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Economic Impact of Migration on a Rural Area in
Bangladesh
Pierre Yves Beaudouin∗
February 2, 2006
Abstract
The main objective of the paper is to analyze the effects of
migration on sending
countries. The objectives are to analyze the direct and indirect
effects of migration
on the migrant household income, to measure the opposed effects
and to discuss
the policy implication of our results.
The study is based on a Three Stage Least Squares estimator to
determine and mea-
sure the net impact of migration on the household income. The
empirical study
show a negative effect of the loss of labor on the total income.
However, this effect
is compensate by remittances sent home by migrants. When we
decompose the
income in three sources of income (farm, self-employed and
wage), we find these
two opposed effects for the farm income, but no effect of
remittances on wage in-
come and only a negative effect of migration for self-employed
income earned by
the household.
Keywords: Migration, Remittances, NEML, Bangladesh
JEL Classification: O15, R23, D13
∗Centre d’Économie de la Sorbonne, Université Paris 1
Panthéon-Sorbonne, CNRS, 106-112 boulevardde l’Hopital, 75647
Paris Cedex 13, France. Tél: +(33)144078243. Fax: +(33)144078337.
Email: [email protected],
Homepage:http://team.univ-paris1.fr/teamperso/beaudouin. Ithank
participants of the AFSE seminar “Economic Development and
Transition” on 19-20 May 2005 forhelpful comments.
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1 Introduction
The United Nations estimates the stock of international migrants
about 175 million in
20001. The proportion of migrants in the world is growing,
international migrants repre-
sented 2.5 per cent of the world population in 1960 and 2.9 per
cent in 2000. This trend
should not change in the next decades despite migration laws,
institutional structures and
tightening of procedures. Despite these small figures, migration
may have some important
developmental effects on developping countries. One of the main
canal of transmission of
migration on sending countries is remittances flow sent back
home by migrants to their
family.
Remittances are now view as a possible source to finance
development. Dilip Ratha
estimated that remittances going to developing countries
represents $150 billion in 2004.
This amount is bigger than foreign aid and is the first source
of foreign capital for many
countries. This flow of formal remittances2 from migrants to
their relatives in their
country of birth has exhibited a high rate of growth. The
doubling of remittances flow3
during the last decade has increase the study of
remittances.
The literature on the impact of migration is biased on the
receiving countries. Most
of the studies on migration are on the receiving countries’
economies and the effect on
sending countries has been neglected. One of the reason is the
absence of data on migra-
tion. But the increase of remittance flows last years, which is
one of the most important
channel of the impact of migration on sending countries, has
developed a recent growing
literature on the effects of migration on sending countries. If
non poor household partic-
ipate to the migration process, like it seems to happen, a study
without controlling for
selectivity bias will overestimates the impacts of
migration.
Most of the literature study the effects of migration only on
one part and the effects
of remittances in another part. Most of the time, migration
studies does not take into
account the effects of remittances when studying the effects of
migration on sending
countries. Likewise a lot of papers on the effects of
remittances does not take into account
the real or potential selectivity of migrant. As migrants may
represent a non randomly
chosen subset of the overall sample, an econometric estimation
by Ordinary Least Squares
(OLS) becomes problematic if migrant and non migrant individuals
differ systematically
in their productive capabilities (individuals characteristics
like education, experience,
1Figures are from the World Migration Report (IOM, 2005,
p.379)2Official statistics only take into account remittances flows
transiting by formal channels (bank or
wire transfer companies like Western union or Money gram). As
some surveys found that the part ofremittances transiting by
informal ways is important, remittance flows seems to be
underestimate. An-other limit of recorded remittance flow is that
because these figures comes from the balance of payments,by
definition they only take into account remittances send by overseas
migrants.
3This increase of remittances flow is more the consequence of a
improvment of the statistics than areal increase of money send back
to family.
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gender. . . ).
But there is few studies which take into account the linkages
between migration and
remittances. The size of remittance flows do not allow us, for
the study of the effects
of migration, to use the classical migration theories (Lewis,
Harris and Todaro) as these
theories did not take into account remittances in the migration
strategy. Analysis on
remittances does not take into account the determinants of
migration. The only way
to take into account in the analysis the migration decision and
remittances effects is to
use the NELM framework. This paper is based on the framework
developed by the new
economics of labor migration (NELM) which analyzes migration as
part of a strategy to
diversify the sources of income of the household in presence of
market failures (Stark 1991;
Stark and Bloom 1986). Futur remittance flows are taken into
account in the decision of
migration. And migration is viewed as an allocation of labor
like non-farm labor or crop
production.
Another particularity of this paper is to analyze the effects of
migration on all the
economic activities of the household and not only on a
particular sector, like it is done
in the previous literature. For example, Azam and Gubert (2002)
study the impact of
migration on the agricultural sector. There is also some
empirical study on the question
of the links between migration, remittances and business
creation. Amuedo-Dorantes and
Pozo (2002) showed that remittances has no statistically
significant impact on business
investment in the Dominican Republic
Using a particularly rich household survey on Bangladesh, the
objective of this paper
is to test the impact of migration on rural communities. Does
migration reduce crop
income and/or crop yield ? Does migration have an impact on
other sources of income ?
