求助：怎么用eviews3进行ADF检验、协整检验和格兰杰因果关系检验？？ 谁帮我用eviews对以下数据做下ADF检验 协整检验和格兰...
\u5982\u4f55\u7528eviews\u8fdb\u884cADF\u68c0\u9a8c\uff0c\u534f\u6574\u68c0\u9a8c\uff0c\u683c\u5170\u6770\u56e0\u679c\u5173\u7cfb\u68c0\u9a8c\u3002\u80fd\u5426\u5e2e\u5fd9\u5f04\u4e0b\u3002\u3002\u3002\u3002\u5f88\u6025\u554a\u3002\u3002\u3002 \u5e74\u4efd \u80a1\u7968\u7b79ADF\u68c0\u9a8c\uff1a\u4f8b\u5982\uff0c\u6253\u5f00GPCZE\u7684\u7a97\u53e3\uff0cview\u2014\u2014unit root test\uff0c\u7136\u540e\u9009\u62e9ADF\u68c0\u9a8c
\u534f\u6574\u68c0\u9a8c\uff1a\u6253\u5f00\u8fd9\u51e0\u4e2a\u53d8\u91cf\u7684\u7a97\u53e3\uff0cview\u2014\u2014cointegration Test
\u683c\u5170\u6770\u56e0\u679c\u68c0\u9a8c\uff1a\u5728\u8fd9\u4e2a\u53d8\u91cf\u7684\u7a97\u53e3\u4e2d\uff0cview\u2014\u2014Granger causality
\uff08\u4e00\uff09\u3001ADF\u662f\u5355\u4f4d\u6839\u68c0\u9a8c\uff0c\u7b2c\u4e00\u5217\u6570\u636ey\u505aADF\u68c0\u9a8c\uff0c\u7ed3\u679c\u5982\u4e0b
Null Hypothesis: Y has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.820038 0.0213
Test critical values: 1% level -4.098741
5% level -3.477275
10% level -3.166190
\u57281%\u6c34\u5e73\u4e0a\u62d2\u7edd\u539f\u5047\u8bbe\uff0c\u5e8f\u5217y\u5b58\u5728\u5355\u4f4d\u6839\uff0c\u4e3a\u4e0d\u5e73\u7a33\u5e8f\u5217\u3002\u4f46\u57285%\u300110%\u6c34\u5e73\u4e0a\u5747\u63a5\u53d7\u539f\u5047\u8bbe\uff0c\u8ba4\u4e3ay\u5e73\u7a33\u3002
\u5bf9y\u8fdb\u884c\u4e00\u9636\u5dee\u5206\uff0c\u5dee\u5206\u540e\u8fdb\u884cADF\u68c0\u9a8c\uff1a
Null Hypothesis: Y has a unit root
Exogenous: None
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -9.328245 0.0000
Test critical values: 1% level -2.599934
5% level -1.945745
10% level -1.613633
\u53ef\u89c1\uff0c\u5728\u5404\u6c34\u5e73\u4e0ay\u90fd\u662f\u5e73\u7a33\u7684\u3002\u56e0\u6b64\uff0c\u53ef\u4ee5\u628a\u539f\u5e8f\u5217y\u770b\u505a\u4e00\u9636\u5355\u6574\u3002
\u7b2c\u4e8c\u5217xADF\u68c0\u9a8c\u5982\u4e0b\uff1a
Null Hypothesis: X has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -3.216737 0.0898
Test critical values: 1% level -4.098741
5% level -3.477275
10% level -3.166190
\u57281%\u30015%\u6c34\u5e73\u4e0a\u62d2\u7edd\u539f\u5047\u8bbe\uff0c\u5e8f\u5217x\u5b58\u5728\u5355\u4f4d\u6839\uff0c\u4e3a\u4e0d\u5e73\u7a33\u5e8f\u5217\u3002\u4f46\u572810%\u6c34\u5e73\u4e0a\u5747\u63a5\u53d7\u539f\u5047\u8bbe\uff0c\u8ba4\u4e3ax\u662f\u5e73\u7a33\u7684\u3002
