Spatial Income Inequality in Turkey and the Impact of Internal Migration

Spatial Income Inequality in Turkey

and the Impact of Internal Migration

Süleyman Özmucur*

and

Jacques Silber**

* The University of Pennsylvania.

** Department of Economics, Bar-Ilan University, Ramat-Gan 52900,Israel.

April 2002

Not to be quoted without the authors’ permission I. Introduction:

Almost fifty years ago, in his Presidential Address to the American Economic

Association, Kuznets (1955) suggested that income inequality was generally rising in the early stages of economic development but declining in the latter phases of the development process. In Kuznets’ words: “One might thus assume a long swing in the inequality characterizing the secular income structure; widening in the early phases of economic growth when the transition from the pre-industrial to the industrial civilization is more rapid; becoming stabilized for a while; and then narrowing in the latter phases.” (Kuznets, 1955, page 18). Such an inverted U relationship between inequality and development has since been known as the Kuznets Curve and has become one of the most famous hypotheses in economics. Kuznets (1955) had in fact centered his argument on the impact of rural to urban migration flows on the distribution of incomes during the development process, the idea being that “even if within-sector inequality is constant and the ratio of mean sectoral incomes is also constant, the shift of population between sectors at first produces a widening in inequality and then a narrowing" (Adelman and Robinson, 1989). Such a result was derived mathematically in subsequent work by Robinson (1976), Knight (1976),

Fields (1979) and Anand and Kanbur (1993).

Fields (1980) considerably extended this approach by making a distinction between a sector enlargement effect, a sector enrichment effect and an interaction terms and there have been numerous empirical investigations testing Kuznets' conjecture (see,

Fields, 2001, for a thorough survey of all these studies). Today the consensus seems to be that “the Kuznets curve is not a necessary feature in the data, nor even the best general description of changes over time….Other variables (than growth) also determine inequality. They include the basic nature of the economic system itself; the structure of output; the composition of exports; regional patterns; the structure of employment; the distribution of land and capital; the state of development of the capital market; the level and inequality in the distribution of human capital; and the distribution of social income.” (Fields, 2001, pages 69-70).

The present study is not another attempt to check the validity of Kuznets' thesis, though it emphasizes a central feature of his story: the internal migration from rural to urban areas. The main theme of this paper is different because its focus is on the impact of internal migration on spatial inequality. Another point to be stressed is that the empirical illustration presented here is based not on a cross-section of countries but on several income surveys that were conducted in Turkey, mainly on the 1987 and 1994 surveys.

Several studies have actually attempted to analyze changes in the distribution of income in Turkey that took place in recent years. An interesting survey of individual income distribution in Turkey is presented in Gürsel et al. (2000). Their study determines the exact impact of various income sources on overall income inequality, using Shorrocks (1982 and 1983) approach., examines the impact of various household characteristics on poverty levels and finally compares the results with those available for other EU countries. Selim and McKay (2000) propose a more detailed analysis of the relationship between households’ heads characteristics and poverty levels but their study is mainly descriptive. This is also generally the case of Özmucur and Silber’s (2000) study of inequality in Turkey in 1994. In this paper they attempted to determine the impact that various income sources (income from the primary job, from a secondary job and from other sources) and different population categories (Wage and Salary Earners, Daily Workers and Proprietors) in both urban and rural areas had on the overall level of income inequality in Turkey in 1994.

To understand the changes that occurred between 1987 and 1994 in the distribution of income in Turkey it is in fact necessary to remember what the macroeconomic environment was during this period. The 1980’s were a period of commodity trade liberalization where the output composition of the country was significantly modified.

This induced a reduction of the employment generation capacity of the Turkish economy and important income redistribution effects. Moreover between 1988 and

1994 the Turkish governments implemented expansionary macroeconomic policies financed largely through domestic borrowing at high interest rates and such policies evidently resulted in transferring incomes between groups. In fact populist policies and the consequent fiscal deficits of the 1990s resulted in the breakdown of the financial system in 1994. It should be clear that such important changes must have had also an impact on regional inequality.

As mentioned previously the main topic of this paper is to analyze the impact that internal migration in Turkey had on spatial inequality. Such an effect may be assumed to take place through various routes. First, because the types of employment and the relative importance of various income sources are not the same in rural and urban areas, internal migration affects inequality because it modifies the structure of the labor force and the composition of income. Second because the average size of households is smaller in urban than in rural areas, internal migration is likely to have an effect on the inequality of per capita or of standardized (per adult equivalent) income. Third internal migration modifies the relative importance of the various regions and this will also have an impact on spatial inequality. The paper is therefore organized as follows. Section II looks at the impact of migration on the composition of the labor force and of income and hence on inequality, both from a methodological (Section II-A) and an empirical point of view (Section II-B). In Section

III the focus is on the role of the size of the household and again there is first a methodological (III-A) and then an empirical (III-B) section. Section IV analyzes, in a similar way, changes over time in the weight of the different regions and their effect on spatial inequality. Short concluding comments are given in Section V. Finally in three

Appendices additional results are given (Appendix A), a survey of the macroeconomic environment in Turkey between 1960 and 2000 is presented (Appendix B) and more precise information on the data sources are provided (Appendix C).

II. Internal Migration and Income Inequality: An Analysis via the

Decomposition of Inequality by Income Source and Population Subgroups:

A) The Methodology:

1) The Decomposition of the Gini Index by Income Sources:

Following Silber's (1989) analysis of the decomposition of income inequality, it is possible to define the Gini Index IG of overall income inequality as:

IG = [e’] G [∑i=1 to I Sji ] (1) where e’ a 1 by n row vector of population shares all equal to (1/n), n being the number of individuals in the population, I the number of income sources, Sji the n by 1 column vector of the share of the amount of money received by individual j from income source i in the total income of the population and G is a n by n matrix, called the G-matrix (see,

Silber 1989), whose typical element ghk is equal to 0 if h=k, to –1 if k >h and to +1 if h

>k. Note that in the vector Sji the elements are ranked by decreasing values of the total income of the individuals. Let Xji be the vector of the shares (Sji /∑j=1 to n Sji ), ranked by decreasing values of the total income of the individuals. The product Hi=[e’]G[Xji ] is then called the Pseudo-Gini of income source i. However if we call Vji the vector of the shares (Sji / ∑j=1 to n Sji ) ranked by decreasing values of the incomes received by the individuals from source i, the product Gi = [e’] G [Vji ] is in fact the Gini index of inequality of income source i (see, Silber, 1989, for more details).

Let S.i represent the share of income source i in the total income of the population. We may then express (see, Silber, 1989) the Gini index IG as

IG = ∑i S.i { [ e’] G [ Sji ] } = ∑i Si Hi = ∑i Ci (2)

where Ci represents the contribution of income source i to the overall inequality.

2) The Breakdown of the Gini Index by Population Subgroups:

Following earlier studies (see, Bhattacharya and Mahalanobis, 1967, Rao, 1969, Fei,

Ranis and Kuo, 1979, Kakwani, 1980, Lerman and Yitzhaki, 1984), Silber (1989) has proven, using the approach based on the G-matrix which was just summarized, that when the population is divided in subgroups, the Gini index may be decomposed into three elements:

- a within populations contribution IW

- a between populations inequality IB

- an interaction or overlap component IO

More precisely if Pa and Wa are the shares in total population and in total income of area a and if Ia refers to the Gini index for area a, Silber (1989) has proven that:

IW = ∑a=1 to A Pa Wa Ia (3) where A is the number of areas distinguished. It can also be shown that:

IB = [...Pa ...] G [...Wa ...] (4) where the elements in the row vector [...Pa...] and in the column vector [...Wa ...] are ranked by decreasing average income (that is by decreasing ratios Wa /Pa ) and G is an

A by A G-matrix. Finally, the overlap component IO is defined as

IO = IG - (IW + IB ) (5) where IG refers to the Gini index for the country as a whole.

3) Combining the Decomposition by Income Source and by Population

Subgroups:

Let the subindices a=1 and a=2 refer respectively to the urban and rural components in the decomposition of inequality by population subgroups. One may then decompose Ia in (3) by income source (using equations (1) and (2) ) so that the within areas inequality IW will be written as

IW = ∑a=1 to A Pa Wa [ ∑i=1 to A Cia ] (6)

⇔ IW = ∑i=1 to I CWi (7) where

Cwi = ∑a=1 to A Pa Wa Cia (8) refers to the contribution of income source i to the overall within income inequality while Cia measures the contribution of source i to the overall income inequality in area a and is defined on the basis of equation (2).

For the between areas inequality, one may proceed as follows. Let Tia refer to the total income from source i in area a. The share Wa in (6) may then be expressed as:

Wa = ∑i=1 to I ( Tia / ∑a=1 to A Tia ) ( ∑a=1 to A Tia / ∑i=1 to I ∑a=1 to A Tia ) (9)

Combining (4) and (9) one derives, in the simple case where two areas only are distinguished (rural versus urban areas), that

IB = [ PU PR ] G [ (∑i=1 to I TiU /T.. ) (∑i=1 to I TiR /T..)] (10) where the subindexes U and R refer respectively to urban and rural areas (assuming the average income is higher in urban areas) and T.. is equal to ∑i=1 to I ∑a=1 to 2 Tia .

When the definition of the G-matrix is applied to (10) one concludes, after some algebraic manipulations, that

IB = - PU ∑i=1 to I (TiR /T..) + PR ∑i=1 to I (TiU /T..) (11)

IB = ∑i=1 to I Cbi (12) where

CBi = ((PR TiU - PU TiR )/T..) (13) refers to the contribution of income source i to the between areas inequality IB .

Finally recalling that Ci in (2) refers to the contribution of income source i to income inequality for the country as a whole, one may define Coi , the contribution of income source i to the overlap component IO in (5) as

COi = Ci - ( CWi + CBi ) (14 ) and conclude, using (2), (8), (13) and (14) that

IG = ∑i=1 to I ( CWi + CBi + COi ) (15)

B) An Empirical Illustration: Turkey in 1994

1) Basic Data on the Distribution of Incomes in Urban and Rural Areas in Turkey in 1994:

In 1987 47.4% of the Turkish population lived in urban and 52.6% in rural areas (see,

Özmucur and Silber, 1995, mimeo). Seven years later the proportions are completely different since 58% of the population lived then in urban and 42% in rural areas. More details on the breakdown of the total population by area of residence (urban versus rural areas) and population subcategory (three categories being distinguished: Wage and

Salary Earners, Daily Workers and Proprietors) are given in Table 1. These data (lower section of Table 1) indicate that three quarters of the Wage and Salary

Earners live, as expected, in urban areas, the corresponding proportion for Daily

Workers being two thirds. For Proprietors the opposite is true since almost two thirds of them live in rural areas. If we now look (upper section of Table 1) at the composition of the population within urban or rural areas, it appears that Wage and Salary Earners represent 56% of the population living in urban areas, the corresponding share being only 24% in rural areas. The same contrast exists for Daily Workers who represent 66% of the urban population but only 34% of the rural population. On the contrary the shares of Proprietors in the total population are 63% in rural but only 37% in urban areas.

