Rural-urban Migration and
its Implications for Food
Security in Bangladesh
Institution: Department of Statistics, Shahjalal University of
Science and Technology (SUST)
Research Team:
Dr. Md. Zakir Hossain, PI
Professor, Dept of Statistics, SUST
Dr. M. Mizanul Haque Kazal, CI
Chairman, Dept of Development & Poverty Studies, SAU
Mr. Jasim Uddin Ahmed, CI
Associate Professor of Economics, Moulvibazar Govt. College
Contents of the Report
CHAPTER I
CHAPTER II
2.1
2.2
CHAPTER III
CHAPTER IV
4.1
4.2
CHAPTER V
5.1
5.2
5.3
CHAPTER VI
INTRODUCTION
METHODOLOGY
Research Methods
Analytical Tools and Techniques
LITERATURE REVIEW
HOUSEHOLD PROFILE AND MIGRATION DIVERSITY
Profile of Surveyed Household
Diversity of Migration Strategy
STATUS AND PREDICTORS OF FOOD INSECURITY
Perception, DCI, Food Expenditure and CSI Methods
General Coping Strategies to Food Insecurity Situation
Predictors of Household Food Insecurity
IMPACT OF RURAL-URBAN MIGRATION ON HOUSEHOLD
FOOD SECURITY STATUS
6.1
Consequence of Migration on different Household Indicators and
Fulfillment of Expectations
6.2
Impact of Migration on Food Security through NELM Models
CHAPTER VII CONCLUSION AND RECOMMENDATION
Key Research Questions
(i) Who migrates? Are the food insecure households more
prone to migration?
(ii) What are the different types of migration including child
migration?
(iii) Are the rural-urban migration flows concentrated towards
some big cities only?
(iv) Is the food security status of migrant households different
from that of non-migrant households and how?
(v) What are the Asian evidences and policy implications of
rural- urban migration associated with food security?
(vi) What is the impact of migration on food security status at
origin?
(vii)What strategies are to be taken to optimize the rural-urban
migration outcome to food security?
Objectives and Expected Outputs
Objectives
• To sharpen policy-makers’ understanding of the diversity of rural to
urban migration strategies and their impacts on household and
individual food security in sending and receiving areas,
• To provide information on potential interventions to strengthen
migrant household food security.
Expected Outputs
(i)Identification of migration diversity through exploring the typology
and mapping of its patterns,
(ii)Determination of food security status of the migrant households and
impact of migration on their food security,
(iii)Review of Asian literature to find out evidence on the association of
food security, rural urban migration and poverty reduction,
(v)Formulation of intervention to address food security of migrant
households.
Data and Methodology
The study has adopted following techniques to gather the primary data:
• Household-level survey at origin
• Tracer survey at destination
• Focus Group Discussion (FGD)
• Key Informant Interview (KII)
In addition, the study has analyzed the HIES-2010 and Panel data of Dr.
Mahbub Hossain to compare the relevant findings of the survey data.
Sample Design for Household Level Survey & Tracer Survey
• The study provided the main Indicators in 2 rural domains, according to the
East-West divide reported by the World Bank study of Bangladesh
• The sample size determination formula yields that 750 migrant households
are required to cover in each domain.
• The study has adopted cluster (PSUs of BBS) sampling and covered 30
clusters in each domain (using systematic PPS)
• Ultimately, 3000 units of analysis have been covered:
- 1500 Migrant and 750 Non-migrant households at origin
- 500 Migrant and 250 Non-migrant households under Tracer survey
Analytical Techniques
Step-1: Measure the flow of migration including selectivity
The flow of rural-urban migration has been explored through
descriptive statistics in different dimensions including flow-mapping.
Step-2: Measurement of the status of food security
(i) Perception analysis; (ii) Direct calorie intake (DCI);
(iii) Food expenditure; (iv) Coping strategy index (CSI) score
Step-3: Identification of the predictors of food insecurity
The binary multiple logistic regression model (BLRM) has been
applied to identify the predictors of food insecurity.
Step-4: Impact of migration on food security
The impact of migration on food security at origin has mainly been
studied using 2-stage and 3-stage NELM models
In particular, instrumental variable (IV) regression has been employed
to study the impact of migration on per capita calorie intake.
