RURAL LIVELIHOOD DIVERSIFICATIONIN RICE-BASED AREAS OF

BANGLADESH

Presented ByMd Tanvir Ahmed

MS Research ScholarSocial Sciences Division

International Rice Research Institute

Presentation Outline

Background of the Study

Study Objectives

Conceptual Framework

Methodology

Results and Discussion

Take home messages

Background of the Study

• It has been seen that, in rural Bangladesh, household income is coming from various sources rather only from farming

• But there is not enough empirical evidence that measured the diversification of income sources in Bangladesh

• Village Dynamics in South Asia (VDSA) project is collecting income and employment data at rural household level.

• Rural livelihood diversification can be defined as the process by which rural households construct an increasingly diverse portfolio of activities and assets in order to survive and to improve their standard of living (Ellis, 2000).

Study Objectives

The general objective is to assess the livelihood diversification in rural rice-based areas of Bangladesh. Specifically;

• To identify the dominant patterns of rural livelihoods; and

• To determine the factors affecting rural livelihood diversification

Conceptual Framework

Research Methodology

• Divisions: 6• Districts: 11• Study Villages: 12

Region Villages

NorthernDharikamariRasun ShimulbariBoikunthapur

MiddleKonaparaNishaiganjPatordia

South-Eastern

BhabanipurBegumpurPaschim BahadurpurDakkhin Kabir Kathi

Western KhudiakhaliKhudiakhali

Study Location

Sampling Design, Sample Size and Data Collection

• Multi-stage random sampling technique

• 45 rural households were randomly chosen from each selected village

• Total 500 out of 540 households were included in the analysis as some households’ data were incomplete

• Primary data were collected for the year of 2012-13 through face-to-face interview using pre-tested semi-structured questionnaire.

Analytical Tools

Descriptive Analysis : Summary statistics, frequency tables, percentage

Test of Significance : ANOVA test, t-test

Net Income from Crops:NI = TR – TC

where, NI = Net income (profit) from the respective crop

per farm TR = Total return per farm (included return from

both main product and by-products)

TC = Total cost pre farm

Measuring of livelihood diversification

Simpson Diversification Index (SDI) was used to measure the livelihood diversification. The formula is

where, n = Total number of income sources and Pi = Income proportion of the i-th income

source.

SDI values ranges from zero to 1. Households with highly diversified incomes will have high SDI values, and lesser diversified incomes will have lower SDI values.

Based on the SDI values, the level of livelihood diversification was defined as following:

LEVEL OF DIVERSIFICATION SDI VALUESNo diversification < 0.01

Low 0.01 - 0.25Medium 0.26 - 0.50

High 0.51 - 0.75Very high > = 0.76

Based on the operating land holdings, households were classified into four groups:

LAND CLASS AMOUNT OF LANDFunctionally Landless > = 0.2 ha

Small 0.21-0.80 ha

Medium 0.81-1.50 ha

Large > =1.51 ha

Definition of the explanatory variables used in the regression modelVARIABLE

NAME DEFINITION MEASUREMENT EXPECTED SIGN

Gender Gender of household head (dummy) 1= Male, 0 = Female + Household size Total number of members in a household Number + Farm size Amount of operating land holdings Hectare +/- Member_org Member of any organization (dummy) 1 = yes

0 = No +

Migrants Number of household members staying outside of house (considering both domestic and international migration)

Number -

Dev-Prog_parti Households’ participation in any govt. Development program (dummy)

1 = yes 0 = No +

Primary_occupation

Main occupation of the household head (dummy)

1 = farming, 0 = otherwise +

HH_Assets Estimated value of all physical assets owned by a household, except the value of cultivable land

BDT (Bangladesh currency) +/-

Dependency ratio Ratio of inactive person over active person Percentage - Age_HH_Head Age of household head Years +/- Edu_HH_Head Education of household head Year of schooling + Amount of credit Received credit from any sources in a year BDT + Amount of savings

