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Estimation of Vulnerability to Poverty Using a Multilevel Longitudinal Model: Evidence from the Philippines

Author

Listed:
  • Mina, Christian D.
  • Imai, Katsushi S.

Abstract

Using the panel data for the Philippines in 2003-2009, the paper estimates a three-level random coefficient model to measure household vulnerability and to decompose it into idiosyncratic and covariate components. It corrects heterogeneity bias using Bell and Jones's (2015) "within-between" formulation. A majority of the poor and 18 percent of the nonpoor are found to be vulnerable to unobservable shocks, while both groups of households are more susceptible to idiosyncratic shocks than to covariate shocks. Adequate safety nets should be provided for vulnerable households that lack access to infrastructure, or are larger in size with more dependents and less-educated household heads.

Suggested Citation

  • Mina, Christian D. & Imai, Katsushi S., 2016. "Estimation of Vulnerability to Poverty Using a Multilevel Longitudinal Model: Evidence from the Philippines," Discussion Papers DP 2016-10 (Revised), Philippine Institute for Development Studies.
    • Handle: RePEc:phd:dpaper:dp_2016-10_(revised)
    DOI: https://doi.org/10.62986/dp2016.10
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    File URL: https://www.pids.gov.ph/publication/discussion-papers/estimation-of-vulnerability-to-poverty-using-a-multilevel-longitudinal-model-evidence-from-the-philippines
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    Cited by:

    1. Shijiang Chen & Mingyue Liang & Wen Yang, 2022. "Does Digital Financial Inclusion Reduce China’s Rural Household Vulnerability to Poverty: An Empirical Analysis From the Perspective of Household Entrepreneurship," SAGE Open, , vol. 12(2), pages 21582440221, June.
    2. Muhammad Masood Azeem & Amin W. Mugera & Steven Schilizzi & Kadambot H. M. Siddique, 2017. "An Assessment of Vulnerability to Poverty in Punjab, Pakistan: Subjective Choices of Poverty Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(1), pages 117-152, October.
    3. Christian D. Mina & Celia M. Reyes, 2017. "Estimating Filipinos' Vulnerability to Poverty," Working Papers id:12080, eSocialSciences.
    4. Connie Bayudan-Dacuycuy & Lora Baje, 2017. "Chronic and Transient Poverty and Weather Variability in the Philippines: Evidence Using Components Approach," Working Papers id:12072, eSocialSciences.
    5. Mina, Christian D., 2017. "Employment Profile of Women with Disabilities in San Remigio and Mandaue City, Cebu, Philippines," Discussion Papers DP 2017-57, Philippine Institute for Development Studies.
    6. Junyan Tian, 2024. "Rural household vulnerability and COVID-19: Evidence from India," PLOS ONE, Public Library of Science, vol. 19(4), pages 1-15, April.
    7. Angeles Sánchez & Eduardo Jiménez-Fernández, 2023. "European Union Cohesion Policy: Socio-Economic Vulnerability of the Regions and the COVID-19 Shock," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 18(1), pages 195-228, February.
    8. Mauricio Gallardo, 2020. "Measuring Vulnerability to Multidimensional Poverty," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(1), pages 67-103, February.
    9. Bresciani, F. & Imai, K.S. & Malaeb, B., 2017. "IFAD RESEARCH SERIES 15 - Remittances, growth and poverty reduction in Asia," IFAD Research Series 280053, International Fund for Agricultural Development (IFAD).
    10. Anh Thu Quang Pham & Pundarik Mukhopadhaya & Ha Vu, 2021. "Estimating poverty and vulnerability to monetary and non-monetary poverty: the case of Vietnam," Empirical Economics, Springer, vol. 61(6), pages 3125-3177, December.
    11. Connie Bayudan-Dacuycuy & Lora Baje, 2017. "Chronic Food Poverty in the Philippines," Working Papers id:12071, eSocialSciences.
    12. Barriga Cabanillas, Oscar & Bossuroy, Thomas & Corral Rodas, Paul Andres & Rodriguez Castelan, Carlos & Skoufias, Emmanuel, 2024. "Sustaining Poverty Gains: A Vulnerability Map to Guide Social Policy," IZA Discussion Papers 17193, IZA Network @ LISER.
    13. Qiutong Xue & Sixian Feng & Muchen Li, 2024. "The Impact of Digital Finance on Industrial Structure: Evidence From China," SAGE Open, , vol. 14(2), pages 21582440241, May.
    14. Oscar Eduardo Barriga Cabanillas & Carlos Rodriguez Castelan & Emmanuel Skoufias & Thomas Bossuroy & Paul Andres Corral Rodas, 2024. "Sustaining Poverty Gains : A Vulnerability Map to Guide the Expansion of Social Registries," Policy Research Working Paper Series 10890, The World Bank.
    15. Ira N. Gang & Kseniia Gatskova & John Landon-Lane & Myeong-Su Yun, 2018. "Vulnerability to Poverty: Tajikistan During and After the Global Financial Crisis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(3), pages 925-951, August.
    16. Connie Bayudan-Dacuycuy & Lora Kryz Baje, 2019. "When It Rains, It Pours? Analyzing the Rainfall Shocks-Poverty Nexus in the Philippines," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(1), pages 67-93, August.

    More about this item

    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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