ECONOMIC RESEARCH CENTERDISCUSSION PAPER

No.187The Role of Migration and Remittances
in a Growing Economy:
Perspectives on Social classes in Rural India and Bihar
by

KATO Mariko*

July 2012

ECONOMIC RESEARCH CENTERGRADUATE SCHOOL OF ECONOMICSNAGOYA UNIVERSITY* Visiting researcher at Economic Research Center, Graduate School of Economics, Nagoya University, and AssistantProfessor, Department of Economics, Seinan Gakuin University
Email : mariko_kato74@hotmail.com

THE ROLE OF MIGRATION AND REMITTANCESIN A GROWING ECONOMY:PERSPECTIVES ON SOCIAL CLASSESIN RURAL INDIA AND BIHAR

KATO Mariko,

Abstract

This study aims to examine the current changes of domestic out-migration fromrural areas and the impact of following remittances for the poorer rural households byeconomic and social strata, specifically focusing on the culturally and socially discriminatedbackwards, Dalits (in the official documents, expressed as “Scheduled Castes”: SC), during
India’s remarkable economic growth from 1990s to the latter half of the 2000s decade, byusing comparative household data sets provided by National Sample Survey Organization(NSSO) for those two decades. This paper also tries to measure the impacts of the recent
economic development on Bihar, not only the poorest state but also of the fastest growing
state in the 2000s.
In the 1990s, at the introductory stages of economic liberalization, the average percapita consumption expenditure (MPCE) levels of households which receive remittancesfrom out-migrant to within India were much lower than non-migrant households.
Conversely, in 2007-08, at the point of highest growth on Indian economy ever, there has
been the evidence that remittances by out-migrants improved economic conditions ofpoorer households, since the levels of MPCE of out-migrant households with remittances
are significantly higher than those of non-out-migrant households for all social classes.
SCs also have benefitted from remittances via increased mobility, and this tendency is very
notable in rural Bihar, where the most socially and economically backward group are
better off by receiving remittances. In Bihar, the level of MPCE of agricultural labour SC
households, the most backward social/economic group, with remittances far exceeds the
MPCE level of the same types of households without remittances.
1

As for thedeterminants of out-migration, rather than pull factors, it appears that “rural distress” and“social distress” worked as push factors to be most influential to the rural poor
out-migrants who make remittances.

Such rural distress and relative

backwardness in a country could have been worsened because the recent economic growth
has accelerated regional disparities.

However, much increased remittances following

out-migration by social backwards could play a role as means of poverty alleviation and asa means of possible empowerment for their backwardness.
Keywords : out migration and remittances, India and Bihar, Scheduled Caste,
backwardness, poverty alleviation
JEL classification: J61, O15 and R23

2

Introduction
There are debates on the causes of migration from rural areas during the economic growth period in India.
The traditional view emphasizes the aspect of rural distress which works as a “push factor” to push the poor
people out from the economically backward areas. In such cases, relatively limited numbers of rural poor,
who are relatively better off among the poor, can move out, while poorer and the poorest are often left out
from the opportunities to migrate-out and thus stay put in the rural areas, due to their lack of mobility, interms of being able to afford moving costs and the availability of useful contracts, contacts or outside
information. However, in response to the rapid economic growth (even to the point of boom) which
requires an increased labour force and the number of newly available jobs in the industrial sector since theeconomic reform period, the current characteristics of rural out-migrants look to have changed to show amore positive side to rural out-migration. As the whole economy grows, the speed of economic growth in
the urban industrial areas becomes much faster than before, which widens the rural-urban economic gap.
It may contribute to relative immissarization of rural areas via increased inequality between those regions.
Moreover, the pattern of Indian economic development is characterized by the insufficient creation of
economic demand and adequate jobs to meet the needs of huge labour force of India, and growing concernsand problems of unemployment have recently emerged in this globalization era (Sen [2007]). However,at the same time, recent Indian economic growth may have also created more access for the rural poor
people to improved opportunities in advanced areas. Now, the question is whether lower or lowest
earning rural household groups, such as economically and socially backward households become moremobile or are still left out from the percolation of recent economic development in the areas in rural India.
This study tries to follow the current changes of population outflow from rural areas in the form of
intra-state migration, and to measure the role of remittances for the rural households. In order to specify
the effect of migration and remittance on the households that are not supposed to be within the “better-off”
strata, this paper specifically focuses on the economic condition of “Dalits,” the rural SC households, that
account for more than 20 percent of rural population, and other backward class households (OBCs), during
the growth period from the early 1990s to the latter half of the 2000s decade in India. Actually, thepoverty incidence of SCs is quite high, 48 percent (1993-94) and 35 percent (1999-00) of rural SCs live
below the poverty line while overall percentage of rural people below poverty line is 38 percent and 27
percent in each period (Planning Commission). Also, it is worth analyzing the pattern of migration by theSCs or other backward classes in the least economically developed region, Bihar, where intra-stateout-migrants as agricultural labourers to Haryana and Punjab used to be very common, but currently thedestination of the migrants in the 1990s shifted to the industrial areas, such as Maharashtra and Delhi, in the
2000s. By comparing the different data collected by the National Sample Survey Organization (NSSO) in
the two different period, 1993 and 2007-08, this article analyzes the dynamics of changing intra-state3

migration and the subsequent remittances by economic and social strata, particularly focusing on rural SCs
and non-backward classes.
1. Research Background of rural-urban Migration: India and Bihar
The classic economic analysis sees that rural to urban migration is induced by the widened economic gap
between rural and urban areas due to high economic growth in the urban sector (Harris and Todaro [1970],
Lewis [1955]). Actually, in the Indian case, the contribution of the primary sector to the GDP is falling:
37% in 1981-82, 32% in 1991-92, and 25% in 2001-02. On the other hand, the percentage of the rural
population to the total population is still high: 76.7% in 1981, 74.3% in 1991, and 72.2% in 2001. In spiteof the rapidly falling importance of the rural economy’ to total GDP, the ratio of the rural population does
not accordingly decrease, and instead remains very high. That means that there is a relative worsening of
the rural economy to the urban economy.

