Income Shocks, Intra Household Resource Allocation and Rice Consumption in a Major

Rice Producing Country

Khondoker Abdul MottalebPostdoctoral Fellow

Social Sciences Division (SSD)K.mottaleb@irri.orgNovember 18, 2013

Exit Seminar

Poverty in the rice economies

• Staple food.• Major source of income • Poverty is persistent in the major rice growing

area• Total extremely poor people (USD 1.25/day): 1

billion• More than half of them live in major rice

producing areas, particularly in SSA and SA.• Improving livelihoods.

Emerging opportunity

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1991

1993

1995

1997

1999

2001

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2005

2007

2009

2011

2013

2015

2017

2019

2021

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2025

2027

2029

2031

2033

2035

Asia Africa Americas Rest of World

Million tons milled rice

Additional rice needed:116 million tons by 2035

2010 global rice production

546

450

Real Challenges

Too much water Too less water

Uncertainty in the Future

More threats

Source: Stern Review on the Economics of Climate, 2006

Futuristic Technology:C4 Rice

C4 Leaf (Sorghum)

C3 Leaf (Rice)

Rice, tobacco Maize, sorghum

C4 Supercharges Photosynthesis Using A Two Compartment CO2 Concentrating Mechanism

2011 Kharif Crop in Jajpur (Orissa)

Swarna

Swarna-Sub1

Drought tolerant rice is available

• IR74371-70-1-1 has been developing targeting india as “souvagi dhan”.

• IR74371-54-1-1 has been developing targeting Philippines

• IR77080-B-34-3,IR81047-B-106- 3-4 identified promising in Mozambique.

Sahbhagi dhan

NSIC RC 192

Economic Benefits of a Drought Tolerant Rice Variety in South Asia

*Using a 5% discount rate

Climate scenario NPV (million USD) Range of IRR %

Base 2018.22 0.26-0.54

A2 1960.77 0.13-0.59

A1B 1805.46 0.17-0.43

B1 1557.79 0.17-0.57

Benefits of Development of Climate smart Rice

New Variety

Existing variety Base A2 A1B B1

World

Milled Production (mt) 530.36 +2.21 +1.74 +1.63 +1.13

Nominal price (USD/Ton) 1107.50 -20.61 -7.43 -10.27 -6.51South AsiaMilled Production (mt) 163.47 +7.40 +6.18 +5.67 +3.98

Consumption (mt) 159.77 +5.21 +5.16 +4.64 +3.39

Full paper can be accessed at: http://ageconsearch.umn.edu/bitstream/124745/2/MottalebRev.pdf

Natural disasters-> income volatility of the rice farmers

Income volatility and Resource allocation

Income volatility and negative income shocks can hamper long run human capital development.

Negative income shock can also have gender differentiated impacts (intra household resource allocation).

Literature is scanty

China, Bangladesh, India are among the disaster prone countries…

…In terms of number killed, Bangladesh topped the list with an average of 15,000 people being killed each year during 1982-1991 period (World Disaster Report-IFRC, 1993)

Year Barisal Chittagong Khulna Total

1960-1980 1 11 1 13

1981-1998 2 13 5 20

1999-2010 2 2 8 12

Total 5 26 14 45

Table 1: Major cyclonic storms from 1960-2010 that caused significant losses of

lives and properties

Source: BBS: Statistical Yearbook of Bangladesh, 2001 and 2010

Cyclone Aila, May 25-27, 2009

190 people were killed, more than 3.9 million people were affected (IFRCRC, 2010 )Destroyed late boro and Aman rice in the field

Table 3: AILA affected districts

Group Division Severely damaged districts

No. of people affected (000)

Experimental Barisal Barguna 390Barisal 357Bhola 128Jhalokati 302Patuakhali 293Pirojpur 359

Khulna Bagerhat 480Khulna 363Satkhira 170

Chittagong Noakhali 116Not affected

Control Chittagong Comilla 94Chandpur 91Feni 30Laksmipur 29Chittagong 13.53

Cox’s Bazar 29.45

A priori Conjectures

Booming repairing and construction sector

Wage rate increasesOpportunity cost for schooling

increased

Affected households need to reconstruct houses, seed beds and bunds.

Small farm households may face liquidity constraints

They need cash !Employ children in farm work

The cyclone caused substantial loss in rice production

Generated negative income shocks

Natural Experiment: double difference model

YDT Affected= D2 Not affected =D1

Difference

T=2010 YD2 (10) YD1(10) YD1(10) - YD2 (10)

T-2005 YD2 (05) YD1(05) YD1(05) - YD2 (05)

T=2000 YD2 (00) YD1(00) YD1(00) - YD2 (00)

Change YD2 (00) -YD2 (05) -YD2 (10)

YD1(00)- YD1(05) -YD1(10)

(YD1(00) - YD2 (00) )-(YD1(05) - YD2 (05))-(D1(2010) - YD2 (10))

