Distributional Impact of the 2008 Rice Crisis in the Philippines George Manzano & Aubren Prado University 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 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 Self-sufficiency in rice as a most challenging goal Talks of a no-import stance Adds to the sensitivity

Food Price Spike Volatile world rice market conditions –Low ending stocks –Export bans by certain countries ‘Herd’ reaction of importers

Source: Authors’ estimations, based on USDA (2013) Context 2008 Rice Crisis World rice market,

Source: Authors’ estimations, based on BAS (2013) Context 2008 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 RiceBudget 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) Context 2008 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 X Budget 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 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 CONCLUSIONS AND POLICY 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