Representativeness of Information in Economic Surveys, RLMS-HSE Example

Student: Garanina Yuliya

Educational Programme: Master

Year of Graduation: 2014

The main aim of paper on «Representativeness of information in economic surveys, RLMS-HSE example» is to analyze how much representative data of RLMS-HSE monitoring are. In this paper the term “representativeness” is defined as the possibility for using the results of monitoring for different studies, the informativeness of collected data, the possibility to extrapolate the results on much greater samples and studies. To evaluate the representativeness was used special part of RLMS-HSE survey – group of questions to be answered not respondents, but interviewers. The main aim of these questions is to reflect the interviewers’ opinion about informativeness of respondents’ answers. To analyze and evaluate these questions and answers were used not only statistical methods and instruments, but econometric model “ordered logit-model” as well. The choice of this type of econometric model was defined due to type and format of answering data – all answers are can be ordered. According to statistical data were formulated hypothesis concerning the impact of different factors on the representativeness of answers. Three regressions on the base of ordered logit model were used to approve or reject hypothesis. The paper also contained a comparison of two models of income dynamics – with special weighted coefficients and without it. Additionally, this paper contains statistical comparison of RLMS-HSE results with official data of Government Statistical Department of Russian Federation.The paper consists of theoretical and practical parts. Theoretical part is devoted to definition of special terms, description of RLMS-HSE, its data and special characteristics, review of literature materials for the same theme and comparison of RLMS-HSE with other international databases of longitudinal surveys. Practical part is consists of defined methods and instruments and results of running regressions. There are also a lot of different statistical information in this part of paper.The paper consists of introduction, two chapters, conclusion and number of appendixes.

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