Such rural distress caused by inequal growth between the ruraland the urban sectors contribute as “push factor” for the rural poor people to migrate out, while urban andeven rich rural prosperity induces the migration out from the rural to the urban sector by showing high real
wages, as a “pull factor”. In 1970s Indian rural villages, the rural push factor has been considered as main
contributor to rural out-migration (Connel et al.[1976]) and remittances from pushed rural labour force
even worsens the rural-urban gap because the amount of remittance is far from sufficient levels to make up
the rural-urban disparities (Lipton [1977]). Studies from the urban side also follow the path which leads torural-urban economic dispersion and further disparities even within rural people. Economic analysis on
the wage data of in-migrants to Delhi showed that the mobility to an urban area like Delhi is strongly
subject to the availability of pre-contract before migration, and information about the urban labour market.
Thus, the mobility and the return of in-migration to Delhi areas for those from rural poor households arelimited, but for those who are already better-off with good urban contact, migration is fairly beneficial interms of wage (Banerjee [1984],[1986]).
Rural out-migrants often make remittances to their household back at home, and the role of remittances
may differ by the characteristics of the households, such as by origin, region, income strata, and social
environment. For rural households in India, remittances and migration appear to work as means of risk
aversion of shortfall of household income, since migration itself diverse economic risks by relocatinghousehold members in regions under different climate conditions and remittances from migrants make up
the shortage, fluctuation, or low level of households’ income which is heavily influenced by weather(Rosenzweig and Stark [1989], Dréze and Sen [1989]).
On the other hand, focusing on regional characteristics, different perspectives, which could be described as“productive” ones, on the determinants and functions of migration and remittances emerge. In Kerala,4

where historical labour movement to foreign countries has long been known, migration and remittances
have contributed to poverty alleviation and accumulation of enhanced human capital, such as education in
those areas, because the cheap and educated labour of Kerala has been long favoured by Arabic countries(Joseph [1988], Zachariah et al. [2003], Banerjee, et al. [2002], Ramachandran [1997], Irudaya Rajan, et al.
[2007]). In spite of such a positive link between education level and remittances in South India, at an all
India level, it is strongly suggested that there have been negative links between households’ consumption
levels and educational levels, as the households’ possibility of receiving remittances increases when
migrants are literate, by NSS data in 1993 (Kato [2010]).
In terms of productive aspects relating to migration and remittances, recent regional micro-level studies also
support the positive effect of migration on the poorer households. Opportunities and benefits of migration
expanded to the many rural poor to alleviate poverty incidence by improving their living conditions(Deshingkar and Farrington [2009]). Urban research in Delhi slums supports that in-migration by thepoor help to stop downward income mobility at least, despite rejecting income upward mobility by
migration (Mitra [2007]).
As for lower castes, such as Scheduled Castes (SCs), it is still reported that most SCs remain poor and also
they are excluded from the opportunities to migrate because of discrimination (Desingkar and Start [2003]).
However, looking at the migrants from Bihar, which has been long known as the least economicallydeveloped state in India, out-migration from rural Bihar appears to gain importance for those social
backward classes.

The state also has a long history of migration from the colonial period (deHaan[2002],Awanish[2009]) and the main players to move out from Bihar were distressed rural landlesspoor towards agriculturally advanced rich areas like Haryana and Punjab in the 1980s (Singh et.al[2007]).
With the coming of the age of economic reform since 1991, the destination of migrants and thecharacteristics of migrants seem to have changed. The destination of migrants shifted from rural Punjab
or Haryana to the urban areas such as Dehli, Mumbai, and Goa (Awanish[2009]). The most notable pointof population movement from Bihar is that many males who belong to the social backward classes like
Dalits, Extremely Backward Classes (EBCs) become mobile, as did rural males from the economic
backward households, rural landless households, and Muslims (Desingkar et. al [2006]). It is naturally
supposed that there is caste discrimination in the job market for those backward classes to enter it via theofficial channel, and most of them are non-skilled and less educated. Accordingly, most of SCs and otherbackward classes from rural Bihar mainly engage in non-skilled jobs such as agricultural labour, casual
construction work, brick kiln work, and rickshaw work (Desingkar et. al [2006]). Most of the rural people
are landless, as 75% of rural households are landless or marginal landholders, according to the NSS
1999-2000, and SCs are certainly the least endowed of the rural population, in terms of social andeconomic resources. Moreover, the SCs are not able to choose jobs, due to caste discrimination. In
5addition to the economic stagnation of the state and unequal land distribution in rural areas, social pressure
mounts on the SCs and other backward castes in Bihar. Therefore, excess rural distress in Bihar looks tobe the main factor to push poor people and SCs / social backwards out from those areas.
However, such an argument of excess rural distress in Bihar may not be enough to give reasonable
explanation for out-migration by socially/economically backward people.

Some studies argue that

out-migrants from rural Bihar are from the regions with relatively high agricultural output (de Haan
[1999][2002]), and, moreover, some journalistic sources suggest that Bihar witnesses increased rural
out-migration by SCs as the economy of Bihar has dramatically improved, after Nitish Kumar’s
appointment as the minister of the state in 2005. Actually, Bihar’s growth rates of Gross State Domestic
Product (GSDP) increased by 11 per cent from 2004-05 to 2008-09, led by the growth of the construction
sector, whose contribution to the growth is estimated at 29%, but the contributions of the agricultural sector
and agricultural-related sector is low, but positive, at 7.1% and 7.7% respectively (Das Gupta[2010]).
Therefore, not only “rural distress” but also recent improvement in the economy may have acteed to
expand the mobility of the rural poor and social backward in the state by enabling them to afford theexpense to migrate-out. In addition, some studies claims that it is a symbol for the SCs and social
backward households to migrate out from Bihar to get an outside job as freedom from the serious social
constraints on them (Awanish [2009]). If the likes of SCs gain more mobility as the economy grows, such
rural out-migration does not necessarily reflect rural distress and does not accompany inequalization of SCs
in rural Bihar. It would rather imply the emerging importance of expanded opportunities that could givepotential empowerment to those socially and economically backward in rural Bihar.
This study focuses on the recent changes in intra-state migration and its effect on the ecpmp,u pf rural
households’ in the migrants’ origin, by focusing on social strata, particularly rural SCs and other backward
classes, from the early 1990s to the 2000s, in order to measure the influence of economic reforms on people
in rural India and SCs in Bihar, in those periods.
1.2. Data
In this paper, raw data from large sampling data that are collected by the Indian Government Body,
National Sample Survey Organization (NSSO) is used. For the purpose of measuring changes of
migration in different periods in the 1990s and 2000s, two data setts provided by NSSO are compared foranalysis; first, the 49th National Sample Survey, 49th round, Sch.1.2 “Housing and Migration Particulars”
whose survey period is from Jan – July 1993 and whose content data collects about 76,000 sample
households in rural areas; and second, 64th NSS, Sch.10.2. “Employment & Unemployment and Migration
Particulars” whose survey period is from July 2007 – June 2008 and whose content date collects 79,000
6household s in rural areas.
2.

