capita among different regions of Turkey in 2000. According to the socioeconomic
development perspective, there is an inverse relationship between female non agricultural
employment and fertility rates. The Pearson correlation coefficient -0.63 indicates a medium level
negative relationship between these variables for the period 1975-2000. It becomes difficult to
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give birth to a child frequently and to raise children for employed women due to career in their
job (Özgür 2004, 8).
The distribution of percentage of female non agricultural employment across regions verifies the
negative relationship. Marmara and Aegean regions, which constitute west of Turkey, have the
highest percentage of female non agricultural employment, 51.4 and 25.3 percent respectively.
The lowest fertility rate also belongs to west, 1.92 children in 2000. It is not surprising that east
part of Turkey (east and southeast Anatolia) has the highest level of fertility, 4.02 children where
percentage of female non agricultural employment is the lowest (6.6 and 8.1) in 2000. The other
regions also fit the same pattern of inverse relationship. Thus, we can say that one of the reasons
that cause regional variation in fertility rates in Turkey can be different percentage of female non
agricultural employment.
Women’s education is another factor that socioeconomic development perspective put forward as
a determinant of regional variation of fertility rate. The fourth column in table 2.4 shows the
percentage of illiterate women who are in their reproductive ages. The percentage increases from
the lowest fertility rate region (west) to the highest fertility rate region (east) which indicates a
positive relationship between illiteracy and fertility rates. The correlation coefficient 0.93 for the
period 1975-2000 verifies this strong positive relationship.
In east and southeast Anatolia where total fertility rates are the highest among regions, percentage
of illiterate women achieved their utmost level 29 and 39 percent respectively in 2000. However,
in low fertility regions, the same rate changes between 8 and 12 percent. Hence, illiteracy is a
strong variable that can explain regional variation in fertility in Turkey.
The income level is accepted as another parameter that affects regional variation in fertility rates
(Özgür 2004, 8). It is expected to increase the fertility rates in low income groups in society
whereas to decrease in high income groups. The correlation coefficient of -0.54 between these
variables indicate medium level negative relationship.
The fifth column in table 3.4 shows GDP per capita in U.S dollars in regions of Turkey in 2000. It
is clear that in regions where GDP per capita is above or close to national average (Marmara,
Aegean, Black Sea, Central Anatolia and Mediterranean) fertility rate is below or near
replacement level. The income level differences can also explain variation of fertility rates among
different regions.
2.5 Previous Research
In this section of thesis, I will discuss studies related with fertility transition and regional
variation of fertility in Turkey.
The earliest study that is available in data bases belong to Farooq and Tuncer (1974). The main
aim of their study is to measure the effect of modernization process undertaken by Turkey to
fertility levels. The period under study is between 1935 and 1965 and the unit of observation is
province. The related hypothesizes were tested with two different models namely cross sectional
chain relationship and pooled OLS regression. This study draws our attention to two independent
variables female literacy and female non agricultural labor force participation. According to the
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results, female literacy affects fertility negatively and this effect is expected to increase its
magnitude and significance. However, the effect of female non agricultural labor force
participation is found low. The pertinent conclusion is that, in Turkey, continuing modernization
and the concomitant spread of female education will result in a continuing decline in fertility rate
(Farooq and Tuncer 1974, 273).
Pinarcioglu and Isik (2006) investigate the causes of regional fertility variation at district level by
using population census of Turkey for the year 2000. The main aim of the research is to reveal the
causes of variation in fertility levels across regions of country. Geographically weighted
regression analysis method is employed to solve the fertility equation. Adult literacy, female non
agricultural labor force participation, urbanization, migration and GDP variables are regressed
into total fertility rate.
The results are interesting. There is an overall negative relationship between adult literacy and
fertility levels yet the magnitude and the direction of the relationship changes across different
regions. As one goes from east to west, this negative relationship between education and fertility
starts to weaken and even turns to positive in regions where the level of education is higher
(Pinarcioglu and Isik 2006, 414). The same relationship is also valid for female non agricultural
labor force participation and fertility. In regions where the female labor force participation
already low, the magnitude of negative effect is stronger than regions with high female labor
force participation. The negative relationship between fertility and female participation is
stronger in east and south eastern Turkey, and in settlements along the Mediterranean and Black
Sea coast (Pinarcioglu and Işık 2006, 414). The impact of urbanization varies according to
different districts. If a district has a percentage of urban population above national average,
urbanization affects fertility positively yet if the percentage is below the national average, the
relationship turns into negative. Out migration and in migration affect fertility levels differently.
Increase in in-migration increases fertility whereas increase in out-migration decreases. Finally
the effect of GDP per capita on fertility is strong and negative in regions which have low level of
GDP. However, in high income regions, GDP per capita loses its effect and the relationship is
neutralized.
Yasit (2007) conducted a study to analyze fertility transition in Turkey. The main aim of her
master’s thesis is to reveal the factors that are effective in Turkish fertility decline and to find
causes of variation in fertility between provinces prioritized in development and the other
provinces. She applied panel data simultaneous equation model for the period 1980 and 2000.
In her study, variables that represent education, income, socioeconomic development,
contraception, culture and population density are used. The main results of the study are that
income, education and socioeconomic development are effective in declining fertility levels in
order of priorities and the main factor that causes differences in fertility between provinces
prioritized in development and the others is the income level.
Different from Yasit (2007), this study covers the period between 1975 and 2000. This brings two
advantages to my study. First of all, number of observations are increased which improves the
precision of estimators. Secondly, by including 1975 census, my study allowed me to analyze
dynamics of transition in wider time span. Moreover, Yasit only looks at fertility differences
between provinces prioritized in development and the rest of provinces. This is a problematic
approach. Although these provinces share the same level of economic development, they differ in
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terms of geography, culture and educational level. Yasit’s division leads to ignore effects of these
differences on fertility. For this reason, I analyze the causes of variation in fertility levels between
five regions which show different characteristics in terms of social, economic and cultural
structure.
Yucesahin and Ozgur (2008) analyze determinants of regional fertility differences in Turkey. In
their study, the special emphasis is given to high fertility in the eastern and southeastern regions.
The unit of analysis is province. The authors conduct multiple regression models at the provincial
level by using population census data belong to 2000. Total fertility rate is chosen as dependent
and educational, occupational, ethnicity, gross domestic product and child mortality variables as
independent variable. Cultural and innovation-diffusion theory of fertility transition are tested.
According to regression results, percentage of Kurdish population in region and illiteracy of
women have positive effect on fertility. The level of secondary schooling of females has
significant effect in declining fertility levels. However, in these regions, the main language is
Kurdish which further prevent women to reach necessary information about modern
contraceptives. The authors conclude that innovation diffusion theory explains the causes of high
fertility in the region.
The study only focuses on cultural and innovation diffusion theories of fertility transition
however this is only one side of coin. The relative economic backwardness of these regions and
political conflicts prevent decrease of fertility. In order to reach a complete picture, economic and
classical theories of fertility transition should be considered.
3. Theoretical Considerations
In this part of the study, first the meaning of the term “demographic transition” will be given and
then theories developed to explain the transition will be analyzed in detail. Second, variables that
construct our fertility equation will be introduced. Their definitions and hypothesis will be
discussed.
3.1 Demographic Transition Theory
In order to analyze demographic transition theory in detail, first we should explain what we mean
by the term “demographic transition”. Demographic transition refers to a shift from high birth
and death rates to low birth and death rates. Before transition, there were many births and deaths,
life expectancy was short, population was young and growth was slow. However, with the start of
transition, this trend changed radically. During the transition, first mortality and then fertility
declined, causing population growth rates first to accelerate and then to slow again, moving
toward low fertility, long life and an old population (Lee 2003, 167). The reason behind the shift
from high births and deaths to low births and deaths has been tried to be explained for almost a
century. The early attempts which focus on “modernization” as a cause of demographic transition
are called as demographic transition theory.
In the context of demographic transition theory, modernization refers to industrialization,
urbanization, development or socioeconomic development. According to the theory, demographic
revolutions are products of the economic and technologic changes of the modern era that have led
to economic development, mass communications, effective programs of public health and
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curative medicine, and related social changes (Hirschman 1994, 204). In other words,
demographic transition theory claims that rise in urbanization, education level, spread of
industrial economies, improvements in nutrition and health, better infrastructure,
individualization, and secularization are all causes of decrease in birth and death rates.
The idea of demographic transition theory was laid foundation in the famous article, “Population”
by Warren Thompson in 1929. Thompson claims that all countries in the world will experience
the trends in fertility and mortality levels that Western Europe experienced forty years ago at that
time as a result of industrialization and urbanization. Landry (1934) further contributed to
demographic transition approach by focusing on an explanation to declining levels of mortality
and fertility. He also investigated the beginning time of transition. After Landry’s important
contributions, it was Notestein who developed the demographic transition theory in 1945.
In his famous essay “Population”, Warren Thompson (1929) analyzes world countries according
to their mortality and fertility levels in three groups namely, A, B and C.