If yes, is it the same effects than for crop production ?
Finally, are the NELM hypothesis
validate ?
The paper is organized as follows. Section 2 presents the
framework of the NELM.
Section 3 presents the data used in this paper and describe some
descriptive statistics
of our household survey. Section 4 presents the empirical
strategy to test our model.
Section 5 presents the results and section 6 concludes the
paper.
2 Theoretical background
The literature on migration is not new. Already in 1889,
Ravenstein presents some
“laws of migration”. The analysis based on the work of Lewis
(1954) and Harris and
Todaro (1970) have permit the study of some aspects of migration
like the determinants
of migration, the effects of migration on the receiving
countries or the impact of migration
on the labor market of the sending countries. But unfortunately
theses models are not
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relevant to analyze the effects of migration on sending
countries.
The trademark of the NELM is that migration decisions are taken
by larger units of
related people - typically the househould, in the contrary to
neoclassical theories who
take the migrant as the unit of decision(Stark, 1991) not only
to maximize the expected
income, but also to minimize risks and loosen constraints
created by a variety of market
failures, including missing or incomplete capital, insurance,
and labor markets.
The persisting bounds between migrants and their households of
origin lead to a re-
ject of the individual-level migration decision model (like the
implicit migration model of
Lewis (1954) or Harris and Todaro (1970)) and to opt for a
household model. The house-
hold provides the funds to finance the cost of migration
(transportation, fees charged by
recruitment agencies, fees to obtain a visa and work permit,
maintenance while searching
for work. . . ) and in return, once migrants become established,
the migrant share a part
of its income by sending back some money and goods. These
repeated interactions lead
us to prefer household model to explain the decisions of
migration Taylor and Martin
(2001).
So NELM focuses on a particular kind of migration: the
short-term labor migration,
with migrants keeping strong tie with their family of origin and
who are expecting to
return rather than settle in the host country (Sana and Massey,
2005).
Taking the household as the unit of analysis is a mean to
understand migration as a
risk minimisation strategy.
The migration of labor is analyzes as an exportation of a part
of the labor factor
of the household. Migration is now an element of the
diversification of the sources of
income of the household. In rural area of developping countries,
crop is still the first
income generating activity. But crop production suffers from
many hazards (aléas de la
production et fluctuation des cours des produits agricoles).
The migration decision is no more view only as an income
maximisation but also as
a risk minimisation. In presence of market failures or missing
of credit and insurance
markets, household members should find an informal method to
insure against risk. Ac-
cording to the NELM, the migration of labor could be a method to
insure against risk.
An informal contracts are conclude between migrants and their
households of origin.
The second role of the migrant is to be a financial
intermediary. Remittances could
help to relax the liquidity constraint of the household by
increasing investment in new
technologies of production, for example by introducing high
yield varieties or by develop-
ing non-farm business (Massey et al., 1993). Migration by
generating some income can
help to increase the agricultural productivity.
For the NELM framework, income differential is no more a
necessary condition to the
migration contrary to the standard approach initiated by Lewis
(Stark and Katz, 1986).
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The theoretical model developed in this section is based on the
NEMT framework de-
veloped par Oded Stark. The analysis below is based on the works
of Rozelle et al. (1999).
The role of financial intermediaries play by the migrants can be
illustrated by the figure 1.
For simplification, we will use a unitary model of household. In
this model, the
household head is the only decision taker of the household.
Consider a household who
could invest a fix sum T̄ , such as agricultural land, labour or
factory. The household can
invest in two possible production activities with a difference
in returns; such Qi, with
i = 0, 1, the production of the low and high-return activity,
respectively.
The production of each activities depend on the investment and
of the individual
characteristics Z (for example education or age), Qi = f(Ti, Z).
The total income is
Y = g(Q0 + Q1). We can draw a production possibility frontier
(PPF) in a graph with
x-axis Q0 and y-axisQ1. For example, for a relative price of P
=P1P0
, the household will
invest all the sum T̄ in the high-return activity. The output
will be Q∗ = f1(T̄ , Zy) and
the household income will be Y ∗ = g(Q∗).
What are the effects of migration and remittances in this
framework ? In an envi-
ronment of perfect market, remittances have no effect on the
household production. The
household model in the case of perfect markets is separable
(Singh et al., 1986). The de-
cisions of production are independent of the dotations and
preferences of the household.
On a theoretical point of view, production and consumption
decisions can be analyzed
as being taken successively. Firstly the household decides its
production level, and after
it deduce its consumption level from the production level
decided before. The negative
effects of migration can imply a negative impact on production
(decrease of the labour
force has for consequences the decrease of the production). But
in this model, remittances
have no effect because as an simple income transfer
Remittances have an effect on the consumption of the household
by allevitaing the
budget constraint but have no effect on the production level of
the household4.