Money saved in any account in a year BDT +/-

Distance_district_town

Distance of household from the district town Kilometre -

Distance_market place

Distance of household from the nearest market place Kilometre -

Region_D1 Regional dummy 1= Northern region 0 = otherwise +/-

Region_D2 Regional dummy 1= Middle region 0 = otherwise +/-

Region_D3 Regional dummy 1= South-Eastern region

0 = otherwise +/-

Land_D1 Land class dummy 1= Landless 0 = otherwise +/-

Land_D2 Land class dummy 1= Small land class 0 = otherwise +/-

Land_D3 Land class dummy 1= Medium land less 0 = otherwise +/-

Tobit Regression

SDI* = β0 + β1 Gender + β2 Household size + β3 Farm size + β4 Member_org + β5

Migrants + β6 Dev_prog_part + β7 HH_assets + β8 Primary_Occupation + β9

Dependency_ratio + β10 Age_HH_Head + β11 Edu-HH_Head + β12

Amount_credit + β13 Amount_savings + β14 Distance_district_town + β15

Distance_market + β16 Region_D1 + β17 Region_D2 + β18 Region_D3 + β19

Land_D1 + β20 Land_D2 + β21 Land_D3+ μi

if SDI* > 0= 0 Otherwise

where, SDI* = Livelihood diversification indexβ0 = Interceptμi = Error term, which is normally distributed with mean zero and

constant variance

RESULTS AND DISCUSSIONSocio-Economic and Demographic Characteristics of Respondent

HouseholdsCHARACTERISTICS UNIT (%) MEAN (+ STD.)

Gender Male headed household % 85.2 Female Headed household % 14.8 Age of HH Head (Years) 51.35 13.908 Age range of all members

0-14 % 26.6 15-64 % 67.4 65 > = % 6.0

Dependency ratio % 56.9 Household size Number 5.33 2.424

Male Number 2.79 1.530 Female Number 2.54 1.388

Adult literacy rate % 83.8 Male % 88.7 Female % 78.9

Farm size (ha) 0.45 0.551 Land ownership class

Functionally landless % 28.2 Small % 43.0 Medium % 19.6 Large % 9.2

Land-Man ratio ha/person 0.21 0.245 Household Assets BDT (USD) 382,331

(4,780) 562073.9

Households with access to credit

% 43.4

Households who saved money in financial institutions

% 57.2

Household Income Sources and Their Share

Income from all the sources were categorised into nine

groups.

1. Rice crop2. Non-rice crops3. Non-crop Agriculture4. Agricultural laborer5. Non-agricultural laborer6. Business and caste occupation7. Salaried job and services8. Remittance 9. Transfer Payment

Farm Income

Non-Farm Income

Off-Farm Income

Household Yearly Total Income from All Sources and Their Share

Average yearly income and share by sources of income

SOURCE OF INCOMEAMOUNT OF INCOME SHARE OF

INCOME (%)BDT/YEAR USD/YEAR

Rice Crop 30,415 380 16

Non-rice Crops 16,152 202 8

Non-crop agriculture 17,668 221 9Agricultural laborer 4,864 61 3Non-agricultural laborer 13,714 171 7Business and caste occupation 38,992 487 20Salaried job and services 12,427 155 6Remittances 55,888 699 29Transfer Payment 1,282 16 1Total 191,402 2,393 100

F-value of ANOVA 14.27 (P = 0.000)

Share (%) of different sources in total household income across four regions

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Northern region

Middle region

South-Eastern region

Western region

Income share (%) in four regions

Transfer payment

Remittances

Salaried job and services

Business and caste occupation

Non-agricultural laborer

Agricultural laborer

Non-crop agriculture

Non-rice crops

Rice crop

69.3% 67.6% 75.1% 72.3%

Farm, Off-farm and Non-farm Income

Farm and non-farm income and their share

SOURCE OF

INCOME

AMOUNT OF INCOMESHARE OF

INCOME (%)BDT/YEAR USD/YEAR

Farm 64,235 803 33.6

Off-farm 4,864 61 2.5

Non-farm 122,303 1,529 63.9

Total 191,402 2,393 100.0

Farm income

34%

Off-farm income

3%

Non-farm income

64%

Share of farm, off-farm and non-farm income

Household Livelihood Diversification

Distribution of households across the level of diversification

LEVEL OF DIVERSIFICATIONNUMBER OF

HOUSEHOLDPERCENTAGE (%)

No 30 6.0

Low 98 19.6

Medium 159 31.8

High 192 38.4

Very high 21 4.2

Average SDI values by region

Distribution (%) of households into different level of diversification by regions

Most of the households from all four regions have diversified their livelihoods in to “medium” and “high” level.

