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

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.


Issue Date:
Dec 30 2011
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/199102
Published in:
Asian Journal of Agriculture and Development, Volume 09, Number 2
Page range:
65-76
Total Pages:
12
JEL Codes:
J1; Q1; R2; D13; D24




 Record created 2017-04-01, last modified 2017-08-28

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