One of the main determinant of migtration for NELM is the
presence of market
imperfections. In presence of imperfections, the household is
credit constraint and can
only invest T̄ , with T1 < T̄ . For exemple, the household
owns an arable land. To cultivate
this land, the household needs to spend some money ex ante. The
credit constraint is
relaxed by the migration process. If the household could not
spend this amount because
of a lack of savings or imperfections of the credit market, then
the household production
would be constraint. The production constraint will be Qc1 and
Qc0. Migration could
4The remittances do not change the profit maximisation condition
which determine the level of pro-duction.
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Figure 1: Migration effects on production
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help to relax this constraint. In the presence of market
imperfections, migration could
be a solution. The model is non separable in presence of market
imperfections. Shadow
prices are evaluated for non-market activities. These prices
linked the production and
the consumption spheres. Remittances could have now some effects
on the household
production sphere.
The relaxation of the credit constraint could be represented by
a shift upward of the
resource constraint line Qc1. However the net effect of
migration is may be not positive.
The constrained output is Qc1 = f1(T1, Z) for the high-return
technology and Qc0 =
f0(T̄−T1, Z) for the technology with low productivity. The
constrained household incomeis so: Y c = g(Qc1 + Q
c0) with Y
c < Y ∗ the non-constrained income.
The overall effect is ambiguous as the partial effects of
migration and remitttances,
c(M) and c(R), are undetermine. However, we can make a
hypothesis on the value of the
coeeficients. The non-separability of the model involve the non
nullity of the coefficients
c(M) and c(R). Test if these coefficient are statisticalley
significant than zero would
be a support or an unfirmation of NELM. Few tests exist of the
NELM hypothesis.
However we can cite Lucas (1987); Taylor (1992); Taylor and
Wyatt (1996); Rozelle et al.
(1999); Taylor et al. (2003). This paper will test the NELM
hypothesis by developping
an estimator.
3 Empirical Methodology
As mentioned below, migration is a strategy to increase the
income of the household or to
insure the household against risks. But the household can also
diversify its production by
developing non-farm activities or taking an employment.
Migration is in competition with
other strategies to attract assets. But migration could
alleviate constraints on production.
In developing countries, household are usually constrained by
imperfection of markets like
a labor constraint, a lack of liquidity or or a credit
constraint. Remittances could have a
positive effect on the household by alleviating these
constraints. Migration can extend the
investment realize by the household. Migration can also help the
household to diversify
its activities.
Migration has a potential negative effect. The lost of labor can
decreases the pro-
duction of the household if the productivity do not increases.
Agricultural activities still
represents the major part of the income of the household.
However this activity can
particularly suffer from migration. This negative impact of
migration on crop production
has been found by Azam and Gubert (2004) in their study on the
Soninke migration and
also by Mochebelele and Winter-Nelson (2000) in their analysis
of migration in Lesotho.
Both papers conclude of a larger farm technical efficiency of
non-migrant household.
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Previous literature testing the effect of migration on sending
countries suffer from
some limitations. An approach used in the literature is based on
descriptive statistics.
Authors use the answer to the question of the use of how do the
household use remittances.
Surveys usually find remittances are used in housing
construction. However, remittances
can free up other sources of income that may be used for other
means. A survey which
find that the principal use of remittances is in the housing
construction can conclude of
an unproductive use of remittances. But because remittances are
fungible, The presence
of fungibility of the resources prevent us using this
method.
Another approach is to examine an outcome of interest by
comparing households
who receive remittances with households that do not. We can
estimate the impact of
remittances on an outcome of interest and controlling for a set
of migrant, household and
community characteristics through ordinary least squares (OLS)
regression.
Outcomei = δ + φ ∗Remittancesi + γ ∗Xi + �iHowever, this
approach could suffer from omitted variable bias. If the only
effect of
migration on the outcome of interest is through remittances, the
results are not biased.
But if migration has other impacts on the outcome in addition to
its effect through
remittances, then the error terms contains omitted variable that
are correlated with
remittances and with the outcome. This will result in a bias of
the results.
That is why we replace in the previous equation the remittances
variable by a variable
of migration, to test the overall impact of migration.
Outcomei = α + β ∗Migrationi + χ ∗Remittancesi + η ∗Xi + �iThe
coefficient β then captures the joint impact of remittances and of
other conse-
quences of migration through the migrant variable.
The production is constrain because of the presence of market
imperfections. This
as for result that (Y c) depends on migration (M) and
remittances (R). A vector of
individual, household and village characteristics may also
affect the income. In order to
test if migration and remittances have different effects
according to the source of income,
the empirical analysis will distinguish three distinct sources
of income: crop production
Yc, self-employed income Ys and wage Yw5.