REGIONLEVEL OF DIVERSIFICATION

TotalNo (%) Low (%) Medium

(%)High(%)

Very high (%)

Northern 2.4 12.8 43.2 38.4 3.2100.0

Middle 10.9 24.2 28.9 32.8 3.1100.0

South-Eastern 6.6 16.3 25.9 43.4 7.8100.0

Western 2.5 29.6 30.9 37.0 0.0100.0

All 6 19.6 31.8 38.4 4.2100.0

REGION NO. OF HOUSEHOLD AVERAGE VALUE OF SDI

Northern 125 0.45Middle 128 0.37

South-Eastern 166 0.46Western 81 0.39

All 500 0.42

Distribution of household (%) at different level of livelihood diversification by region

Average SDI values by household land class

Distribution (%) of households into different level of diversification by household land class

highest percentage of small (47%) and medium (46%) land holding households had high level of livelihood diversification

LAND CLASSLEVEL OF DIVERSIFICATION

TOTALNo(%)

Low (%)

Medium(%)

High (%)

Very high (%)

Functionally Landless 7.1 31.2 34.8 24.1 2.8 100.0

Small 5.6 16.7 25.1 46.5 6.0 100.0Medium 6.1 11.2 31.6 45.9 5.1 100.0

Large 4.3 15.2 54.3 26.1 0.0 100.0All 6.0 19.6 31.8 38.2 4.4 100.0

LAND CLASS AVERAGE VALUE OF SDIFunctionally landless 0.34

Small 0.46Medium 0.47

Large 0.40

Distribution of household (%) at different level of livelihood diversification by household land class

Correlation analysis among the explanatory variables

Factors Affecting Livelihood Diversification

land_d3 -0.1195 0.0524 -0.0472 -0.0699 -0.3094 -0.4288 1.0000 land_d2 0.1806 -0.1003 0.0552 0.1511 -0.5443 1.0000 land_d1 -0.1086 0.0488 -0.0112 -0.1115 1.0000 region_d3 0.2813 -0.4070 -0.4135 1.0000 region_d2 0.5850 -0.3387 1.0000 region_d1 -0.6079 1.0000distant_di~n 1.0000 distan~n region~1 region~2 region~3 land_d1 land_d2 land_d3

