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Jingdong book

数量经济学系列丛书：计量财税建模与应用

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Jingdong book

数量经济学系列丛书：计量财税建模与应用

Name: 数量经济学系列丛书：计量财税建模与应用
Brand: Jingdong book
SKU: 3110050831
Price: 43.17 USD
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《数量经济学系列丛书：计量财税建模与应用》通过实际例子详尽地介绍了如何运用EViews软件对财政、税收及其他经济指标和数据进行建模的操作。具体内容包括：EViews使用初步；线性、非线性模型参数估计；异方差、自相关和多重共线性；虚拟变量、多线段回归与分布滞后模型；模型的诊断和检验；协整分析；联立方程组模型；月度、季度数据处理；向量自回归模型；面板数据模型；主成分分析和因子模型；状态空间模型。
《数量经济学系列丛书：计量财税建模与应用》适合高等院校财税专业及其他经济类专业的本科生和研究生使用。

Catalogue

第1章 EViews软件使用初步
1.1 Eviews软件简介
1.2 Eviews软件窗口功能介绍及基本操作
1.2.1 主窗口
1.2.2 工作文件的建立
1.2.3 输入数据
1.2.4 改动数据
1.2.5 删除某一列数据和插入一列数据
1.2.6 改变工作文件区间
1.2.7 改变z序列和y序列的位置
1.2.8 把若干序列放在一个表格中
1.3 Eviews软件数据及图形操作
1.3.1 数据简单处理
1.3.2 计算描述统计量
1.3.3 用数据绘制图
1.4 EViews编程
1.4.1 EViews编程语言入门
1.4.2 程序文件的相关操作
1.4.3 常用的程序命令

第2章线性、非线性模型参数估计
2.1 双变量线性回归模型
2.1.1 双变量线性回归模型的OLS估计
2.1.2 双变量线性回归模型举例
2.2 多变量线性回归模型
2.2.1 多变量线性回归模型的OLS估计
2.2.2 几点说明
2.3 可以线性化的非线性模型参数估计
2.3.1 可以线性化的非线性模型的含义
2.3.2 双对数回归模型的参数估计
2.4 不可以线性化的非线性模型参数估计（迭代线性化法）
2.4.1 不可以线性化的非线性模型的含义
2.4.2 迭代线性化法
2.4.3 举例

第3章异方差、自相关和多重共线性
3.1 异方差检验及修正
3.1.1 案例
3.1.2 异方差检验
3.1.3 异方差修正
3.2 自相关的检验及修正
3.2.1 案例
3.2.2 自相关的检验
3.2.3 自相关的修正
3.3 多重共线性

第4章虚拟变量、多线段回归与分布滞后模型
4.1 利用虚拟变量建模
4.1.1 案例1
4.1.2 案例2
4.1.3 案例3
4.1.4 测量斜率变动的模型
4.1.5 测量斜率和截距都变动的模型
4.2 多线段线性回归模型
4.2.1 多线段线性回归模型的原理
4.2.2 案例1
4.2.3 案例2
4.3 分布滞后模型
4.3.1 案例
4.3.2 阿尔蒙估计法基本原理
4.3.3 阿尔蒙估计法的EViews软件的简单操作方法
4.3.4 用经验权数法估计有限分布滞后模型的参数

第5章模型的诊断和检验
5.1 检验若干线性的约束条件是否成立的F检验
5.1.1 案例
5.1.2 完成F检验的其他方法
5.2 似然比（LR）检验
5.2.1 似然比（LR）检验的基本原理
5.2.2 似然比（LR）检验的EViews软件操作
5.3 Wald检验
5.3.1 案例
5.3.2 Wald检验原理
5.3.3 Wald检验的EViews软件操作
5.4 拉格朗日乘子（LM）检验
5.4.1 案例
5.4.2 拉格朗日乘子（LM）检验的原理
5.5 邹突变点检验
5.5.1 案例
5.5.2 邹突变点检验的EViews软件操作
5.6 JB正态分布检验
5.6.1 JB正态分布检验的基本原理
5.6.2 案例
5.7 格兰杰因果性检验
5.7.1 格兰杰因果性原理
5.7.2 格兰杰因果性检验原理
5.7.3 案例

第6章协整分析
6.1 单位根检验
6.1.1 协整原理
6.1.2 单位根检验的一般原理
6.2 协整检验
6.3 误差修正模型
6.4 案例
6.4.1 案例1
6.4.2 案例2

