计量经济学英文版

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经济计量学

1930年成立世界Econometrics学会 1933年创刊《Econometrica》 20世纪40、50年代的大发展和60年代的扩张 20世纪70年代以来非经典（现代）经济计量
学的发展。
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第一章
经典经济计量学和非经典经济计量学
经典经济计量学（Classical Econometrics）一般指20世纪70年代以前发展并广泛应用的经济计量学。
贝尔经济学奖得主挪威经济学家R.Frisch（佛里希给定X和Z值，预测Y值
城市劳动力参与率除受城市失业率的影响之外，还受真实的小时平均工资等因素的影响。
）在1926年模仿“Biometrics”(生物计量学)提 Y = B1+ B2X
（2）利用次级资料数据（统计数据）假设用失业率（UNR）来度量经济形势，用劳动力参与率（LFPR）来度量劳动力的参与，两数据由政府按时公布，我们依据上面步骤
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第一章
非经典经济计量学一般指20世纪70年代以来发展的经济计量学理论、方法及应用模型，也称为现代经济计量学。
非经典经济计量学主要包括：微观经济计量学、非参数经济计量学、时间序列经济计量学和动态经济计量学等。
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第一章
简·丁伯根——经济计量学模式建造者之父
拉格纳·弗里希（RAGNAR FRISCH）经济计量学的奠基人
AHE82（美元）
7.78 7.69 7.68 7.79 7.80 7.77 7.81 7.73 7.69 7.64 7.52 7.45 7.41 7.39 7.40 7.40 7.43 7.55 7.75 7.86 7.89 7.99 8.14
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第一章表1-1（新） 1980～2007年间城市劳动力参与率(CLFPR)、城市失业率(CUNR)与真实的小时平均工资(AHE82)资料

计量经济学（英文）重点知识点考试必备汇编

计量经济学（英文）重点知识点考试必备汇编第一章1.Econometrics（计量经济学）：the social science in which the tools of economic theory, mathematics, and statistical inference are applied to the analysis of economic phenomena.the result of a certain outlook on the role of economics, consists of the application of mathematical statistics to economic data to lend empirical support to the models constructed by mathematical economics and to obtain numerical results.2.Econometric analysis proceeds along the following lines计量经济学分析步骤1)Creating a statement of theory or hypothesis.建立一个理论假说2)Collecting data.收集数据3)Specifying the mathematical model of theory.设定数学模型4)Specifying the statistical, or econometric, model of theory.设立统计或经济计量模型5)Estimating the parameters of the chosen econometric model.估计经济计量模型参数6)Checking for model adequacy : Model specification testing.核查模型的适用性：模型设定检验7)Testing the hypothesis derived from the model.检验自模型的假设8)Using the model for prediction or forecasting.利用模型进行预测●Step2：收集数据T hree types of data三类可用于分析的数据1)Time series(时间序列数据):Collected over a period of time,are collected at regular intervals.按时间跨度收集得到2)Cross-sectional截面数据:Collected over a period of time, are collected at regular intervals.按时间跨度收集得到3)Pooled data合并数据（上两种的结合）●Step3：设定数学模型1.plot scatter diagram or scattergram2.write the mathematical model●Step4：设立统计或经济计量模型C LFPR is dependent variable应变量C UNR is independent or explanatory variable独立或解释变量（自变量）W e give a catchall variable U to stand for all these neglected factorsI n linear regression analysis our primary objective is to explain the behavior of the dependent variable in relation to the behavior of one or more other variables, allowing for the data that the relationship between them is inexact.线性回归分析的主要目标就是解释一个变量（应变量）与其他一个或多个变量（自变量）只见的行为关系，当然这种关系并非完全正确●Step5：估计经济计量模型参数I n short, the estimated regression line gives the relationship between average CLFPR and CUNR 简言之，估计的回归直线给出了平均应变量和自变量之间的关系T hat is, on average, how the dependent variable responds to a unit change in theindependent variable.单位因变量的变化引起的自变量平均变化量的多少。