land_d3 0.1065 0.1279 0.3322 -0.0993 0.0356 -0.0572 0.3250 0.1721 -0.0466 0.0375 0.3777 0.0335 -0.0599 -0.0694 -0.0104 land_d2 0.0207 -0.0156 -0.1745 -0.0293 0.0221 -0.0479 0.0385 -0.1206 -0.0105 0.0623 -0.1176 0.0261 -0.0204 0.0079 -0.0780 land_d1 -0.1644 -0.2621 -0.4479 0.1792 -0.1489 0.1000 -0.3892 -0.2106 0.0385 -0.2072 -0.4634 -0.1290 -0.0394 -0.0881 -0.0470 region_d3 -0.1128 0.3137 0.0022 -0.1436 0.3488 0.0477 0.1143 0.1158 0.1037 0.1267 -0.0988 0.0241 0.1466 0.1930 -0.2546 region_d2 -0.0394 -0.0709 -0.1059 -0.1717 -0.0482 -0.1012 -0.0906 -0.1318 0.0342 0.0023 -0.0988 -0.1234 -0.1053 -0.0603 0.0606 region_d1 0.0976 -0.1707 0.1229 0.1284 -0.1824 0.1582 -0.0047 -0.0838 -0.0846 -0.0409 0.2098 0.0239 -0.0347 -0.0938 0.3182distant_di~n -0.0224 0.1444 -0.0893 -0.2315 0.1547 -0.0054 -0.0377 -0.0998 0.1357 0.0290 -0.1496 0.0035 -0.0369 -0.0681 0.1710distance_n~t 0.1253 -0.0569 0.1814 0.0298 -0.0990 0.1822 -0.0389 -0.0863 0.0269 -0.0386 0.2350 0.0696 -0.0377 -0.0852 1.0000 savings -0.1413 0.1837 0.0470 -0.0233 0.2212 -0.0272 -0.0472 0.2386 -0.0044 0.1286 -0.0238 -0.0689 0.1957 1.0000 borrowing 0.0052 0.2040 0.1968 0.0903 0.2445 -0.0007 -0.0723 0.3380 0.0230 0.0162 0.0878 0.1231 1.0000 edu_head 0.0917 0.0376 0.0792 -0.0477 0.0231 -0.0549 -0.0507 0.2197 0.0096 -0.1863 0.0839 1.0000land_manra~o 0.2284 -0.0309 0.8470 -0.1049 -0.1073 -0.0193 0.4112 0.1267 -0.0766 0.0165 1.0000 age_hh_head 0.1853 0.2740 0.0998 -0.1231 0.2792 -0.0728 0.1336 0.1076 -0.0548 1.0000dependency~o -0.0333 0.1277 -0.0375 -0.0230 -0.0299 0.2138 -0.0754 -0.0331 1.0000 hh_assets -0.0551 0.3625 0.2342 -0.0516 0.3117 -0.0591 0.0198 1.0000primaryocc~n 0.3433 0.1561 0.4005 -0.1922 0.0290 -0.0785 1.0000dev_prog_p~i 0.0496 0.0860 0.0124 0.2103 -0.0875 1.0000 migrants -0.1710 0.6392 0.0659 -0.1248 1.0000 member_org 0.0401 -0.0730 -0.1237 1.0000 farm_size 0.2378 0.3223 1.0000 family_size 0.0455 1.0000gender_hh_~d 1.0000 gender~d family~e farm_s~e member~g migrants dev_pr~i primar~n hh_ass~s depend~o age_hh~d land_m~o edu_head borrow~g savings distan~t

(obs=500)> _head borrowing savings distance_nearmarket distant_district_town region_d1 region_d2 region_d3 land_d1 land_d2 land_d3. corr gender_hh_head family_size farm_size member_org migrants dev_prog_parti primaryoccupation hh_assets dependency_ratio age_hh_head land_manratio edu

Variance Inflation Factor (VIF) analysis

.

Mean VIF 2.69 dependency~o 1.13 0.884820 edu_head 1.24 0.803482dev_prog_p~i 1.25 0.799907 member_org 1.28 0.782590 savings 1.28 0.779260 borrowing 1.31 0.760789 age_hh_head 1.34 0.747017gender_hh_~d 1.41 0.708978 hh_assets 1.58 0.634177primaryocc~n 1.61 0.621083distance_n~t 1.92 0.521119 migrants 2.20 0.454858 family_size 2.33 0.429738 region_d1 2.55 0.392273 farm_size 2.60 0.384476 land_d3 3.35 0.298261 region_d3 4.51 0.221857 region_d2 5.00 0.199849distant_di~n 5.49 0.182091 land_d2 6.12 0.163325 land_d1 6.90 0.144865 Variable VIF 1/VIF

. vif

Test of HeteroscedasticityAuxiliary regression

Breusch-Pegan / Cook- Weisberg test (hettest test)

_cons .0606118 .006859 8.84 0.000 .0471356 .0740881 sdihat -.05363 .0155187 -3.46 0.001 -.0841201 -.0231398 error2 Coef. Std. Err. t P>|t| [95% Conf. Interval]