Changes of Migration: between 1993 and 2007-08

2.1. Overview of rural Migrants
How many people migrate out from rural areas to another state or overseas? How poor / how rich are thosehouseholds which sent out-migrants to outside destinations? Are there any changes between the early 1990
and 2000s? In order to clarify those points, some dynamic figures in rural India are shown in Table 1.
Table 1. Migration Rate (Household base) within 5 years
Rates of household with any migrant within 5 years(migration household rates = sample household number / total sample household number)
1993(49th NSS)

2007-08 (64th NSS)

Male out-migrant

0.143

0.139

Female out-migrant

0.013

0.027

First, it should be noted that there are big differences in the way of data was colleced in terms of categories
between the 49th and 64th survey. The objective of the 49th NSS was to collect data of detailed
characteristics of migrants who migrated out within 5 years: e.g., when they migrate out, where they firstmigrate out, what their educational status is, and so on. On the other hand, the main concern of the 64th of
NSS lies in the characteristics of the current household members though the data also collect information ofout-migrants within 5 years. In the 64th survey, where migrants first migrate out is not clear, but where
those migrants currently live is provided. Thus, it is extremely difficult to compare the absolute number
and migration rates on the same basis, yet it appears still useful to show those figures as good approximatesto understanding the rough picture of current migration. Both estimates show that at least 1 out of 7 rural
households have sent out male migrants somewhere, which is high propensity of out-migration, and it canbe safely said that out-migration by males far exceeded that of females during the two periods.
Why do people migrate-out from rural areas? Graph 1 shows the reason of migration throughout those two
periods by sex. The most dominant reasons for migration by males are related to employment, as around 40
percent of male migrants in the 49th survey and more than 50 percent of them in the 64th survey
out-migrated for the reason of “In search of employment / better employment”. Also, around 25 to 30
percent of male out-migrants move for the reason of “Transfer of service / contract / take up employment”
in those periods. Therefore, it can be concluded that most of out-migrants from rural areas are motivatedby job-related reasons.
7On the other hand, most of the reasons for female out-migration are marriage-related. This reflects thecultural background based on the Indian social system, where in-caste marriage and hypergamy arestrongly preferred among Hindu families (Kato[2009][2010]).
Graph 1 Reason for migration by sex

Others64th NSS Female

Movement of
parents/earning
member64th NSS Male

Marriage

49th NSS Female

Studies

49th NSS Male

Transfer ofservice/contract/takeup employment
In search of
employment/better
employment

0

0.1

0.2

0.3

0.4

0.5

0.6

Table 2 shows the destinations of male out-migrants. Out-migration to outside states in India looks frequent
for the rural household throughout these periods. As noted above, it is not easy to compare these two setsof data, but the increase in intra-state and overseas migration is observed in the estimated figures. Thisshows that rural people in India became more mobile in 2000s, by experiencing rapid growth in this period.
Table 2. Destination of Male Out-Migrants within 5 years: within India or overseas?
Destination of Male Migration Rates from rural India: within 5 years
1993 (49thNSS)

2007-08 (64th NSS)

Estimated rate

Estimated rate

Overseas

0.006

Intra-state

Overseas

0.044

Intra-state
0.043(Within India)

0.080(Within India)
Within State

-

0.168
(Intra-district)

Estimation is based on the number of households. migration rates= household with male migrants / total rural households. The definition of “overseas” and“intra-state” differs in the 49th and 64th. In the 49th, overseas migrants are collected as “migrants gone overseas within 5 years and no information on theirpresent residence”. On the other hand, in the 64th, overseas migrants are collected as “migrants gone somewhere within 5 years and their present residence isoverseas”.

8According to the 64thNSS, as it provides some information on out-migrants, it is estimated that 43.7 percent
of persons who migrated for job-related reasons within the last 5 years have come back to their homebecause they currently reside in the same district of their state of origin (Table 3). This means that the
job-related out-migration by males is characterized as quite a temporal one. Conversely, since femalemigration by marriage is usually not temporal in nature, more than half of them move to another district
within their home state, as shown Table 3.

Those very recent figures of higher rates ofmarriage-motivated female migration to “other district nearby” are still consistent with the tendency thathas been argued in the notable research on marriage in rural India because of economic and cultural
conditions which females would face in rural India (Rosenzweig and Stark [1989]).
Table 3. Estimated return-home rates: based on the present place of residence of people who
migrated within the last 5 years (64th NSS)
same district / same stateother district / same state

Male: for job-related reasons

0.437

0.271

Female: for marriage

0.187

0.512

2.2. Economic status of the rural household: households with out-migrants VS. households without
out-migrants
The main concern of this comparative analysis on migrant households is whether there are differences inthe economies of rural households, with out-migrants and households without. Consequently, the levelsof Monthly Per Capita Expenditure (MPCE) as a key economic indicator of Indian rural households arecompared between these two periods.

9

Table 4. Estimated Mean MPCE of Rural Households by Out-migration types: With or Without
Remittances
Mean MPCE of rural households by out-migration types: with remittances and without remittances i
49th NSS （Below MPCE 400Rs）

64th NSS （Below MPCE １500Rs）
No
No

Domestic out-migrants

Overseas

Out

Domestic out-migrants

Overseas
Out migrants

migrants

SC

OBC

Others

With

No

With

No

With

No

With

No

RemittanceRemittanceRemittanceRemittanceRemittanceRemittanceRemittanceRemittance

185.4

197.4

242.3

202.1

187.2

715.6

735.2

789.6

653.8

650.8

(4.13)(9.95)(15.50)(25.85)(4.45)(25.43)(31.36)(61.53)(52.48)(4.86)

-

-

-

-

-

770.9

756.9

819.6

906.1

731.5

-

-

-

-

-

(19.62)(21.31)(31.10)(37.58)(3.77)

202.3

225.8

238.8

257.8

216.4

858

923.1

891.9

1006.4868.3(2.94)(5.35)(5.53)(10.25)(3.19)(22.09)(23.26)(47.82)(64.91)(4.71)

Standard deviation in brackets

Table 4 shows that the mean MPCE level of the rural households with remittances from out-migrants
within India in the 49th survey is, again, apparently lower than the one without out-migrants, considering
the standard deviations of approximately 13-22 percentage points. Nevertheless, in the 64th survey, for allsocial groups, the mean MPCE of the rural households with remittances from domestic out-migrants, aresignificantly higher than the mean of households without out-migrants (at a 1 % level of significance), by
about 5-15 percentage points. In the 49th survey, it appear that remittances from out-migrants overseas,
which incurs high-costs for migrating, only improved household consumption levels.

At present,

however, the consumption levels of domestic out-migrant households have remarkably improved even forSCs. Also, these figures imply possible income mobility and reversal of households’ economic conditions
in rural India, via migration and remittances, during the rapid economic growth period. This is notnecessarily consistent with the idea of push migration by rural distress.
As discussed above, what has made a difference on the economic level for the rural households looks to bewhether they received remittance or not in the recent years. Although data on the amount of remittances
is not available in the 49th survey, the 64th survey included that its scope. The estimated average amount ofremittances received by rural households by social classes is shown in Table 5, and the estimated averageamount of remittances received by rural households close to poverty lines by social classes is shown in
Table 6 below. Preliminary estimates of poverty line MPCE in rural India in 2007-08 is 461.84 Rs(Planning Commission). In order to consider the level of poorer households and the impact of the amount10

of remittance received by rural poor households, estimated average MPCE levels below poverty lines isalso shown in Table 7.
Table 5.

Estimated average amount of yearly remittances by social classes: 64th NSS
Average amount of remittances

Estimated standard deviations

SC

21197.27

330.87OBC

20799.03

327.47

Others25053.39

487.39

Table 6.

Estimated average amount of yearly remittances by social classes below poverty lines:

64th NSS
Average amount of remittances

Estimated standard deviations

SC

9766.12687.09OBC

12526.56

362.285

Table 7.