Model Specification

itii

it

ZdummyYearAD

dummyYearADADdummyYeardummyYearY

)()2010*(

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

5

43210

Y: dependent variables: Paddy income, consumption and expenditure on different itemsAD: equals 1 if a district is affected, 0 otherwise

Z: demographic variables

T: year

5

5 :the effect of the cyclone in the cyclone-affected districts compared to other districts (the difference in the effect of cyclone AILA on Y between treatment and control groups)

Study 1

Major findings:

1. Substantial loss in rice production and income2. Non-food expenditure increased3. Health expenditure increased4. Schooling expenditure decreased (drop out/year

loss)5. School admission expenditure decreased

Study 2:Intra-Household Resource Allocation

Our empirical results confirmed that the cyclone-affected households spent less on their children’s schooling and children’s school admission than did the unaffected household

When they stopped sending children to school, whom did they stop?

Boys or girls, or both? Why? Did they spend less on health issues of

boys/girls?

Lets see our Conjectures once again!

Booming repairing and construction sector

Wage rate increasesOpportunity cost of schooling can

increase

Female secondary school stipend program

Repairing and construction sector is generally male dominated

Wage rate increases-> boys opportunity cost for schooling increases than girls

School expenditure on boys declined substantially compared to the comparison group in 2010

Intra-Household Resource Allocation under Negative Income Shock:

A Natural ExperimentHealth Education

Crop income Male Female Male Female

Year 2005 dummy 16.12** -0.11 -0.34** 1.72*** 0.94***(2.55) (-0.90) (-2.04) (6.14) (4.08)

Year 2010 dummy 21.13*** 0.21* 0.35** 2.87*** 1.88***(3.36) (1.67) (2.15) (10.35) (8.29)

A dummy for cyclone-affected district (=1)

15.11***(3.33)

-0.53***(-4.48)

-0.80***(-5.08)

0.75***(3.04)

0.15(0.73)

Cyclone-affected district X Year 2005 dummy

-14.20**(-2.05)

0.45***(2.83)

0.74***(3.47)

-0.09(-0.25)

0.45(1.59)

Cyclone-affected district X Year 2010 dummy

-17.18**(-2.59)

0.45***(2.93)

0.471**(2.31)

-0.81**(-2.51)

-0.11(-0.41)

Relationship between income and rice consumption

300

350

400

450

500

550

600

Asia Africa Americas Rest of World

Million tons milled rice

Additional rice needed:116 million tons by 2035

2010 global rice production

546

450

The Demand for Cereals in Bangladesh: An Almost Ideal Demand Estimation

Estimated income and price elasticities considering six major commodities: rice, wheat, rice and wheat products, fish lentil, and vegetables.

HIES data 2000, 2005, 2010Number of households: 29760

In 2000, GDP per capita: $363In 2011 : $734 (more than 100% increased)How this income growth affected rice

consumption?

Yearly per capita consumption (KG)

Year 2000 2005 2010Rice 164.25 161.90 150.95Rice and wheat products 4.43 6.78 8.08

Wheat 7.04 5.21 10.43

Lentil 6.00 5.48 5.48

Fish 14.86 16.43 18.77

Vegetables 76.65 86.04 91.51

The Model

WhereWi= expenditure share on commodity i (piqi/M)M= total expenditure on sampled commoditiesZ= household demographics

Two stage budgeting method applied

Expenditure (income) elasticities

Rice Rice and wheat

products

Wheat Pulse Fish Vege.

2000 0.55 3.86 1.47 -0.16 3.05 -0.192005 0.56 3.02 1.56 -0.34 3.13 -0.342010

0.47 2.46 1.37 -0.06 2.21 -0.57Average

0.53 2.87 1.45 -0.17 2.62 -0.38

Price elasticity

Hicksian Marshallian

Year 2000 2005 2010 2000 2005 2010

Rice -0.10 -0.11 -0.09 -0.41 -0.43 -0.30

Rice and wheat products

-0.11 -0.34 -0.45 -0.23 -0.48 -0.60

Wheat -2.50 -2.88 -2.27 -2.53 -2.91 -2.30

Pulses -0.67 -0.63 -0.68 -0.66 -0.62 -0.68

Fish -0.28 -0.37 -0.30 -0.86 -0.95 -0.98

Vegetables -0.62 -0.62 -0.53 -0.60 -0.57 -0.46

Findings

• Income elasticity is large in absolute size and positive

• Rice is a normal and necessary commodity. STRICTLY NOT an INFERIOR commodity.

• In future, total rice consumption in Bangladesh will increase.

I would like to thank• Rodrick M. Rejesus, NC State• A.K. Mishra, LSU• V. Pede• Andy Nelson• MVR Murty• Tao Li• Imelda Molina• Harold. G. Valera• Murali K. Gumma• H. Bhandari, D. Matty • Prof. Y. Chito and Tin Tin• Malu and Rio

Thanks for your support to me always

Tita Mirla and Friend Dehner

Thanks to Dr. S. Mohanty

Please don’t say “good bye” but

please say “see you again”