(1) Y ck = α0k + α1kM + α2kR + α3kZk + �Yk ; k = a, s, w
As mentioned before a potential bias of endogeneity is possible.
We control for this
bias by the instrumental variable method6.
5The total income is the sum of the three sources of income and
the remittances, Y = Ya+Ys+Yw +R6A test of endogeneity has been
completed. A joint test that the coefficient of the residual are
statically
different from zero
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Migration depends of the individual, household and village
characteristics, (ZM):
(2) M = β0 + β1ZM + �M
The dependent variable is the number of migrants.
Remittances are a function of migration, individual and
household characteristics
(ZR):
(3) R = γ0 + γ1M + γ2ZR + �R
After the presentation of the theoretical model and our
empirical method to test the
model, the next section will present the specification of the
system of equation.
3.1 Variable specification
The survey use the following definition to define a member of a
household. A householder
is a person who has been living in the household for at least 6
months or less than 6 months
but plans to stay in the household for more than half a year. So
a person who has been
living at least 6 months outside the household7 or who moved out
of the household for
marriage of migrated overseas will be defined as a migrant.
Remittances include cash and
in-kind transfers8
Following the NELM theory, migration and remittances variables
are linked with the
household income. To control this endogeneity bias, we choose
the instrumental variable
method. The migration network is an instrument in the migration
equation(Taylor and
Wyatt, 1996). Village migration network is approximate by the
number of migrants by
village. We postulate that the variable have a positive effect
on the number of migrants
but have no effect on the income nor on the remittances (minus
the number of migrants
of the household). In our preferred specification, we decompose
the network variable into
an internal migrant network composed by migrants living in
Bangladesh and external
migrant network composed by migrants living outside the
country.
In the remittances equation, the norm of the village to remit is
an instrument. We
use the annual amount of remittances received by a household of
the village to proxy the
norm of the village. This instrument is proposed by Taylor et
al. (2003). This variable
should affect the level of remittances received by the household
but has no effect on the
income of the household.
7without plans to stay more longer in the household8whatever the
method of transfer. The great advantage of using a survey is that
remittances include
transfer transiting by banks or money trabsfer firms like
Western Union or Money gram (formal transfer)and money transiting
by hand, hundi (informal transfer).
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3.2 Functional form
Equations (1) through (3) constitute an equation system. Error
terms �i, i = Y,R,M are
normally and identically distributed with variance σ2i . A
correlation of the error terms
is likely to occur between the income equations and remittances.
An exogene shock can
have an effect on the five equations. To account for
contemporaneous correlation, we
choose to estimate our model by the three-stage least squares.
This estimation method
consist of an estimation of each equation by the two-stage least
squares and a correction
of the error terms to take into account the possible correlation
of the error terms.
4 Data
The data use in this paper, Matlab Health and Socio-Economic
Survey (MHSS), have
been collected by RAND Corporation in 1996. In spite of the goal
of the survey was not
migration, this survey includes a lot of information on our
subject. The dataset contains
informations on non-resident household members9 (their
relationship with the household
head, age, marital status, education level, location,
occupation, remittances send back to
home. . . ). The dataset includes four separate surveys with
different samples. The main
survey consists of household- and individual-level information
on 4,364 households. The
second survey is on the determinants of natural fertility
survey. The third survey is on
internal migrants and the last survey consists of a community
survey. This paper use the
main survey which consists of 4,364 households distributed on
140 villages.
Matlab is a rural area in the south-west part of Bangladesh.
Since 1966, a pro-
gram of demographic surveillance under the Centre for Health and
Population Research
(ICDDR’B, formerly known as International Centre for Diarrhoeal
Disease Research,
Bangladesh) is in place in this area. The sample of MHSS benefit
from this program as
the sample is based on previous surveys and census realized by
ICCDR’B. Moreover the
9We have information on the spouse, children, parents or sibling
of the household head who aremigrants.
Table 1: Number of household migrating
Status Household Percentage
Number of household with at least one migrant 1,992 45.65%Number
of household with at least one migrant abroad 609 13.96%Any migrant
2,372 54.35%Total 4,364 100%Source: MHSS (1996)
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Table 2: Distribution of migrants by relationship and remitting
status
Relationship Number of migrants RemitTotal Internal External
Total Percentage
Spouses 353 203 158 284 80.45%Children 3,883 3,572 1,332 2,143
55.19%Parents 1,015 950 91 83 8.18%Siblings 15,164 12,954 2,210
2,620 17.28%Total 20,415 5,130 25.13%Source: MHSS (1996)
experienced field organization and the respondent population
accustomed answering to
surveys lead to very low attrition rates
Matlab is located about 55 kilometers Dhaka, the country’s
capital and one of the
city with the highest growth rate of the world10. In spite of
this geographical proximity,
a trip between Matlab and Dhaka takes six hours preventing
return trips. This is a cause
of urban migration (Kuhn, 2001). Destinations of overseas
migrants11 can be basically
separate in three groups: Developing countries, Persian Gulf and
Southeast Asian coun-
tries. These destination countries for migrants have changed
over the years. The first
destination was Great Britain. The second destination was Middle
east countries (Saudi
Arabia, Kuwait, UAE. . . ) in the seventies. The last
destination is southeast countries
(Malaysia, Brunei. . . ). In contrast to the migration to
developing countries, migration to
the Middle East and South East Asia has been characterised by
short term employment,
with specific job contracts and migrants returning home after
completion of the contract
period IOM (2005). Informal migration is so very difficult, the
main way to become an
illegal migrant is to stay in the country after the end of the
labor contract.