Western Europe, USA and Australia constitute group A countries. In this group, both birth and
death rates are tend to decline however; since the decline in birth rate is faster than decline in
death rate, population growth rate either low or zero. The age constitution of population is also
affected from this trend. There is an apparent decrease in the number of children and reproductive
adults. On the contrary, the number of middle age and elder people increase. This indicates
further decline in population growth rate.
Italy, Spain and Central European countries constitute group B. Similar to group A, both births
and deaths decline in group B countries. However, the death rate is declining as rapidly or even
more rapidly than the birth rate with the result that the rate of natural increase will probably for
some time remain as great as now, or even become larger in the near future (Thompson 1929,
962). According to Thompson, the reason behind rapid decline in death rates is the improvements
in nutrition and health and the spread of communication. Furthermore, group B countries are
more rural than group A countries that they were forty years ago. Thompson claims that rurality
in group B countries caused further delay in the decline of birth rates.
Russia, Japan, India and rest of the world constitute group C. Group C countries contained
approximately 75 per cent of world’s population. The most important characteristic of these
countries is that birth and death rates are all uncontrolled. Due to the lack of statistical
information, Thompson only focused on Russia, Japan and India where data are available. He
concludes that Malthusian dynamics determine population trends in these countries.
Thompson’s work is very important because he related decline in birth and death rates with
industrialization, urbanization and contraceptive knowledge. He did not attempt to develop a
theory for demographic transition. Even, he did not use the term “transition”. However, he did
present the transition as a continuing global generalization (Kirk 1996, 362).
Landry (1934) is the researcher who uses the term “demographic transition” for the first time in
literature. Similar to Thompson, he examines the population characteristics under three categories
namely; primitive, intermediate, and contemporary. He also suggests that this new demographic
regime is a global phenomenon and all countries will experience it sooner or later. There are two
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things that make Landry’s work very important. First, he focused on the question of “when
transition began?” He points out that birth restrictions are used as early as the latter part of 18th cc
in France. Second, Landry brings more detailed explanation to motives behind transition. Landry
believes them to be largely “egoistical”: the cost of children, their ability to cause pain and
distress to their parents, the limitation of parent’s activities and relaxation, and, of course, the
problems women experience in pregnancy and child care (Kirk 1996, 363).
As we can see, Thompson (1929) and Landry (1934) indeed formulated demographic transition
theory yet they did not call their work as “theory”. According to Szreter, there simply was no
strong social science and policy interest in demographic transition theory and its implications in
the 1930s (Szreter 1993, 664). For this reason, their works did not draw attention of other social
scientists or research institutions. However, change in institutional context, intellectual
developments and political events through 1940s revealed a necessity of population theory
(Szreter 1993).
Frank W. Notestein responded this demand by developing a comprehensive demographic
transition theory. He is accepted as the founding father of demographic transition theory. In his
model, he tried to explain why developed societies experienced a shift from high birth and death
rates to low births and death rates. The original formulation of transition theory was presented in
terms of three stages of demographic evolution from high birth and death rates-“high balance”- to
low birth and death rates-“low balance” (Friedlander et al. 1999, 495). In the intermediate stage
however, death rates decline faster than birth rates and rate of natural increase is high. This
caused the emergence of the issue of high population growth in developing countries. Different
from Landry and Thompson, Notestein brought detailed explanations to motives behind
decreasing birth and death rates. He defended the idea of attitudinal change against the
explanations that took the spread of contraceptive usage at center or biological factors. Notestein
emphasized the changing institutional fabric of society that led to the “emergence of a new ideal
in matters of family size” (Hirschman 1994, 211). The importance of individual freedom, rational
thinking and education, increase in the cost of child rearing, decrease in the economic
contributions of children, emancipation of women through work outside home and finally work
and family incompatibility led modern families to use contraceptive methods and decrease
fertility.
In the previous paragraphs, we examine the classical formulation of demographic transition
theory which takes “modernization” at the center to explain variations of birth and death rates
across countries. However, as it has already been emphasized that “modernization” is a broad
concept which covers changes from urbanization and loss of tradition to economic growth and
rise in per capita income. It is hard to explain all these changes in one theory hence there emerge
different theories focus on different aspects of modernization. In the next section, I will present
these different theories namely; economic theories and cultural theory of demographic transition.
These theories should be considered as complement to demographic transition rather than
competing.
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3.2 Economic Theories of Demographic Transition
3.2.1 Microeconomic Approach to Demographic Transition
In his work “An Economic Analysis of Fertility” Gary Becker applied principles of
microeconomics; “the theory of demand for consumer durables” to fertility decision process. The
most important reason to develop this new approach is that the failure of classical demographic
transition theory to explain sharp rises in post war birth rates. He opened a new era in
demographic research with his economic perspective and he stepped down to family level
decision. Furthermore, his approach is more open to empirical research and gives more concrete
results because it is easier to measure economic variables than measuring socio-cultural variables
like religiosity or individualism. Thus, the theory was attracted much of attention.
According to Becker (1960), parents are rational individuals who seek to maximize their utility
and children are perceived as normal goods. Parent’s demand for children is determined by
income, price and tastes. Under these constraints, they derive utility from consumption of each
child. Becker assumes that parents can derive utility in two ways; either they can have more
children (quantity increase) or they make additional expenditures on them (quality increase). In
case of a change in income, price or tastes, parents make adjustments both on quality and
quantity of children. However, any adjustment in child quantity or child quality is determined
according to quality-quantity interaction.
Since children are normal goods, the law of demand foresees a positive relationship between
child quantity and income. Unfortunately, over a long time period, fertility in developed countries
fell even though they experienced considerable rate of economic growth and increase in income.
This situation indicates a negative relationship between income and fertility. The secular decline
in fertility may also be consistent with a positive relationship since the secular decline in child
mortality and the secular rise in both contraceptive knowledge and child costs could easily have
offset the secular rise in income (Becker 1960, 231). For example, decrease in child mortality
increased the amount of survivors which leads to increase in cost of child, poor families who
have gained knowledge about contraceptives limit their fertility more than rich families and this
cause a decrease in overall fertility and finally, in societies where the returns on human capital are
high parents invest more on child quality than quantity. These forces offset the positive income
effect as a result of economic growth and caused families to prefer child quality than quantity.
It is very clear that the relationship between income and fertility is far from being simple and
much of attention should be given for explaining quality-quantity interaction. Becker and Lewis
(1973) construct a theoretical framework to explain this relationship.
As it is stated in Becker and Lewis (1973, 280) a typical utility function of a family is;
𝑈 = 𝑈(𝑛, 𝑞 𝑦)
(1)
𝑛 refers to the number of children, 𝑞 refers to quality of children and 𝑦 is other goods and
services.
The family maximizes utility under budget constraint 𝐼.
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𝐼 = (𝑛𝑞)𝑝 + 𝑦𝑝𝑦
(2)
𝑝 is the unit price of children with a given quality and 𝑝𝑦 is the price of other goods and services.
However, 𝐼 is not sufficient to explain quality-quantity interaction because family’s decision on
the number or quality of children changes according to cost of quality and cost of quantity which
are the functions of quantity and quality respectively. Hence, we need real income 𝑅.
𝑅 = 𝑛𝑝𝑛 + 𝑞𝑝𝑞 + 𝑦𝑝𝑦
(3)
𝑝𝑛 is the shadow price of children with respect to quantity and 𝑝𝑞 is the shadow price of children
with respect to quality. It is better here to explain what Becker means by “shadow price of
children” For example, shadow price of children with respect to quantity is the marginal cost of
an additional child with a given quality. Similarly, shadow price of children with respect to
quality is the marginal cost of adding one unit of quality with a given quantity. In this framework,
fertility declines are explained in two ways; income effect and price of time effect.
Income Effect
Since children are accepted as normal goods, we expect increase in quantity and quality when
income (𝐼) rises. However, increase in quantity and quality brings about an increase in shadow
price 𝑝𝑛 and 𝑝𝑞 at the same time. Thus, the percentage increase in real income in the sense of 𝑅
deflated by an index of the 𝑝’s is less than the percentage increase in money income 𝐼 (Becker
and Lewis 1973, 281). The real income elasticity with respect to quality and quantity determines
the amount of increase in child quality and quantity as a result of increase in income. Becker
1960 observes that both quantity and quality income elasticity is positive but quality income
elasticity is larger than quantity income elasticity. This means that when income increases,
families spend more on child quality rather than increase the quantity. Since parents demand
more quality than quantity, the shadow price of children with respect to quantity increases and
brings about decrease in quantity.
Increase in income is resulted by the increase in wage rates which make parent’s time more
expensive. In other words, price of time increases as a result of increase in wages. Since child
rearing is a time consuming activity, any increase in wages cause to increase in cost of child thus
decreased demand for quantity. This effect is more powerful in societies where social division of
labor makes women responsible for child rearing. While these economies grow, sectors in which
women have comparative advantage develop and provide women jobs with high wages. Higher
wages for women raise the cost of children relatively more than they raise household income, and
lead to a reduction in the number of children that couples choose to have (Galor and Weil 1996,
375).