Table 1: Shares in Total Population of Various Categories

Category Urban Areas Rural Areas Whole Country

Wage and Salary 0.563 0.241

Earners

Daily Workers 0.164 0.116

Proprietors 0.277 0.643

Together 1.000 1.000

Wage and Salary 0.763 0.237 1.000

Earners

Daily Workers 0.662 0.338 1.000

Proprietors 0.369 0.631 1.000

Together 0.580 0.420 1.000

Important differences between urban and rural areas exist also when one compares the averages incomes of the population categories which have been distinguished. These data are given in Table 2. Here an additional distinction has been introduced in so far as information is also available on the type of income (Income from primary job, from secondary job or from other sources) earned by the individuals.

Table 2 indicates clearly that, whatever the subpopulation category considered, the average income is higher in urban than in rural areas. For Wage and Salary Earners the difference is of 17% ((0.81-0.69)/0.69), for Daily Workers it reaches 41%. The differences are even more striking concerning Proprietors since the latter in urban areas earn 137% more than in rural areas. On average for all categories combined the differential is equal to 40%.

The relative importance of the various income sources is summarized in Table 3.There appears to be significant differences between the various categories. In urban areas income received from the primary job represents on average 78% of the total income while the corresponding figure in rural areas is 85%. On the contrary income from other sources represents 18% of total income in urban areas but only 8% in rural areas. If we now look at specific categories one observes that the weight of income from primary job is highest among daily workers (91%) in urban areas and lowest among Proprietors in urban areas. Note that income from secondary job represents almost 10% of total income among Wage and Salary Earners and 7.5% among daily workers in rural areas. Income from secondary job is much less important in urban areas. Finally other income sources play an important role mainly among Proprietors in urban areas (it corresponds to almost

24% of their total income) and eventually also among Wage and Salary Earners in urban areas (a share of 12.7%). These differences in average income, together with those observed in Table 1 concerning the relative importance in the total population of the various subpopulations, have evidently an impact on the share in total income of the various categories. Table 4 summarizes the results.

If one first looks at the relative share of the different population categories in total income the differences between urban and rural areas is striking. It appears that in urban areas 54% of the total income is received by Proprietors while the share of

Wage and Salary Earners is only equal to 40%. In rural areas the share of Proprietors reaches 75% while that of Wage and Salary Earners is only equal to 21%. Note the small share of Daily Workers both in urban (6%) and rural (4%) areas.

If we now analyze, for each category, the relative importance of urban and rural areas

(see the lower part of Table 4) one observes that 79% of the income received by wage and Salary Earners is earned in urban areas, the corresponding share for Daily

Workers being 73%. On the contrary only 58% of the income received by proprietors originates in urban areas.

Table 2: Relative* Income by Income Source and Population Subgroup

Population All income Income from Other Income Category sources Primary and Sources combined Secondary Job

URBAN AREAS Wage and 0.81 0.83 0.69 Salary Earners Daily 0.42 0.46 0.19 Workers Proprietors 2.25 2.02 3.58 Together 1.14 1.09 1.40 RURAL AREAS Wage and 0.69 0.74 0.43 Salary earners

Daily 0.30 0.32 0.14 Workers Proprietors 0.95 1.02 0.52 Together 0.81 0.87 0.45 URBAN and RURAL AREAS combined Wage and 0.78 0.81 0.63 Salary Earners Daily 0.38 0.41 0.18 Workers Proprietors 1.43 1.39 1.65 Together 1.00 1.00 1.00

* “Relative” means “relative to national average”, for a given income source, as indicated in the table itself (the last row is equal to 1).

Table 3: Income Shares by Income Sources and Population Category

Population Income from Income from Income from Total Category Primary Job Secondary Other Sources Job URBAN AREAS Wage and 0.835 0.038 0.127 1.000 Salary Earners Daily 0.911 0.020 0.069 1.000 Workers

Proprietors 0.731 0.033 0.236 1.000 Together 0.783 0.035 0.182 1.000 RURAL AREAS Wage and 0.809 0.099 0.091 1.000 Salary Earners Daily 0.854 0.075 0.071 1.000 Workers Proprietors 0.857 0.06 0.081 1.000 Together 0.847 0.070 0.083 1.000 URBAN and RURAL AREAS together Wage and 0.830 0.051 0.119 1.000 Salary Earners Daily 0.896 0.035 0.070 1.000 Workers Proprietors 0.784 0.045 0.171 1.000 Together 0.805 0.047 0.148 1.000

Table 4: Share in Total Income of Various Categories

Category Urban Areas Rural Areas Whole Country

Wage and Salary 0.401 0.206

Earners

Daily Workers 0.060 0.042

Proprietors 0.539 0.751

Together 1.000 1.000

Wage and Salary 0.790 0.210 1.000

Earners

Daily Workers 0.734 0.266 1.000

Proprietors 0.581 0.419 1.000

Together 0.659 0.341 1.000

So far we have only taken a look at the average income earned by the different population categories. A more complete view of income distribution in Turkey requires evidently that one analyzes also the distribution of incomes separately for each population category. Such an issue becomes even more important once one recalls the observation made earlier concerning the intensity of the migration flows (from rural to urban areas) which have taken place in Turkey during the period 1987-1994. To measure the degree of inequality of the income distributions considered we have used the Gini

Index and applied the methodology presented in Section II-A.

2) Decomposing the overall income inequality in Turkey in 1994:

The results of this breakdown are presented in Tables 5 to 7.

Table 5 gives the contribution of each income source to the Gini index of each population subcategory. For both urban and rural areas and for each category the greatest contribution to the Gini index is, as expected, that of the primary income. Its relative contribution is however generally higher in rural than in urban areas. For example for Proprietors, the most important category in rural areas, the contribution of primary income to the Gini index of total income among proprietors in rural areas is equal to 88% while for Wage and Salary Earners, the most important category in urban areas, 75% of the Gini index of total income is explained by primary income.

In Table 6 the contribution of each income source to the three components of inequality (between groups, within groups and overlap) is given separately for urban and rural areas.

16 Table 5: Decomposition of Within Groups Inequality by Income Source For Each Population Subcategory

Population Total Income from Income from Other Income Subcategory Inequality Primary Job Secondary Sources (Gini Index) Job

URBAN AREAS Wage and 0.102 0.077 0.007 0.018 Salary Earners Daily 0.004 0.003 0.000 0.001 Workers Proprietors 0.088 0.059 0.003 0.026 All categories 0.194 0.139 0.010 0.045 combined RURAL AREAS Wage and 0.020 0.014 0.003 0.003 Salary Earners Daily 0.002 0.002 0.000 0.000 Workers Proprietors 0.217 0.192 0.013 0.012 All categories 0.239 0.208 0.016 0.015 combined

17 Concerning urban areas one may first note that if the highest contribution to both the between and the within groups inequality is that of primary income, this income source plays, both in absolute and relative terms, a greater role for the between groups inequality (84% of the total between categories inequality) than for the within groups inequality (72% ). In rural areas the situation is reversed. There the contribution of primary income is higher, both in absolute and relative terms, for the within than for the between groups inequality. In the former case its contribution represents 87% of the inequality, in the latter case 76%. The other income sources play a relatively minor role, except in the case of within groups inequality in urban areas since in that case their share in inequality is equal to 23% (.045/.194).

Table 7 summarizes all the previous results since it presents the breakdown of the overall inequality in Turkey in 1994 by type of inequality, by area of residence and by income source

It appears that inequality within categories (the latter referring to the three types of workers: Wage and Salary Earners, Daily Workers and Proprietors) is much more important, for Turkey as a whole, than the between categories inequality and that 77%

(.223/.289) of this within groups inequality is contributed by urban areas. Remember that the share of these areas in the total population is only 58% (see, Table 2) whereas that in total income is only 66% (see, Table 4). One may also observe that the overlap component (.178) for Turkey as a whole is much more important than the between groups inequality, the latter referring here to urban versus rural areas, all categories

(that is all types of workers) combined. In other words there is an important dispersion of income within urban and within rural areas so that the two distributions largely overlap. The results concerning the within groups inequality are very similar to those presented in table 6, the only difference being that the data of Table 6 have been

18 multiplied by the product of the shares of urban (rural) areas in the total population and in total income.1

1 e.g. .223, on the first line of table 10, is simply the product of .583 which appears on the first line of Table 9, by .58, the share of urban areas in the total population and by .66, the share of urban areas in total income.

Table 6: Decomposition of Total Inequality by Income Source separately for Urban and Rural Areas.

