Rural stratification, rural to urban migration, and urban inequality: Evidence from Iran

World Development, Vol. Printed in Great Britain.

14, No. 6, pp. 713-725.

0305-750x/x6

1986.

$3.00 + 00

Pcrgamon Journals Ltd.

Rural Stratification, Rural to Urban Migration, and Urban Inequality: Evidence from Iran HAMID

MOHTADI*

University of Wisconsin, Milwaukee Summary. -Recent findings on India have pointed to the importance of the rural caste structure to rural-urban migration and the creation of (partially) segmented urban labor markets. By considering cross-sectional evidence from Iran and by viewing differential access to land, instead of castes, as the determinant of the migrants’ background, the implication ol’ this view for the impact of migration on urban inequality is examined. It is fclund that where migrants are l’rom a landless group urban inequality increases and where they are from a landed group it declines. cereri.s paribus. Urban inequality is measured by the construction of an urban housing shares index from the census data

ever two aspects of these studies - (1) that the urban informal sector acts as a temporary staging post for migrants on their way to formal sector jobs, and (2) that all migrants are uniform in this have been questioned by recent respect findings on India, with important implications for the present study. For example, a study of Delhi (Banerjee, 19X3) points to a relatively limited mobility of migrants from the informal to the formal sec’tor. while a study of Coimbatore (Harris, 1982) points to the presence of two separate migratory trends: one from the lower rural castes to the informal sector and one from the upper castes to the formal sector. Mazumdar (1983) points to the importance of kinship to the recruitment process as a logic behind this dual trend. The combined logic of these studies suggests that rural-urban migration, at least in the Indian case, may have recreated the pattern of rural stratification, characterized by castes, in the form of urban labor market segmentation (Mazumdar. 1983).’ However, a more common form of rural stratification (including that in Iran, as will be

1. INTRODUCTION In studies of the Less Developed Countries which focus on decomposition of overall inequality into its in&a-urban, intra-rural and inter-rural-urban components, intra-urban inequality is found to contribute the largest component.’ Furthermore, the rapid pace of urbanization is likely to increase the share of urban inequality in the overall inequality profile. By focusing on the Iranian development experience during the 1960s and 197Os, this paper studies the impact of urbanization on urban inequality trends over time. Specifically it examines whether the effect of rural-urban migration on urban inequality may be a function of the migrants’ rural background and if so. how. Thus, the focus of this paper is oil the relative welfare of the migrants within their urban destination, rather than on possible improvements in their absolute welfare because of migration.’ While the latter question is important to the study of the causes of migration (cf. Stark, 1984), the former is relevant to urban policy questions once migration has occurred, and may deserve greater attention than has been given. The notion that a relationship might exist between the migrants’ rural backgrounds and the impact of migration on urban inequality stems from the findings of some recent studies on migration and urban dualism.’ The early studies on the link between migration and urban dualism were conducted by the formal approach of Todaro (1969) and its various extensionsJ How(LDCs)

*I wish to thank Thomas Weisskopf for his invaluable comments. Thanks are also extended to Biswajit Banerjee and Fatemeh Moghadam as well as an anonymous referee for reading the earlier draft of this paper. This work has required the use of extensive census data. I am grateful to the institutions and individuals who provided this data. Finally, I am alone responsible for any possible errors and for the views exprcsscd here. 713

714

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discussed). is based on differential acccsx to land. without this access being based on castes. Thus the question arises whether the Indian pattern would still remain ii logical outcome in this case. i.c., whether migrants from landless backgrounds are absorbed into the informal. and those from landed backgrounds, into the formal sector? Here, the importaInce of kinship to ths recruitment process and hence labor segmentation may be weaker. But differentials in education hased on differential access to land (c.f. Conncll c/ rrl.. lY76, p. 21) may still serve to channel the landless migrants into the informal sector (with less skill requirements) and the migrants from landed backgrounds into the formal sector (with more skill requirements). Furthermore, the mgrants’ background may influence their access to and therefore. their resources (c.g.. savings) desire and capacity to search for formal sector jobs.” If the above hypothesis is correct. i.c. if migrants from landless and landed backgrounds experience a dual pattern of absorption into the informal and formal sectors respectively. then an increase in the number of migrants from landless backgrounds may increase the overall urban inequality profile. ceteris pribus. by raising the relative size of the urban informal sector. and so. of the low income groups. On the other hand. an increase in the number of migrants from landed backgrounds, which would increase the size of the formal sector, may increase or dccrcase urban inequality depending on the existing distribution of income in a city, and thus the relative income position of the formal sector members relative to the rest of population. For example, if the majority of the population were poor in a city, formal sector members would belong to an “upper” income category and an increase in their number would reduce urban inequality. But this result would be reversed in a city whose overall mean income is greater than the mean income of formal sector employees.’ In short, rural stratification. if present, would have predictable effects on urban inequality trends, through the intermediation of rural-urban migration. This derived hypothesis, which will be called “Stratification-Migrntionlnequality” hypothesis (SMI). is tested in the Iranian case. The analysis consists of three components. First. the impact of a land reform program (1962-72) on the status of Iranian peasantry will be studied. Here. a bifurcation of the traditional sharecropping peasantry into two sub-groups. with differential access to land. will be analyzed, both institutionally and empirically. Second, the migration pattern of each sub-group will be analyzed, empirically. Third. the impact of migration by

c:lch group on urban inequality trends will bc estimated empirically. Each stage of this analysis corresponds to a specific component of the overall SMI hypothesis above. These components arc then tested with cross-sectional census data for Iranian &tie> and rural regions. In general, since intra-countr) cross-sectional data on income distribution arc often unavailable for the LDC\. methodologically similar studies are not common in the literature. In the present context, in order to overcome this difficulty, an index of welfare inequality is constructed based on Iranian housing statistics contained in two ccnsuscs. which is then utilized in the subsequent empirical analysis. In what follows, Section 2 provides an overview of the rural sector in IY6Os and lY7Os. and also presents formalized versions of the hypothcscs which are to be tested: Section 3 develops models for the testing of each hypothesis; Section 4 discusses data and methodological issues; Section 5 contains results; and Section 6 provides concluding remarks.

