计量经济学英文论文

　　计量经济学是以一定的'经济理论和统计资料为基础，运用数学、统计学方法与电脑技术，以建立经济计量模型为主要手段，定量分析研究具有随机性特性的经济变量关系的一门经济学学科。下面是小编为你整理的关于计量经济学的英文论文,请你欣赏!

　　Graduates to apply for the quantitative analysis of changes in number of graduate

　　students

　　一、Topics raised

　　In this paper, the total number of students from graduate students (variable) multivariate analysis (see below) specific analysis, and collect relevant data, model building, this quantitative analysis. The number of relations between the school the total number of graduate students with the major factors, according to the size of the various factors in the coefficient in the model equations, analyze the importance of various factors, exactly what factors in changes in the number of graduate students aspects play a key role in and changes in the trend for future graduate students to our proposal.

　　The main factors affect changes in the total number of graduate students for students are as follows：

　　Per capita GDP - which is affecting an important factor to the total number of students in the graduate students (graduate school is not a small cost, and only have a certain economic base have more opportunities for post-graduate)

　　The total population - it will affect the total number of students in graduate students is an important factor (it can be said to affect it is based on source)

　　The number of unemployed persons - this is the impact of a direct factor of the total number of students in the graduate students (it is precisely because of the high unemployment rate, will more people choose Kaoyan will be their own employment weights) Number of colleges and universities - which is to influence precisely because of the emergence of more institutions of higher learning in the school the total number of graduate students is not a small factor (to allow more people to participate in Kaoyan)

　　二、Establish Model

　　Y=α+β1X1+β2X2+β3X3+β4X4 +u Among them, the

　　Y-in the total number of graduate students (variable) X1 - per capita GDP (explanatory variables) X2 - the total population (explanatory variables)

　　X3 - the number of unemployed persons (explanatory variables) X4 - the number of colleges and universities (explanatory variables)

　　三、Data collection

　　1. date Explain

　　Here, using the same area (ie, China) time-series data were fitted

　　2. Data collection

　　Time series data from 1986 to 2005, the specific circumstances are shown in Table 1

　　四、Model parameter estimation, inspection and correction

　　1. Model parameter estimation and its economic significance, statistical inference test

　　twoway(scatter Y X1)

　　twoway(scatter Y X2)

　　twoway(scatter Y X3)

　　twoway(scatter Y X4)

　　twoway(scatter Y X4)

　　graph twoway lfit y X2

　　graph twoway lfit y X3

　　graph twoway lfit y X4

　　Y = 59.22454816*X1- 7.158602346*X2- 366.8774279*X3+621.3347694*X4

　　（6.352288） （3.257541） （157.9402） （46.72256） t= （9.323341） （-2.197548） （-2.322889） （13.29839） + 270775.151 （369252.8） （0.733306）

　　R2=0.996048 Adjusted R-squared =0.994994 F=945.1415

　　DW=1.596173

　　Visible, X1, X2, X3, X4 t values are significant, indicating that the per capita GDP, the total population of registered urban unemployed population, the number of colleges and universities are the main factors affecting the total number of graduate students in school. Model coefficient of determination for 0.996048 amendments coefficient of determination of 0.994994, was relatively large, indicating high degree of model fit, while the F value of 945.1415, indicating that the model overall is significant。

　　In addition, the coefficient of X1, X4, in line with economic significance, but the coefficient of X2, X3, does not meet the economic significance, because from an economic sense, with the increase in the total population (X2), the total number of graduate students should be increased, and due to the increase in the number of unemployed, there will be more and more people choose graduate school, so that the total number of unemployed and graduate students should be positively correlated. X2, X3 coefficient sign contrary to expectations, which may indicate the existence of severe multicollinearity.