Total 1.00931482 499 .002022675 Root MSE = .04449 Adj R-squared = 0.0215 Residual .985676826 498 .001979271 R-squared = 0.0234 Model .023637993 1 .023637993 Prob > F = 0.0006 F( 1, 498) = 11.94 Source SS df MS Number of obs = 500

. reg error2 sdihat

Prob > chi2 = 0.0042 chi2(1) = 8.22

Variables: fitted values of sdi Ho: Constant varianceBreusch-Pagan / Cook-Weisberg test for heteroskedasticity

. hettest

Tobit (Multiplicative Heteroscedasticity) regression results

VARIABLES COEFFICIENTS STD. ERR. Z-VALUE P-VALUE

Intercept 0.1441 0.0687 2.10 0.036 Gender of household head 0.1366 0.0349 3.91 0.000 Household size 0.0209 0.0038 5.53 0.000 Farm size 0.0140 0.0114 1.23 0.219 Member of any organization 0.0148 0.0189 0.78 0.433 Migrants -0.0270 0.0061 -4.43 0.000 Development program participation 0.1054 0.0247 4.27 0.000 Household assets -8.73e-08 1.97e-08 -4.42 0.000 Primary occupation -0.0128 0.0199 -0.65 0.518 Dependency ratio -0.0007 0.0002 -3.83 0.000 Age of household head 0.00002 0.0008 0.02 0.981 Education of household head -0.0077 0.0019 -4.08 0.000 Amount of credit 1.12e-07 2.66e-08 4.21 0.000 Amount of savings -3.05e-07 9.89e-08 -3.08 0.002 Distant to nearer district town 0.0019 0.0013 1.48 0.138 Distance to nearer market 0.0106 0.0078 1.36 0.173 Region_dummy1 0.0142 0.0316 0.45 0.653 Region_dummy2 -0.0651 0.0386 -1.69 0.092 Region _dummy3 0.0719 0.0348 2.06 0.039 Land class _dummy1 -0.0732 0.0370 -1.98 0.048 Land class_dummy2 0.0694 0.0287 2.42 0.015 Land class_dummy3 0.0692 0.0289 2.40 0.017 Sigma 0.1821 LR chi2(21) Prob > chi2

-40.47 1.00

Log likelihood 86.03

Marginal effect VARIABLES DY/DX STD. ERR. Z- VALUE P-VALUE

Gender of household head 0.1366 0.0350 3.91 0.000 Household size 0.0209 0.0038 5.53 0.000 Farm size 0.0140 0.0114 1.23 0.219 Member of any organization 0.0148 0.0189 0.78 0.433 Migrants -0.0270 0.0061 -4.43 0.000 Development program participation 0.1054 0.0247 4.27 0.000 Household assets -8.73e-08 0.0000 -4.42 0.000 Primary occupation -0.0128 0.0199 -0.65 0.518 Dependency ratio -0.0007 0.0002 -3.83 0.000 Age of household head 0.00002 0.0008 0.02 0.981 Education of household head -0.0077 0.0019 -4.08 0.000 Amount of credit 1.12e-07 0.0000 4.21 0.000 Amount of savings -3.05e-07 0.0000 -3.08 0.002 Distant to nearer district town 0.0019 0.0013 1.48 0.138 Distance to nearer market 0.0106 0.0078 1.36 0.173 Region_dummy1 0.0142 0.0316 0.45 0.653 Region_dummy2 -0.0651 0.0386 -1.69 0.092 Region _dummy3 0.0719 0.0348 2.06 0.039 Land class _dummy1 -0.0732 0.037 -1.98 0.048 Land class_dummy2 0.0694 0.0287 2.42 0.015 Land class_dummy3 0.0692 0.0289 2.4 0.017

Take Home Messages• Rural households in Bangladesh are diversifying their

livelihoods mostly at “medium” level

• South-Eastern region has highest livelihood diversification while Middle region has the lowest.

• Small and Medium land holding households have higher level of livelihood diversification than Landless and large land holding households.

• Non-farm income contributes more in total household income, hence it should be encouraged to expand non-farm employment opportunities.

• Functionally landless households should be given more attention to increase and diversify their incomes.

Maraming salamat po!