As we can see, parents tend to substitute quantity for more quality because of high income
elasticity of child quality. This can be accepted as proof for negative relationship between child
quantity and quality. Furthermore, higher demand for quality indicates that children are perceived
as “consumer durable goods” rather than normal good.
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Price Effect
Socioeconomic development in a country causes changes in price of quality and quantity of
children. These changes in prices result in substitution effect between quantity and quality. It is
important to know whether families substitute child quality for quantity or not. For example,
thanks to the improvements in health care services child mortality rates declined and the rate of
survivors increased in developed countries. An increase in the rate of survivors makes the shadow
price of children with respect to quantity more expensive. As a result, quantity demand of
children decreases. However, the decrease in quantity leads to a decrease in the shadow price of
quality which increases the demand for quality. Even though quantity decreases, quality
increases. The same consequence can be reached when price of quality decreases as a result of for
example, spread of free compulsory education. In this case, shadow price of quality decreases and
families consume more quality. This leads to increase in shadow price of quantity which brings
about a decrease in quantity demand of children.
Moreover, Becker emphasizes changing cost of children with modernization as a cause for
families to rearrange their fertility decision. He claims that in traditional agricultural societies,
children were perceived as a source of labor for cultivating lands and parents expected them to
provide old age security. However, with transformation of agricultural-traditional societies to
industrial one, children are no longer seen as a source that provides labor for production or
accepted as old age security for their parents. On the contrary, parents make contribution to their
children’s development even though children do not contribute to parents or household economy.
High wage returns on human capital in developed countries cause families to invest for their
child’s education. Children stay longer in educational institutions instead of entering into labor
market and families spend more money on education than it was in past. As a result, net cost of
children becomes positive and families limit the number of children.
Although demand theory of fertility transition provides a useful framework for analyzing causes
of fertility decline, it has some serious constraints. In general, the model is suitable for explaining
cross sectional variations in fertility rates and considers only currently developed countries yet it
says little about historical variations and developing country case.
According to the model, women’s employment increase the price of time that is necessary for
rearing children thus cost of child. This indicates a negative relationship between fertility and
female labor force participation. However, in developing countries fertility continues to decline
even though female labor force participation rate is lower than in developed countries. On the
other hand, the assumption of positive net cost of children as a cause of fertility decline is
criticized by Cleland and Wilson (1987) because empirical results do not indicate any relation
between changing labor utility of children and fertility response. They noted that some of the
most substantial fertility transitions have occurred in labor intensive rice growing areas of the
world, where the contribution of children might be expected to be particularly great.
There are some problems with the concept of “child cost”. First of all, cost of children is defined
as costs that are necessary for rearing children. However, there is no consensus on which inputs
to children are most important and how their unit prices are measured (Schultz 2004, 5580).
Moreover, cost of child also means price of child in the model. Since families determine how
much to spend on children, child cost cannot be a suitable indicator of market price of children
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which is the function of child demand. The same problem also exists in the calculation of “price
of time”. Market wage of women is not a suitable indicator for implicit cost of children.
The model does not include the effect of changing tastes and preferences on child demand even
though, increasing variety of goods and services with industrialization caused to change the
direction of demand from children to newly introduced consumer goods. Moreover, household
demand theory assumes that cost of fertility regulation is zero. This assumption is far from reality
because contraceptive methods have both monetary, time and physic costs.
3.2.2 The Theory of Intergenerational Wealth Flow
The theory of Intergenerational Wealth Flow belongs one of the most influential demographers of
20th c.c , John C. Caldwell. In the 1976 study, he attempted to combine economic, cultural and
institutional theories of fertility decline to explain causes of fertility transition. Different from
other researchers in his era, he focused on anthropological analysis of fertility decline and applied
qualitative, micro research methods. The most important characteristic of his theory may be that
it is suitable for explaining both high and low fertility regimes.
Initially, Caldwell’s theory draws our attention to some of the improper generalizations of
classical demographic transition theory and reveals that fertility transition is a more complex
process than it was thought before. As Notestein mentioned frequently, industrialization and
urbanization through supporting individualism and secularity transform previously irrational and
superstitious society to the one that is rational. Hence it is expected from these rational
individuals of modern society to limit their fertility. Caldwell opposes the idea that pre
transitional societies are irrational. He criticizes the definition of “rationality” because it is highly
ethnocentric, relies on Western experience and cannot be generalized for all societies. Rather than
using ambiguous definition of rationality, he claims that all societies are economically rational
which means that different economic structure of each society affects decision on production,
distribution and fertility differently. According to this view, there are two types of fertility regime
the one in which it is economically rational to have as many children as possible and the other,
being childless is economically rational. However, in any society, fertility rate is neither in its
biological limits nor there is any childless society. This indicates that not only economic factors
are sufficient to explain fertility decision process. According to Caldwell, non economic factors
namely; social, physiological and psychological prevent unlimitedly high fertility or being
childless. Obviously, the fundamental choices are social ones and economic behavior is rational
only insofar as it is rational within the framework established by social ends (Caldwell 1976,
326).
Caldwell’s emphasize of social factors is also seen in his second criticism of demographic
transition theory. There is a general statement in Notestein’s formulation of demographic
transition theory that economic modernization by supporting the spread of urbanization causes
fertility levels to decline. Urbanization is seen as a process which supports the one’s own
personal advancement and unsuitability of urban life for child rearing brings about nucleation of
families. However, historical evidences do not support such kind of mechanism. For example, in
some areas of Europe, fertility started to decline although these areas were not even in the process
of economic modernization. At this point, Caldwell claims that there must be a social revolution
independent from economic modernization that causes fertility levels to decline. He calls this
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process as “Westernization”. Caldwell’s argument is supported by the fertility declines which
have occurred at very low levels of modernization (Kirk 1996, 372). It is clear that
Westernization precedes economic modernization in developing countries. Western ideas about
familial relations and production are the primary responsible for decline in fertility rates
especially in developing countries.
Caldwell states that whether high or low fertility is economically rational is determined by social
conditions: primarily by the direction of intergenerational wealth flow (Caldwell 1976, 355). In
primitive and traditional societies, socioeconomic structure foresees high fertility as an
economically rational response because the flow of wealth is from children to parents. In such
societies, cost of child rearing is shared by relatives and children are net contributors to
household economy rather than net consumers. They undertake many tasks from farming to
nursing younger siblings. Non monetary contributions of children are also important. Children
are seen as old age security and it is expected from them to guarantee their parents’ future.
Moreover, having many children increases political power of head of household. On the contrary,
in transitional societies, wealth flow directs towards children and parents’ contribution to children
turns into an economically rational behavior. In this context, higher fertility is not economically
rational. According to Caldwell, change in the direction of wealth flow towards children is
responsible for declining fertility levels.
Emotional nucleation of family is the main cause of change in the direction of wealth flow
towards children. In extended family system, conjugal relations are weak or absent and husband
and wife have closer relations with their kindredship such as sisters, brothers or cousins etc. This
characteristic of extended family system maintains its continuity. However, emotional nucleation
erodes the relation between extended family relatives, husband-wife relation strengthens and
parents become more concerned about their children’s future. Economic nucleation follows
emotional nucleation. Nuclear family which is composed of wife, husband and children, started
to act in accordance with their economic interests. Parents concern their children’s future and
invest more on them. Nucleation of families is neither caused by economic modernization nor
urbanization. The adoption of Western type of family relation is the reason behind nucleation of
families.
Western ideals about family relations spread through introduction of mass education in
developing countries. Mass education has special importance because the primary determinant of
the timing of the onset of the fertility transition is the effect of mass education on family
economy (Caldwell 1980, 225). Education transforms family economy thus direction of wealth
flow and causes fertility levels to decline. This process takes place in two phases; first it redefines
family morality which regulates rules of production and distribution, and then it prepares
individuals for market production instead of household production. In primitive and traditional
societies, the absolute authority is the male head of household and wife and children are subject
his authority. Family morality foresees that children have to work hard, not to expect much return
from parents and respect authority of old age relatives. Each members of family are not employed
for their private interest but for the sake of goodness of whole family. The flow of wealth is
apparently upward, from children to elderly. However, mass education substitutes family morality
with community morality by replacing the authority of head of household. Children are no more
seen as devoted members of families but independent individuals who are seeking their own
private interests. Family production is replaced by market production. Parents invest on their
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children’s education for better job in future. [T]he society regards the child as a future rather than
a present producer and that it expects the family to protect the society’s investment in the child
for that future (Caldwell 1980, 228). The direction of wealth flow changes towards children. In
this new economic structure, high fertility is not economically rational because of increasing cost
of children and decreasing immediate economic value.
Caldwell’s Intergenerational Wealth Flow theory is very important from many aspects however
there are some deficiencies in his theory. First of all, Caldwell’s statement of upward wealth flow
of wealth in traditional societies is criticized by evolutionary biology. Biologists expect net
wealth flows to be downward in all organisms, including humans (Kaplan and Bock 2001, 5558).
