The Application Of Principal Component Analysis And Time Series Forecasting In The Research Of Employment In Our Country

Employment is vital to people’s livelihood, it’s important for the stable and rapid development of national economy and social stability, so people pay more attention to urban and rural employment. Many experts and scholars have made deep research on it, but most of them only studied it in theoretical methods, they merely used the statistical methods to analyze the related questions. This article will through principal component analysis and short-term prediction of the time series to analyze the employment problem in China by SAS software.This paper gets the data from China Statistical Yearbook. At the beginning, we use the method of principal component analysis to analyze the China’s urban and rural employment in 2010 by SAS software. After the analysis of urban employment, we can find that the employment of Guangdong and Jiangsu and other eastern coastal province is huge, but the employment in Tibet, Qinghai, Ningxia and other provinces of the western rural are rarely. We can also find that the employment situation of rural employment in 2010 is basically the same as the urban. And then we use the time series forecasting method to analyze and forecast the urban employment from 1990 to2013 through the SAS software. The results show that the urban employment has been showing an increasing trend, while the rural employment has been in a downward trend after a short period of growth. At the same time, the short term prediction show that the urban employment will continue steady growth in the next two years, while the rural employment will continue to decline. These results are in line with the current China’s regional economic development situation, the urban employment situation is good, but the countryside is still much room for growth. The results provide a certain reference for decision makers to formulate the urban and ruralemployment policy in the future.