Estimated average Monthly Per Capita Expenditure below poverty lines by social

classes: With or Without Remittances, 64th NSS
with remittances

without remittances

SC

OBC

374.90376.81(3.50)(1.98)

386.94385.78(2.13)(1.446)

Note: Estimated standard deviation is in brackets.

Estimated figures of remittances received indicate that average levels of remittances are high enough tocause a crucial difference between households with remittances and households without remittances, if they
are below the poverty line. The average amount of received remittances to the SCs are lowest among all
the social classes, which reflect their least celebrated social positions (Table 5). Looking into the very
poor people below the poverty line, the estimated average amount of remittances for the SCs below poverty
line do not show little decrease in spite of remittances for OBCs below poverty line going down to less thanhalf of the average amount of remittances received by all OBCs (Table 5 and Table 6). Considering thelevel of poverty lines, this yearly amount of remittance around 120 thousand rupees, almost equivalent to 3
years’ expenditure per person, is extremely huge and influential to rural poor households. This means that,for SCs, the main beneficiaries of remittances are very poor households as os naturally supposed (because11

of their social classes), but on the contrary, for other types of social classes, mainly remittances are sent torelatively better-off rural households. However, estimated MPCEs of rural SC and OBC households
below poverty lines do not show significant differences between ones with remittances and ones without
remittances. Therefore, there is no clear evidence to deny the traditional argument that only “better-offpoor” are mobile but the poorest will stay still unable to make up their shortage of income, as seen from theanalysis on an all-India level.
2.3.

Factors of receiving remittances by rural household over all major states

Discussed as above, remittances sent to the rural household look to have seriously affected to theireconomic level and remittance becomes very important income source as possible means to improve theirliving conditions. As seen so far, amount of remittances significantly differs by social classes in rural
India, so it is naturally supposed that the household characteristics would be crucial factors for the amountand possibility of remittances received.

This section tries to find relationship between some key

household characteristics and remittances received by those households.
Supposing the model in which the amount of remittances is affected by household characteristics such associal classes, residential areas, mainly engaged work, the regression model and to be tested here is:R  Y   D 
ri

i

i

i

Rri: yearly amount of remittances received by household i in rural areas
Yi: realized monthly per capita consumption level of household i in rural areas
Di: social and economic characteristics of household i in rural areas
Regression results using NSS 64th, which first ever provides the information on the amount of remittances,are shown in Table 8 and Table 9 over non rich households whose MPCE below 700 Rs, as the estimatedmean MPCE level for the selected regions of major statesii is 778 Rs .

12

Table 8

Regression results on amount of remittances and household characteristics: poor

households below 500 Rs MPCE
coefficient
MPCE
household size

std errors

t-value

4.15

0.28

14.97

*

-668.95

116.20-5.76*

land dummy

Landless (less than 0.05ha)

1181.55

344.67

3.43*

religion dummy

non-Hindu-1058.28

344.76-3.07*

Dowry dummy

remittances used for Dowry

2162.21570.15

3.79*

house dummy

remittances used for house / estate

1376.73449.51

3.06*

savings dummy

remittances used for savings / investment

4576.90595.05

7.69*

social dummySC

660.44359.84

1.84*("Others" as base estimation)

OBC

2232.98

314.04

7.11*

regional dummySouth

3096.58472.25

6.56*(Central and West regions*East1386.08428.01

3.24*

as base estimation)

North

1548.37443.01

3.5*

household type dummy

agricultural labourer

1623.66

412.67

3.93*（self-employed in non-agriculture baseother labourer

1059.28556.93

1.9*

as base estimation)

self-employed in agriculture

2200.89406.53

5.41*

others

8579.81448.88

19.11*-1983.02

723.67-2.74*

const.
R2=0.15, sample no=7843* Madhya Pradesh and Gujarat as "Central and West", Andhra Pradesh, Karnataka, and Tamil Nadu as "South", Bihar, Orissa, andWest Bengal as "East", Haryana, Punjab, Rajasthan, and Uttar Pradesh as "North"13

Table 9 Regression results on amount of remittances and household characteristics: households
from 500 Rs to 700Rs MPCE
coefficient
MPCE
household size

std errors

t-value

7.62

0.57

13.48

*

-3718.16

472.24-7.87*

land dummy

Landless (less than 0.05ha)

3108.82

797.403.9*

religion dummy

non-Hindu-7511.54

667.37-11.26*

Dowry dummy

remittances used for Dowry

5099.77

1180.26

4.32*

house dummy

remittances used for house / estate9807.31800.3612.25*

savings dummy

remittances used for savings / investment

15173.50

894.5516.96*

social dummySC

382.99679.11

0.56("Others" as base estimation)

OBC-108.14541.33-0.2

regional dummySouth

7677.97867.92

8.85*(Central and West regions*East4475.40878.23

5.1*

as base estimation)

North8791.90847.73

10.37*

household type dummy

agricultural labourer-2894.02

930.07-3.11*（self-employed in non-agriculture baseother labourer-2047.75

1274.49-1.61*

as base estimation)

self-employed in agriculture-1797.67

793.70-2.26*

others8240.35

832.869.89*

2533.64

1357.63

1.87*

const.
R2=0.19, sample no=10083

Both of the regression results show that the higher amount of remittances received by landless andremittance is positively correlated to the consumption level among poorer households, so the remittancefrom outside could help rural households without productive asset. However, there is notable difference
between relatively poor, 500 to 700Rs MPCE, and very poor below 500 Rs, almost below poverty line.
Among the very poor households, below poverty lines, both of SCs and OBCs receive more remittances
than non-backward households and the amount of remittances for the agricultural labourer households ishigher than self-employed in agriculture. As discussed later, the agricultural labour households areusually landless and the poorest types of households, and SCs and landless are supposed to be the poorest
in the society. Those results indicate that severity of economic and social backwardness of household
characteristics looks highly correlated to the received remittances, and thus work as push factors ofout-migration. This logic clearly follows the argument of “push migration”. While there is someevidence of “pull factor” as the economic levels of backward households improved, this analysis support“push factor” much strongly affected to determine out-migration followed by remittances to rural poor
home.
14

3. Out-migration from the poorest states in India - Bihar: Migration and Remittance by SCs andother Social Backward Classes
3.1. Background of Bihar
As mentioned above, the main stream of frequent out-migration is initiated by males who are motivated by
employment and job-related reasons, and most of them make remittances to their rural home to come backin a short period. The increase in household consumption levels from 1993 to 2007-08 suggests that
out-migration may have helped social backwards’ economic levels in rural India. Even the analysis above
provides the evidence that poorest and much more depressed social and economic classes in rural areas
have become better-off via increased mobility and receiving huge remittance. Therefore, this paper tries
to focus on the “poorest of the economically poorest areas”, SCs in Bihar.
Recently, Bihar has become known as the “fastest growth state” in India as Bihar hit remarkable growth in
Gross State Domestic Product at 11.44 percent in 2008, and this is the second time to record over 11
percent growth since Nitish Kumar was appointed as Chief Minister of the state in 2005 . Such rapid
growth is owed to the growth in the construction oriented secondary sector, exceeding 11 percent growth,under Nitish Kumar’s initiatives (Nagaraj and Rahman [2011]). However, the economic level is still
lowest among all major states, as shown in Table 10, due to its long history of economic backwardness.
Table 10. Gross State Domestic Product by states in 2007-08
2007-2008 Per capita net state domestic product at factor cost - state wise (current prices)
Andhra

