Distributional Impact of the 2008 Rice Crisis in the Philippines

George Manzano & Aubren PradoUniversity of Asia & the Pacific

Manila, The Philippines

UNCTAD Virtual Institute Seminar on Trade and Poverty

Geneva, 8-10 September 2014

Policymakers

– Jerome Bunyi & Maria Araceli Albarece, Permanent Mission of the Philippines to the World Trade Organization

– Dr. Segfredo Serrano, Department of Agriculture of the Philippines

CONTEXT

CONTEXT

Context

• Rice: most sensitive food item– THE Staple– Major food expense for many households– Many farmers depend on rice farming

• … one of the most protected commodities

• … with a government office just to regulate trade in rice primarily

Context

• Philippines has generally been a net importer. Largest importer in 2008.

• Self-sufficiency in rice as a most challenging goal

• Talks of a no-import stance• Adds to the sensitivity

Food Price Spike2007-2008

• Volatile world rice market conditions– Low ending stocks– Export bans by certain countries

• ‘Herd’ reaction of importers

Source: Authors’ estimations, based on USDA (2013)

Context2008 Rice Crisis

World rice market, 1960-2012

Source: Authors’ estimations, based on BAS (2013)

Context2008 Rice Crisis

Monthly trends in rice prices, January 2007 – August 2009

CONTEXT

OBJECTIVES

Objectives of the Study

• Determine the distributional impact of the 2008 rice price shock in the Philippines.

What are the characteristics of the affected households?

Immediate Policy Context

• Why are we interested in knowing who are the vulnerable groups to a rice price spike?

Efficient targeting

Immediate Policy Context

• How to make use of the information?

– Measures to alleviate suffering– Food: time element is critical– Design for rapid mobilization of aid in the

future

Broad Policy Context

• Response is always a rationing exercise– Resources are always scarce compared to

the needs.– Cost-benefit of more permanent solution,

crisis prevention

CONTEXT

METHODOLOGY

Methodology

• In general, when price of a commodity rises– Producer gains (higher income)– Consumer losses (higher expense)

• Extent of benefits and costs varies in degrees– Benefit to household: share of rice income to

total income– Cost to household: share of rice expenses to

total expenditure

Vulnerability Indicator

Net Income Share of rice

Income Share of Rice Budget Share of Rice-

Methodology

• Distribution of Benefit/Cost on per capita expenditures

• Classify according to household groups– Gender of the HH head– Agricultural vs Non-agricultural– Urban vs Rural

Vulnerability of households

• Groups that are more vulnerable to shocks in rice prices:– In general, poorer households across groups– Non-agricultural than Agricultural– Urban than Rural– Female-headed than Male-headed

Methodology

• Simulation– Actual rice price changes– Adjustments for the difference in farm gate and

retail prices of rice– Price changes between the pre-crisis phase

(January 2007 to February 2008) and the crisis phase (March 2008 and September 2008)

• Construction of the Benefits/Costs variable

Source: Authors’ estimations, based on BAS (2013)

Context2008 Rice Crisis

Monthly trends in rice prices, January 2007 – August 2009

Methodology

Constructed a Benefits/Cost Variable (BC)

Change in farm gate prices

X Rice Income Share

Change in retail prices

XBudget Share of Rice

-

Methodology

Constructed a Benefits/Cost Variable (BC)

BC =

[a(rice income share) – rice budget share] x [change in retail price]

where a is the ratio of average rates of changes in farm gate and retail prices

CONTEXT

FINDINGS

Characteristics of the Sample

All Households: 38,400

Male 80%

Female20% Urban

45%Rural55%

Agri26%

Non-

Agri74%

Source: Authors’ calculations, based on the 2009 FIES

Structure of the Sample

Source: Authors’ calculations, based on the 2009 FIES

Source: Authors’ estimations, based on the 2009 FIES and BAS (2013)

Benefits/costs by gender of household head

(controlling for per capita expenditure)

Source: Authors’ estimations, based on the 2009 FIES and BAS (2013)

Benefits/costs by level of urbanity(controlling for per capita expenditure)

Source: Authors’ estimations, based on the 2009 FIES and BAS (2013)

Benefits/costs by Agricultural HH indicator

(controlling for per capita expenditure)

Distributional impact of the 2008 crisis by region

Top 5 Gainers

• Central Luzon• Cagayan Valley• Central Visayas• Autonomous

Region of Muslim Mindanao

• Ilocos Region

Top 5 Losers

• National Capital Region

• CALABARZON• Central Luzon• Western Visayas• Central Visayas

CONTEXT

CONCLUSIONSANDPOLICY RECOMMENDATIONS

Conclusions

• The effect of a rice price shock is regressive.

• Across HH per capita income, those affected more were– Female-headed HHs– Urban HHs– Non-agricultural HHs

• Geographical differences in gainers/losers

Policy Implications

• More efficient targeting exercise for safety net measures– Conditional Cash Transfers – NFA subsidized rice

Future Directions

Access to better data on rice income per household

Effects of rice changes on wages and inflation: second-order effects

Thank you!

George Manzano & Aubren Prado

University of Asia & the Pacific

Manila, The Philippines