计量经济学英文课件 (22)

Comparing fits of regressions
Make sure the denominator in R2 is the same - i.e., same left hand side variable. Example, linear vs. loglinear. Loglinear will almost always appear to fit better because taking logs reduces variation.
o What are the practical implications of this result?
n Transformation does not affect the fit of a model to a body of
data.
n Transformation does affect the “estimates.” If b is an estimate
Dropping a variable(s) cannot improve the fit - that is, reduce the sum of squares.
Adding a variable(s) cannot degrade the fit - that is, increase the sum of squares.
Then, uu = (y - Xd)(y-Xd) = [y - Xb - X(d - b)][y - Xb - X(d - b)] = [e - X(d - b)] [e - X(d - b)]
Expand to find uu = ee + (d-b)XX(d-b) > ee
Dropping a Variable

计量经济学中英文词汇对照

Common variance Common variation Communality variance Comparability Comparison of bathes Comparison value Compartment model Compassion Complement of an event Complete association Complete dissociation Complete statistics Completely randomized design Composite event Composite events Concavity Conditional expectation Conditional likelihood Conditional probability Conditionally linear Confidence interval Confidence limit Confidence lower limit Confidence upper limit Confirmatory Factor Analysis Confirmatory research Confounding factor Conjoint Consistency Consistency check Consistent asymptotically normal estimate Consistent estimate Constrained nonlinear regression Constraint Contaminated distribution Contaminated Gausssian Contaminated normal distribution Contamination Contamination model Contingency table Contour Contribution rate Control

(完整版)计量经济学Econometrics专业词汇中英文对照

Econometrics 专业词汇中英文对照（按课件顺序）Ch1-3Causal effects：因果影响，指的是当x变化时，会引起y的变化；Elasticity：弹性；correlation (coefficient) 相关（系数），相关系数没有单位，unit free；estimation：估计；hypothesis testing：假设检验；confidence interval：置信区间；difference-in-means test：均值差异检验，即检验两个样本的均值是否相同；standard error：标准差；statistical inference：统计推断；Moments of distribution：分布的矩函数；conditional distribution (means)：条件分布（均值）；variance：方差；standard deviation：标准差（指总体方差的平方根）；standard error：标准误差，指样本方差的平方根；skewness：偏度，度量分布的对称性；kurtosis：峰度，度量厚尾性，即度量离散程度；joint distribution：联合分布；conditional expectation：条件期望（指总体）；randomness：随机性i.i.d., independently and identically distributed：独立同分布的；sampling distribution：抽样分布，指的是当抽取不同的随机样本时，统计量的取值会有所不同，而当取遍所有的样本量为n的样本时，统计量有一个取值规律，即抽样分布，即统计量的随机性来自样本的随机性consistent (consistency)：相合的（相合性），指当样本量趋于无穷大时，估计量依概率收敛到真实值；此外，在统计的语言中，还有一个叫模型选择的相合性，指的是能依概率选取到正确的模型Central limit theory：中心极限定理；unbiased estimator：无偏估计量；uncertainty：不确定性；approximation：逼近；least squares estimator：最小二乘估计量；provisional decision：临时的决定，用于假设检验，指的是，我们现在下的结论是基于现在的数据的，如果数据变化，我们的结论可能会发生变化significance level：显著性水平，一般取0.05或者0.01,0.1，是一个预先给定的数值，指的是在原假设成立的假设下，我们可能犯的错误的概率，即拒绝原假设的概率；p-value：p-值，指的是观测到比现在观测到的统计量更极端的概率，一般p-值很小的时候要拒绝原假设，因为这说明要观测到比现在观测到的统计量更极端的情况的概率很小，进而说明现在的统计量很极端。

计量经济学(英文版).