The similar model has also been used by simultaneous consideration
of migration determinants, remittance behaviors and income.
2-Stage NELM Models
Where FS measures the per capita calorie-intake as a proxy food security status
at the household level; Mig measures the number of migrants per household; X
vector encompasses the household characteristics; Z is a vector of instruments
3-stage NELM Models
The basic equation for household income, (as a proxy of household food
security) according to the NELM hypothesis can be expressed as
Y c k  ok  1k M   2k R  3k Z k   k k = on-farm, off-farm;
R   o  1M   2 Z R   R
M  f ( ; Z M )   M
where
f ( ; Z M )  exp(0  1Z M )   M
To model migration, this study considers using count regression functional form,
particularly the Poisson distribution form, since the number of migrants is nonnegative.
Concluding Remarks from Review of Asian Evidence
Migration Pattern/Diversity/Causes:
- Mainly young people strive for migration
- Migration is higher from environmentally fragile areas
- Increasing trend of temporary and circular migration
- Feminization of internal migration
- Concentration of migration towards big cities
- Major causes of migration are wage differentials, population pressure etc.
Positive Impact At origin:
-Poverty reduction & gain of assets
- Human resource development
- Food security at household level
- Women empowerment
- Fertility control
- Change in family composition
Negative Impact At origin:
- Labor depletion in a few cases
- Loss of agricultural productivity
- Family disintegration
-Increase of women and children
chores
Positive Impact at Destination:
- Urban growth
- Availability of workers for urban services
-Availability of manpower for industry,
particularly manufacturing, development sector
Negative Effect at Destination:
- Unplanned urbanization
- Growth of slums
- Environment pollution
- Ultimately, ill consequences on transport,
healthcare & other service sector
General Features of the Study Population for RUM-2012 Survey data
 About 29.2% study population were below 15 years of age, about 66%
fell 15-64 years and about 4.4% were of 65 years or above.
 Approximately 21% of the adult men earned incomes from agriculture,
about 22% were unemployed, 12.6% engaged in study and the rest
earned from off-farm activities. On the contrary, three-quarters of the
women were engaged in household work, 9% engaged in study, about
11% were engaged with agriculture.
 About 21% of the study population aged 5 years or older was found to
have no education, about 36% were found to have primary-level
education, about 39% were found to have secondary/higher secondary
level education and only 5% people attained graduate level education.
 The analysis of housing condition, sources of water & lighting and
sanitation facilities as well as asset score of the surveyed households
according to the migration status indicates that the migrant-households
are better positioned than their non-migrant counterparts in terms of
housing condition and possessing wealth.
Landholdings, Income & Expenditure Pattern of Migrant and Nonmigrant Households for Three Data Sets
Landholding, Income &
Expenditure
RUM-2012 (origin)
Migrant
Average Size of Land
P-value
East (Mean)
West (Mean)
Average On-farm Income
P-value
Average Off-farm Income
P-value
Average Food Expenditure
P-value
Avg. Non-food Expenditure
P-value
Total (n)
114.3
HIES-2010
NonNonNonMigrant
Migrant
migrant
migrant
migrant
73.9
108.6
76.9
160.9
92.6
P<0.01
88.3
140.1
53720
P<0.10
70.2
77.6
46733
47694
P<0.12
115629
89014
86742
68157
77144
72306
50910
P<0.10
55855
33413
P<0.01
71241
p>0.10
51306
P<0.01
1509
61453
P<0.10
P<0.05
68345
55583
P<0.01
P>0.10
P<0.01
73205
Panel Data
49801
44871
P<0.10
746
427
6622
424
1352
Flow of Migration in Bangladesh
Percentage of households reporting migration of any member
by residence
Destination
Origin
Data Source
Period
Domestic Abroad
Mixed
Total
households
Rural
HIES-2010
2006-2010
4.84
9.25
-
7840
Urban
HIES-2010
2006-2010
1.62
6.85
-
4400
Rural
RUM-origin 2006-2010
9.29
-
-
8033
Rural
RUM-origin 2001-2011
22.25
11.47
1.90
8033
Rural-East
RUM-origin 2001-2011
19.20
15.70
2.40
4793
Rural-West RUM-origin 2001-2011
27.20
4.70
1.10
3240
Rural-Urban Migration Flow from Study Clusters/Villages in Bangladesh
Migration Rate according
to East-West Divide
East
West
Total
4.38%
6.86%
5.30%
Are the food insecure households more prone to migration?