2. RURAL

SECTOR AND HYPOTHESIS FORMATION (a) Rwwl sector

This segment contains a brief overview of the background of Iranian rural population and examines the role of land reform in the formation of new rural groupings. with potentially differential access to land. In this way. it serves as background for distinguishing between potential rural-urban migrant groups, which will be the focus of further investigation and hypothesis formulation in the next segment. Two major rural groups of approximately equal size constituted the rural population of each (typical) Iranian village. prior to the land reform: (1) the sharecropping peasantry who enjoyed cultivation rights: (2) the “Khoshneshin” with no formal ties to the land.x The land reform which lasted from 1962 until lY72 covered only the sharecroppers. and consisted of three distinct phases.” In phase I, which began in lY62, a sub-group of sharecroppers (approximately 30%) became owners of their sharecropping portion and formed a landed farmer group. This phase covered the lands of large landlords with more than one village, exempting them from distributing one village of their choice. Phase 11, which began in lY64, covered much of the latter and the lands of small owners with less than one village. Of the five options available to landlords, in this

RURAL

TO URBAN

phase most chose a rental option, and hence the principal contribution of phase II was the creation of a tenant farmers group (approximately 55% of all sharecroppers). ‘I’ The tenancy provision was a temporary reform. In 1968 a third phase was introduced, aimed at abolishing the tenancies by allowing tenant farmers to purchase all or part of their tenancy lands. However, by 1972 (the end of the reform) when all conversions were to be complete and no tenancies to be left, only 65% of tenant farmers appear to have become landed farmers under this phase (Denman, 1973, p. 149). suggesting a possible loss of access to land on the part of the remaining 35%. While this hypothesis will be formally tested later, evidence in many regions does point to a certain increase in the extent of polarization between the landed and the tenant farmers. For example, (i) a study of the regional distribution for the annual installment payments of landed farmers for their purchase of land indicates a drop from their average pre-reform sharecropping payments for 88% of the members of this group (Mohtadi, 1982, pp. 35-39). In contrast, all tenant farmers, before tenancies were abolished, had annual rental payment equaling their pre-form value, averaged for 1961-64 period. (ii) The existence of a provision under phase II allowed landowners to reclaim their tenancy land after 3 years of tenant default, while no similar provision can be observed for the landed farmers. In summary, four rural groups have been distinguished: (1) the “Khoshneshin,” not directly tied to the land; (2) the “landed” farmers (under phase I); (3) the “tenant” farmers (under phase II); (4) the “remaining” farmers (covered under phase II). Even though tenancies were later abolished, category (3) still remains valid since it identifies a specific rural group, and since the landlessness hypothesis for this group is linked to its initial tenancy status. Furthermore, it should be noted that phase III does not form an independent category since it pertains to the same rural group as that in category (3).

(b) Hypothesis

MIGRATION

715

IN IRAN

Third, how did the migration of the tenant and the landed farmers affect the urban inequality profile? (Specifically, we expect to find that increased migration of the tenant farmers will be associated with an increase in urban inequality, given that their increased incidence of landlessness is empirically borne out. However, in the case of the landed farmers this outcome depends on the existing distribution of income within the cities of destination, as was discussed in Section I .) In this way examining the overall SMI hypothesis will be equivalent to answering these three questions jointly. Specifically, question (1) examines the existence of rural stratification; question (2) examines the importance of migration for the specific groups in (I); and question (3) examines the effect of rural-urban migration on urban inequality.

3. MODELS In this section two separate models will be developed. The first model is aimed at identifying “the incidence of rural employment” and “the migration propensity” for each of the rural groups, discussed in Section 2. Estimating these parameters in Section 5 will answer the first two questions that were outlined in Section 2(b). The second model determines the effect of migration by the landed and the tenant farmers on urban inequality. Estimating the parameters of this model will answer the third question in Section 2(b), thus completing our examination of the SMI hypothesis. (a) Rural unemployment

and out-migration

Denoting the four groups of rural labor force, as discussed in Section 2, by numbers 1 (the “Khoshneshin” group), 2 (landed farmers), 3 (tenant farmers) and 4 (the remaining farmers, under phase II) one can write:

formation

h&lN. With the above background and in view of the discussion of Section 1, it is possible to examine the SMI hypothesis of that section by answering the following three questions empirically: First, did the incidence of landlessness in fact increase among the tenant farmers (group 3) but not the landed farmers (group 2)? Second, was the propensity of rural out-migration significant among both the landed and the tenant farmers?

(1)

where N, is the total rural labor force and N, is the labor force of the ith grouping. The superscript 0 is used to denote the ex-ante nature of these variables with respect to rural unemployment and out-migration (see below). Similarly, total rural unemployment, U,, is the sum of rural unemployment in each category, U,:

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Here. the irbsence of superscript 0 denotes the CX-JIOSInature of these variables. Next. for each rural gioup. the ratio of its CJX-yes/ unemployment to the total ~X-NII~Crural labor force is expressed as a proportion (which may or may not hc statistically significant) of that group’s KY-UIZW share of the total rural labor force (for reasons that arc explained below). This equation

is:

