The impact of a large rice price increase on welfare and poverty in Bangladesh

The impact of a large rice price increase on welfareand poverty in Bangladesh

Syed Abul Hasan∗

∗Crawford School of Public PolicyThe Australian National University

Crawford PhD Conference 2013, ANU

Syed Hasan (Crawford School) The impact of a large rice price increase 4 November, 2013 1 / 25

Outline

1 MotivationImportanceFindings and contribution

2 Data

3 Impact on welfare

4 Relation between income and welfare loss

5 Impact on poverty

6 Conclusions


WHY THIS RESEARCH IS IMPORTANT

Rice is important in Bangladesh

1 High share of rice in total expenditure (national average 17%)

2 Low cross price elasticity of rice demand wrt wheat (≈ 0 in a study)

Bangladesh is vulnerable to rice price shocks

1 Dependence on imported rice for fulfilling domestic demand

2 Dependences on the harvest for food security

3 A large proportion of poor households, most of which buy rice


EFFECT OF RICE PRICE CHANGE

Direct/distributional/first round (order) effect

1 Entitlement of net rice buyers and net rice sellers

Indirect/behavioural/second round (order) effect

1 Adjustment of production and consumption

2 Reduce consumption and increase production of rice

Second round effect is mportant if price change is large

1 Rice price doubled in Bangladesh between Jan.,07 and Apr.,08


WHAT WE FIND

With a 50% rise in rice price

1 Indirect effects of price change is important

2 Quadratic relationship between the welfare loss and income

3 A higher rice price may either increase or decrease poverty HCR

4 Per capita income gap increases with a higher rice price


PAST STUDY

Estimating welfare loss

1 Only consider the first round effect (e.g., Deaton, 1989; Ravallion,1990; Ivanic and Martin, 2008)

2 Rely on household income, prone to measurement error in surveys(e.g., Mghenyi, Myers and Jayne 2011; Myers, 2006)

Studying relationship between welfare loss and household income

1 Rely on transitory rather than permanent income measures2 Semiparametric models suffer from endogeneity3 Use subjective equivalence scale (e.g., Mghenyi et al., 2011)

Studying impact on poverty1 Studies on poverty ordering/dominance mostly based on household

income (e.g., Mghenyi et al., 2011; Chen and Duclos, 2011)2 Household expenditure seems appropriate for poverty comparisons


DATA: Bangladesh HIES, 2010

Cross section household survey

Nationally representative socio-economic information

Number of household- 12,240 (rural-7,840 and urban-4,400)

Similar findings with the 2005 round of HIES

Prefer presenting result with 2010 wave of HIES

1 Questionnaire modification

2 Larger sample size

3 Use of ICT to reduce errors


MEASUREMENT ERROR IN HOUSEHOLD DATA

Household income suffers more than household expenditure

Typically severe in survey data from agrarian economies

Significant no. of households in HIES have negative or low income

10% have an income that is 60% lower than their expenditure

25% have an income that is 40% lower than their expenditure

50% have an income that is lower than their expenditure

Suggests that household income in HIES may be unreliable


EMPIRICAL MODEL

Used EV-monetary measures of welfare change

Second-order approximation of proportionate welfare loss (mi )

mi ≈ (ssi − sd

i )λ− 0.5[ssi ξ

psi − sd

i ξpdi ]λ2 +

0.5{(Ri − ξydi )[(sd

i )2 − 2sdi ss

i ] + Ri(ssi )2}λ2, (1)

i denotes household

ssi (sd

i ) rice income (expenditure) share

λ = (p1 − p0)/p0

ξpsi (ξpd

i ) the price elasticity of rice supply (demand)

ξydi the income elasticity of rice demand

Ri the coefficient of relative risk aversion (CRRA)


METHODOLOGICAL CHANGES

To estimate the welfare loss we

Use household expenditure instead of household income

Capture the second order welfare effect of a price increase

Values for the parameters - from World Bank (2010)

Analysis based on a 50% rise in the rice price

Sharp rice price change - to show role of second round


RESULTS

Table: High rice price and households’ proportionate welfare loss (weighted)

1st round (∆1) 2nd round (∆2) ∆2/∆1

Mean SD Mean SD (%)

Barisal -0.0752 0.0912 0.0024 0.0137 -10.8849Chittagong -0.0494 0.0782 0.0058 0.0113 -16.5463Dhaka -0.0604 0.1114 0.0030 0.0168 -14.5099Khulna -0.0484 0.1308 -0.0015 0.0190 -10.7546Rajshahi -0.0333 0.1957 -0.0026 0.0271 -9.4643Rangpur -0.0367 0.1772 -0.0067 0.0247 -8.7385Sylhet -0.0606 0.1319 -0.0004 0.0198 -10.7081

Bangladesh -0.0514 0.1333 0.0008 0.0195 -12.6046

Note: ∆1 = (ssi −sd

i )λ and ∆2 = −0.5[ssi ξ

psi −sd

i ξpdi ]λ2 +0.5{(Ri−ξyd

i )[(sdi )2−2sd

i ssi ]+

Ri (ssi )2}λ2.


