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1、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 graduatestudents一、Topics raisedIn this paper, the total number of students from graduate students (variable
2、) 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 th
3、e 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 f
4、or 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
5、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 rat
6、e, 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 peop
7、le to participate in Kaoyan)二、Establish ModelY=+1X1+2X2+3X3+4X4 +u Among them, theY-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
8、number of colleges and universities (explanatory variables)三、Data collection1. date ExplainHere, using the same area (ie, China) time-series data were fitted2. Data collectionTime series data from 1986 to 2005, the specific circumstances are shown in Table 1四、Model parameter estimation, inspection a
9、nd correction1. Model parameter estimation and its economic significance, statistical inference testtwoway(scatter Y X1)twoway(scatter Y X2)twoway(scatter Y X3)twoway(scatter Y X4)twoway(scatter Y X4)graph twoway lfit y X2graph twoway lfit y X3graph twoway lfit y X4Y = 59.22454816*X1- 7.158602346*X2
10、- 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=945.1415DW=1.596173Visible, X1, X2, X3, X4 t values are significant, indicating that the per capita
11、 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 relat
12、ively 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 econom
13、ic 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
14、positively correlated. X2, X3 coefficient sign contrary to expectations, which may indicate the existence of severe multicollinearity.2.计量经济学检验The above table can be seen to explain the positive correlation between the height of the variable X1 and X2, X3, X4, X2, X1, X3, between the highly positive
15、ly correlated, showing that there is serious multicollinearity. Following amendment stepwise regression：Y = 60.21976901*X1 - 61096.25048（6.311944） （42959.23）t = (9.540606) (-1.422191) Adjusted R-squared=0.825725 F=91.02316Y = 27.05878289*X2 - 2993786.354( 5.622791) (680596.9) t = (4.812340) (-4.3987
16、66) R-squared=0.562668 F=23.15862Y = 1231.659997*X3 - 371863.6509(161.9045) (90051.37) t = (7.607324) (-4.129461)Adjusted R-squared=0.749576 F=57.87138Y = 1053.519847*X4 - 964699.7964 (65.85948) (79072.71)t = (15.99648) (-12.20016)Adjusted R-squared=0.930628 F=255.8874The analysis shows that the four simple regression model, the total number of graduate students for the linear relationship betwee