U,lM: = u,(N)Ni) + E,. i = I

4

(3)

for each group. ZC, is a random disturbance and u, is a proportionality constant (to be estimated). Using the CJ.Y-(I~~IC and C~S-post variables in this particular fashion captures any potential causal relationship that may exist between the institutional changes of the land reform program (discussed in Section 2) and their effect on rural unemployment. Specifically. the c.~~te choice of the labor force ratio for each rural group avoids any potential simultaneous problem created by the reverse impact of unemployment on the siLe of the labor force, if unemployment may have resulted in some rural out-migration, and thus in a fall in the rural labor force. Since u, is the constant of proportionality relating the c~x-~~ostunemployment rate (with an er-mw base) in group i to that group’s CY-NIIIE share of the total rural labor force. it can be interpreted as representing the “incidence of rural unemployment” for group i. Summing equation (3) over i and using cquation (2) yields the following results: where. term,

4

where

e =

Z i=l

F,, is an overall

disturbance

term. Here, UJhJ'i is the ex-posr rate of overall rural unemployment relative to the original rural labor force, and N;/IV~ is each group’s share of the original rural labor force. Estimating a,s in equation (4) (subject to a constraint, discussed later) will then provide an answer to question (1) of Section 2(b). which dealt with the incidence of landlessness among the tenant and landed farmers (groups 2 and 3). To show this, we must be able to argue that a

statistically significant u, is both a necessary and a sufficient indicator of higher incidence of landlessness for the rural groups 2 and 3. Now. while increased landlessness would increase the incidence of rural unemployment, (x,, it may bc argued that the reverse is not necessarily true (i.e., increased u, is not always an indication of increased landlessness), since a landed or tenant farming family may seek extra employment simply to augment its present income. However, such a behavior rural

families

would

with

have to be random

across

ties to

the land and hence any systematic incidence of unemployment for either group. captured by statistically significant values of c(: or
(3, > 0. i = I

4

(5)

where M,/IV~ is the c~x--/~ostrate of overall rural out-migration among the original rural labor propensity” for force, 13, is the “out-migration each rural group i. This interpretation of 13,s is analytically similar to the interpretation of u,s, and can be seen by analogy from equation (3). The specific form of the migration function in (5) requires some elaboration: previous studies of migration functions have shown that ruralurban migration responds to many variables such as education, age. distance, rural-urban income differentials. distribution of land.” Such factors may be equally important in the Iranian case. However, in order to be able to examine the stratification component of the SMI hypothesis. the relevant classification would have to be based on the ttlurdly cwhsive rural grouping of equation (5). rather than on the ovcrluppitrg rural groupings that would correspond to the cxplamtory factors, above. In this way, each grouping of equation (5) acts as a composite index with a different mix of explanatory factors. traditionally used in the migration literature. Admittedly the general logic behind the SMI hypothesis is based on the key role of certain explanatory factors such as education and access to resources, which tend to channel migrants into different urban sector\. and which are likely to depend on their prior rural status (see Section ?).” While a direct te\ting of this logic requires

RURAL

TO URBAN

that migration by each distinct group be studied as a function of all potential explanatory variables, the absence of migration data by group still permits a testing of the derived SMI hypothesis though not the underlying logic itself. However, in view of the relative paucity of research in this area, a testing of the SMI hypothesis, on its own merit, is quite an important one and may warrant the present approach. Since rural population in all four groups equals the total rural labor force, estimation of the equations (4) and (5) is subject to the following constraint:

MIGRATION

717

IN IRAN

for the probable effects of the industrialization process on urban welfare shares. Finally a, e, are the coefficients to be estimated and v, is a random disturbance term. S, and $: are subject to the following constraint-identities: 5 I:

j=l

5

s,=.c

/=l

s;=1.

Since these identities hold for all values of the independent variables, one can derive the following constraints on the coeffiecients a, (I,: 5 5 5 C C,= ,~ di = .~ e, = 0 J=l j=l I=1

Equation (6) is then used to eliminate ui from equation (4) and 0, from equation (5). since these parameters are not relevant to answering questions (1) and (2) in Section 2(b). In fact, for all three questions, it is sufficient to estimate a1 and cci in equation (4) and Pr and B1 in equation (5), corresponding to groups (2) and (3). The data and methodological issues related to the estimation procedure are discussed in Section 4.

(b) Migration

and urban inequality

This segment formulates an empirically testable model aimed at answering the third question of Section 2(b) on the relation between migration and urban inequality. This is based on the following equation:

.r,= a, 1=1...5

+ b,

‘5: + c, . Mj, + d, . M:, + ei . G + v,, (7)

where j is an index of some specific population grouping. In the present analysisj will range from 1 to 5 and thus the urban population groups will be in “quintiles.” S, and $ are the ex-post and the ex-ante values of the share of the jth population group from some overall “welfare” measure, relative to the migration period. (The specific nature of this measure and also the choice of the migration period are discussed in Section 4.) .$j is introduced to control for the effects of the past values of urban shares on their current values; MX and M:, represent the rates of rural-urban migration by the landed and the tenant farmers respectively; G is a general representation of the urban industrialization process, to be specified in Section 4. This variable is introduced to control

W

5 b, = b1 =

= bS = 1 -

2

j=l

a,.

Pb)

The presence of these constraints implies that the disturbances v, will be correlated across the five equations, though they would remain uncorrelated across regions. Hence, estimation in this case is carried out with the Generalized Least Squares estimation method.