Population Contribution Income from Income from Other Income Category and to Inequality Primary Job Secondary Sources Type of Job Inequality URBAN AREAS Overall Gini 0.583 Index Between 0.299 0.251 0.012 0.035 Categories Inequality (Gini Index) Within 0.194 0.139 0.010 0.045 Categories Inequality (Gini Index) Measure of 0.090 Overlap RURAL AREAS Overall Gini 0.464 Index Between 0.123 0.093 0.017 0.013 Categories Inequality (Gini Index) Within 0.239 0.208 0.016 0.015 Categories Inequality (Gini Index) Measure of 0.103 Overlap

20 Table 7: Decomposition of Overall Income Inequality in Turkey (1994) by Population Subcategory and Income Sources

Overall Contribution of Contribution Contribution of Other Contribution Primary Job of Secondary Income Sources Job

Inequality 0.079 Between Urban and Rural Areas

Within 0.289 Urban and Rural Inequality Contribution 0.223 of Urban Areas Between 0.114 0.096 0.005 0.013 Workers categories Inequality

21 Table 7 (cont.)

Overall Contribution of Contribution Contribution of Other Contribution Primary Job of Secondary Income Sources Job Within 0.074 0.053 0.004 0.17 Workers categories Inequality Wage and 0.039 0.029 0.003 0.007 Salary Earners

Daily 0.001 0.001 0.000 0.000 Workers Proprietors 0.034 0.023 0.001 0.010 Overlap 0.034 Contribution 0.066 of Rural Areas Between 0.018 0.013 0.002 0.002 Workers categories Inequality

22 Table 7 (end)

Overall Contribution of Contribution Contribution of Other Contribution Primary Job of Secondary Income Sources Job Within 0.034 0.030 0.002 0.002 Workers categories Inequality Wage and 0.003 0.002 0.0005 0.0005 Salary Earners Daily 0.000 0.000 0.000 0.000 Workers Proprietors 0.031 0.027 0.002 0.002 Overlap 0.015 Overlap 0.178 between Urban and Rural Areas Total 0.546 Inequality for Turkey (Gini Index)

23 III) Internal Migration and the Impact of Changes in Household Size on Income

Inequality:

A) The Methodology:

1) A Simple Formulation for the Decomposition of Income Inequality by

Population Subgroups:

Using concepts defined previously let GTOT, GBET, GWITH and GOVERL refer respectively to the overall value of the Gini Index of income inequality in a given country, to the between regions inequality in this country, to the within regions income inequality and finally to the residual term of the decomposition of overall inequality which measures in fact the degree of overlap between the income distributions of the urban and rural areas. We may then write (see, Silber, 1989, and

Deustch and Silber, 1999) that

GTOT = GBET + GWITH + GOVERL (16)

The within areas inequality GWITH may be expressed (see, expression (6) and for more details, Silber, 1989) as

GWITH = ∑r=1 to R pr sr Gr (17) where pr refers to the population share of region r, sr to the share of region r in the total income of the country, Gr to the Gini index of income inequality within region r while R represents the total number of regions in the country. Let us call respectively ym and ymr the average incomes in the whole country and in region r.

Since sr may be also expressed as sr = pr (ymr/ym) (18) we may also write (17) as

2 GWITH = ∑r=1 to R (pr) (ymr/ym) Gr (19)

24 We have therefore expressed the within areas inequality index GWITH as a function of only three sets of variables: the shares of the various regions in the total population of the country, the ratios of the average incomes in the various regions over the average income in the whole country and the within regions Gini indices.

We will now show that is possible to express the between areas inequality index GBET as a function of only two sets of variables: the shares of the various regions in the total population and the ratios of the average incomes in the various regions over the average income in the whole country.

It may in fact be shown (see, Silber, 1989) that if [pr ] represents the row vector of the population shares of the various regions while [sr ]’ refers to the column vector of the shares of the various regions in the total income of the country, the regions in both vectors being ranked by decreasing values of the regional average incomes, the between areas Gini inequality index GBET may be expressed (cf., expression (10) in

Section II-A-3) as:

GBET = [ pr] G [ sr]’ (20) where G is the G-matrix which was defined previously.

Combining then (18) and (20) one derives that

GBET = [ pr] G [ pr (yr / ym )]’ (21) where as before the elements of the row vector [pr ] and of the column vector

[ pr (yr / ym )]’ are ranked by decreasing values of the regional incomes yr .

2) Measuring the Respective Impacts of Income and Size of the Household on

Inequality Differences:

In the previous section no attention was given to two important questions:

25 - on which measure of the welfare of the household members should the

inequality analysis or comparison be based?

- which are the units (households, individuals) whose distribution of welfare we

want to analyze?

These issues have been analyzed in Danziger and Taussig (197?) and we summarize here the main ideas. a) Measuring the welfare of household members:

The main question here is in fact to determine which part of the goods and services consumed by the household should be considered as purely private goods (whose consumption cannot be shared, e.g. food) and which part as public goods (e.g. a refrigerator). Buhman et al. (197?) proposed a nice formulation to tackle this problem by expressing the welfare xi of household members as

a xi = yi / (ni ) (22) where yi is the total income of the household, ni is the size of the household and a is a parameter included in the interval [0,1]. It may be observed that if a = 0, the welfare of the household members is equal to the total household income, so that it is then assumed that all goods and services are considered as public goods. On the contrary when a = 1, the welfare indicator is equal to the per capita income, in which case one supposes that all goods and services are private. A more general case occurs when

It is also possible to make a difference between adults and children and write (cf.,

Coulter et al., (19??) ) that ni = ai + λ ci (23)

26 where ai is the number of adults in the household and ci is the number of children, while λ is a parameter indicating how the consumption of a children should be converted into an adult’s consumption. b) The selection of the unit whose welfare distribution is analyzed:

This question is different from the previous one. Whatever measure of welfare is analyzed, we may ask whether we want to look at the inequality between households or between individuals. Given that four measures of welfare and two units of observation (individuals or households), we will hence have eight different ways of measuring inequality.

To measure inequality we use the algorithm based on the G-matrix (see expressions

(1) or (4) ) and express the Gini index of inequality Gr within a given region r as

Gr = [e’] G [s] (24) where e’ is a row vector of the shares in the total population of the different subgroups distinguished (these subgroups may for example be the deciles of the total population in region r), G the G-matrix defined earlier and s a column vector of the shares of the different subgroups in total income, the elements of e’ and s being ranked by decreasing values of the average income of each subgroup.

Calling respectively hi and ni the number of households and individuals in subgroup i and yi the average household income in this subgroup, we summarize in Table 8 the way expression (24) will be expressed in the eight cases distinguished. c) Analyzing the respective impacts of household income and size on inequality comparisons:

Let us for example compare the value of the between households Gini index of income per equivalent adult in two regions. Table 8 indicates that for region r this index may be expressed as

27 0.5 0.5 Gr = [hi /∑ihi]’G[(yi /(ni) )hi /∑i[(yi/(ni) )hi ] (25)

Assuming that the data are given by decile so that (hi /∑ihi) = 0.1 for every i, we may write that Gr as a function f (yir,nir ) where the subscript r indicates to which region the function r refers. The difference ∆G between the values of the Gini index in two regions r and s may therefore be expressed as

∆G = f (yir,nir ) - f (yis,nis ) = 0.5(C1 + C2 ) + 0.5(C3 + C4 ) (26) where

C1 = f (yir,nir ) - f (yir,nis ) (27)

C2 = f (yis,nir ) - f (yis,nis ) (28)

C3 = f (yir,nir ) - f (yis,nir ) (29)

C4 = f (yir,nis ) - f (yis,nis ) (30)

It is easy to show that the expressions 0.5(C1 + C2 ) and 0.5(C3 + C4 ) measure respectively the impact of differences between regions r and s in the sizes of the households and in total

28 Table 8: Various ways of expressing the Gini index.

Welfare Inequality between households Inequality between individuals

Indicator

Total [hi /∑i hi ]’ G [yi /∑I yi ] [ni /∑i ni ]’ G [yi /∑i yi ] household income

Per capita [hi /∑i hi ]’ G [(yi /ni)hi /∑i (yi [ni /∑i ni ]’ G [(yi /ni)ni /∑i (yi /ni)ni] income /ni)hi]

0.5 0.5 Income per [hi /∑ihi]’G[(yi /(ni) )hi [ni /∑ini]’G[(yi /(ni) )ni

0.5 0.5 equivalent /∑i[(yi/(ni) )hi ] /∑i[(yi/(ni) )ni ] adult

0.5 0.5 Alternative [hi/∑ihi]’G[(yi/(ai+0.5ci) )hi [ni/∑ini]’G[(yi/(ai+0.5ci) )ni

0.5 0.5 formulation /∑i[(yi /(ai+0.5ci) )hi] /∑i[(yi /(ai+0.5ci) )ni] of the income per equivalent adult

household income. A similar decomposition may be obtained when the alternative definition of income per equivalent adult is used.

In the case where one measures inequality between individuals expression (24) will be expressed as

0.5 0.5 Gr = [ni /∑ini]’G[(Yi /(ni) )ni /∑i[(Yi/(ni) )ni ] (31) where Yi is the total income of all households belonging to subgroup i (e.g. deciles of households).

0.5 The ratio (Yi /(ni) ) may be also expressed as

0.5 0.5 (Yi /(ni) ) = (Yi /hi) / ((ni) / hi) = (zi / ei ) (32) where zi and ei measure respectively the per household income and the number of equivalent adults per household.

The difference ∆G between the values of the Gini index in two regions r and s may therefore be expressed in this case as

∆G = f (zir, eir, nir ) - f (zis, eis, nis ) (33)

Using decomposition techniques quite similar to those given in expressions (27) to

(30) but applied to the case where we have three explanatory variables (zi, ei, and ni ), it is possible to measure the respective impacts on this gap ∆G of differences between the subgroups (e.g. household deciles) in the total number of individuals (role of differences in ni ), in the total household incomes (role of zi) and in the size of the households (differences in ei).

B) An Empirical Illustration: Spatial Inequality in Turkey in 1994:

1) Differences between urban and rural areas:

30 The results of this analysis are reported in Tables 9 to 12. Table 9 indicates that the average income, whether of households or of individuals, in urban areas is about 25% higher that in Turkey as a whole while in rural areas it is about 70% lower. Table 10 then indicates that, whatever concept of inequality one uses, inequality is much higher in urban than in rural areas. If one decomposes the overall inequality in Turkey into between areas (urban and rural), within areas and an overlapping component, Table

11 shows that close to 50% of the overall inequality2 is attributed to within areas inequality, the between areas inequality accounting for 34 to 37% and the overlapping component for 16 to 18% of the overall inequality.

Note also (see, Table 10) that the difference between the two areas in within areas inequality is highest when per capita income is the measure of welfare chosen and lowest when total household income is used, this being true for both inequality between households and between individuals.

In Table 12 we have decomposed the difference between the inequality of per capita or per equivalent adult income in urban and rural areas into two components (see, the methodology exposed in section III-A-2-c) measuring respectively differences between the two areas in total household income and in the average size of the households. It appears that the latter component (role of he household size) explains approximately 60% of the difference while the former component (role of total household income) accounts for the remaining 40%.

The important role played by differences in the size of the household appears clearly in Table 9 which shows that not only the average size of the household is smaller in urban areas but also its standard deviation and th coefficient of variation of the size of the households. Moreover the data indicate clearly that the average size of the

2 Note that the overall inequality levels in this section are smaller than those found in Section II because we use quintiles while in Section II more detailed data were available (by population

31 household, in both urban and rural areas increases with the average income, whether of households or of individuals.

