Mapa, Dennis S. and Castillo, Kristelle and Francisco, Krizia (2015): Rice Price, Job Misery, Hunger Incidence: Need to Track Few More Statistical Indicators for the Poor.
Preview |
PDF
MPRA_paper_61990.pdf Download (266kB) | Preview |
Abstract
Reducing hunger incidence in the country is still the major policy challenge confronting our leaders today. Statistics on hunger produced by both government and private institutions show a very slow reduction in hunger incidence over the last five years. Official data from Philippines Statistics Authority (PSA) show the percentage of Filipinos experiencing extreme poverty (hunger) decreased only slightly from 10.9 percent of the population in 2009 to 10.4 percent in 2012 and increasing marginally to 10.7 percent during the 1st semester of 2013. The results of the 8th National Nutrition Survey (NNS) of 2013 conducted by the Food Nutrition and Research Institute (FNRI) show the same small reduction in the proportion of children aged 0-5 years who are underweight (indirect measure of hunger) from 20.7 percent in 2008 to 19.8 percent in 2013. Self-rated hunger incidence data from the Social Weather Stations (SWS) also reveal a similar bleak picture, where hunger incidence in households averaging at 19.5 percent in 2013 from 19.1 percent in 2009, slowing down slightly to an average of 18.3 percent in 2014. This slow reduction in hunger incidence is a puzzle considering the country’s respectable economic growth performance, with Real Gross Domestic Product (GDP) growing at an annual average of 6.3 percent during the period 2010-2014. This paper looks at the factors that influence the dynamic nature of hunger incidence in the Philippines using the data from the SWS quarterly surveys on hunger. Variables identified as potential determinants of hunger incidence are, among others, changes in the price of rice and job misery index (sum of the employment and unemployment rates). A Vector AutoRegressive (VAR) model is used to determine the effect of a shock to the possible determinants on total hunger. Results show that a shock (increase) in the price of rice at the current quarter tends to increase hunger incidence in the succeeding quarter. A shock (increase) in job misery index at the current quarter also increases the hunger incidence in the next quarter. Further analysis using the time-varying parameter (TVP) model shows a higher effect of changes in the price of rice to hunger incidence after the global rice crisis in 2008. This shows that hunger incidence is becoming very sensitive to changes in the price of rice.
Item Type: | MPRA Paper |
---|---|
Original Title: | Rice Price, Job Misery, Hunger Incidence: Need to Track Few More Statistical Indicators for the Poor |
Language: | English |
Keywords: | Hunger Incidence, Vector AutoRegressive (VAR) model, State Space, Time-Varying Parameters (TVP) model |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation I - Health, Education, and Welfare > I3 - Welfare, Well-Being, and Poverty > I32 - Measurement and Analysis of Poverty I - Health, Education, and Welfare > I3 - Welfare, Well-Being, and Poverty > I38 - Government Policy ; Provision and Effects of Welfare Programs |
Item ID: | 61990 |
Depositing User: | Dennis S. Mapa |
Date Deposited: | 11 Feb 2015 14:24 |
Last Modified: | 27 Sep 2019 15:25 |
References: | Briones, R.M. and Galang, I.M.R. (2014), “Bakit Nagmahal ang Bigas Noong 2013? At Bakit Mahal pa rin? The Continuing Saga of Rice Self-Sufficiency in the Philippines. “ PN 2014-08, Philippine Institute for Development Studies (PIDS). Food and Agricultural Organization of the United Nations (2009), “More people than ever are victims of hunger.” Website, www.foa.org. Food and Agricultural Organization of the United Nations (2011), “The 2007-08 Rice Price Crisis: How policies drove up prices and how they can help stabilize the market.” Economic and Social Perspectives Policy Brief, February 2011. Food Nutrition Research Institute (FNRI), Website, www.fnri.dost.gov.ph. Hodrick, R. and E. C. Prescott (1997), "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit, and Banking, 29: 1-16. Kalman, R. E., (1960), A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME – Journal of Basic Engineering, 82 (Series D), 35-54. Kim, C.J. and C.R. Nelson (1989), The Time-Varying Parameter Model for Modeling Changing Conditional Variance: The case of the Lucas Hypothesis. Journal of Business and Economic Statistics, 443-440 Kim, C.J. and C.R. Nelson (1999). State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications. MIT Press Maligalig, D.S. (2008) “Examining the Existing Direct Measures of Hunger in the Philippines.” The Philippine Statistician, 57: 93-124. Mapa, D. S., F. C. Han and K. C. O. Estrada (2011), “Food Inflation, Underemployment and Hunger Incidence: A Vector Autoregressive (VAR) Analysis.” The Philippine Statistician, Volume 60, pp. 43 – 62, September 2011. Mangahas, M., (2009) “The Role of Civil Society in Poverty Monitoring: The Case of the Philippines.” A paper presented on The Impact of the Global Economic Situation on Poverty and Sustainable Development in Asia and the Pacific, September 28-30, 2009, Hanoi, Vietnam. Peralta, T.V. (2013), “Emerging Trends and Changing Structures: Taking Stock of the Bright Spot in the Labor Market in Recent Years.” Available from URL: http://www.nscb.gov.ph/statfocus/2013/SF_112013_OSG_emergingtrends.asp Philippine Statistics Authority (PSA), Website, http://www.nscb.gov.ph/#page=t1; http://web0.psa.gov.ph/ Pichler, P. (2007), “State Space Models and the Kalman Filter.” [online; cited April 2014.] Available from URL: http://homepage.univie.ac.at/robert.kunst/statespace.pdf Pope Benedict XVI, 2009 Address of His Holiness Benedict XVI to the Food and Agricultural Organization (FAO) on the Occasion of the World Summit on Food Security, November 16, 2009 at the FAO Headquarters in Rome. Pope Francis, 2013 Message to the Caritas Internationalis’ Global Campaign “One Human Family, Food for All.” Saini, N. and A. K. (2014), Forecasting Volatility in Indian Stock Market using State Space Models. Journal of Statistical and Econometric Methods, Vol. 3, No. 1, pp. 115-136. Sciencepress Ltd. Social Weather Station (SWS), Fourth Quarter 2013 Social Weather Survey. [online; cited April 2014] Available from URL: http://www.sws.org.ph/pr20140122.htm Social Weather Station (SWS), Fourth Quarter 2014 Social Weather Survey. [online: cited January 2015]. Available from URL: http://www.sws.org.ph/ Sen, Amartya (2013), McDougall Memorial Lecture at the Food and Agricultural Organization (FOA), 15 June 2013. World Food Programme (WFP), World Hunger. [online; cited April 2014.] Available from URL: http://www.wfp.org/hunger/causes |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/61990 |