4. DATA

AND METHODOLOGY

Estimation is based on cross-sectional data from Iranian censuses (1966 and 1976). In addition, cross-sectional data on rural groupings are obtained from Denman (1973). Data for the estimation of equations (4), (5) and (7) are based on two separate statistical cells: for estimating equations (4) and (5), concerned with rural unemployment and out-migration, these are rural data, from the rural sector of each province (21 provinces in total),” and for estimating equation (7) these are urban data. from the cities of size 25,000 or more (57 cities in total). To avoid biasing the sample in favor of cities that have grown to over 25,000, due to migration, cities are chosen according to their size at the outset of the interval under study (1966). A summary of the procedures for the measurement of the variables is as follows. Migration. Migration is estimated as net rural out-migration and net urban in-migration over the 196676 period.lJ using a common demographic technique known as the Survival Ratio method which measures, for each age cohort and

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region, the difference between the actual population in lY7h and the population that would have survived, based on the natural growth rate and the population of the “base” year, 1966. The estimates of net rural out-migration arc then directly used in equation (S), while those of net urban in-migration are utill”zed to construct two proxy variables to be used in equation (7) (see Section 5). Rural trttattt~~l~~~rtt~ttt. Data for this variable are based on the combined number of rural workers “in search of jobs” and “seasonally unemployed.” The actual variable in equation (3) is the average of the unemployment ratios for I’$66 and IY7h. This is because values at the two endpoints of the interval are each subject to :I shortcoming; the lY66 value is too close to the beginning of phase II, not adequately reflecting developments that may be connected with the potential increase in the landlessness among tenant farmers; the 1076 value reflects the rural unemployment rates at the end of the 196676 migration period and since many migrants may have been among rural unemployed, this would underestimate the rural unemployment rate. Kttrul labor fbrcc, hy group. Data for this variable are based on the total number of titles granted in each province under phases I and II. regardless of any later changes in the status of the farmers in groups (2). (3) and (4). Hence. they are er-mtc magnitudes relative to the unemployment and migration variables and are directly used in equations (4) and (5). Urhutt itzdtrstrializcrtion. This variable is based on the change in the level of total urban employment in industry and mining from lYh6 and lY76. relative to its base value in 1’466. With this representation, variable G in (7) is considered to be exogenous since the expansion of employment in these capital intensive sectors is not generally influenced by the rate of ruralurban migration. On the contrary, it is the investment rate which tends to act as a binding constraint to growth of these sectors in an LDC with general abundance of labor. Urhm wdfurr sitrrres. The welfare shares of each urban quint& in equation (7) is represented by its housing share from the total housing available in each city. Despite the specific nature of this index it is likely to be correlated with other indices such as income or expenditures. In addition it may better capture the “crowding” aspect of urban inequality associated with rapid urbanization. It may be argued that indices based

on expenditures may tend to underestimate the income shares of the poorer migrants (in this case tenant farmers) who are more likely than the richer ones (in this case the landed farmers) to remit

some

of

their

urban

income

to the

rural

sector. Flowever, in the present study. migration of the tenant farmers, if it is connected with their potential landlessness, is more likely to involve the entire family than only a few members of the family and hence remittances are less likely to bc an important consideration in this case. Morcover, the presence of some remittances would not affect the testing of the SMI hypothesis since remittance in this case would be made across lower “horizontal” urban/rural gr0upin.g:. and thus preserve the direction of rural stratification and urban inequality. though they might possibly overestimate the extent of urban inequality. The index of housing shares is developed by utilizing a piccc of information which is systematically available for the urban housing data in the lY66 and lY76 censuses. For each city. this information consists of a IO x IO matrix, representing the distribution of rooms (l-IO+) per dwelling among urban families by size (l-IO+) per dwelling. Following ;I series of mathematical transformations. discussed in the Appendix. this matrix is then convert4 into housing “shai-es” for the five urban cluintiles. defined as the ratio of all the rooms available fol each quintile to the total number of rooms per city. It should be noted that as a cardinal measure this would understate the degree of urban inequality present at any given time, since ;I “room” for upper income groups is quite distinct (greater in value) from that for the poor. On the other hand. the direction of dynamic comparisons is harder to judge since changes in the value of hokng for the upper income groups may be greater

or

groups

over

less

than

those

for

the

lower

income

tinic.‘5

5.

RESULTS

Results from estimating parameters of the constrained equations (4) and (5) are reported in Table 1, where the constraint equation (6) is used to eliminate These

the term

results

incidence”

indicate

among

farmers.

Given

interpret

this

incidence

of

cate significant for

the

landed

farmers.

before.

“unemployment but

discussion of indication m

landlesaness

not the landed

as discussed

significant

the tenant

our as

Mi/tii.

not the landed Section 3, wc of increased

among the tenant Furthermore. thev

“out-migration and the tenant

propensity” farmers.

Thus

but indiboth by

RURAL Table

1. Estimated

Dependent

TO URBAN

MIGRATION

IN IRAN

719

values of “unemploymett~ incidence” atId “migration propemily” by rural groups: equations (4) and (5) Independent

variables*

variables*

Proportions

of: Remaining phase II

Landed

farmers:

Tenant

h$IN1’

farmers:

farmers:

hf:/hi)’

lv:lhf;

Rural unemployment ratio: -0.017 (-0.30)

Wl\r,’ (t value)

0.082 (2.73)t

0.022 (0.003)

Rural out-migration ratio: ‘\4JlVJ (t value) Source:

0.167 (1.92)$ Based on separate

0.211 (5.02)t

OLS estimation of reduced (4) and (5). *Set equations (4) and (5) in the text for further tSignificant at a = 0.01, using a one-sided test. $Significant at a = 0.05. using a one-sided test.