Comparison of some basic indicators between migrant (non-migrant in
2000 and migrated during 2001-2008) and non-migrant households
(non-migrant since 2000) using panel data
Basic Indicators
Average Landholdings (in decimals)
Average Per Capita Income (in Taka)
Calorie intake (% of HHs)
Extreme poor (1805 K.Cal)
Moderate poor (2122 K.Cal)
Non-poor
Poor on the basis of self perception
Extreme poor
Poor
Vulnerable
Solvent
Migrant
Households
Non-migrant
Households
149.12
116.81
10673
9009
18.7
25.1
56.2
22.0
31.1
47.0
9.2
32.2
35.7
23.0
13.0
35.9
36.2
14.9
Selectivity: Age and Education at the time of Migration
Age distribution of migrants for survey data and panel data
% of Migrants
80
69.5
Survey Data
Panel Data
61.3
60
40
20
28
18
10
9
2.4
1.8
0
0-14 years
15-29 years
30-44 years
Age at Migration
45 years & above
% of Migrant
Population
Educational status at the time of migration for Three Data Sets
45
40
35
30
25
20
15
10
5
0
40.7
26.5
31.4 29.5
27.8
27.1 25.2
17.8
8.2
22
10.5
15.1
6.9
4.3
Illiterate
Survey Data
Panel Data
HIES-2010
Primary
Secondary
SSC/HSC
Educational Status of the Migrants
7
Graduate
Selectivity: Occupation of the Migrants
Occupation
Pre-migration period (%)
Occupation at Destination (%)
East
West
Both
East
West
Both
Job/service
5.6
2.5
4.0
32.2
28.5
30.3
Business
2.4
1.5
1.9
3.6
2.7
3.1
Petty traders/ hawker
4.5
1.9
3.1
7.9
5.5
6.7
Garment worker
1.1
.8
1.0
10.7
14.8
12.8
Wage labourer
13.5
7.6
10.5
21.3
17.3
19.3
Student
36.6
38.1
37.4
15.6
20.2
18.0
Household work
4.9
4.7
4.8
4.6
4.9
4.8
Agriculture
10.9
21.5
16.4
1.1
2.0
1.6
Unemployed/Others
20.6
21.3
21.0
2.8
4.0
3.3
Total (n)
801
849
1650
801
849
1650
Intended Nature of Migration
Type of Migration
Permanent
Study
Temporary
Seasonal
% of Migrants
6.7
21.7
66.9
4.7
% of Migrants
Destination of the migrants by region
50
45
40
35
30
25
20
15
10
5
0
46.1
East
West
36
29.8
32.1
14.6
12.3
4.2
Capital
Chhitagong
7.3
0.3
7
7.3
3.1
Rajshahi/
Sylhet/
Khulna/
Barisal
Rangpur
Destination of migrants
District
Upozilla
Exploration of the child migration:
Comparison of Pre-migration occupation and occupation at
destination of the child migrants
Pre-migration occupation
36.9
Others (no specific work)
23.8
Female (%)
Male (%)
Occupation at destination
8.3
3.5
4.9
0
Agriculture
0
0
Housewife
0
6.4
56.0
59.6
Female (%)
Male (%)
1.8
5
Student
0
Construction/transport…
0
Weaver/carpenter
1.8
3.6
0
0.2
Tailoring/garment worker
0
1.1
0
0.9
Petty traders/hawker
0.7
0.7
Job/service
65 60 55 50 45 40 35 30 25 20 15 10 5 0
46.1
36.9
0
5.8
10.6
13.3
25.5
15
0.7
0
Business
5
1.1
8.5
0
5
10
16.2
15
20
25
30
35
40
45
50
Factors for Migration
Push Factors
Poverty/food insecurity
Unemployment
Underemployment/ Demonstration effect
Insufficient education facilities
Others
Pull Factors
Better job opportunities
Better schooling
Relatives/friends there
Wage differential
Others
% of Migrants
23.9
30.4
11.4
23.1
11.2
% of Migrants
39.9
22.8
13.8
13.6
9.9
Extent of Food Insecurity: Perception, DCI and CSI Methods
At Origin
Perception Method
Had been anxious about food in last
3 months (normal insecurity)
Had been bound to take less than 3
meals in a day (moderate insecurity)
Had been bound to sleep in hunger
(severe insecurity)
No food insecurity
At Destination
Migrant Non-Migrant Migrant Non-Migrant
HHs (%)
HHs (%)
HHs (%)
HHs (%)
21.4
27.2
6.2
9.0
12.8
16.2
2.6
0.8
5.0
7.0
1.0
0.4
78.6
72.8
93.8
91.0
Extent of Poverty/Food Insecurity by DCI Method
% of households below hardcore