Chapter 4 Statistical Properties of the OLS Estimators
Xi’An Institute of Post & Telecommunication Dept of Economic & Management Prof. Long
Simple Linear Regression Model y t = b1 + b 2 x t + e t
b1 + b2 x t
Assumptions of the Simple Linear Regression Model yt = b1 + b2x t + e t 2. E(e t) = 0 <=> E(yt) = b1 + b2x t
1.
3. var(e t)
4.3
=
4.
5.
cov(e i,e j)
x t c for every observation
= cov(yi,yj)
s 2 = var(yt)
= 0
6.
e t~N(0,s 2) <=> yt~N(b1+ b2x t,
The population parameters b1 and b2 are unknown population constants.
4.2
yt = household weekly food expenditures
x t = household weekly income
For a given level of x t, the expected level of food expenditures will be: E(yt|x t) =

计量经济学英文课件 (3)

Z
b2 2
2
xi x
2
~ N 0,1
(3.1)

The standardized random variable Z is normally distributed with mean 0 and variance 1.
Slide 3-4
Principles of Econometrics, 3rd Edition

and its standard error
se(b2 ) var(b2 ) 4.38 2.09
Principles of Econometrics, 3rd Edition
Slide 3-12

A “95% confidence interval estimate” for 2:

The critical value tc for degrees of freedom m is the percentile value t1 2,m .
Principles of Econometrics, 3rd Edition
Slide 3-9
Figure 3.1 Critical Values from a t-distribution
Principles of Econometrics, 3rd Edition
Slide 3-16

The Null Hypothesis
parameter.
The null hypothesis, which is denoted H0 (H-naught), specifies a value for a regression The null hypothesis is stated H 0 : k c, where c is a constant, and is an important value in the context of a specific regression model.

计量经济学stata英文论文

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) 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 adirect factor of the total number of students in the graduatestudents (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 influenceprecisely because of the emergence of more institutions of higherlearning in the school the total number of graduate students is nota small factor (to allow more people to participate in Kaoyan)二 Establish ModelY=α+β1X1+β2X2+β3X3+β4X4 +uAmong 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 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 1Table 1：Y X1X2X3X41986110371963107507264.4105419871201911112109300276.6106319881127761366111026296.2107519891013391519112704377.910751990930181644114333383.210751991881281893115823352.210751992941642311117171363.9105319931067712998118517420.1106519941279354044119850476.4108019951454435046121121519.6105419961633225846122389552.8103219971763536420123626576.81020199819888567961247615711022199923351371591257865751071200030123978581267435951041200139325686221276276811225200250098093981284537701396200365126010542129227800155220048198961233612998882717312005978610140401307568391792四、Model parameter estimation, inspection and correction1.Model parameter estimation and its economic significance, statistical inference test. twoway(scatter Y X1)2000004000006000008000001.0e +06twoway(scatter Y X2)2000004000006000008000001.0e +06twoway(scatter Y X3)2000004000006000008000001.0e +06twoway(scatter Y X4)2000004000006000008000001.0e +0graph twoway lfit y X1200000400000600000800000F i t t e d v a l u e sgraph twoway lfit y X2-20000020000040000060000F i t t e d v a l u e sgraph twoway lfit y X3200000400000600000800000F i t t e d v a l u e sgraph twoway lfit y X42000004000006000008000001000000F i t t e d v a l u e s_cons 270775.2 369252.9 0.73 0.475 -516268.7 1057819 X4 621.3348 46.72257 13.30 0.000 521.748 720.9216 X3 -366.8774 157.9402 -2.32 0.035 -703.5189 -30.23585 X2 -7.158603 3.257541 -2.20 0.044 -14.10189 -.2153182 X1 59.22455 6.352288 9.32 0.000 45.68496 72.76413 Y Coef. Std. Err. t P>|t| [95% Conf. Interval] Total 1.3040e+12 19 6.8631e+10 Root MSE = 18535 Adj R-squared = 0.9950 Residual 5.1533e+09 15 343556320 R-squared = 0.9960 Model 1.2988e+12 4 3.2471e+11 Prob > F = 0.0000 F( 4, 15) = 945.14 Source SS df MS Number of obs = 20. reg Y X1 X2 X3 X4Y = 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=945.1415DW=1.596173Visible, 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。