-0.021 (-0.19)

form equations.

derived

from using

equation (6) in equations

questions (1) and (2) of Section 2(b), these results confirm both the rural stratification and the rural-outmigration components of the overall SMI hypothesis. The combined significance of migration propensity and unemployment incidence for the “rural tenant farmers appears to suggest source of migratory inpush” as a possible fluence for this group. In addition, significant migration propensity, combined with insignificant unemployment incidence among the landed farmers suggests that “urban-pull” may have been a more likely cause of the migration for this group. If’ It is now possible to answer question (3) of Section 2(b) by estimating parameters of (7). To do this, first the migration variables in (7) are estimated with the following equations: answering

(1Oa)

where (MU/N,),, denotes the ro ortion of urban migrants into city k and ( JJ z/ r)k and (I’@@;), stand for the proportion of the original rural labor force among the landed and the tenant farmers in the rural sector of the province

elaboration

of the variables.

containing the kth city. Since both (3, and 13; are found to be significant from Table I. the and (A’{/#), in (IOa) terms (AJ;/ti;)1, and (lob), respectively, are proportional to (M:ltii)l, and (M:l/V;)k, from equation (5). Thus, for each rural group, the products on the righthand sides of (IOa) and (1Ob) vary in approximate proportion to the “joint probability” of urban in-migration into the kth city and rural out-migration from the rural sector of its surrounding province or, assuming negligible inter-provincial rural-urban migration,” to the probability of rural-urban migration into the kth city by that group. While this justifies the use of interaction parameters in (IOa) and (lob). this is clearly a second best approach, adopted in the absence of direct survey data on rural-urban migration by the two groups under study. However, due to the historical nature of this particular data set a direct survey is not feasible and thus the present approach may be, in fact. the best that is possible in this context. Parameters of the equation-system (7), with constraints (1Oa) and (lob). are estimated using a Generalized Least Squares method, due to the presence of correlation across equations. Note that despite the presence of .5), equation (7) is not a distributive lagged equation-system, since it applies only to the 196676 period with its distinctive rural features. In fact, the explicit use of variables connected with the land reform

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DEVELOPMENT

[equations (l(h) and (lob)] precludes the possibility of applying (7) to other previous decades. The most significant feature of the results. reported in Table 2, is the opposite impacts of Mi,, and M:,, on S, for all values of j, except when j = 4. In addition, the following observations can be made. First. taking the five quintiles together. these results indicate that rural-urban migration by tenant farmers is associated with an increase. and ruraLurban migration by landed farmers with a decline. in the overall urban inequality from lY66 to 1976. Thus. in answering question (3) of Section 2(b), this confirms the inequality component of the overall SMI hypothesis. i.e., the presence of a definitive inequality pattern associated with the rural background of the migrants. Moreover, given the distinctively dual impact of the migration by the two rural groups on urban inequality, it indicates that rural

“Current” (lY7h) shares*: s, 1st quintilc:

“Initial” (1966) shares*: 9;

stratification is actually reproduced in the urban sector in the form of urban inequalitya finding that is quite analogous to Mazumdar’s (1983) view on the link between rural stratification and urban labor market segmentation (see Introduction to this paper). Secondly. looking specifically at the first three rows we may draw the following inferences with respect to the differential absorption of the two groups into the informal and formal sectors: where migrants are predominantly from ;I higher (landed) rural group, formal sector absorption must be high and the relative welfare shares of the lower urban quintiles improves; where migrants are predominantly from an increasing landless (tenant) rural group, informal sector absorption must be high and the relative shares of the lower urban quintiles declines. Row 2 suggests that this effect is strongest in the case of the second lowest quintile. falling off in size and significance on both sides as one moves towards

Rural-urban migration by strata? Landed farmers: Tenant farmers: MT,,

MA,

S,

-0.02’)~~ (pI.SX)

(I value) 2nd quintile:

S, O.O7Y$ (2.50)

(I value) 3rd quintilc:

S,

9; (J.Wll (0.4)

(/ value) 4th quintile:

0.0.521/ (1.45)

S, 0.000

(0.01)

(t value) 5th quintilc:

0.014 (0.60)

Ss -0.175

(t value)

-0.000 (4.07)

(-2.S.5)

O.IIS (2.35)

-0.001

(0.41)

Source: Based on Generalized Last Square estimate of system (7) and constraints (Ya) and (Oh). *The share indices represent the housing shares of urban population quintiles, which is calculated from the ccnsu\ data. as discussed in the text. tThe rural-urban migration is estimated as product of rural out-migration and urban in-migration. based on assumptions and methods discussed in the text. $The industrialization index is measured hy urban employment expansion in industry and mines from IY66 and 1976, relative to the 1’966 base. $Significant at a = 0.025 for onc-sidcd test. JISignificant at u = 0. I for one-sided tat. IThe constancy of this coefficient is the consequence ol the fact that shares must add up to I. See the constraint equation (Yb).

RURAL

TO URBAN

the first and the third lowest quintiles. In terms of the earlier theoretical logic, these quintiles are probably not as closely linked with the formal sector as the second quintile is. Thirdly, since S, S5 are indices of welfare shares and must add up to I, a reduction in Si S3is necessarily associated with an increase in SJ and/or S5, and vice versa. That this phenomenon is captured mainly by S5 and not by Sj, as seen from Table 2. can be explained by the fact that this quintile is probably an “intermediate quinfeatile,” carrying some of the socioeconomic tures of the third as well as the top quintiles. This would result in a “cancelling out” effect of the impact of migration on & and would explain the insignificance of the respective coefficients, though this remains speculative at this point. Furthermore, note that industrialization, as indicated by the growth of urban employment in the industry and mining has been equalizing since it has increased the share of the third and reduced that of the fourth quintiles. Finally, the highly significant coefficients of the lagged welfare shares indicate that the pattern of urban inequality profile in 1976 remains highly correlated with that in 1066. This indicates that even though migration and industrialization have significant influence on the pattern of urban inequality, neither factor proof the relative welfare duces a “switching” position of any urban quintile from 1966 to lY76.