RESULTS (Contd.)

2nd round effect –a significant proportion of 1st round (9-17%)

In rice importing (exporting) regions –2nd round partly offsets(intensifies) 1st round welfare loss

Ignoring 2nd round –underestimates (overestimates) welfare lossin the rice exporting (importing) regions

Households associated with rice production suffer least

Using household income provides higher 2nd round impact


EMPIRICAL MODEL

Semiparametric (SP) model used to analyse relationship betweenhousehold permanent income and welfare loss (mi )

mi = F (xi) + Ziβ + ui , (2)

xi -(log of) adult equivalent permanent income

Zi -demographic and socioeconomic variables that enter linearly

β is a vector of parameters

F is an unknown function

the error term ui ∼ NID(0, σ2)



Household expenditure proxys permanent household income

Welfare loss and expenditure –may be jointly determined

Endogeneity of household expenditure –controlled by usingnon-farm household income as an instrument

Generate residuals through NP regression of endogenous variableon instruments

These residuals are used as a covariate in the SP model

Employed a recent SP estimate of ES for Bangladesh

SP estimation employ local linear regression using Kernel method


SEMIPARAMETRIC REGRESSION

Figure: SP regression of welfare loss


RESULTS

Table: Hardle and Mammen test results: p-value

With HH With PC With equivalent exp.exp. Exp SP

scaleOECDscale

SRFSscale

Barisal 0.05 0.61 0.74 0.55 0.52Chittagong 0.02 0.62 0.14 0.25 0.03Dhaka 0.14 0.21 0.12 0.13 0.68Khulna 0.60 0.14 0.17 0.11 0.22Rajshahi 0.35 0.86 0.32 0.18 0.11Rangpur 0.00 0.38 0.02 0.07 0.17Sylhet 0.85 0.79 0.07 0.02 0.05Bangladesh 0.00 0.00 0.00 0.05 0.00

Note: H0 : Nonparametric fit can be approximated by a parametric ad-justment of order 2, H1 : Nonparametric fit cannot be approximated by aparametric adjustment of order 2. A low p-value rejects the quadratic fitand vice-versa.


RESULTS

Relationship between welfare loss and permanent householdincome –appears quadratic

Specification test – if a quadratic fit can approximate the SP fit

Cannot reject in 5/7 regions but for the whole country

Cannot reject when we use the per capita expenditure

Two possible explanationsRich agricultural households benefits from higher rice price

Rich non-agri households –low expenditure share –lose marginally

Need income support for the poor in the face of a food price shock

Use of household expenditure and including 2nd round effectprovides expected results


POVERTY DOMINANCE

Employed FGT poverty measures

P1 is the poverty HCR

P2 is the per capita income gap (normalized poverty gap)

For two distributions F and G with the same population

Plot of HCR at all poverty lines gives the poverty incidence curve

If poverty incidence curve for F lies below G, then F FOPD G

Area under poverty incidence curve gives the poverty deficit curve

If poverty deficit curve of F is below G then F SOPD G

SOPD ranks distributions in terms of PC income gap



Replace household income with household expenditure

Generate a new distribution by incorporating welfare loss

New distribution represent income distribution with high rice price


RESULTS

Figure: First order poverty dominance


RESULTS (Contd.)

Figure: Second order poverty dominance


RESULTS (Contd.)

No evidence of first order poverty dominance

Rice price increase unambiguously increases PC income gap

Exclusive use of the first round impact or household income–results are not in line with our expectations

Poverty policies that rely on expenditure provide better outcomes

Use of poverty lines shows dependency of HCR on poverty line

Poverty lines may provide wrong assessment of poverty


CONTRIBUTION

Improved way of estimating the welfare loss

Improved modelling of welfare loss on income

Confirms usefulness of poverty ranking


SUMMARY

This paper improves methodology to estimate of welfare loss

Suggest a quadratic relationship between welfare change andhousehold income

Confirms that changes in HCR depends on poverty line used


The impact of a large rice price increase on welfare and poverty in Bangladesh

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Transcript of The impact of a large rice price increase on welfare and poverty in Bangladesh

￼ ￼ The impact of a large rice price increase on welfare and poverty in Bangladesh

Business

Transcript of ￼ ￼ The impact of a large rice price increase on welfare and poverty in Bangladesh

The impact of a large rice price increase on welfare and poverty in Bangladesh

Transcript of The impact of a large rice price increase on welfare and poverty in Bangladesh