Remembering that our analysis is based on date collected for quintiles, we have computed also the ratio of the average size of the households in the richest over that in the poorest quintile. This ratio turns out to be equal to 1.12 in urban areas and to 1.56 in rural areas. We have similarly computed the ratio of the average total household income in the richest over that in the poorest quintile and found that this ratio was equal to 11.8 in urban and 8.6 in rural areas. Combining these two types of results on derives that the ratio of the per capita income in the richest over that in the poorest quintile is equl to 10.3 in urban and 5.5 in rural areas.

What these data imply is that migration from rural to urban areas induces an increase in the inequality of per capita income (whether one talks about inequality between households or between individuals) not only because the inequality of total household incomes is higher in urban areas but probably also because that of household size is higher in rural areas.

2) Regional Differences:

The results of this analysis are presented in Tables 13 to 16. Table 13 indicates that, whether for household or per capita income, the average income is highest in

Marmara and the region of the Aegean Sea and lowest in Eastern and Souther

Anatolia (see, in Table 13, the data on the relative income of the various regions, the comparison being made with Turkey as a whole). Table 14 then shows that the within region inequality is highest for total household income and lowest for per capita income, this being true whether one looks at the between households or the between individuals inequality.The data of table 14 indicate also clearly, that, whatever

subcategories, income source, etc…).

32 concepts of inequality are used, the within region inequality is highest in the three richest regions (Marmara, Aegean Sea and the Mediterranean region) and lowest in the two poorest regions (Eastern and Southern Anatolia). Note also that the greatest difference between the regions is observed when per capita income is the measure of welfare used and the smalles one when total household income is used, this result being similar to the one we observed when comparing urban and rural areas.

A look at Table 15 shows that when regions are compared the between regions inequality is much higher than the within regions inequality, whatever measure of welfare is used and whether one looks at inequality between households or individuals. In fact 40 to 60% of the overall inequality is explained by between regions and only 15 to 18% by within regions differences.

In table 16, we have decomposed the difference between inequality within a given region and that in Turkey as a whole into three components (see, the methodology presented in section III-A-2-c). The first component is due to differences between the quintiles in population shares (this is a consequence of the fact that whereas the share of the households in each quintile is by definition equal to 20%, that of individuals is not necessariy equal to 20%). The second component reflects differences between the quintiles in total household income while the third element is a consequence of differences in the size of the households. It appears that in the poor regions (Eastern and Southern Anatolia) the component reflecting differences in total household income accounts for 80 to 90% of the total gap while that due to differences in household size explains 10 to 20%. In rich areas (Marmara and Aegean Sea) the results are not clear, total household income contributing to even more than 100% of the overall difference in Marmara but to only 60$ in the Aegean Sea area.

33 As far as the size of the households is concerned it appears (see, Table 12) that first this average size is much higher in poor regions (the average being there equal to 5.5 to 5.7 individuals) than in rich regions (average varying from 3.85 to 4.12). Similarly the standard deviation of household size is lower in rich than in poor regions but the results for the coefficient of variation of household size are not clear.

When comparing household size with relative (to Turkey as a whole) total household income or per capita income in the various regions we find a negative correlation between average household size and total household income (correlation: -0.61) or per capita income (correlation: -0.77). A similar analysis shows a negative correlation between the standard deviation of household size and relative total household income

(correlation:-0.48) or per capita income (correlation:-0.55).

The results of this regional analysis are thus quite similar to those derived in the urban versus rural areas comparison, though sometimes less clear-cut conclusions may be derived because some of the regions are not specifically urban or rural areas. But as a whole they seem to confirm the important role played by internal migration which affects inequality both through its impact on the inequality of total household incomes and on the size of the households.

34 Table 9: Summary Data for the Urban and Rural Areas

Table 10: Summary Data on Within Areas Inequality

Table 11: Summary Table of Decomposition of Inequality for Urban and Rural Areas

Concept of Total Between Within Overlap Share of Share of Share of Inequality and (Whole Areas Areas Between Within Overlap Measure of Country) Inequality Inequality Areas Areas in Total Welfare of Inequality Inequality Inequality Inequality Household in Total in Total Inequality Inequality INEQUALITY BETWEEN HOUSEHOLDS Inequality of 0.479 0.178 0.229 0.072 0.37 0.48 0.15 Household Income Inequality of 0.443 0.149 0.216 0.078 0.34 0.49 0.18 Per Capita Income Inequality of 0.462 0.164 0.223 0.075 0.35 0.48 0.16 Per Equivalent Adult Income Inequality of 0.458 0.163 0.221 0.074 0.36 0.48 0.16 Alternative Measure of Per Equivalent Adult Income

36 Concept of Total Between Within Overlap Share of Share of Share of Inequality and (Whole Areas Areas Between Within Overlap Measure of Country) Inequality Inequality Areas Areas in Total Welfare of Inequality Inequality Inequality Inequality Household in Total in Total Inequality Inequality INEQUALITY BETWEEN INDIVIDUALS Inequality of 0.467 0.183 0.220 0.064 0.39 0.47 0.14 Household Income Inequality of 0.433 0.153 0.207 0.073 0.35 0.48 0.17 Per Capita Income Inequality of 0.450 0.168 0.214 0.068 0.37 0.48 0.15 Per Equivalent Adult Income Inequality of 0.446 0.167 0.212 0.067 0.37 0.48 0.15 Alternative Measure of Per Equivalent Adult Income

37 Table 12: Decomposition of the Difference* in Inequality between Urban and Rural Areas

Areas Inequality Inequality Inequality Inequality Inequality Inequality Inequality Between Between Between Between Between Between Between Households Households Households Individuals Individuals Individuals Individuals Total Gap due to Gap due to Total Gap due to Gap due to Gap due to Difference difference differences Difference difference difference differences between in in size of between in Shares in in size of Urban and household households Urban and household households Rural incomes Rural incomes Areas Areas Comparison of +0.122 +0.076 +0.046 +0.126 +0.004 +0.078 +0.044 Urban and (0.097) (+0.075) (+0.022) (+0.104) (+0.006) (+0.077) (+0.021) Rural Areas

• The number not in parenthesis refer to the case where the welfare of the household (individual) is measured by the per capita income while that in parenthesis corresponds to the case where this welfare is assumed to be equal to the per equivalent adult income. The component “population shares “ which appears in the case where one measures inequality between individuals is due to the fact that the data were given for deciles of the household population, not of the population of individuals.

Table 13: Summary Data for the Regions in 1994

Region Share in Share in Share Average Standard Coefficient Relative Relative Total Total in Size of Deviation of Income of Income of Number of Number of Total Household of Size of Variation Household Individuals Households Individuals Income Household of Size of Household Marmara .266 .247 .386 4.12 0.36 0.088 1.45 1.56 Aegean .157 .136 .139 3.85 0.52 0.136 0.89 1.02 Mediterranean .125 .127 .111 4.54 0.31 0.068 0.88 0.87 Central .179 .172 .154 4.27 0.44 0.102 0.86 0.90 Anatolia Black Sea .128 .135 .109 4.68 0.43 0.093 0.85 0.81 Eastern .071 .088 .057 5.51 0.75 0.136 0.80 0.65 Anatolia Southern .074 .096 .045 5.72 0.56 0.098 0.61 0.47 Anatolia

Table 14: Summary Data on Within Regions Inequality in 1994

Region Between Between Between Between Between Between Between Between Households- Households- Households- Households- Individuals- Individuals- Individuals- Individuals- Per Per Capita Per Alternative Per Per Capita Per Alternative Household Income Equivalent Per Household Income Equivalent Per Income Adult Equivalent Income Adult Equivalent Income Income Income Income Marmara 0.490 0.460 0.475 0.472 0.482 0.454 0.468 0.466 Aegean 0.401 0.347 0.375 0.373 0.388 0.340 0.365 0.363 Mediterranean 0.423 0.399 0.411 0.407 0.417 0.395 0.406 0.402 Central 0.412 0.380 0.397 0.394 0.400 0.372 0.386 0.384 Anatolia Black Sea 0.414 0.376 0.395 0.394 0.405 0.370 0.388 0.387 Eastern 0.342 0.279 0.311 0.309 0.329 0.271 0.301 0.299 Anatolia Southern 0.351 0.306 0.329 0.325 0.345 0.304 0.325 0.321 Anatolia Turkey as a 0.442 0.414 0.428 0.425 0.434 0.408 0.421 0.418 whole

Table 15: Summary Table of Decomposition of Inequality

Concept of Total Between Within Overlap Share of Share of Share Inequality and (Whole Regions Regions Between Within of Measure of Country) Inequality Inequality Regions Regions Overlap Welfare of Inequality Inequality Inequality in Total Household in Total in Total Inequality Inequality Inequality INEQUALITY BETWEEN HOUSEHOLDS Inequality of 0.549 0.339 0.085 0.125 0.62 0.15 0.23 Household Income Inequality of Per 0.442 0.182 0.0078 0.182 0.41 0.18 0.41 Capita Income Inequality of Per 0.494 0.261 0.081 0.152 0.53 0.16 0.31 Equivalent Adult Income Inequality of 0.490 0.259 0.081 0.150 0.53 0.17 0.31 Alternative Measure of Per Equivalent Adult Income

41 Concept of Total Between Within Overlap Share of Share of Share Inequality and (Whole Regions Regions Between Within of Measure of Country) Inequality Inequality Regions Regions Overlap Welfare of Inequality Inequality Inequality in Total Household in Total in Total Inequality Inequality Inequality INEQUALITY BETWEEN INDIVIDUALS Inequality of 0.548 0.352 0.079 0.117 0.64 0.14 0.21 Household Income Inequality of Per 0.439 0.191 0.073 0.175 0.44 0.17 0.40 Capita Income Inequality of Per 0.493 0.273 0.076 0.144 0.55 0.15 0.29 Equivalent Adult Income Inequality of 0.488 0.269 0.076 0.143 0.55 0.16 0.29 Alternative Measure of Per Equivalent Adult Income

Table 16: Decomposition of the Difference* in Inequality between Turkey as a Whole and the Various Regions