6. CONCLUSION It has been shown that urban inequality tends to increase with migration when migrants are from a poorer, landless group and to decrease when they are from a better off, landed group. Measuring urban inequality by urban housing shares, this is demonstrated in the Iranian case, by a cross-sectional study of 57 Iranian cities and 21 rural regions for 1966 and 1976. In particular, it is found that the housing shares of the three lowest quintiles decline relative to the top quintile, when migrants come from a landless rural group, and increase when migrants come from a landed rural group. Among the lower quintiles this dual effect is strongest for the second quintile, and among the two top quintiles it is almost absent for the fourth quintile (60th to 80th percentiles). These findings suggest that the pattern of rural stratification has been transformed into urban

MIGRATION

IN IRAN

721

inequality through the intermediate role of ruralurban migration. A dual absorption pattern of rural-urban migrants in which the landless migrants would be absorbed into the urban informal sector and those from landed backgrounds into the urban formal sector could produce these results when the majority of population have mean income less than the mean income of the formal sector members (see Introduction to this paper for explanation). Previous studies of India (Mazumdar. 19X3; Banerjee. 1983; Harris, lY82) have pointed to the presence of such a dual absorption pattern when migrants are distinguished by their rural castes of origin. But the question remains whether this pattern persists if castes are replaced by differential access to land. Our findings on Iran shed some light on this question, based on the observed inequality pattern, but they cannot provide a definitive answer without a direct test of the dual abaorption thesis. The importance of a study which focuses on migration and urban inequality. as opposed to economy-wide inequality, is defensible on several grounds. First, the largest and increasingly important component of overall inequality stems from urban inequality, as shown in previous sectoral analyses of inequality (Fields, 1980). Second, migrants are likely to identify with their new urban surroundings after some time (Stark, 1984). Thus, the relative welfare of migrants within the urban sector is gradually perceived as more important than their possible welfare improvements vix-ri-vis the rural sector. Finally, problems of urban overcrowding and growth of the shanty-towns in many Third World cities render an analysis of this type essential to the urban policy issues. In the area of measurement, a specific contribution of this paper has been to construct an index of urban welfare inequality from census data, based on urban housing shares, which can be used in the absence of systematic income distribution data. While this index may be only a proxy for income distribution, it is likely to be much more sensitive to the urban crowding effects of migration than is income data and thus to serve as a more appropriate index for urban housing policies. On the other hand, this measure would tend to underestimate the extent of inequality since housing for the poor and the rich are quite distinct and this distinction does not enter into our measure of housing share which treats “rooms” as a homogenous unit of distribution.

722

WORLD

DEVELOPMEN

NOTES I. For cxamplc. Flclds (IYXO. pp. II-Cl I.?). in his detailed survey of the literature on 5cctoral decomposition 01 inequality concludes that (I) intr;l-scctoral inequality is larger than inequality bctwecn 5cctors and (2) that intra-urban incqualiiy IS grcatcr than intr;lrural inequality. 2. Stark (IYXJ) argues that relative deprivation can bc used to explain migration. and that the welfare 01 migrants incrcascs as a result of migration. Howcvcr, he also argues that. over time. the migrants’ rcfcrcnce group may shift to their new urban environment. II relative deprivation is now pcrccived ~.i.s-(i-~~i.s the nc\h urban sector, the relative welfare of migrants in this sector bccomcs a critical point for analysis. 3. Urban dualim is the view that the urban labor market consists of a “formal” and an “informal“ sector. ‘l‘hc “formal” sector is charactcrizcd by high and downwardly rlgid wages, higher skill requirements and low unemployment rates. The “informal” sector. in earlier studies. was traditionally characterized by low, wages, low skill requirements and high unemployment (underemployment) rates. though recent studies of the informal sector distinguish between wage-earning and non-wage-earning job% within the formal sector (c.f. Banerjee, lYX.3). 4. See ‘I‘odaro (lY76) for a summary extensions to his original contribution.

of various

5. This conclusion is only partially accepted by Bancrjcc (19X.1) based on the fact that in the latter‘s study of Delhi education does influence the informal to formal sector mobility. though the overall magnitude is found to he rather small. 6. The influcncc of migrant’s resources on his search intensity and therefore on the probability of obtaining formal sector jobs has been analyzed by Mohtadi (IYXJ). 7. The importance of “sector of cmploymcnt” on the variance of urban earnings in Bombay has been found to dominate the influence of education, age, training and knowledge of English (Mazumdar. 1979). X. The “Khoshneshin” included both some of the richest and poorest peasants in each village (including rural laborers). Because of this heterogeneity and because not enough disaggregated data are available on the detailed composition of this group, its migration pattern cannot be adequately studied. However. the testing of the SMI hypothesis, in Section 1, does not require the study of all rural-urban migrants. Hence, while this group will he included for analytical purposes (Section 3) it will not be a key group in the examination of the SMI hypothesis. For a detailed study of the “Khoshneshin.” see Hooglund (1973). 9.

For detailed

studies of the Iranian

land reform,

set Lambton (196”)). Dcnman and Katouzian ( I YNI ).

(lY73).

Hooglund

(lY75)

IO. The other four options, which covered the rcmaining 15% of sharccroppcrs. arc cxtcnsivcly discus\ed in Lamhton (196Y). Howcvcr. since the focus of this study i\ on the landed and tenant farmers, the status 01 this group ~ as of the “Khoshneshtn” ~ will not be discussed hcrc. though they will be included in the modclling aspect of this analysis (Section 3). 1 I. See Yap (1077) for a survey of the literature. as well ax BancrCjce (19x1) for an examination of the effects of addltlonal explanatory factors. 12. IIowever, it may be speculated that in the prehcnt study the importance of educational differentials in the spcclal circumstance of landed and tenant farmers (the main groups of this analysis) is less important than that of access to resources, since both groups branched from :I single rural grouping (sharecroppers). and \ince the hypothesized landlessness of some tenant farmers. il verified, would be the result of institutional factors over a relatively short time period. I.?. This is based on ;I IYhh definition of geographic boundaries. Because of boundary changes between 1966 and lY76. thcrc wcrc a total of 1.3 provinces in 1076. In an claboratc process these changes have been adjusted for, by recasting the 1Y76 data in terms of lY66 definitions. wherever necessary. See Mohtadi (IYXZ). 14. Using the lYhC76 period for migration Ilou when the land reform period. itself. was lY62Z72 is delcnslblc on the following grounds: (I) The reform did not proceed in all provinces simultaneously and in many provinces its start was long after IYh2. (In particular. phase II of the reform, did not begin until lY6J and was implemented with various time lags in different protime lag vinccs.) (2) Without doubt, :I considerable must have existed between hemg granted an ownership or tenancy title and the decision to migrate by the landed or the tenant farmers. IS. The author wishes to thank an anonymous for pointing this out.

