Research on Regional Economic Vitality Based on Factor Analysis

Abstract

In order to stimulate regional economic vitality, various regional governments have introduced many preferential policies, but how to seize key factors and effectively improve economic vitality is still an urgent issue to be resolved. Take Zhejiang Province as an example, first perform dimensionless standardization on the collected data (see Appendix I for details), select the factor with eigenvalue greater than 1 and satisfy the cumulative contribution rate of 80% as the main factor, and analyze it through R. The relationship between the factor load and the main factor is used to establish a relationship model. The weights of each indicator's total index influence are obtained by using Matlab; Secondly, the analysis found that the changes in the number of resident population and corporate law in the past five years have a great correlation with the region's GDP. Based on this, a binary linear regression model was established. The change is positively related to changes in population and corporate vitality, and the economic vitality increases. Finally, the regression analysis model is used to verify the rationality of the model and to draw an operating plan to improve economic vitality to adjust the consumption structure. Promote industrial transformation and upgrading, increase the Create industry support. The factors are used as indicators of economic policy transition to establish a gray differential equation to obtain estimated parameter values, and then a gray prediction model is established—GM (1,1). Then establish a test error ratio model to compare the estimated data with the real data to test the rationality of the model, and then use the model to predict the next ten years . From the perspective of long-term effects, economic policy transformation has improved the regional economic competitiveness provides residents with a long-term sustainable quality of life and enhances the sustainable green development of the city. Finally, by observing the data from 2015-2017, it can be seen that the short-term impact is that economic policy transition will affect some economic indicators Immediately showing a positive trend, but the impact on other economic indicators may not be obvious in the short term, and some may even decline.
The data is normalized using range normalization; the standardized matrix, correlation coefficient matrix and its eigenvalues, eigenvectors and contribution rates, R analysis factor load, and main factor load are obtained. Establish an economic vitality model and use Matlab to obtain the urban economic vitality index . Finally, perform a descending order on the urban economic vitality index to obtain the urban economic vitality ranking.