Secondly, the theory is very hard to prove especially when researchers come to calculate non
monetary contribution of children such as; old age security. Some studies conducted in high
fertility regions reveals contradictory results. In those societies, although children are employed
in domestic work or farming, their contributions are far from compensating family’s expenditure
for children throughout life.
3.2.3 The Supply-Demand Framework
According to Easterlin’s framework for fertility decision process, fertility is the product of the
interaction between three mechanisms namely; demand for children, supply of children and the
cost of fertility regulation. These three aspects of fertility decision closely interrelated with
intermediate variables that directly affect fertility. Before analyzing Easterlin’s framework in
detail, first we should explain what we mean by intermediate variables of fertility decision
approach very briefly.
The relation between socioeconomic change and fertility has always attracted many researchers’
attention in demography literature. There exist a various statistical studies conducted in
developed and developing countries to explain the effect of socioeconomic change on fertility.
However, the direction and magnitude of socioeconomic variables differs according to country or
region within the same country and time interval the study is conducted. Thus, results gained
from these studies are far from constructing a general socioeconomic theory of fertility transition.
The direct effect of socioeconomic variables on fertility is ambiguous. However, Davis and Blake
(1956) and Bongaarts (1978) developed a different approach and claim that there are some
intermediate variables which affected by socioeconomic change and directly affect fertility rates.
For example, education through increasing the age at first marriage decreases productive life span
of women and hence causes fertility to decline. In general, the biological and behavioral factors
through which socioeconomic, cultural and environmental variables affect fertility are called
intermediate fertility variables (Bongaarts 1978, 105). At first, Davis and Blake defined eleven
proximate determinants, and then their work is further developed by Bongaarts and reduced to
eight factors. These are;
I Exposure factors
1. Proportion married
II Deliberate marital fertility control factors
2. Contraception
3. Induced Abortion
III Natural marital fertility factors
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4. Lactational infecundability
5. Frequency of intercourse
6. Sterility
7. Spontaneous intrauterine mortality
8. Duration of the fertile period
In Easterlin’s framework, socioeconomic factors operate directly on the exposure and natural
marital fertility and indirectly on marital fertility control (Panopoulou & Tsakloglou 1999, 1139).
The amount and quality of children is the outcome of the interaction between demand for and
supply of children and cost of fertility regulation, which in turn are affected by intermediate
variables. These three mechanisms should be analyzed in detail in order to understand Easterlin’s
model.
The Demand for Children
According to Easterlin, demand for children can be explained as the number of surviving children
parents would want if fertility regulation were costless (Easterlin 1975, 55). Similar to the theory
of demand for children developed by Becker (1960) and Becker & Lewis (1973), Easterlin
assumes that parents determine the amount and quality of children they want to have according to
income, price of children, price of other goods and services and preferences.
Becker and other economists become successful to formulate the relationship between demand
for children, income and prices but they fail to include “preferences” into theory. Easterlin’s
model on the other hand, while still taking an economic approach, was based on the notion of
“shifting preferences”: preferences (i.e., material aspirations) which changed systematically as a
function of the same variables used to predict fertility- income and prices (Macunovich 1998,
54). Easterlin combines sociological and other theories of fertility with economic theory via the
concept of preferences. Preferences are formed by cultural, religious, ethnic or individual factors.
The stronger are a couple’s (relative) preferences for children, the greater the demand for
children, other things equal (Shapiro 1997, 2). For example; extended family norm in a society
can lead parents to have many children or highly educated parents want to become childless for
some other reason regardless of income and prices.
In Easterlin’s model, apart from income, prices and tastes, demand for children also depends on
infant and child mortality rates. Since parents concern about number of surviving children,
demand for children would be high if infant and child survival rates were low or vice versa.
The Supply of Children
Easterlin defines the concept of supply of children as a potential number of children parents
would have if they did not deliberately limit their fertility (Easterlin 1975, 55). Two factors,
namely; natural fertility and child/infant survival rates are the determinants of supply of children.
Increase in infant/child survival rates increase the potential number of children. However, even if
infant/child survival rates are identical in two societies, supply of children varies due to natural
fertility.
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We can term as natural the fertility which exists or has existed in the absence of deliberate birth
control (Henry 1961, 81). Bongaarts identifies natural martial fertility factors in intermediate
variables of fertility scheme. Biologic structure of women and sociocultural fabric of a society
through affecting these factors determine the level of natural fertility. For example, genetic
disorder, diseases or malnutrition affect the ability to carry a fetus or cultural factors, norms and
customs may determine coital frequency, fecundity and fetal mortality (Easterlin 1975, 56).
Cost of Fertility Regulation
The cost of fertility regulation is an important mechanism through which Easterlin includes effect
of cultural and diffusion theories of fertility transition into the model. According to Easterlin,
there are two types of fertility regulation costs which are physic and market costs. The biases
against idea of fertility control and problems emerged from improper use of contraceptive
methods constitute physic costs of fertility regulation. Market costs; on the other hand include
time and monetary cost of fertility control methods. These costs depend upon the attitudes in
society toward the general notion of fertility control, availability of information, price and
prevalence of specific techniques (Easterlin 1975, 56). For example, the spread of information
about contraceptive methods through family planning programs increase the legitimacy and
proper use of contraception thus leading to decrease physic cost. Free distribution of
contraceptives decreases market price of contraceptives.
Apart from costs, parents’ decision about the usage of fertility regulation is also related with their
strength of motivation for limiting fertility. Under the assumption of perfect contraceptive
society, desired number of children would be equal to supply if parents are motivated adequately.
Easterlin analyzes the transition from high to low fertility rates while modernization is
proceeding via the interaction between demand for, supply of children and cost of fertility
regulation in five stages. Figure 2.1 shows different behavior of these three mechanisms in
different phases of modernization.
In the first stage, there is excess demand for children because the output of children is far from
meeting the demand. Infant and child mortality rates are extremely high due to lack of modern
knowledge about puerperant and new born care, malnutrition and inadequacy or absence of
health services. Thus, infant and child survival rates are low.
In the second stage, social and economic development brings about improvements in nutrition
and health services thus infant and child mortality rates decrease. In other words, society
experiences mortality transition. The output of children starts to increase while the demand for
children decreases.
In the third stage, demand for children continues to decrease because of change in cost and
benefit of children. Socioeconomic development by transforming economic and family structure
of society increases cost of children and decreases benefit. In this stage, there emerges motivation
for fertility regulation however; it is not strong enough to lead parents to use contraceptive
methods. The cost of unwanted children is still less than cost of fertility regulation.
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Graph 3.1 Trends in supply of, demand for, and number of surviving children associated with modernization
Source: Bongaarts (1993, 439)
In figure 3.1 first, second and third stage of transition is represented between origin and point h.
In this interval, demand for children is constant until a point and supply of children continuously
increase due to improvement of health and nutrition. The actual number of children parents could
have is determined by output of children. The gap between demand and supply of children is
further extended between m and h. Fertility is the result of social and biological rather than
individual factors in this interval.
In the fourth stage, parents are highly motivated for limiting their fertility because cost of
unwanted children exceeds cost of fertility regulation. In the final stage demand and supply
reaches equilibrium.
3.3 Cultural Theories of Demographic Transition
There are two fundamental cultural theories of fertility transition namely; ideational theory and
innovation-diffusion theory. Ideational theory was developed by Lesthaeghe (1983) as a reaction
to new home economics’ approach. It aims to combine economic theory with sociological theory
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of taste formation.
According to new home economics’ approach parents determine the number of children they
want to have according to expected utilities resulted from having children. However, the theory
can not explain according to which criteria parents evaluate their utility. If person engage in
evaluation of utilities and disutilities, they operate on the basis of a preference map, and if such a
preference structure exists, there must also be meaning giving or ideational system that directs it
(Lesthaeghe 1983, 411). In other words, ideational structure forms our preferences then according
to these preferences, we derive utility or disutility. Economic theories are necessary for
explaining fertility transition but they are insufficient. They accept exogenous and constant tastes
even though tastes are opened to change in parallel with ideational change.
Innovation diffusion theory on the other hand emphasizes the importance of cultural similarities
across different regions in timing and speed of fertility transition. According to the theory, the
information about fertility regulation diffuses culturally similar regions quicker than culturally
dissimilar regions. Especially language constitutes an important barrier to the diffusion of new
ideas. Lesthaeghe’s famous study on Belgium is a good example. According to his findings, the
areas with high marital fertility and a late decline are nearly all on the Flemish (Dutch speaking)
side, and those with an early and faster decline are on with the Wallon (French speaking) side
(Knodel and Van de Walle 1979, 236). Since fertility transition in Europe first started in France, it
is not surprising that fertility regulation behavior spread quickly in French speaking regions of
Belgium.
3.4 Definition of Variables and Hypothesis
In this section, I will introduce dependent and independent variables that constitute the fertility
equation. First of all, I will give the definition of variables then I will indicate the expected
direction of relationship between dependent and independent variable in the light of demographic
transition theories. The table that contains dependent and independent variables, their sources and
abbreviations are given in Appendix D.