Region Inequality Inequality Inequality Inequality Inequality Inequality Inequality Between Between Between Between Between Between Between Households Households Households Individuals Individuals Individuals Individuals Total Gap due to Gap due to Total Gap due to Gap due to Gap due to Difference difference differences Difference difference difference differences between in in size of between in Shares in in size of Turkey household households Turkey household households and the incomes and the incomes Region Region Marmara -0.046 -0.050 +0.004 -0.046 0 -0.051 +0.004 (0.047) (-0.049) (+0.002) (-0.048) (0) (-0.050) (+0.002) Aegean +0.067 +0.042 +0.024 +0.068 +0.003 +0.043 +0.022 (+0.053) (+0.041) (+0.011) (+0.057) (+0.004) (+0.042) (+0.011) Mediterranean +0.015 +0.019 -0.004 +0.013 -0.001 +0.019 -0.004 (+0.017) (+.019) (-0.002) (+0.015) (-0.002) (+0.018) (-0.002) Central +0.034 +0.030 +0.004 +0.037 +0.002 +.0032 +0.003 Anatolia (+0.031) (+0.030) (+0.002) (+0.035) (+0.002) (+0.031) (+0.001) Black Sea +0.033 +0.029 +0.005 +0.038 0 +0.029 +0.009 (+0.033) (+0.029) (+0.004) (+0.033) (0) (+0.029) (+0.004) Eastern +0.135 +0.104 +0.031 +0.137 +0.002 +0.105 +0.030 Anatolia (+0.117) (+0.l02) (+0.015) (+0.120) (+0.003) (+0.103) (+0.014) Southern +0.108 +0.097 +0.010 +0.104 0 +0.094 +0.010 Anatolia (+0.099) (+0.094) (+0.005) (+0.096) (0) (+0.091) (+0.005) • The number not in parenthesis refer to the case where the welfare of the household (individual) is measured by the per capita income while that in parenthesis corresponds to the case where this welfare is assumed to be equal to the per equivalent adult income. The component “population shares “ which appears in the case where one measures inequality between individuals is due to the fact that the data were given for deciles of the household population, not of the population of

43 IV) Analyzing the changes over time in regional inequality:

A) Decomposing the Change Over Time in the Gini Index:

Let the subscripts 0 and 1 refer respectively to times 0 and 1. Using (4) it may easily

3 be shown that the change ∆GWITH in the within areas inequality index GWITH may be expressed as

∆GWITH = A + B (34) where

2 2 A = ∑r=1 to R {[(1/2)((pr0) + (pr1) )][( (ymr1/ym1) Gr1 ) - ( (ymr0/ym0) Gr0 )]} (35) and

2 2 B = ∑r=1 to R {[(1/2)(((ymr1/ym1) Gr1 ) + ( (ymr0/ym0) Gr0 ))] [((pr1) - (pr0) )]} (36)

However expression A in (35) may be also written4 as

A = C + D (37) where

2 2 C = ∑r=1 to R {[(1/4)((pr0) + (pr1) )][((ymr1/ym1) + (ymr0/ym0)) (Gr1 - Gr0 )]} (38)

2 2 D = ∑r=1 to R {[(1/4)((pr0) + (pr1) )][(Gr1 + Gr0 ) ((ymr1/ym1) - (ymr0/ym0))]} (39)

Combining now expressions (34) to (39) we conclude that

∆GWITH = B + C + D (40) where B, C and D measure respectively the impacts of the change in the population shares of the various regions, in the within regions inequality and in the relative (to the overall average income) income of the different regions.

Using (21) we may now similarly decompose the change ∆GBET in the between areas inequality. This change will be expressed as

∆GBET = [ pr1] G [ pr1 (yr1 / ym1 )]’ - [ pr0] G [ pr0 (yr0 / ym0 )]’ (41)

3 We use here again the well known result according to which (ab-cd) = ((a+c)/2) (b-d) + ((b+d)/2)(a-c) 4 Alternative decompositions may be derived and one could think of using an average of all the possible decompositions.

It may then be shown that this change may be expressed as

∆GBET = E + F (42) where

E = (1/2) (H + I) (43) and

F = (1/2) (J + K) (44) with

H = { [ pr1] G [ pr1 (yr1 / ym1 )]’} - {[pr0] G [ pr0 (yr1 / ym1 )]’} (45)

I = { [ pr1] G [ pr1 (yr0 / ym0 )]’} - {[pr0] G [ pr0 (yr0 / ym0 )]’} (46)

J = { [ pr1] G [ pr1 (yr1 / ym1 )]’} - {[pr1] G [ pr1 (yr0 / ym0 )]’} (47)

K = { [ pr0] G [ pr0 (yr1 / ym1 )]’} - {[pr0] G [ pr0 (yr0 / ym0 )]’} (48)

It may be observed that F measures the impact on the change in the between areas inequality of changes in the relative (to the overall average income) income of the various regions while E measures the effect of the change in the shares of the different regions in the total population.

Combining finally (16) with expressions (40) and (48) we conclude that the change

∆G in the overall inequality may be expressed as

∆G = (B + E) + C + (D + F) + ∆GOVERL (49) where (B + E) , C, (D + F) and ∆GOVERL measure respectively the impacts of the change in the population shares of the various regions, in the within regions income inequality, in the relative income of the regions and in the amount of overlapping between the distributions of income in the different regions.

45 B) An empirical illustration: Changes Over Time in Turkish Regional Inequality

In order to be able to compare changes in overall inequality over time we have

grouped the regions in five entities: Marmara and Aegean area, Mediterranean

area, Central Anatolia, Black Sea, Eastern and Southern Anatolia. In table A-1 to

A-4 we present data on the regional distribution of income in 1968, 1973, 1987

and 1994. As may be observed the classification in regions varies from one year to

the other but in grouping the regions in five big entities we manage to take a look

at the changes that took place over time.

Such a grouping implies evidently that the number of observations on which the

comparison is based may be different from one year to the other. Assume for

example that the data on the distribution of incomes are given at the level of

quintiles in 1987 and 1994 but that the regions of Marmara and of the Aegean Sea

were grouped in one area in 1987 but not in 1994. We may evidently group these

two regions in one area in 1994 but then the computation of the inequality index

for this aggregate area in 1994 will be based on 10 and not 5 observations. The

comparison of the inequality in 1994 and 1987 is hence not rigorous since the

grouping of data is not identical in both years. Another issue is that the income

surveys of the different years are not always perfectly comparable, given the

definitions of the units of observations or of income that were used. The only

cases where the data are apparently compatible are 1987 and 1994. In what

follows we will ignore these issues and decompose the changes in inequality in

each of the three sub-periods distinguished (1968-1973, 1973-1987 and 1987-

1994).

In Table 17 we give the share of each of the five aggregate areas in the total

Turkish population in 1968, 1973, 1987 and 1994. It appears that the share of the

46 Marmara and Aegean areas increased considerably during these 26 years since it was equal to 30.7% in 1968 and 42.3% in 1994. On the contrary the shares of three other areas decreased during the same period: for the Mediterranean area from 15.3% to

12.5%, for Central Anatolia from 22.6% to 17.9% and for the Black Sea area from

17.7% to 12.8%). The share of Eastern and Southeastern Anatolia on the contrary barely varied over time.

Assuming that the income data for the four years may be compared, we may observe in Table 18 that for some areas the changes in income shares were even more important (Marmara and Aegean areas: 0.393 to 0.525; Central Anatolia: from 0.231 to 0.154 and Black Sea: 0.147 to 0.109) while for the two other areas (Mediterranean

Sea and Eastern and Southern Anatolia) there were no important changes.

Data on within area inequality are presented in Table 19. Assuming again that the data are comparable we observe as a whole a decrease in inequality in each region between

1968 and 1987 and for four of the five regions an increase in inequality between 1987 and 1994, an increase being observed during this period only in Eastern and

Southeastern Anatolia.

Using the methodology exposed in section IV-A we present in tables 20 and 21 the breakdown of changes over time in the between and within areas inequality into various components. For the variation in between inequality there are two components, one reflecting variations in the population shares of the various regions and one measuring the impact of changes in the relative income (relative to the mean for Turkey as a whole) of the various regions. The results refer to total household income and we concentrate our analysis on the 1987-1994 period. It appears that the between regions inequality increased from 0.091 to 0.113 and that almost the whole

47 change (+0.022) was a consequence of changes in regional population shares

(+0.021).

For the analysis of changes in within regions inequality the theoretical breakdown is different. Since the within regions inequality is a weighted sum of the inequality observed for each region, the weights being equal to the product of the population and income shares of each region, the change in the overall within regions inequality will include three elements reflecting respectively variations in population shares, relative incomes and within region inequality. The results of the analysis are presented in

Table 21. The overall within regions inequality increased from 0.0419 to 0.0435. Here again the greatest part of the change is a consequence of variations in regional population shares (+0.0020 out of a change of +0.0016). Changes in regional relative incomes did not play any role. One may observe however the negative (but weak) effect of changes in Gini indices, this implying that if population and relative incomes had remained constant, overall within regions inequality would have eventually decreased.

The central role played here also by variations in population shares confirms the important impact that internal migration has on income inequality, whether it be between or within regions inequality. This study of changes in inequality over time has been applied only to the case of inequality between households of total household income. From the results of the analysis presented in section III-B we may expect that similar conclusions would have been derived if the analysis had concerned per capita or per equivalent adult income or if we had looked at between individuals inequality.