Tamil
Bihar

GujaratHaryana

Karnataka

KeralaMaharashtra

OrissaPunjabPradesh
40902

45773

59008

36266

43104

47051

26654

46686

West

23986

All
Delhi

Nadu
11074

Uttar

Rajasthan

40757

PradeshBengal

32884

32065

India
78690

33283

Source: Economic Survey [2010]

Such backwardness in the economy of Bihar os hugely attributed to the low productivity in rural areas. In
rural Bihar, whose population constitutes about 90% of the whole state, it is estimated that about 20 % of
the total rural population is SCs (20.1% in the 49th survey and 23.7% in the 64th survey) 56.4% is otherbackward classes, and pure “other” households are only 17.7 %, according to the estimation based on the
64th. The rest of the population is classified as “Scheduled Tribe”. Thus, the main composition of the
population in Bihar is socially and economically backwards, and this is part of the reason why Bihar has
been known as the “poorest state” in India. Backwardness in social classes is strongly related to theoccupations in rural Bihar, as well. Around (more than) 60 percent of SC households are categorized as“agricultural labour” without owning land for cultivation in both of the survey periods, (the 49th and 64th15NSS). Incidentally, the Planning Commission of India reports as an official figure that poverty incidence(population below the poverty line) of SCs in 1999-2000 is almost 60 percent. By applying thepreliminary all-India poverty line MPCE of 461.84Rs onto the 64th survey data, it is estimated that 52.4
percent of agricultural labour SC households’ MPCE level is below that line, and, SC households show thehighest poverty incidence in all types of rural households in Bihar. Using the same poverty criteria on the
64th data set, 49 percent of all SCs, 30 percent of all OBCs, and 19 percent of all “Others” live below that
MPCE line.
Table 11. Estimated rates of population below the poverty line of 461.81 Rs in 2007-08: byhousehold type and social classes in rural Bihar
agricultural labour

self -employed in agriculture

self -employed in non-agricultureSCs0.52420.37660.4323OBCs

0.41650.21840.2737

Others

0.46830.12690.1792Those arguments above, however, are based on the findings of all-India level investigation. Then, what
happens in more economically backward areas? In this section, considering such regional difference, it isaimed to measure the changes of the implications of migration and remittances to the most backward
people in the least economically developed area, rural Bihar, by comparing the data obtained from the two
NSS round in 1993 and 2007-08 as above. In addition to the argument in the section 1 of this paper, somejournalistic sources revealed that after Nitish Kumar’s appointment in 2005, there has been growth ofout-migration by SCs, who were unable to find jobs other than as agricultural labourers or highly
discriminated jobs such as cleaners (Livemint [2010]). According to the research initiated by the Indian
Institute of Public Administration [2010], they have found that more and more people from Bihar are
migrating out all over India to find short-terms job to earn extra money, and also have found that money
sent home as remittance is mostly spent for consumption and seldom saved, as based on the survey of 150
rural households in Bihar in 2010. It looks that there has been a coincidence of the benchmark years of
economic growth and the increase in migration in Bihar – welcoming Nitish Kumar’s appointment andeconomic growth in the area.

If such domestic out-migration by socially and economically backward

classes has been encouraged by recent economic development, migration affected by economic growth not
only worsens inequality but also could help the realization of self-empowerment for the least celebrated inIndia via increased mobilization of rural populations to outside areas.
Figures calculated by those NSS periods used in this paper also support the out-migration-prone characterof rural Bihar. Estimated out-migration rates to domestic destinations is 12.2 percent in 1993 and 15.7
16

percent in 2007-08, whose figures both exceed the average rate of migration rates of All-India (Table 12).
Table 12.

Estimated out-migration rates for rural SCs: Bihar and All-India Comparison
49thoutside the state, within India

64th
Bihar

All-India

Bihar

All-India

0.12230.03580.15720.1

3.2. Migrant households and Non-Migrant households by social classes in rural Bihar
Based on the special regional background of rural Bihar, this section tries to specify the changes of
economic conditions by social strata by using these two sets of NSS data from the 49th and 64th surveys.
In order to provide the simple pictures of changes between those two period, first, the average levels of
MPCE are estimated by social strata and occupation-related household types in Bihar and All-India.
Secondly, deducting the MPCE levels of the households which receive remittances made by out-migrants
within India from ones without out-migrants in each period.

The difference in MPCE between

households with remittances and non-migrant households obtained should be compared by social classes
and household types, both in Bihar and All-India. It should be noted that the figures displayed here are notdeflated by prices and thus it is not possible to compare the crude numbers in those different periods.

17

Table 13 Rural Estimated Mean MPCE by social group and household types: Bihar VS. India
Rural Household with "within India" out-migrant (A)
64th

49th
Bihar

India

SC

SC

Bihar

India

Non

Non

SC/ST

SC/ST

Bihar

India

Bihar

India

SC

SC

OBCs

OBCs

Bihar

India

Non ST

Non ST//SC/OBC

SC/OBC

Self employed in

118

182.9

148.6

231.8

497.1

678.8

655.3

788.2

802.2

920.1

non agriculture(15.4)(10.86)(17.24)(10.55)(36.32)(20.28)(22.45)(25.94)(67.05)(31.31)Agricultural labour

148.9

175.3

184.8

200.9

532.99

589.2

514.7

572.4

514.7

644.9

(8.89)(5.52)(8.14)(5.10)(15.60)(12.17)(9.56)(9.75)(50.18)(27.30)

178

218.1

252

278.7

614.3

656.5

512.5

726.1

396.5

764.8

(13.87)(13.63)(21.72)(13.66)(33.67)(27.38)(25.80)(40.23)(28.45)(55.38)Self employed in

176.89

214.2

200.6

232.6

523.7

656.6

610.5

740.5

787.8

998.6

agriculture(11.3)(10.01)(6.77)(3.59)(24.73)(13.44)(12.27)(10.29)(27.26)(26.17)

Others

197.9

214

186.8

235.6

537.2

741.3

642.6

869.2

711.6

1172.7(17.7)(9.13)(9.21)(6.45)(22.81)(20.66)(18.11)(27.90)(34.35)(53.08)Other labour

Rural Household without out-migrants (B)
49th

64th

Bihar

India

SC

SC

Bihar

India

Non

Non

SC/ST

SC/ST

Bihar

India

Bihar

India

SC

SC

OBCs

OBCs

Bihar

India

Non ST

Non ST/SC/OBC

SC/OBC

Self employed in

144.3

200.7

203.7

234.5

507

624

561.9

714.4

636.2

821.7

non agriculture(9.3)(3.53)(12.97)(2.88)(19.38)(10.53)(9.27)(9.86)(29.38)(14.76)

