determinants of rice income and access to land by the rice farmers: the case of bangladesh

7/31/2019 Determinants of Rice Income and Access to Land by the Rice Farmers: The Case of Bangladesh

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Determinants of Rice Income and Accessto Land by the Rice Farmers: The Case of

Bangladesh

Kh. A. Mottaleb, T. W. Tsusaka, M. S. Rahman and S. Mohanty

Presented by

Kh. A. Mottaleb

Postdoctoral Fellow-Agricultural Economist

Social Sciences Division

International Rice Research Institute (IRRI)

August 08, 20128/15/2012 1


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Importance of rice

Contribution of agriculture to GDP:20.29%

-Rice to GDP: 11%.

cultivated on 75 % of the totalcropland.

93% of the total cereal production

is rice (335 Mt out of 360 Mt)

Total labor force: 54.1 million

-Into agriculture: 25.59 million (47%)

-Into rice: 19.19 million (35%)

93%

3%

4%

Rice

Wheat

Maize

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Need to produce more rice!

Demand for rice has

been increasing--

Need to produce

more rice.

Projection is based on IGRM

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31.9

38.16

42.84

0 10 20 30 40 50

2010

2020

2035

rice required

rice required


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Real Concern

Rapidly shrinking rice farmland

Area: 147,570 km2 (

Ranked 94th

in the world ) Population: 149.77 million (ranked 9th in the world)

Population per sq.: 1015

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

1961 1971 1981 1991 2001

per capita Arable land

per capita Arable land

Source: World Development Indicators, 2012Source: Bangladesh Bureau of Statistics (BBS): HIES 2000, 2005, 2010

0.78

0.9

1.15

0 0.5 1 1.5

2010

2005

2000

cropland

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40.7

49.5

54.1

0 10 20 30 40 50 60

1990

2005

2010

labor force

labor force

Source: Labor force survey 1990 and Bangladesh Economic Review 2010.


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Change in global climate

23

24

25

26

27

28

29

30

31

32

33

1956 1966 1976 1986 1996 2006

sylhet

Jessore

Bogra

Chittagong

Figure 1: Monthly avg. max Temp (0C) in four stations

Source: Bangladesh Agriculture Research Council, 2012

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0

1000

2000

3000

4000

5000

6000

1956 1966 1976 1986 1996 2006

Sylhet

Jessore

Chittagong

Bogra

Figure 2: Yearly total rainfall (mm) in four stations

40

50

60

70

80

90

100

110

1967 1977 1987 1997 2007

Jessore

Chittagong

Bogra

Sylhet

Figure 3: Monthly total average bright sunshine (hours)

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South Asia Needs to Produce more Rice

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Actual Required

2012 2035

India 94.99 113.22

Nepal 2.97 3.36

Pakistan 2.5 5.5

Sri Lanka 2.8 3.2

Projection is based on IGRM


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And per capita arable land is declining too.

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0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

1960 1970 1980 1990 2000

Bangladesh

India

Nepal

Pakistan

Sri Lanka

Bangladesh

Source: World Development Indicators 2012


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Research question-1

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How to ensure higher rice production and income of

the farmers from increasingly declining arable land?


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Research question-2

How to reduce burden on arable land?

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Climate, infrastructure, household

characteristics, physical and humancapital

Access to agriculture land

market (rent in, rent out,

purchase)

Farm income: rice income fishery,

livestock, forestry and agriculture

wage incomeNonfarm income (salary, nonfarm

wage income, business income,

remittance )

A working model on Rice income and Access to Land Market

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Research hypotheses

Major hypotheses:

1. As rice income can be adversely affected by climate

change, high rice income can be ensured by

developing and disseminating more climate resilientrice varieties.

2. Increases in rice, and nonfarm income, on the other

hand enhances access to land to poor farmers and

indirectly reduces pressure on arable land, as richfarmers tend to adopt the role of managers by

renting out their land.

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Materials and Method

GOB: Household Income and Expenditure survey, 2000,2005, 2010

Two stage stratified random sampling.

Sample size: HIES 2000: 7440, HIES 2005: 10080 HIES 2010:12200

In this study: 8630 households who were only rice farmers(rice income>0).

Coverage: Entire Bangladesh: 7 divisions, 64 districts, 384sub-districts.

Climate data sources:

-unpublished data collected from Bangladesh MetrologicalOffice, Agargaon, Dhaka.

-Online data from Bangladesh Agriculture Research Council(BARC).

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Demographic characteristics of the sampled

households over the sampled periods

Year 2000 2005 2010

No. of households 2624 3501 2505

Age of the HH head 45.90 47.01 47.61

% Male HH head 96.3 95.7 92.8

HH heads year of

schooling

3.15 3.24 3.08

% Rural HH 92.5 83.1 84.6

No. of family members 5.61 5.28 5.01

Source: BBS, HIES 2000, 2005, 2010. Authors own calculation.8/15/2012 14


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Sources of Income and Income from Rice of the

Sampled Households (BDT 000)

Year 2000 2005 2010

Yearly total income (farm+

nonfarm) 60.78 71.38 137.12

Income from rice % 23.5 21.8 31.8

Non-farm income %56.7 56.9 40.1

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Source: BBS, HIES 2000, 2005, 2010. Authors own calculation.