48 Table 17: Population shares of the various regions over time

Region Population Population Population Population share in 1968 share in 1973 share in 1987 share in 1994 Marmara and 0.307 0.337 0.370 0.423 Aegean area Mediter- 0.153 0.152 0.134 0.125 ranean area Central 0.226 0.219 0.243 0.179 Anatolia Black Sea 0.177 0.149 0.106 0.128 Eastern and 0.138 0.147 0.147 0.145 Southeastern Anatolia

Table 18: Income shares of the various regions over time

Region Income share Income share Income share Income share in 1968 in 1973 in 1987 in 1994 Marmara and 0.393 0.377 0.450 0.525 Aegean area Mediter- 0.114 0.132 0.107 0.111 ranean area Central 0.231 0.234 0.215 0.154 Anatolia Black Sea 0.147 0.158 0.089 0.109 Eastern and 0.115 0.099 0.139 0.102 Southeastern Anatolia

Table 19: Gini index of the various regions over time

Region Gini index in Gini index in Gini index in Gini index in 1968 1973 1987 1994 Marmara and 0.559 0.478 0.398 0.488 Aegean area Mediter- 0.530 0.554 0.394 0.423 ranean area Central 0.533 0.475 0.402 0.412 Anatolia Black Sea 0.553 0.522 0.346 0.414 Eastern and 0.621 0.494 0.418 0.360 Southeastern Anatolia

Table 20: Change in between regions inequality

Components of 1968-1973 period 1973-1987 period 1987-1994 period 1968-1994 period Between Regions Inequality Change Between regions 0.1138 0.078 0.0913 0.1137 Inequality in period of origin Between regions 0.0780 0.091 0.1130 0.1131 inequality in final period Total Change -0.0356 0.013 0.0218 -0.0006 Component due to -0.0465 0.032 0.0205 0.0059 change in population shares of various regions Component due to 0.0108 -0.019 0.0012 -0.0065 change in relative income of various regions

Table 21: Change in within regions inequality

Components of 1968-1973 period 1973-1987 period 1987-1994 period 1968-1994 period Within Regions Inequality Change Total Change -0.0013 0.0018 0.0016 0.0021 Within regions 0.0414 0.0401 0.0419 0.0414 Inequality in period of origin Within regions 0.0401 0.0419 0.0435 0.0435 inequality in final period Component due to 0.0011 0.0015 0.0020 0.0049 change in population shares of various regions Component due to -0.0007 0.0034 0.0001 0.0025 change in relative income of various regions Change in within -0.0017 -0.0032 -0.0005 -0.0053 (each) region Gini index

53 V. Concluding comments:

This paper attempted to analyze the impact of internal migration on spatial inequality in Turkey via its effect on the structure of output, the composition of income, the size of the households and the relative importance of the various regions. In 1994 in

Turkey 72% of the household heads in urban areas were Wage and Salary Earners or

Daily Workers and 28$ were Proprietors while the corresponding proportions in rural areas were 36% and 64%. Although Wage and Salary Earners and Daily Workers had a lower income in rural than urban areas, the difference was much greater for

Proprietors since the latter earned 95% of the national average income in rural areas but 225% in urban areas. For these Proprietors other sources of income (other than income from primary or secondary job) represented 24% of their total income in urban but only 8% in rural areas. All these data clearly imply that internal migration, by modifying the relative importance of urban and rural areas in Turkey as a whole and in the various regions, will have an impact on spatial inequality.

The present investigation indicated also that internal migration from rural to urban areas and between regions induces an increase in the inequality of per capita income, whether one looks at inequality between households or individuals, because first the inequality of total household income is higher in urban areas, second that of the size of households is higher in rural areas.

Finally a comparison of the 1987 and 1994 data showed that the impact of inter- regional migration on inequality between and within regions was maily the consequence of changes in the (population) weight of the various regions rather than in that of their relative income or in the inequality within each region (in the case of overall within regions inequality).

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Özmucur, S. and J. Silber “Income Inequality Decomposition by Area of Residence (rural versus urban areas) and Income Source: The Case of Turkey in 1987”, mimeo, 1995. Özmucur, S. and J. Silber, 2000, “Decomposition of Income Inequality: Evidence from Turkey,” with S. Ozmucur, Topics in Middle Eastern and North African Economies, electronic journal, Vol. 2, Middle East Economic Association and Loyola University Chicago, September 2000, http: //www.luc.edu/publications/academic/ Robinson, S., "A Note on the U Hypothesis Relating Inequality and Economic Development," American Economic Review 66 (1976): 437-440. Selim, R. and A. McKay, 2001, “The Changes in Income Poverty in Turkey over a period of economic liberalization,” paper presented a the Workshop on Poverty and Governance in the Middle East and North African Region, August 2-3, Yemen.

Shorrocks, A. F., 1982, “Inequality Decomposition by Factor Components,” Econometrica 50(1): 193-211.

Shorrocks, A. F., 1983, “The Impact of Income Components on the Distribution of Family Incomes,” Quarterly Journal of Economics 98(2): 311-26.

Silber, J. “Factor Components, Population Subgroups and the Computation of the Gini Index of Inequality”, Review of Economics and Statistics, 71, 1989, pp 107-115.

56 Appendix A: Some Additional Tables

Table A-1: The regional income distribution in Turkey in 1968

Region Share of region in Share of region in Gini index of total Turkish total Turkish household number of household income incomes households Central Anatolia 0.182 0.160 0.549 Black Sea 0.177 0.147 0.553 Marmara and 0.235 0.187 0.449 Aegean Area Mediterranean 0.153 0.114 0.530 Area Eastern Anatolia 0.138 0.115 0.621 Ankara 0.044 0.071 0.368 Istanbul 0.052 0.136 0.488 Izmir 0.020 0.070 0.622

Summary indicators

Gini within areas = 0.075 Gini between areas = 0.185 Overlap between regional income distributions = 0.305 Gini for whole Turkey = 0.565

Table A-2: The regional income distribution in 1973

Region Share of region in Share of region in Gini index of total Turkish total Turkish household number of household income incomes households Central Anatolia 0.175 0.180 0.486 Black Sea 0.149 0.158 0.522 Marmara and 0.233 0.208 0.454 Aegean Area Mediterranean 0.152 0.132 0.554 Area Eastern Anatolia 0.147 0.099 0.494 Ankara 0.044 0.054 0.424 Istanbul 0.085 0.139 0.454 Izmir 0.019 0.030 0.506

Summary indicators

Gini within areas = 0.075 Gini between areas = 0.128 Overlap between regional income distributions = 0.302 Gini for whole Turkey = 0.505

Table A-3: The regional income distribution in 1987

Region Share of region in Share of region in Gini index of total Turkish total Turkish household number of household income incomes households Marmara and 0.370 0.450 0.398 Aegean area Mediter- 0.134 0.107 0.394 ranean area Central Anatolia 0.243 0.215 0.402 Black Sea 0.106 0.089 0.346 Eastern and 0.147 0.139 0.418 Southeastern Anatolia

Summary indicators

Gini within areas = 0.105 Gini between areas = 0.091 Overlap between regional income distributions = 0.220 Gini for whole Turkey = 0.416

Table A-4: The regional income distribution in 1994

Region Share of region in Share of region in Gini index of total Turkish total Turkish household number of household income incomes households Marmara 0.266 0.386 0.490 Agean area 0.157 0.139 0.401 Mediterranean 0.125 0.111 0.423 area Central Anatolia 0.179 0.154 0.412 Black Sea 0.128 0.109 0.414 Eastern Anatolia 0.071 0.057 0.342 Southeastern 0.074 0.045 0.351 Anatolia

Summary indicators

Gini within areas = 0.085 Gini between areas = 0.139 Overlap between regional income distributions = 0.240 Gini for whole Turkey = 0.464

60 Appendix B: The Macroeconomic Environment in Turkey

between 1960 and 20005.

The primary goals of economic policies of the 1960s and 1970s was the protection of the domestic market and rapid industrialization (Owen & Pamuk, 2000) Five-year plans and annual programs, which were binding for the public sector but indicative for the private sector, were used to coordinate investment decisions for long-term growth.

The state played a major role by putting restrictions on imports (direct quotas or high tariffs), undertaking major investment projects, determining prices of major factors and goods and services, and giving subsidies. This role was necessary to support an import substitution industrialization (ISI) policy. In this framework, monetary policy, which was generally geared towards short-term goals, played a secondary role. The

Central Bank governor was regarded as just another civil servant accountable to the

Ministry of Finance.

During most of this period, the private sector operating in a highly protected environment made handsome profits. This protection enabled the private sector to achieve a major shift from producing food and clothing to producing cars, household durables and electronic goods. However, because of the large domestic market and relatively low quality of goods, exports of manufactured goods were almost nonexistent. The required foreign exchange to import necessary raw materials and machinery came from workers’ remittances and agricultural exports (hazelnuts, figs, cotton). During this period the growth rate of the GDP was close to 7 percent, while

5 See Alper & Onis (2001), Aricanli & Rodrik(1990), Boratav & Yeldan (2001), Boratav, Yeldan, &Kose (2000), Cecen, Dogruel & Dogruel (1994) Cizre-Sakallioglu & Yeldan (2000, Dibooglu & Kibritcioglu (2001), Ertugrul & Selcuk (2001), Metin_Ozcan, Voyvoda & Yeldan (1999), Onis (2000), Onis & Riedel (1993), Owen&Pamuk(2000), Rittenberg (1998), Rodrik (1991), and Yeldan (2000).

61 the growth rate in the manufacturing sector exceeded 10 percent. As a result of these favorable developments on the economic front and new rights under the 1961

Constitution real wages were doubled. In rural areas, farmers benefited also from this expansion of the domestic market as well as from agricultural price support programs, subsidies for fertilizers and low-interest credits for tractors. Governments were also able to control the domestic terms of trade in favor of agriculture, especially before elections.

The growth in Europe also helped Turkey. The number of “guest workers” in Europe increased, and by 1973 workers’ remittances exceeded export revenues and reached almost 5% of the GDP. This major inflow, however, contributed to an overvaluation of the Lira, and increased the demand for imports while reducing the demand for exports. Intermediate goods which were to be imported for industrial production became rather expensive, especially after the first oil price shock in late 1973. Instead of taking drastic measures (similar to the ones taken in Europe) to save energy, populist coalition governments continued to adopt expansionary policies. The consequences of these policies were a depletion of foreign exchange reserves and a significant increase in foreign debt. A new instrument created by the government,

“convertible Lira deposit”, allowed private firms to borrow abroad, with an exchange rate guarantee, at the expense of the state. In 1978 Turkey had its most severe balance of payments crisis. The IMF demanded the elimination of import controls, a devaluation of the Lira, and cutbacks in government subsidies. The coalition government was not ready to bear the political consequences of such measures.

Foreign exchange and price controls adopted by the government, and the second oil

62 price shock resulted in shortages. The monetary expansion to finance budget deficits resulted in a rising inflation so that the rate of inflation was three digits in 1980.

The new coalition government had to announce a radical policy package in January of

1980. Its goals were to lower the rate of inflation and to create an export-oriented and liberalized economy. This required a major devaluation, the elimination of price controls and subsidies, a liberalization of the trade regime and of the banking sector, and reductions in real wages and agricultural incomes. The coalition government was willing to adopt these policies, but did not have the political support to implement them. Political and social unrest was the reason for the military coup of September

1980. The military government, which promised to have general elections in 1983 and kept that promise, adopted this program, prohibited labor union activity and put controls over wage increases. The program was successful in lowering the rate of inflation from over 100 percent in 1980 to below 30 percent in 1983, and doubling exports during the same period. It was also successful in lowering the shares of agricultural incomes and wages in national income. Since the program had the full support of the IMF and the World Bank, external debt was rescheduled and foreign exchange problems were practically ended. The full support of the program by international organizations, despite a military government, was largely due to the revolution in Iran and the strategic location of Turkey.