rcfcrcc

16. This is consistent with Lipton’s view (19X0) that the poor landless migrants tend to be “pushed” out of the rural sector, and the better off landed migrants. “pulled” by the urban sector. 17. Studies from other less developed countries generally suggest that rural-urban migration flow tends to be local (Merrick and Brito. 1974. for Belle Horizontc. Brazil; and Simmons, 1970, for Bogota, etc.) as well as highly correlated with Colombia, cultural and ethnic similarities (Greenwood, 1972-73: Huntington, 1974). Given the highly diverse ethnic and cultural hackground of the Iranian population across provinces. their rural-urban migration is likely to he also primarily intra-provincial.

RURAL

TO

URBAN

MIGRATION

IN IRAN

723

REFERENCES sector in the Banerjee, B.. “The role of informal migration process: A test of probabilistic migration models and labor market segmentation for India.” Oxford Economic Papers. Vol. 35. No. 3 (November 1983) pp. 399-422: Banerjee. B.. and S. Kanbur, “On the specification of estimation of macro rural-urban migration function with an application to Indian data,“Oxfbrd BulleGn ofEconomics and Starisrics. Vol. 43. No. 1 (Februarv I&I), pp. 7-29. Connell. J. et al., Migrarion from Rural Areus: The Evidence from Villanr Studies (Delhi: Oxford University PI&S, 1976): Denman, R.. The King’s Vista (London: Berkamsted Geographical Publications. 1973). Fields, G.. Poverfy. Inequality and Development (Cambridge: Cambridge University Press, 1980). Greenwood. M., “The influence of family and friends on geographic labor mobility in a less developed country: The case of India.” Review of Regional Studies, Vol. 3. No. 3 (Spring 1972-1973). pp. 27-36. production and labor Harris, .I. A., “Small-scale markets in Coimbatore,” Economic arld Polifical Week/y, Vol. 17, No. 24 (June 1982). pp. 993-1002. Hooglund, E., “The Khoshneshin population in Iran.” Iranian Studies, Vol. 6, No. 3 (Autumn 1973). pp. 229-245. Hooglund, E.. “Effects of Land Reform Program on Rural Iran,” PhD dissertation (Johns Hopkins Universitv, 1975). Study of Ethnic Huntington, H., “An Empirical Linkages in Kenvan Rural-Urban Migration,” PhD disserktion (Staie University of New York at Binghamton, 1974). Iran, Plan Organization, Iranian Statistical Center, Iranian National Census of Population and Housing, 1966. Provincial and County Volumes (Tehran: Plan Organization, 1967). Iran,Plan and Budget Organization, Statistical Center of Iran, National Census of Population and Housing, 1976. Provincial and Counfy I;blumes (Tehran: Plan Organization, 1980). Katouzian. H., The Political Economy of Modern Iran (New York: New York University Press, 1981). Lambton, A., The Persian Land Reform 196246 (Oxford: Clarendon Press, 1969).

from rural areas of poor Lipton, M., “Migration countries: The -impact on rural productivity and income distribution.” World Develomnenf. Vol. X. No. 1 (January 19HO), pp. l-24. ‘ Mazumdar, D.. “Paradigms in the study of urban labor markets in the LDCs: A reassessment in the light of an empirical summary in Bombay City.” World Rank Stajy Paper. No. 366 (December 1979). labor markets in the Mazumdar, D.. “Segmented LDCs,” American Economic Reviews. Vol. 73, No. 2 (May 19X3). pp. 254-259. Merrick, T.. and F. Brito. ‘IStudy of Labor Market in a Rapidly Growing Arca.” IBRD Summary report (Washington, D.C.: The World Bank. 1974). Mohtadi, H., “Internal Migration and Urban Inequaity: An Econometric Analysis of the Iranian Devclopmcnt Experience.” PhD dissertation (University of Michigan-Ann Arbor. 19X2). Mohtadi, H., “A micro-economics model of migration. job search and urban unemployment in less developed countries: Choice of search intensity.” Working Paper (University of Wisconsin-Milwaukee. 1984). Simmons. A., “The Emergence of Planning Orientations in a Modernizing Community: Migration. Adaptation, and Family Planning in Highland Colombia,” PhD dissertation (Cornell Univcrsitv. 1970). in L-DCs: A Stark, 0.. “Rural to urban migration relative deprivation approach.” Economic Development and Cultural ChanEr, Vol. 32. No. 3 (April 19X4), pp. 475-486. Todaro. M.. “A model of labor migration and urban unemployment in less developed countries.” Amrrican Economic Review, Vol. 59, No. 1 (March 1969), pp. 138-148. Torado, M., Internal Migralion in Developing Countries: A Review of Theory, Evidence, Methodology and Research Priority (Geneva: International Labor Organization. 1976): of cities: A review of the Yap, L.. “The attraction migration literature,” Journal of Developmenr Economics. Vol. 4, No. 3 (September 1977), pp. 239-264.