poverty line
% of households below absolute
poverty line
13.5
18.1
5.2
8.2
32.6
38.3
29.7
35.9
15.0
12.2
30.4
746
3.6
2.6
26.0
499
5.8
3.1
27.8
256
Food Insecurity Status by CSI Method
Low/Medium CSI Score
High CSI Score
Average CSI Score
Total (n)
12.3
9.1
30.3
1509
Figure 5.2: Percentage of Households using Consumption Coping Strategies
% of household
Strategies
a. Rely on less preferred and less expensive foods
100 88.8
87.1
90
80
68.3
70
60.5
60
49.2
50
40
29.5
30
17.5
14.1
20
10.6 7.4 8.9
10.1 8.9
6.8
10
0
a. b. c. d. e. f. g. h. i. j. k. l. m. n.
Adopted coping strategies during food insecurity
b. Undertaking more jobs and/or working longer
hours
c. Borrow food or rely on help from a
friend/relative
d. Purchase food on credit
e. Gather wild food, hunt or harvest immature crops
f. Consume seed stock held for next season
g. Send household members to eat elsewhere
h. Sending children for working
i. Send household members to beg
j. Limit portion size at mealtimes
k. Restrict consumption by adults in order for
children to eat
l. Feed working members at the expense of nonworking members
m. Reduce number of meals eaten in a day
n. Skip entire days without eating
Predictors of Food Insecurity: Relative risk against different
categories of the covariates for different levels of food insecurity
Variables
Model 1:Normal Model 2:Moderate Model 3:Severe
food insecurity
food insecurity
food insecurity
Landholding
None®
1.000
1-49
0.346***
50-99
0.149***
100-249
0.094***
250 & above
0.048***
Occupation of the Household Head
Agriculture Farmer ®
1.000
Labor
1.628***
Service
0.618*
Others
1.537**
Education of the Household Head
Illiterate®
1.000
Primary
0.792*
Secondary
0.664***
Post-secondary & above
0.315***
1.000
0.340***
0.124***
0.085***
0.088***
1.000
0.385**
0.088***
0.060***
0.050***
1.000
1.506*
0.591
1.518*
1.000
1.171
0.397
1.825
1.000
0.633***
0.478***
0.283***
1.000
0.604**
0.462***
0.289
® Ref. category; *** Sig. at 1% level; ** Sig. at 5% level; * Sig. at 10%
Cont.
Model 1:Normal
food insecurity
Debt Status of the Household
Did not receive loan®
1.000
Received loan
2.484***
Location (East-west divide)
West®
1.000
East
0.847
Dependency ratio
1.004***
Family Size
0.961
Tilling Technology
Non-mechanized
1.000
Mechanized
1.063
Sex of the Household Head
Male
1.000
Female
1.822***
0.733
Constant
Model2:Moderate
food insecurity
Model3:Severe
food insecurity
1.000
2.699***
1.000
2.432***
1.000
1.255*
1.004***
0.892***
1.000
2.547***
1.006***
0.818***
1.000
1.106
1.000
1.094*
1.000
1.994***
1.000
1.899*
0.433**
0.135***
® Ref. category; *** Sig. at 1% level; ** Sig. at 5% level; * Sig. at 10%
Impact of Migration on Different Household Indicators
(Perception-based)
Socio-economic indicators
Frequency of meal
Quality of food
Food security condition
Educational status of the
migrants
Working hours of the
household members
Land Size (in Decimal)
Type of House
Number of rooms
Type of toilet
Television
Fridge
Economic condition of the
HH
Impact/Change due to migration (% of households)
At Origin
At Destination
Positive
Negative
Positive
Negative
4.8
12.0
17.8
0.7
3.2
5.2
4.4
26.5
29.7
3.4
11.4
10.6
14.5
0.0
16.6
0.0
25.7
10.6
35.7
12.2
5.4
6.1
5.3
6.2
9.0
2.9
13.4
70.8
1.1
0.9
1.4
2.5
0.5
2.6
1.8
58.1
11.2
47.9
16.8
8.4
17.8
31.7
12.2
40.1
10.2
17.4
4.8
4.6
Labor compensation and fulfillment of expectations
due to migration
East
West
Both
Annual cost of labour compensation due to migration (%)
Yes
19.8
4.5
12.5
Average amount (Tk.)