Dependent variable
Child women ratio
Child women ratio is the dependent variable in our regression equation. It can be defined as the
number of children at "0-4" age group per 1000 women of "15-49" age group. Since total fertility
rate for each province before 1980 is not calculated by State Institute of Statistics, child women
ratio is selected to represent the fertility level.
Independent variables
Education
The direction of the relationship between education and fertility differs according to the level of
education. Illiteracy or low levels of education results in high fertility whereas increasing level of
education decreases fertility rates. In order to capture both of these effects, I employed illiterate
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women and high school graduate women variables. Illiterate women variable can be defined as
percentage of illiterate women 14 years of age and over in total population of women 14 years of
age and over. High school graduate women variable refers to the percentage of high school
graduate women 25 years of age and over in total population of women 25 years of age and over.
I expect a positive relationship between illiteracy and child women ratio. Illiterate women have
lower position in society. They marry at earlier ages compared to educated women and have
lower bargaining power in fertility decision process. Early marriages have positive impact on
exposure and hence, increase the fertility. Moreover, diffusion of the knowledge about modern
contraceptive methods is limited among illiterate women. They are deprived of important
information sources like conventional or social media.
I anticipate a negative relationship between literacy and child women ratio. High educated
women have higher position in society. According to Becker (1973), educated parents desire to
have educated children. They tend to invest more on child quality rather than child quantity
because of time and money constraints. As a result, they limit their fertility.
In Easterlin (1975), education has both negative and positive effect on fertility. On the supply
side, education decrease infant mortality rates and increase supply of children by providing
information about child care to mother. However, on the contrary to illiterate fellows, educated
women stay in educational institutions longer and marry at older ages. Longer years of schooling
and older age at marriage shorten the reproductive life span of women, affect exposure negatively
and thus decrease the supply of children. On the demand side, the effect of education on fertility
is negative. Increase in education through changing preferences away from child to other goods
contributes to fertility decline. On the fertility regulation side, increase in education decreases
physic and monetary cost of fertility regulation and leads to reductions in fertility levels.
Educated women have higher level of position in society. They can oppose norms and traditions
that forbid fertility control. They have more bargaining power in fertility decision process and
they are well informed about modern contraceptives. Educated women also have more income
compared to uneducated women. They can easily compensate monetary cost resulted from
contraceptive methods. The strength of these effects changes according to culture, stage of
transition and level of development.
Non-Agricultural Female Labor Force Participation
Non-agricultural female labor force participation is defined as the ratio of the number of females
12 years of age and over employed in the nonagricultural sectors to the total female population 12
years of age and over. The relationship between non agricultural female labor force participation
and child women ratio is expected to be negative in the model. Increasing employment
opportunities out of agriculture, expanding hours of working outside the home, and upward trend
in female wages in developed countries make women’s time more valuable. However, as Becker
(1985) states that since women have natural comparative advantage in child rearing, they are
accepted as prime responsible for time consuming child rearing activity. Time spent raising
children cannot be spent working, and so the opportunity cost of children is proportional to the
market wage (Galor & Weil 1996, 378). As a result, increase in price of women’s time increases
the cost of children thus leads to decrease in demand and decrease in fertility.
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The inverse relationship between female labor force participation and child women ratio is
expected to be stronger in advanced industrialized countries where women’s employment takes
place outside home than developing countries where domestic production is widespread
(Panopoulou& Tsakloglou, 1999). The relationship may even turn into positive in developing
countries because of work and home compatibility. In order to purge the effect of work-home
compatibility, I employed female non agricultural labor force participation rate rather than
aggregate participation as independent variable.
Employment in Modern Sectors of Economy
Employment in modern sectors of economy variable represents the percentage share of
employment in industry, construction and services sector in total employed population. A
negative relationship is expected between this variable and child women ratio. Employees
working in these sectors of economy have a certain level of education which leads to decrease in
their fertility levels. Job opportunities in these sectors are mostly in urban areas where the
conditions for child bearing are less suitable compared to rural areas. Moreover, they are aware of
the fact that education is important to find a high quality job. It is expected for them to invest in
child quality rather than child quantity. Lastly, employment in modern sectors of economy
increases the price of time which makes time intensive child care activity more expensive. Thus,
parents choose to limit the fertility.
Rurality
The rurality variable refers to the percentage of population living in sub-districts and villages in a
total population of a province. A positive relationship is expected between the share of village
population and child women ratio. The main economic activity in rural parts of Turkey is
agriculture and husbandry (Özgür 2004). Since these economic activities are labor intensive, it is
economically rational to guarantee enough offspring to cultivate lands in the future (Caldwell
1976). Fertility is expected to be high in these parts of the country. Rural parts of Turkey are
more closed than urban parts. Information about fertility regulation, nuclear family type and
changing value of children reach and diffuse slowly in rural areas especially during the time
interval that study is conducted. We expect high fertility in these regions. Strong kinship relations
and the dominance of traditions which regulate social life are other two characteristics of rural
areas (Thompson 1929, Notestein 1945). In such an environment, the adoption of modern
contraceptives is more difficult because fertility regulation behavior may be sanctioned by the
other group members. The moral cost of fertility regulation increases and the demand for these
methods decrease (Easterlin 1975). As a result, fertility levels are expected to be high.
Infant Mortality
Infant mortality is defined as the number of infants who dies under 1 year old per 1000 live born
infants. It is expected a positive relationship between infant mortality rate and child women ratio
in the model. Infant mortality rate has both economical and biological effects on fertility. In
traditional, agricultural societies where mortality rates are high and survival prospects are low,
parents increase the number of births in order to reach desired family size or guarantee a certain
amount of labor force and the old age security (Caldwell 1976, 1980).
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Change in infant mortality rates also affects women’s physiology. Increase in infant mortality
rates decreases the length of post partum amenorrhea and make women eligible to a new
gestation or decrease in infant mortality prolongs the lactation period and reduces the fertility
(Yamada 1985).
Public Libraries
Public libraries variable refers to total number of public libraries in a province. They provide
written work to users free of charge. Through these works, users can reach different information
such as family planning, reproductive health and new contraceptive methods each of them have
fertility decreasing effect. The importance of public libraries increases in east part of Turkey
where communication and diffusion of information is limited because of economic constraints.
In the literature, different proxies are used to represent the effect of diffusion of information. For
instance, Yasıt (2007) uses percentage of public library users or Lehmijoki (2003) uses number of
radio listeners. I chose total number of public libraries in a province as a proxy for diffusion of
information. I expect a negative relationship between number of public libraries and child women
ratio.
Income
The relationship between income and fertility levels is subject to many researches however the
direction of the relationship is ambiguous. To represent income, I use the Gross Provincial
Product which is GDP of the provinces in millons of Turkish lira and in 1987 prices.
Becker and Lewis (1973) suggest that increase in income is expected to increase both demand for
child quality and quantity. However, price of quality depends on quantity and price of quantity
depends on quality. Since the income elasticity of demand for quality is higher than quantity,
increase in income leads couples to invest more in quality. Hence, price of quantity increases and
couples demand fewer children.
In Easterlin (1975) framework, the effect of increase in income has both negative and positive
effects on fertility. On the supply side, higher income provides better nutrition and health care
services for new born which causes infant mortality rates to decline. As a result of decrease in
infant mortality rates, fertility reduces. However, increase in income increases the demand for
breast feeding substitutes which shorten the postpartum infecundability and prevent marriages to
be delayed and thus, may increase fertility (Panopoulou& Tsakloglou 1999).
On the demand side, increase in income decreases fertility. Easterlin maintained the common idea
of economic perspective that households tend to shift their expenditures from items
complementary with children towards a new consumption items that are substitute for children
(Yavuz 2008, 76). As a result, rise in income provides a variety of goods which are competitive to
child rearing.
On the cost of fertility regulation side, higher income make easy for couples to reach
contraceptive methods through decreasing the financial burden of these products.
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Galor and Weil (1996) investigate the effect of increase in men’s and women’s income on fertility
separately. On the one hand, increase in men’s income increases the demand for children. On the
other hand, increase in women’s income render women’s time more valuable and increase the
cost of children. Hence, the demand decreases. The total effect resulted from increase in both
men’s and women’s income however, is ambiguous.
4. Data and Method
4.1 Source Material
In this study, the main aim is to reveal determinants of Turkish fertility transition and causes of
variation in fertility level across five different regions of Turkey during the period 1975 and
2000. In order to achieve my aim, I will employ panel data fixed effects method using data
belong to population censuses of 1975, 1980, 1985, 1990 and 2000. Panel data fixed effects
model is the most suitable method for Turkish case because of data limitations. In demographic
transition studies, time series method is preferable yet yearly data for important variables such as
child women ratio, infant mortality or gross domestic product per province is not available.
However, panel data method allowed me to benefit from both time series and cross sectional
information found in population censuses.
Data for the study comes from State Institute of Statistics (SIS) census of population; social and
economic characteristics of population for various census years and provincial census books. I
also used cultural statistics and statistical year books of SIS for related years. Since SIS is an
official institution that conducts population censuses exclusively, reliability of data is at utmost
level. The topic of thesis is demographic transition and regional variations of fertility thus; macro
data approach is the most suitable approach because it covers whole population and regions.
