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The Link between Agricultural Output and the States of Poverty in the Philippines: Evidence from Self-Rated Poverty Data

Author

Listed:
  • Mapa, Dennis S.
  • Lucagbo, Michael
  • Garcia, Heavenly Joy

Abstract

The high poverty incidence in the county is a concern that needs to be addressed by our policy makers. Official poverty statistics from the National Statistical Coordination Board (NSCB) shows that the reduction in poverty over the past two decades has been quite dismal from 38% in 1988 to 26% in 2009 or less than one percent reduction per year. Since poverty incidence has dynamic patterns, studies using official poverty data encounter difficulty because of limited number of data points. This study builds econometric models in analyzing the movement of poverty in the country using the quarterly self-rated poverty series of the Social Weather Stations. The first model uses Markov Switching to determine the states of poverty. It assumes two states: high and moderate states of poverty. A high 61% of the population considered themselves as poor when the country is in the state of high poverty. In times of moderate poverty, 49.5% of the population considered themselves as poor. The result shows that once the country is in the state of high poverty, it stays there for an average of 24 quarters, or six years, before moving out. The paper then builds a logistic regression model to show what determines the states of high poverty. The model shows that a one-percent increase in agricultural output in the previous quarter reduces the probability of being in the high state of poverty by about 8 percentage points, all things being the same. The study shows that poverty incidence in the country is dynamic and frequent monitoring through self-rated poverty surveys is important in order to assess the effectiveness of the government programs in reducing poverty. The self-rated poverty surveys can complement the official statistics on poverty incidence.

Suggested Citation

  • Mapa, Dennis S. & Lucagbo, Michael & Garcia, Heavenly Joy, 2012. "The Link between Agricultural Output and the States of Poverty in the Philippines: Evidence from Self-Rated Poverty Data," MPRA Paper 40791, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:40791
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    File URL: https://mpra.ub.uni-muenchen.de/40791/1/MPRA_paper_40791.pdf
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    References listed on IDEAS

    as
    1. Arsenio Balisacan & Sharon Piza & Dennis Mapa & Carlos Abad Santos & Donna Odra, 2010. "The Philippine economy and poverty during the global economic crisis," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 47(1), pages 1-37, June.
    2. Arsenio M. Balisacan, 2011. "What Has Really Happened to Poverty in the Philippines? New Measures, Evidence, and Policy Implications," UP School of Economics Discussion Papers 201114, University of the Philippines School of Economics.
    3. Tabuga, Aubrey D. & Mina, Christian D. & Reyes, Celia M. & Asis, Ronina D. & Datu, Maria Blesila G., 2011. "Dynamics of Poverty in the Philippines: Distinguishing the Chronic from the Transient Poor," Discussion Papers DP 2011-31, Philippine Institute for Development Studies.
    4. Tamás Bartus, 2005. "Estimation of marginal effects using margeff," Stata Journal, StataCorp LP, vol. 5(3), pages 309-329, September.
    5. Balisacan, Arsenio M. & Fuwa, Nobuhiko, 2004. "Going beyond Crosscountry Averages: Growth, Inequality and Poverty Reduction in the Philippines," World Development, Elsevier, vol. 32(11), pages 1891-1907, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Abrigo, Michael R.M., 2016. "Who Weans with Commodity Price Shocks? Rice Prices and Breastfeeding in the Philippines," Discussion Papers DP 2016-28, Philippine Institute for Development Studies.
    2. Abrigo, Michael R.M., 2016. "Who Weans with Commodity Price Shocks? Rice Prices and Breastfeeding in the Philippines," Research Paper Series DP 2016-28, Philippine Institute for Development Studies.

    More about this item

    Keywords

    Markov Switching; Logistic Regression; Self-Rated Poverty;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General

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