This survey collected data on such diverse topics as income,
expenditures, education,
employment, food consumption, health and nutrition, landownings,
assets, migration and
rural credit. . . . The particularity of the dataset that is
interesting for us is the information
on migrants: education, remittances, employment, location . . .
. The survey also include
a village survey.
4.1 Descriptive statistics
A little bit less than half of households in the survey have at
least one migrant, and 13.96%
have at least one migrant abroad (table 1). The data does not
allow us to know precisely
in which country resided migrants, but in general Bangladeshis
migrate to Middle East
10The population of Dhaka was 1.3 million before the
independance (1971) and 8.5 million in 1997.11Figures are available
on the SAMReN website http://www.samren.org/FactsandF
igures/bangladesh/1.1.htm
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Table 3: Remittances
Internal External Total
Spouses 4395.733 30002.18 12921.53Children 2412.394 6106.651
9109.04Parents 21.910 7.412 110.735Siblings 569.027 104.573
939.772Total 2541.451 12531.9 7166.73Source: MHSS (1996)
countries (Saudi Arabia, Kuwait, Oman, Qatar. . . ) and more
recently to South East
Asian countries (Malaysia, Singapore. . . ).
The dataset included information on different type of migrant:
spouse of the household
head, its children, parents and siblings. Table 2 shows
statistics on remittances received
by surveyed households. The incidence of remittances vary a lot.
80% of household head
spouses send money to their spouse. More than half of the
children of the household head
remit. This figure fall to 17.28% and 8.18% for parents and
siblings of the household
head. This lead us to restrict our analysis to spouse and
children migrants. A migrant
household is defined, in the following of the paper, as a
household having at least one
person (the spouse of the household head or its children) who
was previously a member
of the household has left for more than six months to live or
work elsewhere, either in
Bangladesh or abroad.
The average respondent received tk7,166.733 per year from
migrants (Table 3). But
this figure vary a lot between the destination of migration and
the relationship of the
migrant. International migrants send more money back home as
they earn more abroad.
Also, the spouse of the household head or these children send
more money than parents
or siblings. A household who actually had a migrant son or a
migrant spouse received
tk4,395.733 from internal migrant and tk30,0002.18 from
international migrants. In con-
trast, siblings living outside the district or the country
account for a very little sum of
transfer.
Table 4 shows the number of migrants per household. On average a
household count
4.68 migrants, with a minimum of 1 and a maximum of 29.
Table 5 presents the means of variables used in the regression
analysis, broken down
by migration status. The household size and the composition of
the household are not sig-
nificantly different between migrant household and non-migrant
household. The human
capital is more important in migrant household as non farm
assets, but it is not the case
for farm assets and the agricultural land per capita own by the
household. A significant
difference comes out from comparing the two sub-samples
regarding the amount of remit-
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Table 4: Number of migrants and amount of remittances received
per house-hold
Number of Mean Number Mean Numbermigrants amount of of amount of
ofwithin remittances households remittances householdsthe household
received received
0 0 422 0 3,7551 499 1686 24,221 4272 538 2749 35,223 1233 516
4612 62,335 404 468 5569 63,884 165 418 5715 26,866 3>5 1503
10674 - -Total 5898 4,364 4,186 4,364Source: MHSS (1996)
tances received by the household. This is not a surprising
figure, because children and
spouses have the higher propensity to send remittances and they
send a larger amount
of money than siblings. The fact that we restrict our analysis
to overseas migration is
also an explanation of this high amount of remittances send back
home by migrants.
Households with migrants abroad get in general about 83% more
income than the others.
But this figure is not sufficient to answer the question of the
impact of migration. That is
why in the following sections we develop an econometric analysis
to answer this question.
A p-value of less than 0.05 means that the null-hypothesis of
equal means for both groups can be
rejected at an error level of less than 5 percent [H0:
Differences in means = 0].