This program however was not as successful in other areas. Because of higher interest rates and lower credits, private investment was affected adversely. As a result the growth of the GDP was not as impressive as during the ISI period. Foreign debt which accumulated at a much higher pace, acted as a drag on the public sector. The principal

63 and interest payments on debt represented about fifty percent of the entire budget, which made it difficult for the government to adopt any social program. Wages and agricultural prices were kept down until the general elections of 1987. In urban areas, wage and salary earners started to moonlight in the “informal sector”. In rural areas, agricultural output failed to keep pace with population growth. Migration from rural to urban metropolitan areas gained momentum6. On the other hand, a new class of

“rentiers” emerged living from high interest rates on bank deposits (domestic and foreign currency). Before the general elections of 1987 public sector wages and salaries and agricultural incomes were increased sharply. Similar policies were adopted in 1989 at the time of the election of the President by the Parliament. By the end of the decade, the economy was vulnerable to another crisis.

In 1989 the capital account was fully liberalized. The need to finance the increasing public sector deficits was also an important motivation to liberalize the capital account. Under the new regime, short-term capital inflows became the ultimate financing source of the fiscal deficit. As the government tried to fix the real exchange rate and the real interest rate to maintain the international competitiveness and to attract foreign capital, with persistent public sector deficits, the result was high and variable inflation, which led to further volatility in real interest rates and real exchange rates.

The Gulf War made things much worse for Turkey in the 1990s. Oil pipeline revenues, close to a billion US Dollars ended, as well as cross-border trade with neighbors. The livelihood of the people living close to the border were adversely

6 See Celasun (1986, 1989), Mutlu (1989, 1998) and Tekeli (1981). See also Shoter (1995) on population.

64 affected. This was another reason for a rapid migration to metropolitan areas in the region and to the West of the country. This rapid movement to urban areas increased the cost to municipalities. The debt of municipalities also increased during this period.

An attempt to fix the interest rate, despite large fiscal deficit and high inflation, led to another crisis in 1994. The growth rate of the GDP was negative for the first time after the crisis of 1980. With the help of the new stabilization program, the economy was quick to recover, but the damage was already done. Turkey had economic difficulties a few years later. IMF supported stabilization programs were implemented in 1998 and 1999. Despite IMF supervision, the economy had a banking crisis in

November 2000 and a currency crisis in February 2001. The Lira had to float after

February.

A crisis with a negative growth rate and a high rate of inflation always leads naturally to a more unequal distribution of income. Since, the government is still the biggest player in the economy (biggest employer, producer, and policy maker), the economic policies adopted had a direct effect on the level of inequality. There was for example a deliberate policy of keeping real wages under control but the policy aiming at increasing public revenues by increasing the price of oil, irrespective of international prices, had evidently also an impact on inequality. Similarly the value-added tax which was implemented in 1985 with the dual goal to increase government revenue and to reduce tax evasion ended up being a regressive tax which contributed to inequality in after-tax incomes. It is not easy to distinguish the contribution of each of these policies to income inequality, but it should be clear that, given the dominance of the state in the economic decision-making process and its active participation in the

65 production and service sectors, government policies must have an impact on income distribution so that inequality is likely to have increased also in 2001.

66 TABLE B1: MACROECONOMIC INDICATORS GDP Inflatio Unemployme Share Current Exports/GD (Exports+imports)/G Percentag growt n nt Rate of account P ratio (%) DP ratio (%) e h rate wages balance/GD Changes in P ratio (%) in nationa Lira/USD l income 195 9.4 -5.5 1.4 21.3 -1.4 7.6 15.9 0.0 0 195 12.8 -1.0 1.7 19.8 -2.3 7.6 17.2 0.0 1 195 11.9 5.8 1.8 20.6 -4.1 7.6 19.2 0.0 2 195 11.2 3.7 2.8 20.9 -2.9 7.1 16.7 0.0 3 195 -3.0 10.0 3.1 23.3 -3.1 5.9 14.3 0.0 4 195 7.9 8.2 3.0 22.4 -2.6 4.6 11.9 0.0 5 195 3.2 14.3 3.1 22.8 -1.0 3.9 9.0 0.0 6 195 7.8 11.8 2.7 20.7 -0.6 3.3 7.1 0.0 7 195 4.5 12.5 2.8 21.0 -0.5 2.0 4.5 0.0 8 195 4.1 26.0 2.8 22.2 -0.9 2.3 5.3 0.0 9 196 3.4 5.6 3.1 22.1 -2.7 6.2 15.2 221.4 0 196 2.0 3.8 3.4 24.4 -3.1 6.3 15.6 0.0 1 196 6.2 3.6 3.3 22.7 -3.8 6.0 15.7 0.0 2 196 9.7 9.8 3.3 22.8 -4.0 5.0 14.2 0.0 3 196 4.1 0.2 3.5 24.7 -1.4 5.2 12.0 0.0 4 196 3.1 4.6 3.6 27.6 -0.9 5.4 12.2 0.0 5 196 12.0 8.4 3.6 27.7 -1.6 4.8 11.9 0.0 6 196 4.2 14.1 4.7 28.9 -1.0 4.6 10.7 0.0 7 196 6.7 6.2 5.1 29.5 -1.2 2.7 6.9 0.0 8 196 4.3 7.8 5.8 29.1 -1.1 2.6 6.6 0.0 9 197 4.4 8.1 6.3 29.9 -0.9 3.2 8.4 26.0 0 197 7.0 16.5 6.6 30.2 -0.6 3.9 10.6 32.1 1 197 9.2 13.7 6.2 29.4 0.0 3.9 10.9 -6.5 2 197 4.9 16.0 6.6 33.4 1.7 4.6 11.9 0.0 3 197 3.3 18.6 7.1 29.5 -1.8 3.9 13.6 -1.9 4 197 6.1 19.8 7.4 28.8 -3.4 2.9 12.3 4.5 5

67 197 9.0 16.4 8.7 30.9 -3.7 3.6 12.5 10.8 6 197 3.0 28.0 9.8 31.9 -5.0 2.8 11.6 11.6 7 197 1.2 47.2 9.8 33.1 -1.9 3.4 9.8 36.6 8 197 -0.5 56.8 8.6 31.0 -1.6 2.5 7.9 31.9 9 198 -2.8 115.6 8.1 27.6 -4.7 4.0 14.4 128.0 0 198 4.8 33.9 7.1 27.4 -2.8 6.9 19.5 61.2 1 198 3.1 21.9 7.0 26.0 -1.4 9.0 21.9 37.1 2 198 4.2 31.4 7.7 24.8 -3.1 9.5 23.8 38.7 3 198 7.1 48.4 7.6 22.9 -2.4 12.2 29.2 63.2 4 198 4.3 45.0 7.1 23.1 -1.5 12.1 28.6 42.2 5 198 6.8 34.6 7.9 25.1 -1.9 9.9 23.9 28.9 6 198 9.8 38.9 8.3 24.4 -0.9 11.8 27.3 28.1 7 198 1.5 77.6 8.4 25.4 1.8 13.2 28.4 67.0 8 198 1.6 63.2 8.6 28.0 0.9 10.8 25.6 48.1 9 199 9.4 60.3 8.0 31.8 -1.7 8.5 23.4 22.8 0 199 0.3 66.1 7.9 37.4 0.2 9.0 22.8 60.2 1 199 6.4 70.1 8.0 37.2 -0.6 9.2 23.5 64.6 2 199 8.1 66.4 7.7 36.3 -3.6 8.5 24.9 60.5 3 199 -6.1 106.3 8.1 30.2 2.0 13.9 31.0 169.9 4 199 8.0 88.6 6.9 26.5 -1.4 12.6 32.9 53.5 5 199 7.1 80.3 6.0 28.5 -1.3 17.4 40.6 77.9 6 199 8.3 86.0 6.7 31.1 -1.4 16.6 41.3 86.9 7 199 3.9 84.7 6.8 30.7 1.0 15.0 36.9 71.7 8 199 -6.1 65.0 7.6 37.4 -0.8 15.5 36.7 60.9 9 200 6.3 54.6 6.6 35.8 -4.9 15.2 41.7 48.5 0 200 -9.4 54.4 8.5 35.7 2.3 23.5 50.1 96.5 1

Sources: GDP growth rate: State Institute of Statistics, Inflation rate : 1950-1968 - Treasury, 1969-2001- State Institute of Statistics, Unemployment rate: 1950-1987 – Bulutay (1995), 1988-2001 – State Institute of Statistics, Share of wages in national income: 1950-1986 – Ozmucur (1996), 1987-2001 - State Institute of Statistics, Current account balance – State Institute of Statistics and Central Bank, Exports – State Institute of Statistics and Central Bank Exports +imports – State Institute of Statistics and Central Bank Turkish Lira/USD – Central Bank

Table . Urban and Rural Population in Turkey year Total Popunnual growt Urban Popnnual growt Rural Popunnual growt share of urb (million) (million) (million) 1927 13.648 3.306 10.342 24.2 1935 16.158 2.11 3.803 1.77 12.355 2.25 23.5 1940 17.821 1.96 4.346 2.71 13.475 1.75 24.4 1945 18.790 1.06 4.687 1.52 14.103 0.92 24.9 1950 20.947 2.17 5.244 2.27 15.703 2.17 25.0 1955 24.065 2.78 6.927 5.72 17.138 1.76 28.8 1960 27.755 2.85 8.860 5.05 18.895 1.97 31.9 1965 31.391 2.46 10.806 4.05 20.585 1.73 34.4 1970 35.605 2.52 13.691 4.85 21.914 1.26 38.5 1975 40.348 2.50 16.869 4.26 23.479 1.39 41.8 1980 44.737 2.07 19.645 3.09 25.092 1.34 43.9 1985 50.664 2.49 26.866 6.46 23.798 -1.05 53.0 1990 56.473 2.17 33.656 4.61 22.817 -0.84 59.6 2000 67.804 1.83 44.006 2.72 23.798 0.42 64.9

Note: population censuses were conducted in October

TABLE B2. Average Annual Growth Rates in Population - Geographic Regions (%) Turkey Marmara Agean Black Mediterranean Central South Eastern Sea Anatolia Eastern Anatolia Anatolia

