granger因果关系是什么?格兰杰因果关系是什么?看论文时常出现 不知有什么用处

icq_wyq2022-10-04 11:39:541条回答

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岳阳vv 共回答了20个问题 | 采纳率95%
格兰杰因果关系 是格兰杰因果检验的结果
原假设为x不是y的格兰杰成因
是为了说明 x对y是否存在影响的一种检验方法
前提是:x和y 平稳 或者是一阶协整
可参考时间序列相关书籍
1年前

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In the Harry Potter films, Hermione Granger is better than h
In the Harry Potter films, Hermione Granger is better than her male friends and is considered the brightest pupil in her grade. Isn’t it often the same in schools of our real world? A great many boys fall behind their female classmates.
“It’s surprising but true that most of the top students have been girls since primary school. Girls are class leaders, club presidents and the top ones in exams,” said Wang Feixuan, 15, who studies at a Chengdu school. By any measure, Wang herself is a high-achiever. She is a top student, a team leader in her school’s sports club and a winner in national English and IT competitions.
But why do so many girls outperform their male peers(同辈)?
In Sun Yunxiao’s latest book Save Our Boys, he points out that the education system is “more suited to girls, who are good at memorizing and like to sit quietly and read.” Yet he also says that girls have to do so much more when they compete with males for honors, top universities and later good jobs. They can feel great pressure(压力)nearly every day.
This seems to be the same in most countries in the world. Young women in the United States are also reported to feel the same pressure to be perfect.
“Let’s look at what we ask of our teenage girls,” says an American professor Stephen Hinshaw in an interview.
He thinks that it’s no longer enough that a girl does well in school and is a caring friend. On the TV, on the Internet, and everywhere, girls see images of impossible perfection(完美).
Today’s young women must be good learners, good athletes, and fill their after-school lives with other activities. But they’re also asked to have the styles and looks of popular stars. “Be pretty, sweet and nice. Be athletic, competitive and get straight. Be impossibly perfect.” Stephen Hinshaw sums up.
小题1:The passage suggests that________.
A.our society asks far too much of teenage girls
B.teenage girls shouldn’t be so perfect at school
C.boys are always lazy ones rather than girls
D.American girls have less pressure than Chinese girls
小题2:According to the passage, it is true that .
A.boys are less smart than girls throughout school life
B.boys usually don’t have so much pressure as girls do
C.girls are all fond of the Chinese education system
D.girls are better at school because boys don’t work hard
小题3:The underlined word outperform means_________.
A.mistake B.misunderstand C.ignore D.defeat
小题4:What’s the best title for the passage_________?
A.Impossibly Perfect Is Possible. B.Why Are Girls So Perfect?
C.Perfect? Pressure Every Day! D.Perfect: Boys or Girls?
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小题1:A
小题2:B
小题3:D
小题4:C