Agricultural labour

148.6

184.5

170.9

201.6

463.5

548.9

498.8

573.9

487.1

589.6

(4.53)(1.85)(3.62)(2.10)(7.41)(4.73)(11.15)(4.36)(27.56)(7.80)

197.5

226.4

212.4

281.6

432.6

620.2

498.8

688.9

547.2

798.2

(8.2)

(4.70)(7.30)(3.96)(14.59)(8.47)(11.15)(10.41)(35.77)(19.67)

Self employed in

177

203

208.9

238.4

558.3

657.3

625.3

696.9

658.7

828.2

agriculture(8.05)(2.42)(7.54)(1.59)(23.18)(12.28)(10.16)(5.25)(13.92)(9.10)

Others

142.2

206.9

185.9

246.8

536.9

810.1

610.5

1204.3742

1486.8(9.08)(4.61)(17.04)(4.07)(39.61)(28.24)(24.06)(121.95)(43.79)(125.61)

Other labour*Standard deviation in brackets

18

Table 14 Differences in the rural estimated mean MPCE of the households with out-migrants /without out-migrants: Bihar VS. India（A）-（B）
49th

64th

Bihar

All India

SC

SC

Bihar

All India

Non

Non

SC/ST

SC/ST

Bihar

All India

Bihar

All India

SC

SC

OBCs

OBCs

Bihar

All India

Non ST

Non ST/SC/OBC

SC/OBC

Self employed in
-26.3

-17.8

-55.1

-2.7

-9.9

54.8

93.4

73.8

166

98.4

0.3

-9.2

13.9

-0.7

69.49

40.3

15.9

-1.5

27.6

55.3

-19.5

-8.3

39.6

-2.9

181.7

36.3

13.7

37.2

-150.7

-33.4

-0.11

11.2

-8.3

-5.8

-34.6

-0.7

-14.8

43.6

129.1

170.4

55.7

7.1

0.9

-11.2

0.3

-68.8

32.1

-335.1-30.4-314.1

non agriculture
Agricultural labour
Other labour
Self employed inagriculture
Others

According to the estimates in Table 13, the levels of the mean MPCE for the all social groups and household
types are considerably lower in Bihar than in he rest of India. Moreover, the degree of the differences in
MPCE between Bihar and India widen for all types of households, from 1993 to 2007-08. Thus, there are
growing economic gaps between Bihar and outside Bihar in recent years.
Table 14 shows the differences in the mean MPCE between the households with out-migrants (A) and ones
without out-migrants (B). As for SC, there are no significant differences in MPCE in the categories inagricultural labour and self-employment in the 49th survey, even if standard deviation is considered.
Nevertheless, on the other hand, the estimates in the 64th survey provide a completely different picture: thevalue of (A)-(B) for the SC households engaged in agricultural labour in Bihar is positively large. Thismeans that the economic situation of SC households which sent out migrants to within India is far better-off
compared to the SC agricultural labour households without out-migrants in Bihar. A similar tendency iscommon for both of the SC and other backward classes in the category of any labour households - MPCE
levels with migrants are significantly higher than those without migrants in the 64th survey. In the 64th
survey, while even for “other” households (non-backward or non-STs) the average levels of MPCE with
out-migrants are relatively higher than non-migrant households. The difference in MPCE, (A)-(B), isbiggest for the self-employed in agriculture and also is the largest of all types of households and social classes.
The MPCE level of the household group whose combination is “other households” and “self-employed inagriculture” is the richest of all groups in rural Bihar, so, migration looks to have helped not only socially andeconomically backward groups but also the richest groups.
19In order to measure the effect of remittances, similar analysis is employed for the average MPCE levels ofhouseholds with remittance from out-migrants and ones without out-migrants.
Table 15 Differences in estimated mean MPCE of the households with remittances / without
out-migrants: Bihar VS India
Rural Household with remittances from "within India" out-migrants （C)
49th

64th

Bihar

India

SC

SC

Bihar

India

Non

Non

SC/ST

Bihar

India

Bihar

India

SC

SC

OBCs

OBCs

SC/ST

Bihar

India

Non ST

Non ST/SC/OBC

SC/OBC

Self employed in

113.1

177.6

134.1

223.8

484.9

650.52

665.2

715.2

734

850.3

non agriculture(17.33)(12.88)(19.18)(14.62)(44.63)(28.24)(30.60)(28.54)(62.33)(29.15)Agricultural labour

146.3

168.4

185

198.2

555

583.2

519.2

560.8

528.3

609.5

(5.02)(4.58)(8.97)(6.00)(17.87)(14.61)(10.82)(11.08)(60.40)(24.01)

185.3

213.9

221.7

244.6

620.6

573.7

536.1

682.8

399.3

683.8

(17.23)(14.45)(14.86)(11.70)(47.64)(28.63)(36.83)(40.00)(35.11)(49.57)

Self employed in

170.6

208

192.8

220.7

509

628.3

595.1

711.9

702.7

904.9

agriculture(9.82)(13.63)(8.27)(3.80)(28.14)(17.3)(14.36)

12.65(25.21)(24.14)

Others

195.5

213.4

181.6

229.6

526.8

651

599.4

784.9

703.4

1060.4(19.21)(9.96)(9.68)(7.12)(26.16)(16.91)(16.64)(28.51)(36.44)(61.60)

Other labour(C) - (B)
49th

64th

Bihar

India

SC

SC

Bihar

India

Non

Non

SC/ST

Bihar

India

Bihar

India

SC

SC

OBCs

OBCs

SC/ST

Bihar

India

Non ST

Non ST/SC/OBC

SC/OBC

Self employed in
-31.2

-23.1

-69.6

-10.7

-22.1

26.52

103.3

0.8

97.8

28.6

Agricultural labour

-2.3

-16.1

14.1

-3.4

91.5

34.3

20.4

-13.1

41.2

19.9

Other labour

-12.2

-12.5

9.3

-37

188

-46.5

37.3

-6.1

-147.9-114.4

-6.4

5

-16.1

-17.7

-49.3

-29

-30.2

15

44

76.7

53.3

6.5

-4.3

-17.2

-10.1

-159.1-11.1-419.4-38.6-426.4non agriculture

Self employed inagriculture
OthersTable 15 provides the differences in the estimated mean MPCE of the households which receive
remittances from out-migrants(C) and ones from which no out-migrants are sent out (B). By the estimates20