1945-1950 2.17 1.47 2.13 1.90 2.67 2.42 2.78 2.71 1950-1955 2.77 3.18 2.65 1.84 3.42 3.34 5.52 1.47 1955-1960 2.85 2.95 2.72 2.57 3.38 2.55 2.96 2.68 1960-1965 2.46 2.38 2.27 2.12 2.80 2.62 2.81 2.63 1965-1970 2.52 3.17 2.03 1.59 2.96 2.60 3.38 2.45 1970-1975 2.50 3.30 2.07 1.35 3.45 2.63 2.73 2.15 1975-1980 2.07 3.14 1.97 1.20 2.87 1.58 2.10 1.47 1980-1985 2.49 3.25 2.50 1.22 3.05 2.19 3.75 1.77 1985-1990 2.17 3.61 2.37 0.36 2.75 1.52 3.62 0.51 1990-2000 1.83 2.67 1.63 0.37 2.14 1.58 2.48 1.38

2000 67.803 17.365 8.939 8.439 8.706 11.609 6.609 6.137 population (million) 2000 share 100.0 25.61 13.18 12.45 12.84 17.12 9.75 9.05 (%) ______Source : State Institute of Statistics

Table B3. Income Distribution in Turkey, 1963- 1994

70 Turkey 1963 1968 1973 1987 1994 lowest 20% 4.5 3.0 3.5 5.2 4.9 second 20% 8.5 7.0 8.0 9.6 8.6 middle 20% 11.5 10.0 12.5 14.1 12.6 fourth 20% 18.5 20.0 19.5 21.2 19.0 top 20% 57.0 60.0 56.5 49.9 54.9

Gini 0.550 0.560 0.515 0.437 0.492 lowest 40% 13.0 10.0 11.5 14.9 13.5 top /bottom 20% 12.7 20.0 16.1 9.5 11.3 Kuznets 0.463 0.500 0.456 0.389 0.436 ______Sources: 1963- Cavusoglu & Hamurdan (1966), 1968 – Bulutay, Serim, Timur (1970), 1973 – Devlet Planlama Teskilati (1976), 1987 – Devlet Istatistik Enstitusu (1990), 1994 – Devlet Istatistik Enstitusu (1997)

71 Table B4. Income Distribution in Urban and Rural Turkey, 1973-1994

Urban 1973 1987 1994 lowest 20% 5.4 4.8 second 20% 9.3 8.2 middle 20% 13.6 11.9 fourth 20% 20.7 17.9 top 20% 50.9 57.2

Gini 0.479 0.444 0.515

Rural 1973 1987 1994 lowest 20% 5.2 5.6 second 20% 10.0 10.1 middle 20% 15.0 14.8 fourth 20% 22.0 21.8 top 20% 47.8 47.7

Gini 0.543 0.417 0.414 ______Sources: 1973 – Devlet Planlama Teskilati (1976), 1987 – Devlet Istatistik Enstitusu (1990), 1994 – Devlet Istatistik Enstitusu (1997)

72 Appendix C: More on the Data Sources on the Distribution of Incomes in Turkey (1963-1994)7

The 1963 income distribution study was the first income distribution study carried out by the State Planning Organization (Cavusoglu & Hamurdan, 1966). Incomes were gathered from the income tax revenues of 327000 taxpayers. The study was criticized on the grounds that income taxes had a very limited coverage. According to

Cavusoglu & Hamurdan (1966), the lowest twenty percent of households received 4.5 percent, the second lowest 20% receives 8.5 percent. The share of the middle group was 11.5 percent. The top two groups received 18.5 and 57 percent of incomes (Table

1). Boratav (1966) claimes that inequality was underestimated because of tax evasion, while Sarc (1967, 1970) argues the opposite.

The 1968 study was based on a survey carried out by Institute of Demographic

Studies of Hacettepe University (Bulutay, Ersel, Timur, 1971). Disposable income data used in the calculations were based on the replies given by married males whose wives were less than 45 years of age in each household. The households with no married women younger than 45 years of age were excluded from the study. Those households constitute 17.2 percent of the total in Turkey. The reason for this exclusion was due to the initial goal of the survey, which was to look at demographic data (fertility in particular) rather than at income distribution. After having talked to one of those who launched this survey (Timur) the authors, Krzyzaniak and Ozmucur

7 See Boratav (1966, 1969, 1990), Bulutay & Ersel(1967), Bulutay, Timur, & Ersel (1971) ,Celasun(1986, 1989), Cavusoglu & Hamurdan (1966) , Dervis & Robinson (1980), Esmer, Fisek &Kalaycioglu (1986), Hansen (1991), Herslag (1990), Gursel, Levent, Selim, & Sarica (2000), Kasnakoglu (1978,1997),Kazgan, Onder, Kirmanoglu & Tuncer (1992),Krzyzaniak & Ozmucur (1973) ,Özbudun & Ulusan (1980) ,Özmucur (1996),Sarc (1966, 1967, 1970),Sonmez (1971), Sonmez (1990), State Planning Organization (1976), State Institute of Statistics (1979, 1982,1990,1997), Tansel (1992), Varlier (1982)., and World Bank (2000).

73 (1973) made a correction for excluded households and got an estimate of the Gini coefficient equal to 0.57, which is slightly higher than the one in the original study.

The 1973 study was also based on a country-wide survey carried out by the

Demographic Studies Institute of Hacettepe University (State Planning Organization,

1976). In addition to five geographical regions, the cities of Istanbul, Ankara and

Izmir were considered as metropolitan areas. The regions remaining outside the metropolitan areas were divided into urban and rural areas. The Gini coefficient was found to be equal to 0.51. Dervis and Robinson (1980) argued that non-agricultural incomes and agricultural population in the survey were underestimated, which led to a downward bias in equality. Their estimate of the Gini coefficient was slightly lower

(0.50). Agricultural incomes had a Gini coefficient of 0.56 compared to 0.45 for the non-agricultural incomes. In the original study the corresponding coefficients were

0.60 and 0.63, respectively. According to Celasun (1986) the Gini estimates were 0.51 for the total, 0.57 for the agricultural, and 0.43 for the non-agricultural incomes.

The 1987 study was the first survey covering Turkey as a whole (State Institute of

Statistics, 1990). Income definitions included personal disposable income (actual payments made e.g. salaries, interest, profit, rent and unilateral transfers from the public and private enterprises and from abroad) and income in kind. The Gini coefficient was equal to 0.43. Such an estimate, the lowest coefficient obtained in income distribution surveys, was questioned by many researchers8. Celasun (1989) reported also preliminary results of this survey. They indicated that the top 20 percent had received 55 percent of the total income, and bottom 40 percent have received 11

74 percent of total income. These figures are very different from the ones reported in the final report. Esmer, Fisek, Kalaycioglu (1986) obtained a Gini coefficient of 0.50, which is in line with the 1973 results.

The 1994 study covered also Turkey as a whole and was conducted by the same organization (State Institute of Statistics, 1997). These two survey results are therefore probably the most comparable. Income definitions included personal disposable income (actual payments made e.g. salaries, interest, profit, rent and unilateral transfers from the public and private enterprises and from abroad) and income in kind. The Gini coefficient was found to be equal to 0.49 and this was significantly higher than the one obtained in the 1987 survey.

8 The State Institute of Statistics has conducted consumer expenditure surveys in rural areas in 1973-74 (SIS, 1979) and urban areas in 1978-79 (SIS, 1982). Gini coefficients obtained from consumer expenditure surveys were 0.47 and 0.40, respectively.

75 Additional Bibliography for Appendices B and C.

Alper, E. and Z. Onis, “Financial Globalization, the Democratic Deficit and Recurrent Crises in Emerging Markets: The Turkish Experience in the Aftermath of Capital Account Liberalization”, July 2001, mimeo.

Aricanli, T. and D. Rodrik, eds. The Political Economy of Turkey, Debt, Adjustment and Sustainability, St. Martin’s Press, New York, 1990.

Boratav, K., “Turkiye’de Kisisel gelir Dagilimi ve Devlet Planlama Teskilatinin Arastirmasi”, Ankara Universitesi Siyasal Bilgiler Fakultesi Dergisi, XXI (1966), 45- 102.

Boratav, K., 100 Soruda gelir Dagilimi (Kapitalist Sistemde, Turkiye’de ve Sosyalist Sistemde), Gercek Yayinevi, Istanbul, 1969.

Boratav, K.,”Inter-class and intra-class Relations of Distribution under ‘Structural Adjustment’: Turkey During the 1980’s” in Aricanli, T. and D. Rodrik, eds. The Political Economy of Turkey, Debt, Adjustment and Sustainability, St. Martin’s Press. New York, 1990.

Boratav, K. and E. Yeldan, Turkey, 1980-2000: Financial Liberalization, Macroeconomic (In)-Stability, and Patterns of Distribution, December 2001, mimeo.

Boratav, K., E. Yeldan, and A. Kose, Globalization, Distribution and Social Policy: Turkey, 1980-1998, CEPA (Center for Economic Policy Analysis, New School, February 2000, mimeo.

Bulutay, T., Employment, Unemployment and Wages in Turkey, International Labor Office and State Institute of Statistics, Ankara, SIS Printing Division, 1995.

Bulutay, T., H. Ersel. “The Distribution of Income in Certain Cities”, Milletlerarasi Munasebetler Turk Yilligi, 1967.

Bulutay, T., S. Timur, and H.Ersel, Turkiye’de Gelir Dagilimi, 1968, Ankara Universitesi Siyasal Bilgiler Fakultesi Yayinlari No: 325, Ankara.

Cecen, A., S. Dogruel and F. Dogruel, “Economic Growth and Structural Change in Turkey, 1960-1988, International Journal of Middle East Studies, Vol. 26, Issue 1, February 1994, pp.37-56.

Celasun, M., “Income Distribution and Domestic terms of Trade in Turkey, 1978- 1983”, METU Studies in Development, 13 (1986), 193-216.

Celasun, M., “Income Distribution and Employment Aspects of Turkey’s Post 1980 Adjustment”, METU Studies in Development, 16 (1989), 1-31.

76 Cizre-Sakallioglu, U and E. Yeldan, “Politics, Society and Financial Liberalization:Turkey in the 1990s”, Development and Change, Vol. 31, 2000, pp. 481-508.

Cavusoglu, T. and Y. Hamurdan, Gelir Dagilimi Arastirmasi, 1963, Devlet Planlama Teskilati Yayin No. 500. Ankara.

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