求问大神！我用eviews做面板数据时遇到这种情况应该怎样选择模型？！

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我分别研究全要素生产率和劳动生产率对我国OFDI的影响。16个行业作为截面数据，9年，分别以OFDI为因变量+ATFP为自变量，OFDI为因变量+LTFP为自变量，做面板数据。在选择模型时，我先假设是变截距模型，做了固定效应的冗余变量似然比检验，显示混合回归模型无效，那么就是应该变截距固定效应模型咯。但是我后来用各个模型的残差平方和计算出的F2就小于5%的临界值，那就说明要用混合回归模型啦！这前后不是矛盾吗？！请问各位大神，这种情况我该怎么处理？！谢谢！下图是固定效应的冗余变量似然比检验的结果：

Redundant Fixed Effects Tests			[size=9.0000pt]	[size=9.0000pt]
Pool: POOL2		[size=9.0000pt]	[size=9.0000pt]	[size=9.0000pt]
Test cross-section fixed effects				[size=9.0000pt]
Effects Test		Statistic	d.f.	Prob.
Cross-section F		8.821333	(15,112)	0.0000
Cross-section Chi-square		112.317109	15	0.0000
Cross-section fixed effects test equation:				[size=9.0000pt]
Dependent Variable: OFDI?			[size=9.0000pt]	[size=9.0000pt]
Method: Panel Least Squares			[size=9.0000pt]	[size=9.0000pt]
Date: 05/19/15   Time: 17:11			[size=9.0000pt]	[size=9.0000pt]
Sample: 2004 2012			[size=9.0000pt]	[size=9.0000pt]
Included observations: 9			[size=9.0000pt]	[size=9.0000pt]
Cross-sections included: 16			[size=9.0000pt]	[size=9.0000pt]
Total pool (balanced) observations: 144				[size=9.0000pt]
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	-1120319.	215719.7	-5.193400	0.0000
_TRANS--LTFP_TRANS	435182.9	73706.88	5.904238	0.0000
_INF--LTFP_INF	314452.6	62168.33	5.058083	0.0000
_SELL--LTFP_SELL	446808.9	61493.40	7.265964	0.0000
_HOTEL--LTFP_HOTEL	337543.6	68330.14	4.939894	0.0000
_REALTY--LTFP_REALTY	278030.9	52787.05	5.267030	0.0000
_RENT--LTFP_RENT	864099.5	78090.89	11.06531	0.0000
_SCI--LTFP_SCI	449318.5	87588.09	5.129904	0.0000
_IRRI--LTFP_IRRI	632203.4	128130.1	4.934075	0.0000
_RES--LTFP_RES	266984.4	53257.23	5.013111	0.0000
_HYG--LTFP_HYG	564612.6	114894.4	4.914189	0.0000
_CUL--LTFP_CUL	417198.5	84524.56	4.935826	0.0000
_MIN--LTFP_MIN	551025.8	69678.46	7.908122	0.0000
_MAN--LTFP_MAN	441834.5	71048.44	6.218778	0.0000
_POWER--LTFP_POWER	371423.9	71420.88	5.200494	0.0000
_CON--LTFP_CON	449559.7	85547.45	5.255092	0.0000
_AGR--LTFP_AGR	271956.6	53387.88	5.093976	0.0000
R-squared	0.769268	Mean dependent var		210779.9
Adjusted R-squared	0.740199	S.D. dependent var		433227.0
S.E. of regression	220818.6	Akaike info criterion		27.55856
Sum squared resid	6.19E+12	Schwarz criterion		27.90916
Log likelihood	-1967.216	Hannan-Quinn criter.		27.70102
F-statistic	26.46385	Durbin-Watson stat		0.983839
Prob(F-statistic)	0.000000

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关键词：EVIEWS Eview Views 选择模型 面板数据 模型

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