如何用Eviews做ADF检验我这里有很多很多数据需要做ADF检验,然后做协整检验以及Granger检验等.我的数据现在
如何用Eviews做ADF检验
我这里有很多很多数据需要做ADF检验,然后做协整检验以及Granger检验等.我的数据现在都在EXCEL里面,我需要把所有的数据都一个个输入到eviews里么?...
还有这些检验都该怎么做啊
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file--New--Workfile...
以时间序列为例:输入相关起始时间后回车
建立时间序列的方法:Object--New Object,选择对象类型Series,并为之命名.
首先告诉你不用一个一个输入,
1.先说一种最笨的方法,建立序列以后,打开该序列,点击“Edit=+/-”,粘贴即可.粘贴之后还得在点击一下该键哦~,以此类推.
2.这是一劳永逸的方法,你先将相关数据放入一个Excel文件中,File--Import--Read Text-Lotus-Excel...,选择导入的Excel文件,在“Names for series or Number if named in file”中按顺序填入你的各个指标的名称,各指标名称之间应该用空格空开,在“Upper-left data cell”下填入数据的起始位置,如“B2”,这样数据就输入了.
至于ADF检验,一般最好是对数据求对数之后进行,当然要因情况而异,要对某序列进行ADF检验,先双击该序列打开,View--Unit Root Test...,在Test type中选择ADF检验,“Test for unit root in”下的三种情况都可以试试,例如,选择“Level”,“Include in test equation”中有常数项、有趋势项和常数项、None三种情况都要试试,当三种情况下都有单位根时(一般PRO.大于0.05则存在单位根),改变“Test for unit root in”中的“Level”为“1st difference”再试,直至我们发现其不存在单位根.当“Level”时通过检验无单位根时,该序列则I(0),当1st情况下时则I(1),以此类推.
VAR模型分析中遇到的一些问题,与granger也相关!
VAR模型分析中遇到的一些问题,与granger也相关!
小女子新手中的新手!一切从0学起!悬赏分值不高,
在完成ADF检验等程序后,经行了granger检验,结果如下!reer是人民币实际有效汇率,ex是出口.
Null Hypothesis:F-Statistic Probability 结论
△LNREER does not Granger Cause △LNEX 6.06305 0.00366 拒绝
△LNEX does not Granger Cause △LNREER 0.57844 0.56332 接受
这个没错吧?
然后问题就来了,在VAR模型分析时,是否可以用以下的方程?以下是非限制性VAR.
LNEXt=#+#LNEXt-1+#LNEXt-2+#LNREERt-1+#LNREERt-2
LNREERt=#+#LNREERt-1+#LNREERt-2 (没有加入LNEX,因为△LNEX does not Granger Cause △LNREER,也就是说LNEX是LNREER的外生变量)
#代表截距项和系数值.
这样想是正确的吗?
还是说在第二个方程仍然要加入LNEX的滞后项?
或者是否只需要第一个方程?
之后还要进行脉冲响应和方差分解的分析,如果按照我自己那样想的方程去做,总感觉和书上的理论不搭调……
正在一头雾水中!求引路人!
LNEX does not Granger Cause △LNREER,也就是说LNEX是LNREER的外生变量
用eviews计算,输入内生变量和外生变量时怎么输?
VAR定义:VAR模型把系统中每一个内生变量作为系统中所有内生变量的滞后值的函数来构造模型.
而且许多描述VAR(向量自回归)方程的优势是事先无需对进入方程的变量进行内生或外生的划分,避免理论的误导.
这是否意味着,无论granger的检验结果如何,都是要把所有变量都包含进去作为内生变量构建VAR模型?
那granger检验对于VAR 又能有什么意义呢?
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1.Null Hypothesis:F-Statistic Probability 结论
△LNREER does not Granger Cause △LNEX 6.06305 0.00366 拒绝
△LNEX does not Granger Cause △LNREER 0.57844 0.56332 接受
这个没错.
2.LNREERt=#+#LNREERt-1+#LNREERt-2 (没有加入LNEX,因为△LNEX does not Granger Cause △LNREER,也就是说LNEX是LNREER的外生变量)
这个错了,要加入LNEX滞后项.
这意味着无论granger的检验结果如何,都是要把所有变量都包含进去作为内生变量构建VAR模型.
3.那granger检验对于VAR 又能有什么意义呢?
granger检验确认先后变化关系,其实granger检验的回归方程与VAR 模型的回归方程是一样的.
4.正如你所说,VAR(向量自回归)方程的优势是事先无需对进入方程的变量进行内生或外生的划分,所以不明白你说这话是什么意思:“用eviews计算,输入内生变量和外生变量时怎么输?”我的理解是不用区分.
5.如果你想要VAR方程,可以选中两变量,右键openvar,选择滞后阶数,可得方程.
不知道能不能帮到你,第一次回答问题啊哈哈
用EViews做granger检验的时候选项的 lags填多少?
用EViews做granger检验的时候选项的 lags填多少?
做两个序列之间的格兰杰检验(20年年度数据)
view-granger causality 然后弹出一个对话框 lags to include:___
系统好像默认是2
我发现填1,2,3,4,5,6的结果会差很多,数字再大就开始报错了
这个地方的lags到底应该是多少?
谢谢了!
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默认2,计算VAR后:view-->lag structure-->lag lengh criteria
结果出来 按多种标准,选出来的最佳滞后阶数,你可从中选一个适合你预期的滞后阶数,重新计算VAR,再granger causality .
这个地方随意性比较大,也是现在大家都说时间序列模型不靠谱的主要原因之一.
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罗恩:没.
赫敏:哦,你在施魔法么?然我看看吧.
罗恩:阳光,菊花,软黄油,让这个又胖又蠢的老鼠变黄.
赫敏:你确定那是真的咒语么?不过.不是很好使嘛.不是么?当然,我只尝试过很少的一些简单的咒语.但他们都奏效了.例如.恢复如初(哈利的破眼镜修好了).好了不是么.天呐~你是哈里坡特!我是赫敏 格兰杰.那么,你是?
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