《计量经济学》课程教学大纲

《计量经济学》课程教学大纲课程代码：ABGS0106课程中文名称：《计量经济学》课程英文名称：Econometrics课程性质：必修课程学分数：3学分课程学时数：48学时授课对象：国际经济与贸易本课程的前导课程：微（宏）经济学, 线性代数、概率论、统计学等课程一、课程简介《计量经济学》是国际经济与贸易专业的必修专业基础课,其任务与目的是讲述的基本理论和知识，并为进一步学习专业课，运用数学模型方法定量分析和描述具有随机性特征的经济变量关系打下良好基础。

二、教学基本内容和要求课程教学内容：（一）导论课程教学内容：1. 什么是计量经济学：计量经济学的产生与发展，计量经济学的性质，计量经济学与其他学科的关系；2. 计量经济学的研究方法：模型设定，估计参数，模型检验，模型应用；3. 变量、数据、参数与模型：计量经济模型中的变量，计量经济学中应用的数据，参数及其估计准则，计量经济模型的建立；课程重点、难点：课程重点体现在计量经济模型中的变量，计量经济学中应用的数据，难点在于参数及其估计准则。

课程教学要求：了解计量经济学的产生与发展，理解计量经济学的研究方法以及计量经济模型中的变量，掌握参数估计准则。

（二）简单线性回归模型课程教学内容：1. 回归分析与回归方程：回归与相关，总体回归函数，随机扰动项，样本回归函数；2. 简单线性回归模型的最小二乘估计：简单线性回归模型的基本假定，普通最小二乘法(OLS) ，最小二乘估计的统计性质；3. 回归系数的假设检验，ß1和ß2回归系数的假设检验；4. 拟合优度的度量，总变差的分解，可决系数，可决系数与相关系数的关系；课程重点、难点：课程重点在于简单线性回归模型的最小二乘估计，课程难点体现在回归系数的区间估计和假设检验。

课程教学要求：了解回归分析的基本概念，理解最小二乘估计方法，掌握相关的检验。

（三）多元线性回归模型课程教学内容：1. 多元线性回归模型：模型设定，矩阵表示方式；2. 多元线性回归模型的最小二乘估计：多元线性回归模型的基本假定，普通最小二乘法(OLS) ，最小二乘估计的统计性质。

计量经济学(Econometrics)

课程学时：48学时（课内实验16学时）
课程学分：3学分
课程概述：计量经济学是一门以经济理论为基础
以统计数据为依据
以数学为方法
定量研究具有随机特征的经济现象及经济变量之间数量关系的一门经济学科
是经济学研究常用的一种方法
是当前经济学研究的一个重要分支
其研究方法主要以回归分析方法为基础
主要包括单方程计量经济模型
2005
[10] 于俊年．计量经济学．对经济贸易大学出版社
2000
[11] 袁建文．经济计量学实验．科学出版社
2002
[12] 易丹辉．数据分析与eviews应用．中国统计出版社
2002
[13] 高铁梅．计量经济分析方法与建模--Eviews应用及实例．清华大学出版社
2006
其他说明：课程中所有的例子和问题我们使用EVIEWS4.1来计算
2．异方差的检验第五章
第一~三节 11. 异方差II
自相关I 1．异方差的解决方法
2．自相关的概念及后果第五章
第四节
第六章
第一、二节 12. 上机实验3 多元线性回归模型的参数估计与假设检验上机实验指导书3 13. 自相关II 1．自相关的检验
2．自相关的解决方法第六章
联立方程模型
向量自回归模型
时间序列分析等
本课程是一门为本科生开设的入门性质的计量经济学课程
主要讲述：（1）单方程计量经济模型：a)经典线性回归模型b）违背经典假设的回归c)线性回归模型的扩展d）模型设定误差（2）联立方程模型：a)基本概念；b)模型识别；c）参数估计
时间：周二上午8：00-9：50
周四上午8：00-9：50

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