Determinants of income class in Philippine households: Evidence from the Family Income and Expenditure Survey 2009

Year: 2014       Vol.: 63       No.: 2      

Authors: Stephen Jun Villejo; Mark Tristan Enriquez; Michael Joseph Melendres; Dexter Eric Tan; Peter Julian Cayton

Abstract:

The government has instituted projects aimed at helping the poor, and has implemented mechanisms to make the services accessible to them. The wisdom of the projects of the government should not be defeated by misidentification of deserving households to enjoy those projects which could be remedied through proper and thorough assessment of their economic status.The study aims to provide a methodology and model for classifying households using demographic and household assets that may be used in identifying recipients of poverty-targeted projects. Cluster analysis was employed to identify household classification using income data from the Family Income and Expenditure Survey 2009. Five income clusters were identified. To study the relationship between the income classes and several predictors of income identified from previous researches, a family of logistic regression models have been utilized, culminating to the generalized logistic regression model. Nine significant predictors were included in the final reduced model. The model is assessed to have good fit via multiple Hosmer and Lemeshow tests. These variables were the following: location of the household whether in NCR or not, or in urban or rural area; education and employment status of the household head; number of cars, air-conditioners, and television sets; and the building type and household type. The sensitivity table suggests that the model is biased towards predicting the lower income classes. The research has identified a viable methodology for classification of income classes for households.

Keywords: mutlinomial logistic model, income determinants, clustering methods

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