\u5bf9y\u8fdb\u884c\u4e00\u9636\u5dee\u5206\uff0c\u5dee\u5206\u540e\u8fdb\u884cADF\u68c0\u9a8c\uff1a
Null Hypothesis: X has a unit root
Exogenous: None
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -7.627041 0.0000
Test critical values: 1% level -2.599934
5% level -1.945745
10% level -1.613633
\u53ef\u89c1\uff0c\u5728\u5404\u6c34\u5e73\u4e0ax\u90fd\u662f\u5e73\u7a33\u7684\u3002\u56e0\u6b64\uff0c\u53ef\u4ee5\u628a\u539f\u5e8f\u5217x\u770b\u505a\u4e00\u9636\u5355\u6574\u3002
\uff08\u4e8c\uff09\u3001\u53ea\u6709\u4e00\u9636\u5355\u6574\u7684\u5e8f\u5217\u624d\u53ef\u4ee5\u8fdb\u884c\u534f\u6574\u68c0\u9a8c\uff1a
\u5229\u7528engle\u548cgranger\u63d0\u51fa\u7684\u4e24\u6b65\u68c0\u9a8c\u6cd5\uff1a
\u9996\u5148\u5efa\u7acb\u6a21\u578b\uff1ay=ax+c+e\uff0c\u7ed3\u679c\u4e3aY = 0.720902361403*X + 788.046309221
\u518d\u5bf9\u65b9\u7a0b\u7684\u6b8b\u5dee\u8fdb\u884cADF\u68c0\u9a8c\uff1a
Null Hypothesis: E has a unit root
Exogenous: None
Lag Length: 0 (Automatic based on SIC, MAXLAG=10)
t-Statistic Prob.*
Augmented Dickey-Fuller test statistic -4.093534 0.0001
Test critical values: 1% level -2.599413
5% level -1.945669
10% level -1.613677
\u4ece\u68c0\u9a8c\u7ed3\u679c\u53ef\u4ee5\u770b\u51fa\u6b8b\u5dee\u5e8f\u5217\u662f\u5e73\u7a33\u7684\uff0c\u56e0\u6b64x\u548cy\u4e4b\u95f4\u5b58\u5728\u534f\u6574\u5173\u7cfb\u3002
\uff08\u4e09\uff09\u3001granger\u56e0\u679c\u68c0\u9a8c\uff1a
Pairwise Granger Causality Tests
Date: 03/13/11 Time: 14:15
Sample: 1 69
Lags: 2
Null Hypothesis: Obs F-Statistic Prob.
Y does not Granger Cause X 67 1.11304 0.3350
X does not Granger Cause Y 5.72061 0.0052
\u4ece\u7ed3\u679c\u53ef\u77e5\u62d2\u7eddy\u4e0d\u80fdgranger x\u7684\u5047\u8bbe\uff0c\u5373y granger\u5f15\u8d77x\uff1b\u4f46\u662f\u4e0d\u80fd\u62d2\u7eddx\u4e0d\u80fdg\u5f15\u8d77y\uff0c\u5373\u63a5\u53d7x\u4e0d\u80fdgranger\u5f15\u8d77y\u3002
打开序列，View-unit root test，选择差分阶次以及模型，点击ok。若p小于alpha，则无单位根
2.协整检验
分两步走：
第一步：根据你的模型估计参数（这里可能用ols也可能用其他的模型估计方法）
第二步：对第一步估计得到模型的残差做单位根检验，若无单位根则说明满足协整关系
3.格兰杰因果检验
以group的形式打开两个序列，View-granger causality，选择差分阶次，点击ok。若p小于alpha，则是因果关系
现在一般读至少用eviews6啦
3版本太低啦
你有数据和参考论文没有
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