Population census in Turkey was conducted quinquennial between 1927 and 1990. However,
after 1990, it was determined to be decennially. For this reason, population census after 1990 was
held in 2000, not in 1995.
The smallest unit which data for all variables are available is province. Since some of the
important variables such as; GDP by provinces were not calculated before 1975 thus, time period
that I conduct my study is limited between 1975 and 2000. There were 67 provinces in Turkey
before 1990. The number of provinces increased in 1990 and it reached 81 in 2000. To maintain
the consistency of the study, I adjusted the data for the years 1990 and 2000 by adding the
information for new provinces back to old provinces which they were separated. Hence, the total
number of provinces became 67 in all four models.
I faced with some difficulties to find GDP by province data for the years 1975, 1980 and 1985
because this data before 1987 is not available either in internet data base or publications of SIS.
However, Karaca (2004) acquired GDP per capita by provinces between the years 1979 and 1986
from Özötün (1980). I calculated GDP by provinces for the years 1980 and 1985 by multiplying
GDP per capita by provinces with population of each province respective census years. I did not
make any adjustment apart from these. All other variables are used as it is founded in database or
publications. There is no missing observation in my data set. My panel is strongly balanced.
Descriptive statistics belong to data set is given in Appendix C.
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4.2 Statistical Method
The statistical method used in this study is panel data-fixed effects method. A panel of data
contains information about cross section of individuals (countries, provinces, firms or households
etc.) who are observed at multiple points in time (Lundborg 2010)4. It combines both time series
and cross sectional aspects of information. In our case, the panel of data contains information
about 67 provinces of Turkey which was observed five times between the period 1975 and 2000.
Panel data regression analysis is a widely used tool in the field of economics and demographics
due to its advantages over cross-section or time series approaches. The most important advantage
of panel data analysis is that it is easy to deal with omitted variable problem. With panel data, one
can correct for certain types of omitted variable without observing these or having to rely on
instrumental variables (Lundborg 2010, 3). The nature of panel data, inclusion of both time series
and cross sectional information, allows researchers to increase number of observation. Owing to
increase in number of observations, precision of estimators improve. Moreover, panel data
provides more dynamic view in contrast to static view of cross section.
The basic specification of the linear panel data model is;
𝑌𝑖𝑡 = 𝛼 + 𝑋𝑖𝑡 𝛽 + 𝜐𝑖𝑡
i = 1, … N
t = 1, … T
(4.1)
In the model, i represent individuals and t represents time. Thus, the model indicates that N
number of individuals is observed until the time T. In panel data models, we assume that the error
term 𝜐𝑖𝑡 can be divided into two parts that enter additively (Lundborg 2010, 7).
𝜈𝑖𝑡 = 𝜂𝑖 + 𝜀𝑖𝑡
(4.2)
The equation (4.2) indicates that error term of panel data model can be divided into two parts; 𝜂𝑖
which does not vary over time and 𝜀𝑖𝑡 which varies over time. To be more precise 𝜂𝑖 refers to all
unobserved characteristics of individuals which either dependent or independent of time.
There are two ways to analyze panel data namely; fixed effect and random effect. Researchers
determine which method to use according to the assumption that they made about 𝜂𝑖 .
If we assume that there are no any unobservable characteristics which are time invariant as it is
shown in equation (4.3), random effect method is used.
E [𝜂𝑖 |𝑋𝑖1 , … , 𝑋𝑖𝑇 ] = 0
(4.3)
If we assume that there are unobservable characteristics which are time invariant as it is shown in
equation (4.4) , fixed effect method is used.
E [𝜂𝑖 |𝑋𝑖1 , … , 𝑋𝑖𝑇 ] ≠ 0
4
(4.4)
Lundborg, P. Applied microeconometrics lecture slides and lecture notes, Lund University.
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The fixed effect assumption is more realistic because there are of course unobserved
characteristics that are time invariant. In our case, these characteristics may be historical and
political background of provinces. Apart from theoretical motivation, Haussmann test is
performed to decide whether there exist unobservable and time invariant characteristics
correlated with our independent variables or not. The result indicates that there exist
unobservable and time invariant characteristics correlated with independent variables.
The correlation between 𝜂𝑖 and 𝑋𝑖𝑡 violates the zero conditional mean assumption which
maintains unbiasedness and consistency of estimation. Thus, the correlation must be eliminated.
There are two ways to eliminate the effect of 𝜂𝑖 ; dummy variable estimation and within
estimation. Dummy variable estimation necessitates dummy variables for each individual in data
set. This estimation procedure is not practical when there are thousands of individuals. In my
model, I used within estimation procedure because we have many individuals to add dummy.
Within estimation procedure relies on a simple idea. Since 𝜂𝑖 is time invariant, we can take
average of all parameters over time in our equation and then subtract it from the basic equation.
The derivation of within estimation procedure is taken from Lundborg (2010).
𝑌̅𝑖 = 𝑋̅𝑖 𝛽 + 𝜂̅𝑖 + 𝜀̅𝑖
(4.5)
Where;
1
𝑌̅𝑖 = 𝑇 ∑𝑇𝑡=1 𝑌𝑖𝑡
1
1
1
𝑋̅𝑖 = 𝑇 ∑𝑇𝑡=1 𝑋𝑖𝑡 𝜀̅𝑖 = 𝑇 ∑𝑇𝑡=1 𝜀𝑖𝑡 𝜂̅ 𝑖 = 𝑇 ∑𝑇𝑡=1 𝜂𝑖
(4.6)
Next subtract equation (6.5) from the equation (6.1) ;
𝑌𝑖𝑡 - 𝑌̅ = 𝑋𝑖𝑡 𝛽 + 𝜂𝑖 + 𝜀𝑖𝑡 - 𝑋̅𝑖 𝛽 − 𝜂̅𝑖 − 𝜀̅𝑖 = (𝑋𝑖𝑡 − 𝑋̅𝑖 )𝛽 + (𝜀𝑖𝑡 - 𝜀̅𝑖 )
(4.7)
Since 𝜂̅𝑖 = 𝜂𝑖 , this implies that we get the specification
𝑌̃𝑖𝑡 = 𝑋̃𝑖𝑡 𝛽 +𝜀̃𝑖𝑡
i = 1, …N
t= 1, … T
𝑋̃𝑖𝑡 = 𝑋𝑖𝑡 − 𝑋̅𝑖
𝜀̃𝑖𝑡 = 𝜀𝑖𝑡 - 𝜀̅𝑖 (4.9)
(4.8)
With
𝑌̃𝑖𝑡 = 𝑌𝑖𝑡 - 𝑌̅
The within estimator 𝛽𝑤𝑖𝑡ℎ𝑖𝑛 is then obtained by applying OLS. Fortunately powerful Stata
command xtreg, fe automatically calculate within estimator. Owing to fixed effect estimation, I
could omit time invariant and unobservable characteristics which correlated independent
variables.
𝐶𝑊𝑅 = 𝛼𝑖 + 𝛿𝑖 + 𝛽1 𝐻𝑆𝐺_𝑊𝑖𝑡 + 𝛽2 𝐼𝐿_𝑊𝑖𝑡 + 𝛽3 𝐹𝑁𝐴𝐿𝐹𝑃𝑅𝑖𝑡 + 𝛽4 𝐼𝑀𝑅𝑖𝑡 + 𝛽5 𝐸𝑀𝑆𝑖𝑡 +
𝛽6 𝑅𝑈𝑅𝐴𝐿𝐼𝑇𝑌𝑖𝑡 + 𝛽7 𝐿𝑁_𝐺𝑃𝑃𝑖𝑡 + 𝛽8 𝑃𝐿𝑖𝑡 + 𝛽9𝑡 𝐴𝑆𝐻𝐴𝑅𝐸𝑖𝑡 + 𝜂𝑖 + 𝜀𝑖𝑡
(4.10)
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The equation (6.10) is the main regression equation that will be estimated to find answer for
research questions stated in the thesis. In the equation, 𝛼𝑖 refers to unobserved provincial fixed
effects and 𝛿𝑖 variant time effects among provinces.
5. Empirical Analysis
The main aim of this section is to reveal the factors that are effective in the decline of fertility
during demographic transition and cause variation in fertility levels across different regions of
Turkey between 1975 and 2000. In order to achieve my aim, I estimated my regression equation
with panel data fixed effects estimation method. The estimation of regression equation and the
interpretation of results are given in section 5.1. Section 5.2 is shared for the discussion of results.
5.1 Statistical Results
In this section, firstly the results of the estimation of regression model which covers all provinces
of Turkey will be given. Secondly, the results of the estimation of regression models constructed
for each statistical region separately will be discussed. In all models, dependent variable is child
women ratio and the period under consideration is between 1975 and 2000.