5760±4741 4157±2976 5481±4521
Fulfillment of expectations (based on responses against key migrants)
Don’t know
7.1
2.8
4.9
Satisfactory
51.5
61.6
56.6
Partially satisfactory
33.3
29.8
31.5
Unsatisfactory
8.1
5.8
7.0
Involvement of women and children in economic
activities due to migration
Increase
27.2
Decrease
8.8
Constant
59.0
Impact of Migration on Food Security through 2-Stage NELM Models
Dependent Variable: Logarithm of per capita calorie intake
Endogenous Variables: Number of migrants in the household
Instrumental variables: Migration network, Share of male/female in 16-39
age groups at household level
Variables
Number of migrants of Household
Total operative land of Household
Occupation of HH (Farming)
Occupation of HH (Labourer)
Occupation of HH (Service)
Education of HH (Years of schooling)
Age of Household Head
Region (East=0, West=1)
Housing (poor quality=0, Good quality=1)
Religion (Muslim=0, Non-Muslims=1)
Score of household durables
Sex of the household head (Female=1)
GMM estimates of IV regression
Coefficient
P>z
.021872
0.002
.0000477
0.034
.0265117
0.048
-.0117138
0.401
.0118429
0.493
.0029068
0.004
.0006258
0.072
.0020233
0.787
.0127442
0.146
.0194966
0.080
.0000245
0.931
.0304034
0.098
Cont.
Variables
Number of adult male members
Tilling technology (mechanized=1)
Distance from commercial centre
Cropping nature of land (multi-crop=1)
Constant
No. of observations
R-squared centered & R-squared uncentered
Coef.
-.011606
.0116239
.0002534
.0046391
7.592765
2255
P>z
0.024
0.291
0.197
0.637
0.000
0.0375 & 0.9995
F-test
6.23 (P-value=0.000)
Tests of overidentifying restrictions:
Sargan N*R-sq test statistic
1.433 (P-value= 0.2313)
Basmann test
1.422 (P-value= 0.2330)
Hansen-J-Statistic
1.488 (P-value= 0.2225)
Test for endogeneity of Number of Migrants (Ho: Regressor is exogenous)
Wu-Hausman F-test; F(1, 2237)
2.968 (P-value= 0.085)
Durbin-Wu-Hausman chi-sq test; chi-sq(1)
2.988 (P-value=0.084)
Impact of Migration and Remittance on Household Income using 3-Stage NELM Models
Dependent Variable: On-farm income; Off-farm income without remittance
Endogenous Variables: No of migrants in the HH; Amount of annual remittance
Instrumental variables: Migration network, Share of male/female in 16-39 age groups at household level,
Relation of the migrants with household head
Explanatory variables
Remittance
Number of migrants, predicted
Total operative land of Household
Education of HH (Years of schooling)
Age of Household Head
Region (East=0, West=1)
Housing (poor quality=0, Good quality=1)
Religion (Muslim=0, Non-Muslims=1)
Household headship (Female=1)
Distance from commercial centre
Household size
Tilling technology (mechanized=1)
Cropping nature of land (multi-crop=1)
Number of adult male member
Remittance
Coef.
P>t
2317.255
-15.11037
149.7093
2.285204
2310.529
4144.307
-4941.468
-268.6574
-114.1954
-332.9233
-5833.086
-11298.73
3394.913
0.573
0.000
0.392
0.974
0.073
0.006
0.018
0.939
0.003
0.578
0.003
0.000
0.009
R2 centered and R2 uncentered
On farm income
Coef.