in the 49th survey, unlike the value of (A)-(B), the value of (C)-(B) is significantly negative for most of thesocial groups and household types (at 1% of significance). These mean that the remittance-receiving
households are worse off than ones without out-migrants and also that the initial economic conditions forthe households that sent out-migrants out are at considerably low levels. Thus, in the 1990s, the economic
level of out-migrant households is so low compared to other households that it can be interpreted as
evidence of “push-factor” for the poorer populations to be pushed-out from the rural areas of Bihar.
Contrary to these findings from the estimations based on the 49th survey, in the 64th survey, the value of(C)-(B) for SC agricultural households is far higher than the values for the other types of households, andalso, much higher than (A)-(B) for the same category of the household, SC agricultural labour. Therefore,
in 2007-08, the average economic level of the most backward social group, SC agricultural households,
is remarkably improved by remittances, unlike in 1993. Moreover, remittances look to have contributed
to the improvement of these household’ consumption level, as compared to the mean MPCE levels of the
SC households that just sent out-migrants out, and similar situations, in 2007-08. Such tendency has
never been found by the data obtained in 1993. Also, the differences in economies between rural Biharand other regions outside are still large enough in 2007-08 to support rural distress in Bihar, but the idea ofpure forms of push migration is not enough to give reasonable explanation since there is evidence that theout-migrant SC household is getting especially richer in recent years.
Unlike the 49th survey data, information on the amount of remittances is disclosed in the 64th survey and theamount of average remittances for the poor households in rural Bihar are estimated in Table 16.
Obviously, the worst-off group is SC agricultural labour households without remittances, as the estimatedmean MPCE level shows. However, the MPCE of rural agricultural SC below the poverty line, naturally
supposed to be the poorest, with remittances and recent out-migrants is higher than those without
remittances (at a 10% level of significance). As for other social classes, OBCs and Others, below thepoverty line, estimated MPCE shows a rather higher value for the households without remittance thanhouseholds with remittances, a despite significance level ithat s very low. Moreover, the mean amount ofremittance that is received by SC households is extremely high, taking account of their level of MPCE forpoor families. Recalling the result of an all-India level, as shown in Table 7, Bihar’s clear tendency, whichsuggest that very poor SC households with remittances are becoming better-off than those without
remittances, is never observed from all-Indian data. In addition, the estimates which are calculated in thesame way as Table 7 brings much clearer evidence of differences in economic conditions for the social
backward classes in rural Bihar from remittances (Appendix Table 3), since the poor backwards withremittances in Bihar are significantly better off than no-remittance households, while poor “Others”, notsocially backwards, are even worse off in they receive remittances.

21

Thus, it is concluded that rural SCs could benefit from out-migration most of all the social classes in Bihar
because of improved mobility in the recent years. However, it does not necessarily mean those SCs are
gaining wealth of it, as most of the remittance is used to make up the expense on the food purchases – 80
percent of SC rural households reply that the first reason to use remittance is for food items and no SC
households regard education and savings as the primary use of remittances (Appendix Table 4).
Therefore, remittances following out-migration for the SC households in Bihar look to play an importantrole as a means of poverty alleviation or as a means of easing their income liquidation, by allowing them toconsume more food.
Table 16. Estimated amount of average MPCE and remittances received by rural households
which sent out any migrant in the last 5 years in Bihar in 365 days in 2007-08: below poverty line*
F-value *Estimated average
Estimated MPCE

(difference between

Sample householdwithout remittancenumbers

amount of yearly
remittances received
and with remittance)*
SC

SC

OBC

OBC

OthersOthersAgricultural labour

370.017345.77

2.7

with remittances(7.16)(460.48)(10.10%)Agricultural labour

346.52-

without remittances(12.36)-

Agricultural labour

360.467958.36

1.8

with remittances(5.94)(428.16)(18.02%)Agricultural labour

371.8

-

without remittances(6.00)-All households***

381.7911491.8

0.5

with remittances(10.08)(940.26)(47.88%)All households

394.74-

without remittances(15.22)

-

208

69

239

109

128

36

* Using the national rural poverty line of 461.84Rs in 2007-08** Estimated significance of the difference in brackets.
*** “Others” in agricultural labour and the sample size is too small.

In former studies, it has been thought that remittances to the rural poor households are not enough to
improve their living conditions (Lipton [1977]) and very poor households cannot afford to migrate out fromrural areas because only richer and relatively well-off poorer households looked at are most likely to moveout from rural areas (Kato [2009][2010]). However, contradictory results which indicate that much worse
rural households, and even the most backward social/economic classes are mobile enough to be able to22earn outside income in order to make remittance, have obtained from these recent estimates using the dataof Bihar in 2007-08 in this paper. In addition, economic and social backwardness is strongly correlatedwith the amount of remittance received shown in the section 4. Bihar’s case shows clear evidence thatsocial classes like rural agricultural labour SCs, who are naturally regarded the poorest in the society, now
look not only mobile, butalso have even made up their consumption expenses with remittances by sending
migrants outside.
3.3. Remittances, household characteristics, and migrant’s profile for the poor in Bihar: analysis
This section tries to examine the factors and determinants of remittances by considering the characteristics ofrural poor migrant’s household and male migrant’s personal profile in Bihar. Assuming the model whereamount of remittances made by a male migrant1 is affected by household and his personal profiles,

R Y   D   P  
rij

i

j

j

ij

Rrij: yearly amount of remittances made by male migrant j and sent to household i of his origin
Yj: realized monthly per capita consumption level of household i of migrant j’s origin in rural areas
Di: social and economic characteristics of household i in rural areas of migrant j’s origin
Pij: personal characteristics of migrant j
Education levels are good indicators of human capital accumulation, so here educational levels are indexed toobtain proxy of average level of household education: not literate=1, literate below primary school=2,
primary to middle school=3, secondary school=4, higher secondary=5, above diploma=7.

1 See Appendix Table 5.

Sex ratio of out-migrants who make remittances is 96 to 97 percent is male.
23

Table17.

Regression analysis on amount of remittances, household characteristics, andmigrant’s profile for the poor in Bihar: below 400Rs MPCE, 64th NSS
coefficients
MPCE
average level of household education
migrant's education

std errors

t-value

19.12

4.40

2.17

*

-1146.03

493.12-2.32*-45.27245.88-0.18

marital status dummy (estimation base=single)

currently married-678.78417.22-1.63

migrant’s generation

20s

2024.54734.872.75*(estimation base=10s)

30s

6385.81725.29

8.8

*

40s

6080.82826.87

7.35*

social class dummySCs-4346.47

860.01-5.05*(estimation base="others")

OBCs-3362.59803.06-4.19*

household land holdings dummyless than 0.01ha

209.68479.980.44

agricultural labour dummy

agricultural labour-2534.76

450.78

-5.62

53.16

91.30

0.58

19.12

4.40

4.34

-146.56

612.04-0.24

household size
Hindu dummy (estimation base=non Hindu)

Hindu

const

*

*

R2 = 0.2684, sample =704

Table 18. Logit analysis on making remittances (=1), household characteristics, and migrant’s
profile for the poor in Bihar: below 400 Rs MPCE, 64th NSS
coefficients

std errors

t-value

MPCE

0.00

0.00

1.87

*

average level of household education

-0.96

0.13

-7.59

*

migrant's education

0.02

0.06

0.35

marital status dummy (estimation base=single)

currently married

-0.15

0.10

-1.41

migrant’s generation

20s

0.29

0.16

1.79

*

(estimation base=10s)

30s

1.06

0.17

6.17

*

40s

1.59

0.22

7.23

*

social class dummy

SCs

-0.11

0.22

-0.49

(estimation base="others")

