Typical Correlation Score between Economic Development Speed and Employment Rate

In order to discuss the relationship between the employment rate and the economic development speed, the typical correlation analysis between the development speed and the employment rate is made in the past 20 years. Three indicators of development speed are considered: per capita energy consumption, per capita GDP, fixed asset investment price index, and two indicators of employment rate are considered: number of graduates and number of employees. The results show that economic development has a great impact on the number of employment, and that economic development can increase the quantity of employment.


Introduction
With the rapid development of society, the economy is in the process of normalization from high-speed growth to high-quality growth, and the employment situation and employment rate have also attracted people's attention. Whether a society's employment problem is solved well or not involves all aspects of society, and its influence is extremely extensive and far-reaching. Therefore, the relationship between employment rate and economic change is a topic worthy of discussion.
The speed of economic development refers to the relative number reflecting the degree of change of economic and social phenomena in time, which is an important indicator to measure the economic operation. The rate of employment and the speed of economic development are more worthy of discussion. Many scholars at home and abroad have also discussed this issue.
In order to understand the internal relationship between the employment rate and the economic development speed objectively, we select the relevant indicators of the economic development speed and the employment rate, and make a typical correlation analysis based on the data of 2000-2018. Wang et al. (2017) obtained that there is a long-term equilibrium relationship between economic growth and employment in Xinjiang based on the data from 1992-2014. Lin (2016) explored the role of labor employment in promoting economic development in China. Liu et al. (2016) analyzed the evolution characteristics of China's economic growth and employment quality index system.  (2017) analyzed the existing problems and some restrictive factors in the employment process of college students, such as national policies, social and economic development, professional structure of schools, curriculum setting, college students' personal orientation and employment attitude. Byerlee and Eicher (1974) pointed out that the problem of urban unemployment is becoming more and more serious and many economists changed the main development index to redefining development. Tsaliki (2009)

Canonical Correlation Analysis
Canonical correlation analysis is a multivariate statistical method to study the correlation between two groups of variables. According to the correlation between variables, we find a few pairs of comprehensive variables (linear combination of actual observation variables) and use them to replace the original observation variables, so as to focus the relationship between two groups of variables on a few pairs of comprehensive variables.
are two random vectors. Using the principal component theory, we find the i-th pair of typical related variables , i = 1, 2, …, m = min(p, q); the canonical correlation coefficient between the m-th pair of canonical correlation variables is In this paper, the typical correlation analysis of energy consumption per capita, GDP per capita, fixed asset investment price index with the number of graduates and employment is carried out. For convenience, let 1 x be the per capita energy consumption, 2 x be the per capita GDP, 3 x be the fixed asset investment price index, 1 y be the number of graduates, 2 y be the number of employees (Table 1).

Typical Correlation Coefficient and Significance Test
Two typical correlation coefficients are given in Table 2, the first one is CanR 1 =

Typical Variable Coefficient and Typical Structure
Because the units of the five indexes are not uniform, the standardized coefficient is considered.
Among them, 1 V is the first typical variable of economic development speed, 1 W is the first typical variable of employment rate.
Formula (1) is the weighted difference between the per capita energy consumption and the per capita GDP approximately, with a greater weight in the per capita energy consumption and a coefficient of 0 in the fixed asset investment price index; Formula (2) shows that the first typical variable of employment rate, W 1 , has the largest coefficient in the number of employed people.   Table 10 is the proportion of variance explained by the normalized variance of the rate of economic development through its typical variables and paired typical variables. It can be seen that the proportion of shared variance explained by the index of economic development through its first typical variable is 65.23%, and the proportion of variance explained by the other's first typical variable is 62.54%, and its ratio 62.54/65.23 = 0.9586 is exactly CanR 1 2 . Table 11 is the proportion of variance explained by the standardized variance of the employment rate variable through its canonical and paired canonical variables. It can be seen that the proportion of the shared variance explained by the employment rate index through the first canonical variable is 91.70%, which is accounted for. The proportion of variance explained by the typical variable is 87.91%, and the ratio is also 0.9586. Table 12 and Table 13 give the squares of the complex correlation coefficients between the original variables and the typical variables of the paired group, that  To sum up, 1 W , the first typical variable of economic development speed index, has quite good explanatory power to the number of graduates and the number of employed people. 1 V , the first typical variable of employment rate index, has a good explanatory power to per capita energy consumption and per capita GDP, but has little explanatory power to fixed asset investment price index. The first typical variable of the speed index of economic development has the strongest ability to explain the number of employed people in the employment rate index, which shows that economic development has a great influence on the number of employed people, and at the same time, accelerating economic development can increase the number of employed people.

Conclusion
We mainly discuss a typical correlation analysis on the development speed and employment rate. The research results show that the first typical variable of the economic development speed index has the strongest ability to explain the employment index in the employment rate index, that is, economic development has a greater impact on employment, and accelerating economic development can increase employment.
The research on the promotion of college students' employment under the new economic situation is helpful for people to objectively understand the relationship between economic development and employment and its evolution trend, and has certain reference significance and application value for relevant