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Quantitative Analysis Of The Living Standard Of Urban Residents

Posted on:2017-01-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y N LiFull Text:PDF
GTID:2279330488463023Subject:Applied statistics
Abstract/Summary:PDF Full Text Request
Since the reform and opening up, with the development of China’s economic and the progress of science and technology, people’s living standard has also undergone tremendous changes. The proposing of 13 th Five Year Plan indicates that we have a new goal of "building a well-off society in an all-round way". State and Government has been taking various measures to improve the living standard of the residents. As a member of society, we should not only care about own basic necessities of life, but we should also have some knowledge of the situation of our living standard, so in this article, we will do a quantitative analysis on urban residents’ living standard.In this article, first of all, based on time-series data of the Engel’s coefficient of urban residents’ living standard, we do a model fitting and make short-term forecasting to our urban residents’ living standard. We find that urban residents’ living standard in China will continue to improve in the future. Then we make a thorough analysis of urban residents’ living standard, and we get four main factors by making a factor analysis of cross-section data: income and expense and employment factor, medical treatment and public health factor, population pressure factor and resource factor. At last, based on cross-section data, we make a ranking of our provinces based on urban residents’ living standard by different methods. According to the information, we find that there are big differences between regions, and urban residents in the eastern coastal region are of relatively high standard of living when urban residents in the western underdeveloped areas are of low standard of living. These conclusions are consistent with the actual situation of our urban residents’ living standard, which has some significance to propose policies on improving living standard.
Keywords/Search Tags:living standard, grey forecasting model, factor analysis, weighted relativity
PDF Full Text Request
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