Statistical matching of sample survey data: application to integrate Iranian time use and labour force surveys

Abstract

Survey data are still contemplated as one of the main sources in official statistics. However, due to the high cost of conducting a survey, as well as the respondent burden, it may not be possible to collect all variables of interest in a data set. To obtain a more comprehensive source of data, one possible way is to integrate available data from different data sets such as already existing data, administrative registers, and official surveys. This helps to minimize the shortcomings of each survey and to maximize their advantages. In this paper, a mixed method at the micro-level has been applied to integrate data sourced from two surveys, involving the ‘Iranian Labour Force Survey’ and the ‘Iranian Time Use Survey’ which have been performed in the Fall of 2015. Thereby, besides increasing the coverage of the variables from two sources, we could also study the peculiarities of work and life qualities. For this objective, we develop a statistical matching micro approach by proposing the conditional predictive Dirichlet distribution and conditional predictive multinomial distribution in the regression step of mixed methods. In the end, the quality of matching along with the similarity of marginal distributions of specific variables (variables of interest) pre-and-post the integration are assessed by some similarity measures and the Kolmogorov–Smirnov test.