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Farm size and Information on Land Market access by

the Sampled households over the years

Year 2000 2005 2010

Farm size (ha) 1.15 0.90 0.78

% Purchased land 4.23 5.17 5.47

% Rented in land 49.77 50.47 59.32

% Rented out land 20.08 20.82 22.28

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Characteristics of the HH based on their access to land market

Land purchased Rented in

No Yes No Yes

No. of households 2368 137 1019 1486Farm size (ha) 0.76 1.24 0.82 0.76

Income from rice 42.14 68.43 45.88 42.01

Non-farm income 31.75 50.68 37.64 29.46

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Characteristics of the HH based on their access to land market

Rented in Rented out

No Yes No Yes

No. of households 1019 1486 1947 558

Farm size (ha) 0.82 0.76 0.73 0.96Income from rice 45.88 42.01 41.04 52.45

Non-farm income 37.64 29.46 29.88 42.93

Both rice and nonfarm income is positively related with land

purchase

-tively with rent in

+tively with rent out

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Correlation between Rice & nonfarm income with some

climate variables

Rice income Nonfarm income

Rice income 1

Nonfarm income 0.03*** 1

(0.00)

Distance to Dhaka 0.07*** -0.10***(0.00) (0.00)

Length of metal road -0.03*** 0.05***

(0.00) (0.00)

Monthly avg. max. Temp

0.21***

0.02

(0.00) (0.14)

Monthly average humidity -0.07*** -0.03***

(0.00) (0.01)

Yearly total rainfall -0.03*** 0.07***

(0.00) (0.00)8/15/2012 19


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Model specification

Y = 1 if purchased land 0 otherwise

Y=1 if rented out land, 0 otherwise

Y=1 if rented in land, 0 otherwise

X is the vector of variables: age, sex, location, dummies for administrative

divisions, and year dummiesZis the vector of exogenous variables: strictly correlated with income from

rice (RI and nonfarm sector (NFI) and uncorrelated with the error term of

equation (1): climate variables, distance to Dhaka and the length of metal

roads at the district level.

Simple linear probability model is used to estimate the model with clusteredstandard errors.

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)3()2010()2005()()()(

)2()2010()2005()()()(

)1()(

)2010()2005()()()(

210

210

43210

ititiitit

ittiitit

ititi

tiititit

dummyYearbdummyYearbXiZbNFI

dummyYearadummyYearaiXiZaRI

X

dummyYeardummyYeariXNFIRIY

D t i t f i d f i


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Determinants of rice and nonfarm income

Rice income Non farm income

Distance from Dhaka to district headquarter 0.02***

(3.00)

-0.08***

(-6.59)Maximum temperature monthly average 26.68***

(3.12)

-19.31

(-1.27)

Variation in monthly average maximum

temperature in the last 5 years

6.78***

(3.89)

-3.72

(-1.32)

Square of monthly average maximum

temperature

-0.40***

(-2.86)

0.35

(1.53)

Years of schooling of HH head 0.97***

(10.65)

2.61***

(14.75)

Total annual rainfall -0.14(-0.04)

0.42(0.08)

Variation in annual rainfall in the last 5 years -0.01*

(-1.88)

0.002

(0.44)

No. of observations 8630 8630

First stage F 43.89 18.988/15/2012 21


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2SLS-Determinants of land market participation

Land purchased

(yes=1)

Land rented

in (yes=1)

Land rented

out (yes=1)

Rice income 0.002*

(1.79)

-0.01*

(-1.86)

0.01***

(3.45)

Nonfarm income 0.001*

(1.66)

-0.01***

(-6.38)

0.005***

(4.73)

Distance from Dhaka to districtheadquarter

0.0001(1.51)

-0.001***(-4.30)

0.0002(1.15)

Maximum temperature monthly average -0.29***

(-3.75)

-0.19

(-0.85)

-0.13

(-0.73)

Variation in monthly average maximum

temperature in the last 5 years

0.01

(0.52)

-0.004

(-0.09)

-0.04

(-1.37)

Square of monthly average maximum

temperature

0.004***

(3.92)

0.004

(1.19)

0.001

(0.54)

Hansen J statistic 4.99 3.92 2.95

Chi-sq(6) P-val 0.54 0.69 0.828/15/2012 22


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Major findings

Change in global climate may affect rice income negatively

and significantly.

Years of schooling of the HH head significantly and positively

determine both rice and nonfarm incomes.

Increase in rice and nonfarm incomes allows farmers to take

managerial roles by rent out their land.

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Policy implications

To reduce burden on farmland, both rice and nonfarm

income should be increased. It can be done through

the development and dissemination of more climate

resilient rice varieties.

Expansion of general education can play important

roles.

The provision of training can be an alternative.

Intervention by the government with the help of

International donor agencies.

Short term/medium term

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Policy implications

Climate resilient rice varieties should be combined

with super high yielding traits (may be C4 rice) tobreak the yield ceiling.

It can ensure more production/income even from

small parcels of land -> even under volatile climate ->reduce extra burden on land.

Long term

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Thank You

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determinants of rice income and access to land by the rice farmers: the case of bangladesh

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