Table 5.1 The results of fixed effects estimation including all provinces, 1975 and 2000
INDEPENDENT VARIABLES
MODELS
(1)
(2)
-6.255595 -13.99855
High School Graduate Women
(-2.20)
(-4.68)
2.867424
Illiterate Women
(6.24)
2.316693 6.195142
Female Non Agricultural Labor Force Participation
(1.12)
(2.74)
.9747368 -.1948635
Employment in Modern Sectors of Economy
(1.30)
(-0.25)
2.45204
Rurality
(3.52)
1.043354 1.803506
Infant Mortality Rate
(7.70)
( 16.09)
1.140075
.78344
Public Libraries
(1.85)
(1.14)
-3.662918 -8.482244
LN_GPP
(-0.87)
(-1.82)
0.9054
0.8801
R-squared within
0.6354
0.2340
between
0.6234
0.3983
overall
0.0000
0.0000
Prob > F
Note: In the parenthesis t-ratios are given
37
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Table 5.1 indicates the results of fixed effects estimation for all provinces of Turkey between the
years 1975 and 2000. In model (1), all independent variables are regressed into dependent
variable, child women ratio and in other model, some of the independent variables were omitted
to improve the efficiency of results. The F-test value for all models is less than 0.05 which
indicates that all models are well structured.
In model (1), percentage of illiterate women, infant mortality rate and rurality variables are found
significant at the 1% significance level. The direction of the relationship between these variables
and dependent variable is in line with expectations. Holding all other independent variables
constant, one unit increase in the percentage of illiterate women increases child women ratio 2.87
units. One unit decrease in the rurality variable decreases child women ratio 2.45 units and one
unit increase in infant mortality rate increases child women ratio 1.04 units.
Percentage of high school graduate women variable is significant at 5% significance level. This
variable has the most significant effect in declining fertility level. One unit increase in the
percentage of high school graduate women decreases child women ratio 6.26 units.
Finally, the last significant variable is total number of public libraries in a province. It is
significant at 10% significance level. However, the direction of the relationship between this
variable and child women ratio is different than expected. One unit increase in public libraries
increases child women ratio 1.14 units
Female non agricultural labor force participation, employment in modern sectors of economy,
and log of gross provincial product variables are found as insignificant. The relationship between
gross provincial product and child women ratio is negative as expected. However, the sign of
coefficient of other variables are different than expected.
In the model (1), there exist correlations between employment in modern sectors of economy and
rurality variables. Illiterate women and high school graduate women are also correlated. The
model (2) corrects the problem by omitting related variables.
The model (2) omits rurality and illiterate women variables. In this model, female non
agricultural labor force participation and gross provincial product variables turn into significant at
5% and %10 significance level. However, the sign of coefficient of female non agricultural labor
force participation is still positive which is contrary to expectations. The coefficient of gross
provincial product grows compared to first model. One unit increase in this variable decreases
child women ratio 8.48 units.
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Table 5.2 The results of fixed effects estimation for each regions, 1975 and 2000
MODEL
High School Graduate
Women
INDEPENDENT VARIABLES
Illiterate Women
Female Non Agricultural
Labor Force Participation
Employment in Modern
Sectors of Economy
Rurality
Infant Mortality Rate
Public Libraries
LN_GPP
R-squared within
between
overall
Prob > F
WEST
-15.27829
(-3.01)
2.660337
(2.75)
7.054281
(2.59)
1.47736
(1.38)
.9305866
(1.25)
1.275819
(5.03)
.5440306
(0.59)
41.27267
(1.42)
0.9392
0.1320
0.7283
0.0000
EAST
-18.29215
(-2.56)
.7431045
(0.68)
-5.869053
(-0.65)
3.797901
(2.10)
7.909428
(3.30)
.8674711
(3.33)
3.754618
(2.19)
-10.7435
(-1.15)
0.9068
0.1576
0.4425
0.0000
SOUTH
1.233259
(0.22)
3.135761
(3.50)
-12.5746
(-2.77)
4.704779
(1.93)
2.002298
(1.31)
2.129531
(5.30)
1.495578
(0.79)
-2.667633
(-0.37)
0.9747
0.9321
0.8695
0.0003
NORTH
-7.321088
(-0.68)
2.65598
(2.90)
-12.80907
(-1.88)
4.823018
(2.13)
1.012794
(0.54)
1.343115
(3.76)
-.9460295
(-0.30)
3.435788
(0.31)
0.9478
0.0000
0.7909
0.0003
CENTRAL
1.411512
(0.21)
2.160448
(2.11)
-.8251003
(-0.17)
2.488425
(1.27)
1.013123
(3.26)
1.013123
(3.26)
-.5471117
(-0.64)
-5.97348
(-0.99)
0.9260
0.3954
0.7613
0.0000
Note: In the parenthesis t-ratios are given
Table 5.2 shows the results of fixed effect estimation for provinces situated in five different
regions of Turkey between 1975 and 2000. In all models, the F-test value is less than 0.05 which
means that they are well structured.
In WEST, all independent variables are regressed into dependent variable, child women ratio.
However, half of the variables are found insignificant. Infant mortality rate variable is found
significant at 1% significance level. The percentage of high school graduate women, illiterate
women and female non agricultural labor force participation rate are found significant at %5
significance level. The sign of coefficient of the high school graduate women variable and
illiterate women variables is found as expected yet the sign of female non agricultural labor force
participation rate is different than expected. The highest magnitudes of the effect among
significant variables belong to high school graduate women variable. Holding all other
independent variables constant, one unit increase in this variable decreases child women ratio
15.3 units in west part of Turkey. One unit increase in the illiterate women variable increases
child women ratio 2.66 units. However, female non agricultural labor force participation rate has
positive sign and one unit increase in this variable increases child women ratio 7.05 units. All
other insignificant variables except from employment in modern sectors of economy and number
39
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of public libraries variables have expected sign of coefficient.
It is interesting to note that the sign of coefficient of gross provincial product is positive and it
has the most important effect in fertility equation even though it is not significant. One unit
increase in gross provincial product increases child women ratio 41.27 units holding all other
variables constant.
In EAST, all independent variables are regressed into dependent variable child women ratio. Five
variables are found significant. The most significant variable in declining fertility level is the
percentage of high school graduate women. The direction of relationship is in line with the
expectation. One unit increase in this variable decreases child women ratio 18.29 units at %5
significance level. Employment in modern sectors of economy is found significant yet the sign of
coefficient is positive contrary to expectations. One unit increase in this variable increases child
women ratio 3.80 units at 5% significance level holding all other independent variables constant.
Rurality and infant mortality rate variables are also found as significant at 5% and 1%
significance level respectively. One unit decrease in rurality decreases child women ratio 7.9
units and one unit increase in infant mortality rate increases child women ratio 0.9 unit. The
number of public libraries variable is significant at 5% significance level but the sign of
coefficient is positive. One unit increase in this variable increases child women ratio 3.75 units.
Illiterate women, female non agricultural labor force participation and gross provincial product
variables are found significant but the sign of the coefficient are in line with expectations.
In SOUTH, all independent variables are regressed into the dependent variable, child women
ratio. Infant mortality rate is found significant at 1% significance level. One unit increase in this
variable increases child women ratio 2.14 units. Illiterate women and female non agricultural
labor force participation are significant at 5% significance level. One unit increase in illiterate
women increases child women ratio3.14 units and one unit increase in female non agricultural
labor force participation decrease child women ratio 12.57 units. Finally, employment in modern
sectors of economy is significant at 10% significance level but the sign of coefficient is positive
opposed to expectations. One unit increase in employment in modern sectors of economy
increases child women ratio 4.70 units. The sign of insignificant variables are in line with
expectations except high school graduate women and public libraries variables.
In NORTH, all independent variables are regressed into the dependent variable, child women
ratio. Four variables are found significant. The interpretation of the coefficients belong to
significant variables are given as follows. Infant mortality rate is significant at 1% significance
level. One unit increase in this variable increases child women ratio 1.34 units. Illiterate women
and employment in modern sectors of economy variables are significant at 5% significance level.
One unit increase in illiterate women increase child women ratio 2.66 units. One unit increase in
employment in modern sectors of economy increases child women ratio 4.82 units as opposed to
expectations. Female non agricultural labor force participation is significant at 10% significance
level. One unit increase in this variable decreases child women ratio 12.81 units. All other
insignificant variables have the expected sign of coefficient.
Finally, in CENTER, dependent variable child women ratio is regressed into all independent
variables. However, most of the variables are found insignificant. The only significant variables
are illiterate women and infant mortality rate. Holding all other variables constant, one unit
increase in infant mortality rate increases child women ratio 1.01 units at 5% significance level
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and one unit increase in illiterate women increases child women ratio at 2.16 units at 5%
significance level. The direction of the relationship between all other variables except
employment in modern sectors of economy and child women ratio is in line with the
expectations.
5.2 Discussion
The results of the regression models estimated with data for all provinces reveal the main factors
that are effective in Turkish fertility transition during the period between 1975 and 2000. When
we consider all two models presented in table 5.1, we see that the most significant effect belongs
to education. In model (2), one unit increase in the percentage of high school graduate women
decrease child women ratio 13 times more unit. In model (1) and (2), one can also understand that
how education is important in Turkish case by looking at positive relationship between female
illiteracy and child women ratio. The negative relationship between education and fertility is also
in line with related demographic transition theories. Educated women want to have educated
children. It means that they invest in child quality of children rather than quantity. Thus,
government as well as non governmental organizations should develop necessary policies to
increase female high school graduation rate and to exterminate illiteracy if fertility level is
achieved to low levels.