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Table 5: Descriptive statistics
Variable Non migrant Migrant t P>|t|household
household(N=3755) (N=609) (*)
Household size 5.516 5.84 -3.187 0.0014Dependence ratio 0.403
0.381 2.269 0.0233Education 2.901 3.804 -5.522 0.0000Experience
38.922 43.656 -7.563 0.0000Non productive assets 10206.81 27970.1
-7.663 0.0000Land per capita 0.091 0.152 -1.516 0.1295Number of
cows 0.069 0.080 -1.023 0.1889Farm assets, lagged 501.039 789.557
-1.349 0.1774Non farm assets, lagged 8843.42 38660.83 -4.008
0.0001Remittances 2238.482 32587.45 -23.812 0.0000Total income
40967.45 81102.68 -11.1164 0.0000N 4364
Source: MHSS (1996)
5 Results
5.1 Migration
Estimations of the determinants of migration are presented in
table 6. Results are consis-
tent with previous empirical findings. Results are quiet similar
between each specification.
The first specification is a simple OLS, the others are Poisson
estimations12. Specifica-
tions 2 and 3 only change in the variable that we belive can act
as instruments to identify
migration.
The first set of regressors are household demographic
characteristics. One would
expect that the number of migrants would rose as the size of the
household rose and
fall as the the number of dependents rose. The coefficient of
the household size has a
statistically significant impact on the number of migrants.
However, the dependance ratio
has no statistically significant impact. Education and
experience variables have both a
statistically significant and positive impact on the number of
migrants. The coefficient
of land per capita is not statistically significant. But the
proxy variable for wealth, the
value of non-productive assets, has a positive effect on
migration. This could reflect the
fact that migration has a cost.
The migration networks variables include in the regression have
a statistically sig-
nificant impact on the number of migrants. More precisely, the
coefficient of the total
12The OLS estimator is biased, because the migration variable is
non-negative and there is a lot ofnull observation.
14
-
number of migrants of the village is positive. But when we break
down this figure between
the number of migrants living in the country and the number of
migrants living abroad,
we found a different effect between these two variables. The
external migration networks
has a positive effect on the number of migrants, but contrary to
Mendola (2005) who
found a positive but smaller effect, we cannot conclude to a
effect different from zero of
the internal migration networks on the migration variable.
The final set of regressors are village characteristics. The
negative coefficient of this
dummy reflect the fact that a better environment decrease the
incitation to migrate. The
coefficient of the village size is negative. The presence of
markets in the village have no
significant impact on the number of migrants.
5.2 Three Stage Least Squares
5.2.1 Remittances
Estimations of the Three Stage Least Squares are presented in
table 7. The first column
represents the remittances equation. Only few coefficients are
statistically significant.
Wealthier households (measured by the value of the value of the
nonproductive assets
owned by the household) receive more remittances. The village
norms to remit has a
positive coefficient. Only for the specification with the
different source of income, the
coefficient of the dependence ratio is statistically significant
and positive. A household
living in a village with a stronger norm to remit will receive
more remittances than a
household staying in a village with a less strong norm. The
coefficient of the migration
variable is positive. Each additional migrant increase
remittance by Taka 17,892. This
support the descriptive statistics presented in the previous
section.
5.2.2 Total income and sources of income
Results are quite similar between total income regression and
sources income regression
(table 7 and 8). Remittances have a positive effect on income,
except on the wage income.
Migration do not have any significant effect on the total
income. However, crop income
falls when migrants leave the household. This negative effect is
even bigger on wage
income. With the departure of a household member, the labor
force of the household
decreases, and the income also decreases.
Coefficients for the other exogenous variables affect income in
ways that are consistent
with findings by other researchers. The household siez has a
positive effect on both total
income and income by sources. It is also the same with the
number of years of education
of the household head, except for the wage income where its
impact is non statistically
15
-
significant. Stock of capital (farm and non-farm) positive
effects on income, like the
amount of land per capita.
Although the coefficients of the village size are generally
insignificant, the population
of the village negatively affects crop income. This is the same
for large and small markets
which negatively affects respectively crop and self-employed
income.
