Errors of Indices in Household Surveys of Punjab Urban through Principal Components

Abstract

In this research article, household wealth indices are calculated to estimate the sampling errors, which gave us complete information on the quality and reliability of published data upon the household surveys. Estimates are calculated based on simple random sampling, which contains sampling errors. Here principal components analysis (PCA) estimate standard errors of wealth indices as orthogonal transformation to develop solid measures of individual economic status. These measures evaluate the significance and explain the living status and economic dissimilarity of Punjab urban. Instrumental variables are used here to the enlightened social status of the Punjab urban area of Pakistan by using PCA of household surveys.  Twenty-five variables are included in this study. Total variance analysis explains the variation of total components.  A comparison study (PCA) approaches to estimating the standard error of indices of the household survey are presented in this paper. We conclude that errors of indices in household surveys through PCA, when compared to direct measures of estimating household wealth indices, are an efficient and reliable method.