Gross provincial product is responsible for the second highest effect in fertility decline during
demographic transition of Turkey. The negative relationship between this variable and fertility
satisfied our hypothesis and theory. One unit increase in gross provincial product has 8 times
decreasing effect on fertility. This variable is selected as a proxy for income level. Thus, we can
say that families in Turkey choose to invest in child quality rather than quantity. In order to
achieve low levels of fertility, income level of Turkish citizens should be increased by applying
efficient development policies.
The importance of the effect of infant mortality rate and rurality on fertility rate is less than
income and education. However, the direction of the relationship between these variables and
child women ratio is in accordance with our expectations and theories. Infant mortality rate
positively affects fertility. This indicates that Turkish families continue reproduction until they
reach desired number of children in case of high infant mortality rates. To decrease infant
mortality rates, public health services should be accessible for every citizens of Turkey.
Especially, crucial information about infant and child health should be diffused in regions where
infant mortality is high. The effect of rurality on fertility is positive. The transformation of rural
areas into modern, urban areas will result in changing tastes and preferences about parenthood,
emergence of variety of new goods and services alternative to child bearing and loosing of old
culture will expected to decrease fertility levels.
The sign of employment of modern sectors of economy variable turns into negative as expected
after omitting rurality variable which causes correlation problem with it. However, the decreasing
effect of this variable on fertility is rather small. Female non agricultural labor force participation
variable is found significant yet the sign of the coefficient are different than expected. The
simultaneity between child women ratio and female non agricultural labor force participation rate
may reverse the relationship.
41
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In order to reveal the causes of regional variation of fertility, the same model is applied five
different statistical regions of Turkey separately. In the following paragraphs, evaluation of the
significant variables will be presented.
The most significant effect in declining fertility levels in west belongs to high school graduate
women variable. The western part of Turkey has already had low levels of fertility. This is a very
good example of how education is effective in declining fertility levels. The effect of female non
agricultural labor force participation comes after the education. However, the sign of coefficient
is negative as opposed to expectations. That is may be due to mothers need to earn more money
because there are more children to look after when the child women ratio increase (Yasit 2007,
111).
Gross provincial income has an impressive effect on child women ratio in west even though it is
not significant. One unit increase in this variable increases child women ratio 40 times more
units. As it is stated in theory and hypothesis section, income may affect fertility in both
directions. For west, direction of relationship is positive. It indicates that families choose
reproduction when they achieve certain amount of income and among these families, wives who
are mother are also wage earner. Thus, it is not surprising that the relationship between female
non agricultural labor force participation and child women ratio is also positive and significant.
The factors that determine fertility level in east region which is the highest fertility region of
Turkey are education, income and rurality. The most significant effect in declining fertility levels
belong to the percentage of high school graduate women. In order to achieve low fertility levels
in this region, policies that support female education until at least high school level, should be
developed.
The second highest effect in declining fertility levels belongs to income variable yet it is not
significant. Income has ten times declining effect on fertility. Thus, income level of citizens
living in east should be increased in order to achieve low levels of fertility. Rurality is another
factor that has powerful effect in increasing fertility levels. The rural population transformed into
urban via the planned urbanization policies. This might be another option to decrease fertility
levels. Female non agricultural labor force participation also decreases fertility but the effect is
not significant. Finally, illiterate women and infant mortality rate have their positive effect also in
that region. In order to decrease fertility in this region; the percentage of female graduated from
high school should be increased, income level of citizens should be improved with necessary
development policies, the rural population should be transformed into modern, urban societies.
In south, female non agricultural labor force participation has the most significant impact on
declining fertility levels. To achieve low levels of fertility, employment opportunities for women
in modern sectors of economy should be created before anything else. Income variable has also
negative effect on fertility but it is not significant. Illiterate women and infant mortality rate
increase child women ratio also in this region. Thus, the levels of these development indicators
should be pulled down as soon as possible to decrease the fertility.
Female non agricultural labor force participation rate is the most significant determinant of
fertility levels in north of Turkey. New job opportunities out of agriculture for women living in
42
Alper AVSAR
north part of Turkey will have resulted in more declines in fertility rate. Thus, policy programs
that support female employment in non agricultural sector should be developed to decrease
fertility levels in the region. High school graduate women variable has the second highest effect
in declining fertility yet it is not significant. The social interaction variable, namely number of
public libraries has negative impact on fertility decline in north even though it is not significant.
The spread of new ideas about family, value of children and contraceptives via public libraries
seems to contribute more to fertility decline.
In center region of Turkey, gross provincial product has the highest effect in fertility decline but
this effect is not significant. Illiterate women and infant mortality rate are the determinant of
fertility decline in this region. Both of these variables have positive effect on fertility thus they
must be reduced to promote fertility decline in center region of Turkey.
To sum up, factors determine the level of fertility in five different regions of Turkey differs yet in
general; education and female labor force participation seems to have significant effects. In west
part of Turkey, education and income variables have significant effects on determining fertility
levels. However, different from other regions, income has a positive effect on fertility. In south
and north part of Turkey, female non agricultural labor force participation is the most significant
variable that decreases fertility levels. In center, infant mortality rate and illiterate women are
significant variables. In east, education and income have strong effect in declining fertility levels.
6. Conclusion
In this study, the main aim is to find factors that are effective in fertility Turkish fertility transition
and to reveal causes of regional variation of fertility by using panel data fixed effects estimation
for the period between 1975 and 2000. The study contributes to accumulation of knowledge in
the field of Turkish demography. First of all, this is the first study that applies panel data fixed
effects estimation to a longer time interval to the best of my knowledge. Different from the study
which covers the period between 1980 and 2000, this study goes back five years more in Turkish
demographic transition and includes related information for the population census of 1975.
Secondly, studies that consider regional variation of fertility in Turkey apply cross sectional OLS
regression method which provides static view whereas this study applies panel data approach to
regional fertility variation question.
According to results, education and income emerge as the most significant factors that contribute
fertility decline in Turkey. However, when we look at the picture in regional level, we see that
different factors are effective in transition and the direction of the effect of these different factors
change across the regions. For example, in west income and female non agricultural labor force
participation increase fertility as opposed to expectations yet these variables have expected
effects in all other regions. In the highest fertility region, east part of Turkey, education, income
and rurality variables have the most significant effect on transition. In south and north, female
non agricultural labor force participation rate has the highest decreasing effect. In center illiterate
women and infant mortality rate variables are significant. These results should be considered by
policy makers if low fertility levels are to be achieved.
43
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Appendix A.
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Appendix B.
Appendix C.
Variable Obs
Mean
Std. Dev.
Min
Max
cwr
hsg_w
il_w
fnalfp
ems
335
335
335
335
335
537.4507
3.526866
43.50054
4.66197
33.55057
196.3405
2.766764
19.37778
3.112449
14.91276
234
0.21
11.36
0.76
11
1108
14.49
93.25
18.2
94.9
rurality
imr
ln_gdp
pl
335
335
335
335
56.61352
102.9224
13.09188
10.85075
14.66156
47.37593
1.217461
10.03654
4.83
31
8.164511
1
84.16
233
17.10767
58
49
Alper AVSAR
Appendix D.
Dependent Variable
Child Women Ratio
Source
Census of Population 1975 and 2000, Social
and Economic Characteristics of Population,
Province Yearbooks of 2000.
Abbreviations
CWR
Independent Variables
Highschool Graduate Women
Illiterate Women
Non-agricultural Female
Labor Force Participation
Rate
Employment in Modern
Sectors of Economy
Rurality
Infant Mortality Rate
Census of Population 1975 and 2000, Social
and Economic Characteristics of Population,
Province Yearbooks of 1975 and 2000.
Census of Population 1975 and 2000, Social
and Economic Characteristics of Population,
Province Yearbooks of 1975 and 2000.
This variable is calulated according to
definition in Tansel (2002). The variables
found in numerator and denominator comes
from population censuses 1975 and 2000
Census of Population 1975 and 2000, Social
and Economic Characteristics of Population,
Province Yearbooks of 1975 and 2000.
Census of Population 1975 and 2000, Social
and Economic Characteristics of Population,
Province Yearbooks of 1975 and 2000.
The number of infants who die under 1 year
old per 1000 live born infants. İt has been
indirectly estimated
with Brass-Trussell method.
HSG_W
IL_W
FNALFP
EMS
RU
IMR
Public Libraries
State Institute of Statistics, Cultural
Statistics 2000, 1990, 1985, 1980 and 1975
PL
Gross Provincial Product of a
Province
For the years between 1975and 1985:
Karaca (2004)For the years 1990 and 2000:
Turkish Statistical Institute web site
http://www.turkstat.gov.tr/VeriBilgi.do?tb_i
d=56&ust_id=16
GPP
50
Alper AVSAR
51