APPENDIX For each urban center the entries of the 10 x 10 matrix in question are denoted by N,,; with k referring to the family size and j to the number of rooms per dwelling (and with the city subscript suppressed for simplicity). The total number of individuals and rooms corresponding, respectively, to all j room dwellings are given by:

10 R, = kz 1 N, .k.

(A2)

Denoting the total number of individuals and rooms for each city with N and R respectively, the proportion of individuals and rooms in all j room dwellings (n, and r, respectively) are given by: n, = N, IN

(A31

r, = R, IR.

(A4)

10 N, = kz,

N, .k

(AI)

724

WORLD

DEVELOPMENT

As it stands 11,and r, do not yet represent an ordinal ranking of the urban population from those with the fcwcst to those with the largest number of rooms per person. This ih bccausc defining a given stratum by index j does not distinguish bctwcen diffcrcnt popula tion densities in diffcrcnt strata. The problem arises hecausc one cannot form a monotonic ranking of the index of r~~,n.s /XI ,x’~.Yo,~ hy a simple matrix wphich is obtained by dividing clemcnts. j, of it vector. .I, to elements, h, of another vector. K. To rcsolvc this problem. one may hcgin with a matrix. L. resulting from such a diviiion. This matrix is of the followinp form:

L=

l/I Ii?

?/I 212

;/lo

211;)

10/l 1012

::::::

(AS)

lt;/l‘o.

Let L’ rcprchcnt ;I vector formed from the ranking ol the elements. L,k. of matrix L in II non-dccrea
(I’,. I’:. ., I’,,, l’,. I’,, . I’,,,,,) = (I 10.11 l,,.,.. .. 15.1.I,,,.,. I,,,.. .>11.d = (l/IO, l/Y. ., l/5. l/S. l/4. ., IO).

(A())

elements in vector I,‘. one obtains: L” = (I”,, l”,. I”?, (1.2.3.4.5.h.h.7.7 ‘l‘hc matrices space arc:

Qkj

=h;j

k

(AX)

10).

(A’))

x

defined

in the reordered

It is now possible to calculate the two vcctora denoting, rcspcctively, the total numhcr of individuals and rooms associated with 1~ rooms per person, where 171is strictly incrcaxing elements of vector M defined carlicr. Denote thcsc vector\ a> N,,, and R,,. ‘I‘hen: N,,, = l’k, ,,,,,.,‘,,,,,and. R,, = sn,

N,

=ZP,,

\

, I,,,.,, , ,_,Ifor

(Al%) unique values for I”.

C,‘,v),,, ,,,,,,, and,

(Al%)

(AI&) identical values of I”.

(Al&)

where v rcprescnta the index for identical values of I” (e.g.. v = 6 for I’,, = I”, = 7. and v = 7 for I”, = I”,, = 7. etc.). Vectors N, and R, arc then used to form the housing shares of the five population quintiles. In order to do so. the fractions. )I,,,, of all individuals from the total urban population, and r,,,, of all rooms from the total number of rooms,. arc calculated for the welfare level of ITI rooms per person. This is as follows:

N,,,

r,,, = R,,D ,,I R,,,

(10 x IO) (10

and Qkj.

(AlO)

(AlS)

(A7)

To make use of the ahove procedure, define two matrices, P and Q. as the total number of individuals and rooms. respectively, corresponding to families of size k which occupy j room dwellings: Pkj = Nk,

rank (L’) = . . . . . 5X) (lx 100).

(AlI)

‘I,,, = N,,l;

_,m6,m,. ., WI,,) .. l/S. 114,. ., 10).

this rank vector a\ 1.”

., l”,,n,) =

Rm=~C?A. ,rv,. ,’ (I’x,,for 1,

With this reordering procedure. the elements of vector L’ represent a rearrangement of the 100 possible comblnationa of the number of room, per person from the smallest (1 room per 10) to the largest (IO rooms per I). However. due to the presence of “tie” clemcnts in the initial matrix L. one must dcfinc a new vector M consisting only of distinct values of 1’ in vector L’. As such, vector M. representing the number of rooms per person, is a vector of 5X strictly increasing elements (the number of distinct possibilities in the entries ol L’). This vector is:

M = (m,. ,,I:, = (l/IO. l/Y..

P,

Delining

It IS now necessary to rewrite P, and Qki in the reordered space. To do this replace the indice\ k and j, coming from the elements of vectors K and J, with k’ and j’ rcspcctively. coming from the elcmcnts of vector L’. Thus the pairs (l.l), (1,2). ., (1.10). (2,l). .. (7.10). _, (10.10) are replaced by the pairs (10.1). (Y.l). _.(1, IO) as seen in equation (Ah). This makes the new indices k’ and j’ functions of the ranking of the

(AI6)

Since the number of rooms per person. )u. is now a strictly increasing index, it can be used as a “pointer” to form the housing shares of each population quintile. This is done as follows: beginning with the sm;dlest value of 1~1(m = 0. 1). vectors II,,, and r,,, arc summed over the index m. up to the ,?I = r,ll where r,rI is such that II,,,, = 0.2 (corresponding to the first 20% of the urban population with the fewest numbers of rooms per person). At this point, the corresponding value of Y,,, = the housing share of the lowest J-r,,I . representing population quintile. S,, is recorded. Next. I,,, and ,I,,, are summed over the index m from the next value of ITI. (immediately following m,) until 111= n12. where ~112ih such that ,I,,,~ = 0.4. The corresponding value of r,,, = r,,ll represents the housing share of the lowest 40% of the urban population. The share of the second population quintlIe. S,. i\ then determined as r,,ll ~ r,,,,. The

RURAL

process is continued until the population quintiles are obtained.

shares Thus:

TO

of

URBAN

all

five

S, =r,,and

(A17)

S = r,“, - Trn(,Fl). i=2...5.

(A181

MIGRATION

IN IRAN

72s

The above procedure is carried out with the aid of a computer program written by the author. The calculations are carried out for the measurement of both S, (1976) and S, (1966).