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Analysis On Employment Structure Of Main Cities In Shandong

Posted on:2017-03-08Degree:MasterType:Thesis
Country:ChinaCandidate:W X JiaFull Text:PDF
GTID:2309330488966769Subject:Applied Statistics
Abstract/Summary:PDF Full Text Request
Employment structure is also called the social labor distribution structure, generally refers to the labor departments of the national economy occupies the quantity, scale and their mutual relations. For a total employment through the analysis of the internal structure can be from many aspects, including the employment of industry (department) of the ownership structure, employment structure, employment of urban and rural structure, region structure of employment and so on. Employment ownership structure reflects the employment tendency of ownership, industry (department) of employment structure reflects the technology structure and scale of the industry, the regional structure of obtain employment reflects regional productivity layout, so the employment structure can reflect the status of the industrial structure from various angles, including the level of productivity, layout, technical structure of the industry, as well as the employment tendency. Paper mainly studies the employment structure in shandong province regional features and trends. Detailed study of 17 major cities employment ownership structure, industry structure, by adopting the method of clustering analysis in recent years in shandong province between different types of enterprises and employment over the distribution between different industries, regional employment structure characteristics and development trend. At the same time, according to the empirical results comparing two clustering methods applicable conditions.According to the analysis result, it may safely draw the conclusion as follows:first, ownership type differences of urban and rural employment, urban and rural employment duality phenomenon, and ownership types in different parts of the urban and rural employment also have obvious difference. Second, the employment of the industrial structure shows the characteristics of obvious degree of economic development:economic relatively developed area, the third industry employment proportion bigger, economy is relatively backward area, the first big industry employment proportion. By all kinds of industry employment to distinguish between urban industrial structure similarity, according to the result of clustering, the local resources, economic development level between cities, such as geographical location affect the different emphasis of industrial structure, capital and coastal developed city, the first industry employment proportion is low, the second and third industry is balanced; Mainland economic development level is higher, the second industry employment proportion relatively smaller, the tertiary industry is relatively high; Development is relatively backward, the primary industry employment proportion is higher, the second industry is still the third industry is on the high side. Third, from 2005 to 2014 municipal industry employment trends, according to the analysis of the employment trends to significantly reduce the primary industry, secondary industry number increase slow slow, the third industry employment in cities and towns increase steadily, and basically consistent with the restructuring of the firm growth targets in shandong province, but according to the municipal industrial structure deviation degree index, employment trends in some parts of the industry is not consistent with this trend, need corresponding policy intervention, further optimize the structure of employment. Fourth, look from the clustering method, the empirical analysis shows that the value is bigger, less variable, smaller correlation between variables on the classification of k-means clustering are using two methods and system clustering results are basically identical, but for smaller numerical more objects, variables, K-c-mean clustering analogy system more accord with the reality.
Keywords/Search Tags:Employment structure, Industrial structure, Clustering analysis, Trend analysis
PDF Full Text Request
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