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Determinants of Household Income: A Quantile Regression Approach for Four Rice-Producing Areas in the Philippines

Author

Listed:
  • Thelma R. Paris

    (Social Sciences Division, International Rice Research Institute)

  • Valerien O. Pede

    (Social Sciences Division, International Rice Research Institute)

  • Joyce S. Luis

    (Social Sciences Division, International Rice Resaerch Institute)

  • Justin D. McKinley

    (International Rice Research Institute)

Abstract

This paper investigates the determinants of total household income in selected rice-based farming villages in the Philippines. A quantile regression approach was applied on cross-section data obtained from 656 farming households across four provinces. Determinants of household income were examined using an ordinary quantile regression approach, which, unlike conditional mean regression, allows parameter variation across income quantiles. The quantile regression approach also enables the analysis of income determinants for extreme categories such as low-income households. Results indicate that coefficients estimated through ordinary least squares (OLS) could be misleading. The quantile estimates preserved their signs in most cases but their magnitude varied across quantiles. The paper particularly emphasizes the determinants of income for poor households. The quantile estimations show that education of the male head and the existence of migrant workers in households are the most important determinants of income for poor households.

Suggested Citation

  • Thelma R. Paris & Valerien O. Pede & Joyce S. Luis & Justin D. McKinley, 2012. "Determinants of Household Income: A Quantile Regression Approach for Four Rice-Producing Areas in the Philippines," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 9(2), pages 65-76, December.
    • Handle: RePEc:sag:seajad:v:9:y:2012:i:2:p:65-76
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    Cited by:

    1. Hung Van Vu, 2020. "The Impact of Education on Household Income in Rural Vietnam," IJFS, MDPI, vol. 8(1), pages 1-8, February.
    2. Amar Anwar & Colin F. Mang & Sonia Plaza, 2024. "Remittances and inequality: A meta‐analytic investigation," The World Economy, Wiley Blackwell, vol. 47(6), pages 2664-2705, June.
    3. Emre Toros & Seyit Cilasun & Aykut Toros, 2018. "Social and Economic Indicators of Household Income in Turkey: Does Ethnicity Matter?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(1), pages 191-208, November.
    4. Quang Tran, Tuyen & Anh Tran, Tai & The Tran, Nu & Thi Nguyen, Hai, 2018. "Education and the livelihood of households in the Northwest Region, Vietnam," MPRA Paper 90414, University Library of Munich, Germany, revised 17 May 2018.
    5. Gemechis Teshome & Leta Sera & Amsalu Dachito, 2021. "Determinants of income inequality among urban households in Ethiopia: a case of Nekemte Town," SN Business & Economics, Springer, vol. 1(11), pages 1-21, November.

    More about this item

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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