P>z
-0.1390744
0.342
39470.6
0.113
417.1255
0.000
963.8006
0.172
-309.4796
0.336
17186.38
0.000
-8846.836
0.036
-10435.31
0.030
-20634.86
0.145
419.9384
0.001
-2956.947
0.265
9684.968
0.091
-4839.286
0.251
-7491.228
0.218
Off farm income
Coef.
P>z
-1.003135
0.000
38218.01
0.010
28.93649
0.376
4677.405
0.000
299.3748
0.369
-37694.12
0.000
21187.33
0.000
5661.703
0.453
-6384.119
0.789
413.6162
0.001
3622.47
0.204
13920.83
0.123
-14804.77
0.016
0.5310 & 0.6283
0.1082 &0.3506
28.43 (p<0.0001)
20.97 (p<0.0001)
Sargan N*R-sq test Statistic
0.035
3.480
P-value
0.8517
0.0621
Hansen-J-Statistic
0.042
2.363
P-value
0.8374
0.1243
F-test with P-value
36.72 (p<0.0001)
CONCLUSIONS
•In rural Bangladesh, over half of the households are functionally landless
and the migrant-households are economically better positioned.
•Internal migration flow is higher from the West and international migration is
higher from the East.
• Food insecure or poor are not more prone to migration.
•The migrants tend to concentrate to capital city and district headquarters.
•The young people (aged 15-29 years), males and sons/daughters of the
household heads are more exposed to rural-urban migration.
•Temporary migration dominates over other types of migration and
independent/single migration over family migration.
•Literate people are more prone to permanent migration and illiterate people
are more prone to temporary migration.
•Type of migration from food insecure households significantly differs from
that from food secure households.
•Poverty, unemployment and poor educational facilities are found out as the
main push factors. In contrast, better employment opportunities, better
schooling, and wage differentials are sorted out as the main pull factors.
Cont…
•About three-fifths of the migrants sent remittances (average amount of
Tk.38397) and household heads mainly decide to utilize remittances.
•All the estimates of food insecurity indicate that non-migrant households
are more vulnerable to food insecurity. The estimates also show that the
migrants at destination are significantly less food insecure than their origin
counterparts.
•Reliance on less preferred and less expensive food items and purchase of
food on credit are explored as the top coping strategies of food insecurity.
•Landholding, occupation and education of the household head, debt status,
location, dependency ratio, family size and household headship are
determined as predictors of household level food insecurity.
•Perception-based estimates on change pattern of some socioeconomic
indicators reveal that migration puts mixed impact with positive net
impact.
•NELM-models determine that rural-urban migration exerts significantly
positive impact on food security through different dimensions.
•The major findings covered by the review of Asian literature are
corroborated by the findings of the present study.
Recommendation
•Improve educational facilities for quality education in rural areas, which
matches the skill needs of rural labour markets including vocational and
training facilities.
•Promote programmes to enhance more and better opportunities for
employment and entrepreneurship development in rural Bangladesh to
provide alternatives to distress rural-urban migration, especially for youth.
•The Government should also invest in better labour market information
systems and job information services so that youth can access to better jobs
and undertake migration in a more informed manner.
•Actions to prevent and eradicate child labour, especially its most hazardous
forms, with particular attention to unaccompanied child migrants.
•Decentralize both administrative and developmental activities to discourage
the concentration of rural-urban migration to capital city in particular and
other big cities in general.
•Local government should make proper arrangements for safety and security
in rural areas for a sound environment to make rural stay hassle and anxiety
free to discourage rural-urban migration and encourage reverse migration.
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Overall Message of the Study
The study explores that different kinds of adversity at origin compel a
stipulated section of rural population to strive for migration to urban
end where different kinds of prosperity attract them.
Different impact determining analyses based on descriptive,
perception-based and model-based estimates identify that impact of
rural-urban migration is significantly positive on food security in
particular and overall living condition in general.
The majority of the findings of the present study are found to be
aligned with those extracted from the review of literature, particularly
on Asian countries.
One final message is that since migration is a revealed preference of
the migrants, it cannot be stopped; rather, the policy-makers can
make policies to better manage migration flows by providing support
to leverage the opportunities arising from migration and remittances.