The identification of socio-economic classes of Metro Manila household population

• Main Author: Concepcion, Antonio Visaya
• Format: text
• Published: Animo Repository 1987
• Subjects: Social classes > Philippines > Manila.; Social status > Philippines > Manila.; Market surveys.
• Online Access: https://animorepository.dlsu.edu.ph/etd_doctoral/1281
• Institution: De La Salle University

Segmenting the household population into socio-economic classes (AB - upper class, C - middle class, D - lower class, and E - lower-lower class) is a tool which marketing men use to identify viable markets to target for their product offerings. To support the marketing men's need for this data, marketing researchers routinely classify survey households according to their socio-economic classes. Past studies, however, show that the way that the households are classified, and the proportions of these classes to total population, vary from one researcher to another. It is the intent of this dissertation study to look into the basic issue of whether there exist segments of households that can be considered as socio-economic classes. And if so, the study further attempts to establish the proportions of these segments to total household population, and to determine which variables will consistently and distinctively classify socio-economic status. To achieve the study's objectives, an ideal sampling approach was adopted. This approach is different from current industry practice which commonly generates samples that are random only within each segment. For this study, a representative sample of 1,067 Metro Manila households was generated using the sample size formula for population data.Using the multi stage sampling procedure, a household was randomly selected and the housewife interviewed. They were asked to provide information on the variables commonly used for socio-economic classification. These include occupation of the household head, educational attainment, possession of household facilities, income and expenses. The dwelling unit was observed by the interviewer and classified according to type, make and painting. All these information were subjected to the multivariate statistical tool of cluster analysis. Five computer runs were done. The results revealed the following: 1. Cluster analysis confirms the existence of socio-economic segments. 2. The distribution of the segments is highly skewed to the E class. 3. Comparing the proportions derived from this study with the proportions currently used by marketing researchers: the proportion of AB's are just about the same, the C's and the D's are currently over-represented, and the E's are grossly underestimated.