OBCs

-0.19

0.20

-0.95

Household land holdings dummyless than 0.01ha

-0.66

0.12

-5.41

agricultural labour dummy

agricultural labour

-0.19

0.11

-1.69

-0.08

0.02

-3.76

*

-0.93

0.18

-5.3

*

1.60

0.50

3.2

*

household size
Hindu dummy (estimation base=non Hindu)

Hindu

const
R2 = 0.1000, sample =1888

24*

Besides the regression analysis of the amount of remittances received, logit analysis on making remittances(making remittances=1) by male migrants is also examined, in order to capture possibilities of making
remittances by social classes (Table 17 and Table 18). The latter table shows that there is no significant
difference in possibilities of making remittances by social classes among very poor households. Also,
household type as agricultural labour household does not affect the possibilities. On the other hand, theformer table shows amount of remittances significantly declines most if the migrant is SC and fromagricultural labour households. However, for both of the estimation, possibilities of making remittances andamount of remittances, migrant’s educational level does not affect them at all and even the average educationlevel of the household of his origin shows negative effects on them – indicating less remittances sent to moreeducated families and less possibilities for the educated families to receive remittances from out-migrants.
Households which have lower human and physical capital, logically worse off group, are remitting more sohuman capital accumulation is not important for them to earn outside, but the SC out-migrants appear to
make considerable lower remittances compared to others while the possibilities of remitting is indifferent
among all the social groups. Therefore, these results should be interpreted by the context of social andcultural perspectives that migrants from the backward households could face poorer conditions of evenoutside jobs due to social discrimination.
4. Conclusion
This paper aimed to measure the changes of the role of migration and remittances for the rural poor
households, particularly focusing on SCs and social backwards in India-wide and Bihar, in the recent
economic growth from the 1990s to 2000s. It was found that there have been significant increases inopportunities for the least socially and economically celebrated in rural areas, such as SCs and other social
backwards, as there is evidence that they became more mobile to migrated out to earn more outside of theirnatal place, between 1993 to 2007-08. While out-migrants to overseas only came from these well-off
among the out-migrant households in the 1990s, recent figures obtained by 2007-08 NSS data have shownthat within India, out-migrant households for all social classes even from the very poor families show
remarkable improvement in terms of economic conditions. This could reflect that current Indian economic
growth eased mobility of all kinds of people in rural areas, and this could support some aspects of pro-poor
growth of India recently. Furthermore, increased opportunities of migration and remittance in 2007-8 seemto have contributed to improve consumption levels of rural SC households most of all the social groups.
However, at the same time, these increased needs of domestic mobility and remittances imply that regional
economic disparities are rising within a country, because people would not move unless they think there isconsiderable difference in expected wage outside and realized wage at home, as the classical theories ofLewis and Todaro predict.

25

As for the argument on “rural distress” which pushes people out to economically better-off areas, thisarguments still looks applicable. However, it does not necessarily connote negative aspects, as the
economic conditions of SCs and other social backwards significantly improved by increased mobilization.
Also the evidence from Bihar’s case is - that SC agricultural labour households in Bihar, who are considered
to be one of the poorest social strata because of social discrimination, are the group that benefited most fromby the increased mobility and receiving remittances in 2007-08. Although mobility for the backward
classes look to be confined yet, more remittances sent by those migrants could play a role to give possible
empowerment to the SCs in rural Bihar, as the amount of remittances are considerably large enough to
support considerable part of their household consumption. This could reflect the importance of “getting outof Bihar” as very important for those social backwards. In future, going outside Bihar by social backward
classes may potentially affect the rigid social structure of rural Bihar. It should be noted that the growing
economic gaps between Bihar and other parts of India in these times of rapid economic growth might be
crucial to increase mobility and remittances of SCs, since the backwardness of Bihar’s economic conditions
gives strength to provide relative cheap labour to all parts of India and, of all labour.
While this analysis has limitation lacking price factors between different regions by applying appropriate
deflators, this paper has shown a rough picture of the role of out migration and remittance for the
economically and sociologically backward households in rural India and Bihar. It cannot be denied that
remittances and rural out-migration could contribute as a means of “inclusive growth” or positive paths of
distribution of economic growth in the era of globalization for the social backward like Dalits in Indiansociety.

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Appendix
Appendix Table 1.

Estimated composition of the population by social classes in rural Bihar
49th (1993)

64th (2007-08)

ST

0.089

0.022

SC

0.201

0.237

-

0.564

0.710

0.177

64531000*

82999000**

89.59

89.53

Other Backward
Non ST/SC
Total Population of the state
Rural / Urban Ratio*1991 Census, ** 2001 Census

Source: Kato [2011]

Appendix Table 2

Estimated composition of household types by social classes in rural Bihar

49th

64th

SC
self-employedNon SC/ST

SC

Other Backward

Non SC/ST

in
0.085

0.112

0.102

0.188

0.141

0.604

0.272

0.606

0.152

0.020

0.081

0.098

0.055

0.055

0.043

0.127

0.419

0.127

0.486

0.648

Others

0.104

0.100

0.110

0.120

0.148

Total

1.000

1.000

1.000

1.000

1.000

non-agriculture
agricultural labour

other labour
self-employedinagriculture29

Appendix Table 3

Estimated amount of average MPCE and remittances received by rural

households in Bihar in 365 days in 2007-08: below poverty line
F-value *Estimated average
Estimated MPCE

(difference between

Sample householdwithout remittancenumbers

amount of yearly
remittances received
and with remittance)*
SC

SC

OBC

OBC

OthersOthersAll households with

378.04

9988.95

6.4

remittances(4.66)All households

363.54-

without remittances(3.35)-All households with

386.1514548.7

8.02

remittances(2.79)(740.99)(0.00%)All households

375.91-

without remittances(2.31)-All households with

381.7911491.8

1.34

remittances(10.03)(940.26)(24.88%)All households

367.86

without remittances(6.69)

338(0.01%)
634

1156

704

128

546

Appendix Table 4 The “first reason” for use of remittances in rural Bihar: by social classes
SCs
for household consumer expenditure: on food items

0.799

education of household members

-

OBCs

Others

0.689

0.534

0.004

0.005

household durables

0.003

0.003

0.018

marriage and other ceremonies – 04

0.018

0.023

0.058

health care

0.031

0.078

0.083

others items of household consumer expenditure

0.084

0.112

0.137

for improving housing condition (major repairs, purchase of land and buildings, etc.)

0.018

0.043

0.040

debt repayment- 08

0.003

0.007

0.011

financing working capital

0.002

0.003 -

initiating new entrepreneurial activity

-

0.000

0.001

saving/investment

-

0.002

0.013

others

0.043

0.036

0.102

sample households

1026

2892

950

30

Appendix Table 5 Estimated ratio of making remittances by out-migrant out within 5 years by sex:
64th NSS, within 365 days
Male

FemaleAll India

0.95790.0421Bihar

0.96790.0321i Each of the figures is estimated by multipliers.
ii Here, major states are Madhya Pradesh, Gujarat, Andhra Pradesh, Karnataka, Tamil Nadu , Bihar,

Orissa, West Bengal, Haryana, Punjab, Rajasthan, and Uttar Pradesh.

31