Hunger Incidence in the Philippines: Facts, Determinants and Challenges

Mapa, Dennis S. and Han, Fatima C. and Estrada, Kristine Claire O. (2010): Hunger Incidence in the Philippines: Facts, Determinants and Challenges.

Abstract

The high level of hunger incidence in the country is perhaps one of the most pressing issues that need to be addressed by our policy makers. Official government statistics and data from self-rated hunger surveys show an increasing trend in hunger incidence among Filipino households. Data from National Statistical Coordination Board (NSCB) show that the percentage of subsistence poor in the country increased to 14.6 percent in 2006 from 13.5 percent in 2003. The Social Weather Stations (SWS) quarterly surveys on hunger incidence also show an increasing trend in the percentage of families that experienced hunger, reaching an alarming level of 24 percent in December 2009, representing about 4.4 million households. One probable cause of the increasing trend in hunger is the rising food prices akin to what the country experienced in 2008. This paper aims to determine the impact of food inflation and underemployment on hunger incidence in the Philippines, using the hunger incidence data from the SWS quarterly surveys on hunger. A vector autoregressive (VAR) model is used to determine the effect of a shock or increase to food inflation and underemployment on total involuntary hunger. Results from the model show that an increase in food prices at the current quarter will increase hunger incidence for a period of five quarters, starting with immediate quarter after the shock occurred. Shocks to underemployment will also increase hunger incidence but the effects last for only two quarters, also starting with immediate quarter after the shock. The results of this study provide relevant information that will be useful in crafting policies related to the Hunger Mitigation Program of the government.

• Item Type: MPRA Paper
• Language: English
• Keywords: hunger; food inflation; underemployment; vector autoregressive models
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; I - Health, Education, and Welfare > I3 - Welfare, Well-Being, and Poverty > I32 - Measurement and Analysis of Poverty

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