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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:
  • Dennis S. Mapa

    (UP School of Statistics)

  • Michael Daniel Lucagbo

    (UP School of Statistics)

  • Heavenly Joy Garcia

    (UP School of Statistics)

Abstract

The high poverty incidence in the country is a concern that needs to be addressed by our policy makers. OfÞcial poverty statistics from the National Statistical Coordination Board (NSCB) show that the reduction in poverty over the past two decades has been quite dismal from 38 percent in 1988 to 26 percent in 2009, or less than 1 percent reduction per year. Since poverty incidence has dynamic patterns, studies using ofÞcial poverty data encounter difficulty because of alimited number of data points. This study builds econometric models in analysing the movement of poverty in the country using the quarterly self-rated poverty series of the Social Weather Stations. The Þrst model uses Markov Switching to determine the states of poverty. It assumes two states: high andmoderate states of poverty. A high 61 percent of the population considered themselves poor when the country is in the state of high poverty. In times of moderate poverty, 49.5 percent of the population consider themselves poor. The result shows thatonce 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 1 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 ofÞcial statistics on poverty incidence.

Suggested Citation

  • Dennis S. Mapa & Michael Daniel Lucagbo & Heavenly Joy Garcia, 2012. "The link between agricultural output and the states of poverty in the Philippines: evidence from self-rated poverty data," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 49(2), pages 51-74, December.
  • Handle: RePEc:phs:prejrn:v:49:y:2012:i:2:p:51-74
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    File URL: http://pre.econ.upd.edu.ph/index.php/pre/article/view/886/785
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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. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. 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.
    5. Tabuga, Aubrey D. & Mina, Christian D. & Reyes, Celia M. & Asis, Ronina D. & Datu, Maria Blesila G., 2010. "Are We Winning the Fight against Poverty? An Assessment of the Poverty Situation in the Philippines," Discussion Papers DP 2010-26, Philippine Institute for Development Studies.
    6. 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.
    7. Tamás Bartus, 2005. "Estimation of marginal effects using margeff," Stata Journal, StataCorp LP, vol. 5(3), pages 309-329, September.
    8. Arsenio M. Balisacan & Hal Hill (ed.), 2007. "The Dynamics of Regional Development," Books, Edward Elgar Publishing, number 4178.
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    Cited by:

    1. Abrigo, Michael Ralph 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.

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    More about this item

    Keywords

    Markov switching; logistic regression; self-rated poverty;
    All these keywords.

    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
    • 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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