16
-
Table 6: Determinants of migration
Explanatory variables Number of migrants(1) (2) (3)
Household characteristicsHousehold size 0.013∗∗∗ 0.060∗∗∗
0.062∗∗∗
(0.001) (0.000) (0.000)Dependance ratio 0.440 0.104 0.121
(0.281) (0.524) (0.460)Education 0.011∗∗∗ 0.073∗∗∗ 0.069∗∗∗
(0.000) (0.000) (0.000)Experience 0.056∗∗∗ 0.028∗∗∗ 0.028∗∗∗
(0.000) (0.000) (0.000)Non productive assets 0.000∗∗∗ 0.000∗∗∗
0.000∗∗∗
(0.000) (0.000) (0.000)Land per capita 0.002 0.006 0.006
(0.833) (0.850) (0.847)Village characteristicsVillage size
-0.000∗∗∗ -0.001∗∗∗ -0.000∗∗∗
(0.003) (0.000) (0.006)Large market 0.017 0.098 0.014
(0.396) (0.354) (0.899)Small market 0.009 0.058 0.071
(0.732) (0.472) (0.389)Total Migrant -0.005 -0.008
(0.871) (0.946)Internal migrant 0.093
(0.542)External migrant 1.255∗∗∗
(0.001)
N 4236Significativity levels : ∗ : 10% ∗ : 5% ∗ ∗ ∗ : 1%
17
-
Table 7: Estimated effects of migration and remittances on total
income
Explanatory variables Number of migrants Remittances Total
incomeNumber of migrants 17892.79∗∗∗ -7200.424
(0.000) (0.109)Remittances 1.245∗∗∗
(0.000)Household characteristicsHousehold size 0.062∗∗∗
4702.144∗∗∗
(0.000) (0.000)Dependance ratio 0.119 -1494.178
(0.467) (0.362)Education 0.069∗∗∗ 1480.925∗∗∗
(0.000) (0.000)Experience 0.028∗∗∗ 2.967
(0.000) (0.966)Non productive assets 0.000∗∗∗ 0.077∗∗∗
0.311∗∗∗
(0.000) (0.000) (0.000)Land per capita 0.006 -157.568
1327.261
(0.833) (0.679) (0.038)Farm assets, lagged 0.910∗∗∗
(0.000)Non farm assets, lagged 0.089∗∗∗
(0.000)Village characteristicsVillage size -0.000∗∗∗ 0.982
-4.963∗∗∗
(0.005) (0.502) (0.204)Large market 0.025∗∗∗ –543.444
265.778
(0.817) (0.670) (0.946)Small market 0.082∗∗∗ 1064.253
-9177.352
(.307) (0.248) (0.000)Number of industries
Industry 481.722∗∗
(0.038)External migrant 1.271∗∗∗
(0.000)Village remittances 0.822∗∗∗
(0.000)Remittance facilities -1386.039
(0.274)Mills ratio 1154.361
(0.531)
N 4236Significativity levels : ∗ : 10% ∗ : 5% ∗ ∗ ∗ : 1%
18
-
Tab
le8:
Est
imat
edeff
ects
ofm
igra
tion
and
rem
itta
nce
son
tota
lin
com
eExpla
nato
ry
varia
ble
sN
um
ber
ofm
igrants
Rem
itta
nces
Agric
ulturalin
com
eW
age
incom
eSelf-e
mplo
yed
incom
eN
um
ber
ofm
igra
nts
17969.6∗∗∗
-4130.6
01∗∗∗
-7755.1
91∗∗
245.4
60
(0.0
00)
(0.0
00)
(0.0
15)
(0.8
92)
Rem
itta
nce
s0.2
89∗∗∗
0.0
68
0.1
51∗∗
(0.0
00)
(0.6
69
(0.0
47)
House
hold
characte
ris
tics
House
hold
size
0.0
62∗∗∗
903.4
61∗∗∗
3079.0
52∗∗∗
380.8
50∗∗
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
28)
Dep
endance
ratio
0.1
19
-13696.8
19∗∗
(0.4
67)
(0.0
11)
Educa
tion
0.0
69∗∗∗
199.9
11∗∗∗
1066.3
57
25.2
44
(0.0
00)
(0.0
00)
(0.0
00)
(0.8
25)
Exper
ience
0.0
28∗∗∗
28.8
02∗∗
-79.1
13
-65.3
64∗∗
(0.0
00)
(0.0
34)
(0.1
30)
(0.0
21)
Non
pro
duct
ive
ass
ets
0.0
00∗∗∗
0.0
78∗∗∗
-0.0
16∗∗∗
0.2
10∗∗∗
0.0
16
(0.0
00)
(0.0
00)
(0.0
09)
(0.0
00)
(0.2
66)
Land
per
capita
0.0
06
-163.1
33
2036.2
53∗∗∗
940.3
65
-159.3
20
(0.8
33)
(0.6
69)
(0.0
02)
(0.2
17)
(0.7
00)
Farm
ass
ets,
lagged
0.2
16∗∗∗
(0.0
00)
Non
farm
ass
ets,
lagged
0.0
29
(0.0
00)
Liv
esto
ck-0
.030
(0.5
80)
Villa
ge
characte
ris
tics
Villa
ge
size
-0.0
00∗∗∗
0.6
51
-1.2
56∗∗
-3.4
68
-1.2
02
(0.0
05)
(0.6
56)
(0.0
86)
(0.2
17)
(0.4
29)
Larg
em
ark
et0.0
25
-846.6
49
-1129.9
21∗
-703.3
46
867.4
80
(0.8
17)
(0.4
96)
(0.0
56)
(0.8
12)
(0.5
90)
Sm
all
mark
et0.0
82
880.0
57
-190.5
90∗
-8099.8
59∗∗∗
-1116.0
84
(.307)
(0.3
29)
(0.6
65)
(0.0
00)
(0.2
47)
Num
ber
ofin
dust
ries
703.7
66
(175.0
52)
Indust
ry722.2
95∗∗∗
-32.1
71
(0.0
00)
(0.7
36)
Exte
rnalm
igra
nt
1.2
71∗∗∗
(0.0
00)
Villa
ge
rem
itta
nce
s0.7
58∗∗∗
(0.0
00)
Rem
itta
nce
faci
lities
-619.1
80
(0.5
81)
Mills
ratio
1644.2
84
(0.3
68)
N4236
Sign
ifica
tivi
tyle
vels
:∗
:10
%∗
:5%
∗∗∗
:1%
19
-
6 Conclusion
This study used a rich dataset from rural Bangladesh to examine
the different effects of
overseas migration and remittances on the different sources of
income of the household.