第7章联立方程组模型
7.1 联立方程组模型初步建立
7.1.1 建立简单的凯恩斯宏观经济模型
7.1.2 数据
7.1.3 模型的参数估计
7.2 克莱因（KleinⅠ）模型
7.2.1 克莱因（KleinⅠ）模型的形式
7.2.2 数据
7.2.3 模型参数的估计方法
7.3 联立方程模型的模拟与预测
7.3.1 克莱因（KleinⅡ）模型
7.3.2 克莱因（KleinⅡ）模型的参数估计
7.3.3 联立方程模型的模拟

第8章月度、季度数据处理
8.1 移动平均法
8.1.1 简单的移动平均公式
8.1.2 中心化移动平均
8.1.3 加权移动平均
8.2 X12季节调整方法
8.2.1 X12季节调整方法介绍
8.2.2 X12季节调整方法的几种模型
8.3 移动平均比率方法
8.3.1 基本原理
8.3.2 EViews软件操作
8.4 趋势分解
8.5 指数平滑方法
8.5.1 基本原理
8.5.2 指数平滑方法简介
8.5.3 指数平滑方法的EViews软件操作
8.6 季度、月度和旬度指标的预测
8.6.1 季度预算拨款预测
8.6.2 月度预算拨款预测
8.6.3 旬度预算拨款预测

第9章向量自回归模型
9.1 单位根检验与协整检验
9.1.1 数据说明
9.1.2 单位根检验
9.1.3 协整检验
9.2 向量自回归模型的设定和参数估计
9.2.1 向量自回归模型的设定
9.2.2 向量自回归模型的参数估计
9.3 脉冲响应函数与方差分解
9.3.1 脉冲响应函数EViews软件操作
9.3.2 方差分解EViews软件操作
9.4 向量误差修正模型
9.4.1 向量误差修正模型的建立
9.4.2 向量误差修正模型参数估计的EViews操作
9.4.3 向量误差修正模型参数估计结果的另一种形式
9.4.4 结果

第10章面板数据模型
10.1 利用Pool处理面板数据
10.1.1 建立面板数据文件
10.1.2 利用Pool进行数据计算
10.2 混合模型
10.2.1 混合模型的形式
10.2.2 混合模型的EViews软件操作
10.3 固定效应变截距回归模型
10.3.1 个体固定效应变截距回归模型的形式
10.3.2 个体固定效应变截距回归模型的估计方法
10.3.3 时点固定效应变截距回归模型的形式
10.3.4 时点固定效应变截距回归模型的估计方法
10.3.5 个体时点固定效应变截距回归模型的形式
10.3 一个体时点固定效应变截距回归模型的估计方法
10.4 随机效应变截距回归模型
10.4.1 个体随机效应变截距回归模型的形式
10.4.2 个体随机效应变截距回归模型的估计方法
10.4.3 时点随机效应变截距回归模型的形式
10.4.4 时点随机效应变截距回归模型的估计方法
10.4.5 个体时点随机效应变截距回归模型的形式
10.4.6 个体时点随机效应变截距回归模型的估计方法
10.5 固定效应变系数回归模型
10.5.1 个体固定效应变系数回归模型
10.5.2 个体固定效应变系数回归模型的估计方法
10.5.3 时点固定效应变系数回归模型
10.5.4 时点固定效应变系数回归模型的估计方法
10.5.5 个体时点固定效应变系数回归模型的形式
10.5.6 个体时点固定效应变系数回归模型的估计方法
10.6 面板数据模型的其他问题
10.6.1 固定效应和随机效应检验
10.6.2 面板数据的单位根和协整检验
10.6.3 面板结构的工作文件

第11章主成分分析和因子模型
11.1 主成分分析
11.1.1 数据及处理
11.1.2 主成分分析EViews软件操作
11.2 因子模型分析
11.2.1 因子模型
11.2.2 实例

第12章状态空间模型
12.1 状态空间模型概述
12.1.1 状态空间模型原理
12.1.2 状态空间模型的定义
12.2 状态空间模型估计
12.2.1 创立状态空间对象
12.2.2 可变边际消费倾向的状态空间模型
12.3 状态空间模型的视窗和过程
12.3.1 视窗（View）
12.3.2 过程（Procs）
参考文献

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