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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
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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
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CONTEXT
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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
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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
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Food Price Spike 2007-2008 Volatile world rice market conditions –Low ending stocks –Export bans by certain countries ‘Herd’ reaction of importers
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Source: Authors’ estimations, based on USDA (2013) Context 2008 Rice Crisis World rice market, 1960-2012
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Source: Authors’ estimations, based on BAS (2013) Context 2008 Rice Crisis Monthly trends in rice prices, January 2007 – August 2009
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CONTEXT OBJECTIVES
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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?
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Immediate Policy Context Why are we interested in knowing who are the vulnerable groups to a rice price spike? Efficient targeting
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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
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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
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CONTEXT METHODOLOGY
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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
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Vulnerability Indicator Net Income Share of rice Income Share of RiceBudget Share of Rice -
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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
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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
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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
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Source: Authors’ estimations, based on BAS (2013) Context 2008 Rice Crisis Monthly trends in rice prices, January 2007 – August 2009
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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 -
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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
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CONTEXT FINDINGS
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Characteristics of the Sample All Households: 38,400 Source: Authors’ calculations, based on the 2009 FIES
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Structure of the Sample Source: Authors’ calculations, based on the 2009 FIES
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Source: Authors’ estimations, based on the 2009 FIES and BAS (2013) Benefits/costs by gender of household head (controlling for per capita expenditure)
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Source: Authors’ estimations, based on the 2009 FIES and BAS (2013) Benefits/costs by level of urbanity (controlling for per capita expenditure)
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Source: Authors’ estimations, based on the 2009 FIES and BAS (2013) Benefits/costs by Agricultural HH indicator (controlling for per capita expenditure)
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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
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CONTEXT CONCLUSIONS AND POLICY RECOMMENDATIONS
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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
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Policy Implications More efficient targeting exercise for safety net measures –Conditional Cash Transfers –NFA subsidized rice
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Future Directions Access to better data on rice income per household Effects of rice changes on wages and inflation: second-order effects
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Thank you! George Manzano & Aubren Prado University of Asia & the Pacific Manila, The Philippines
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