Three conclusions emerge from it. First, our results supports
the NELM framework that
remittances are an element of a household strategy to alleviate
market failures. Secondly
the loss of labor affect negatively the household income.
Finally the impact of migration
is complex. It should be break down into two different effect:
the lost of labor and the
amount of remittances received. Effects also differ from income
sources. Migration have
no effect on self-employed income and remittances have no
statistical impact on wage
income.
20
-
Annex 1. Variable definition
Household characteristics
Number of migrants: a person (the spouse of the household head
or its children) who was
previously a member of the household has left for more than six
months to live or work
elsewhere
Remittances : value of remittances send by migrants
Household size: size of the household
Dependence ratio: (children 0-14 years + adults > 65
years)/persons 15-64 years
Education: number of years of education of the household
head
Experience: number of years of experience
(Experience=Age-Education-16 based on work
of Jacob Mincer, Schooling, Experience, and Earnings (New York:
Columbia University
Press, 1974)
Non productive assets : value of non productive assets
Land per capita: agricultural land owned by the household per
capita
Farm assets, lagged : value of farm assets owned by the
household in 1995
Non farm assets, lagged : value of non farm assets owned by the
household in 1995
Village characteristics
Village size: size of the village
Large market : dummy variable, 1 if a large market is present in
the village
Small market : dummy variable, 1 if a small market is present in
the village
Number of industries : number of industries in the village
Total migrant : number of migrant in the village minus the
number of migrants of the
household
Internal migrant : number of internal migrant in the village
minus the number of migrants
of the household
External migrant : number of external migrant in the village
minus the number of mi-
grants of the household
Village remittances : mean value of remittances received by the
village minus the amount
of remittances received by the household
Remitances facilities : dummy variable, 1 if there is a bank or
a post in the village
21
-
References
Amuedo-Dorantes, C. and S. Pozo (2002). “Workers’ Remittances
and the Real Exchange
Rate: A Paradox of Gifts.” mimeo.
Azam, J. P. and F. Gubert (2002). “Those in Kayes. The Impact of
Remittances on their
Recipients in Africa.” Document de Travail 11, DIAL.
IOM (2005). “World Migration Report.” Technical Report, IOM.
Kuhn, R. (2001). “Never Far from Home: Parental Assets and
Migrant Transfers in
Matlab, Bangladesh.” RAND Labor and Population Working Papers
01–12.
Lucas, R. E. (1987). “Emigration to South Africa’s mines.”
American Economic Review.
77 (3), 313–330.
Massey, D. S., J. Arango, G. Hugo, A. Kouaouci, A. Pellegrino,
and J. E. Taylor (1993).
“Theories of International Migration: a Review and Appraisal.”
Population and Devel-
opment Review. 19 (3), 431–466.
Mendola, M. (2005). “Migration and Technological Change in Rural
Households: Com-
plement or Substitutes ?” Working Paper 2005-15.
Rozelle, S., E. J. Taylor, and A. de Brauw (1999). “Migration,
Remittances and Agricul-
tural Productivity in China.” American Economic Review. 89 (2),
287–291.
Sana, M. and D. S. Massey (2005).“Household Composition, Family
Migration, and Com-
munity Context: Migrant Remittances in Four Countries.” Social
Science Quaterly.
June 86 (2), 509–528.
Singh, L. Squire, and J. Strauss (1986). Agricultural household
models, extensions, aplli-
cations, and policy,
Stark, O. (1991). The Migration of Labor, Basil Blackwell,
Cambridge, U.K.
and E. Katz (1986). “Labor Migration and Risk Aversion in Less
Developed
Countries.” Journal of Labor Economics. 4 (1), 134–149.
Taylor, J. and T. Wyatt (1996). “The Shadow Value of Migrant
Remittances, Income and
Inequality in a Household–Farm Economy.” Journal of Development
Studies. 32 (6),
899–912.
Taylor, J. E. (1992). “Remittances and Inequality Reconsidered:
Direct, Indirect and
Intertemporal effects.” Journal of Policy Modeling. 14 (2),
187–208.
22
-
and P. L. Martin (2001). “Human Capital: Migration and Rural
Population
Change.” in B. L. Gardner and G. C. Rausser, eds., Handbook of
Agricultural Eco-
nomics, Elsevier.
, S. Rozelle, and S. de Brauw (2003).“Migration and Incomes in
Source Communi-
ties: A new Economics of Migration Perspective from China.”
Economic Development
and Cultural Change. Octobre 52 (1), 75–101.
23
