A Study on the Number of Domestic Unemployment Based on the Combination Forecasting Method

Achieving full employment is one of the important goals of modern socio-economic development. Solving the unemployment problem is of vital significance to promoting social harmony, maintaining economic stability and achieving sustainable development. Our government has long attached great importance to this issue, and has elevated re-employment to the strategic position of "the basis of people's livelihood", giving priority to it and planning it carefully. Therefore, forecasting and analyzing the future unemployment situation in China, and exploring the specific causes of the unemployment problem, is very important for the promotion of people's well-being and the sustainable development of China. Based on the sample data of the National Bureau of Statistics from 2004 to 2023, this paper explores the impact of GDP and urban population on the number of unemployment in China by using multiple linear regression forecasting model and stepwise regression method, and predicts the urban registered unemployed population in 2024 by applying time series and extrapolating the trend. The research indicated that GDP has a significant positive impact on the number of unemployment; and the number of unemployment in 2024 will probably be 11,192,760,000. Accordingly, this paper suggests strengthening the investment in training and re-education for the unemployed people, and enhancing the re-employment capacity of the unemployed people; strengthening the regulation of macroeconomic policies, focusing on the synergistic effect of economic growth and employment creation of; and sounding the unemployment protection system, improving the unemployment insurance system, and providing the unemployed people with a more comprehensive protection, in order to reduce the unemployment problem.

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Published
2024-10-18
DOI
https://doi.org/10.1145/3708036.3708251
Primary Topic
Regional Economic and Spatial Analysis
Type
article
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article

A Study on the Number of Domestic Unemployment Based on the Combination Forecasting Method

Weiyan Wu, Mengqiang Wu, Hongyan Fan
Regional Economic and Spatial Analysis
article

A Study on the Number of Domestic Unemployment Based on the Combination Forecasting Method

Weiyan Wu, Mengqiang Wu, Hongyan Fan
article en

Abstract

Achieving full employment is one of the important goals of modern socio-economic development. Solving the unemployment problem is of vital significance to promoting social harmony, maintaining economic stability and achieving sustainable development. Our government has long attached great importance to this issue, and has elevated re-employment to the strategic position of "the basis of people's livelihood", giving priority to it and planning it carefully. Therefore, forecasting and analyzing the future unemployment situation in China, and exploring the specific causes of the unemployment problem, is very important for the promotion of people's well-being and the sustainable development of China. Based on the sample data of the National Bureau of Statistics from 2004 to 2023, this paper explores the impact of GDP and urban population on the number of unemployment in China by using multiple linear regression forecasting model and stepwise regression method, and predicts the urban registered unemployed population in 2024 by applying time series and extrapolating the trend. The research indicated that GDP has a significant positive impact on the number of unemployment; and the number of unemployment in 2024 will probably be 11,192,760,000. Accordingly, this paper suggests strengthening the investment in training and re-education for the unemployed people, and enhancing the re-employment capacity of the unemployed people; strengthening the regulation of macroeconomic policies, focusing on the synergistic effect of economic growth and employment creation of; and sounding the unemployment protection system, improving the unemployment insurance system, and providing the unemployed people with a more comprehensive protection, in order to reduce the unemployment problem.

University of Electronic Science and Technology of China (CN)
Decent work and economic growth
Openalex Percentile: Top 69%
Regional Economic and Spatial Analysis
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