Log(FDI) = 5.725779 + 3.428861Log(CPI) + 0.892895Log(GDPR) 0.936270Log(EX) 0.339816Log(LF)
Dependent Variable: LOG(FDI)|
Method: least(prenominal) Squares|
Date: 04/29/12 Time: 16:46|
Sample(adjusted): 1991:01 1992:09|
Included observations: 21 after adjusting endpoints|
Variable| Coefficient| Std. Error| t-Statistic| Prob. |
C| 5.725779| 8.800845| 0.650594| 0.5245|
LOG(CPI)| 3.428861| 0.612231| 5.600601| 0.0000|
LOG(GDPR)| 0.892895| 0.465065| 1.919937| 0.0729|
LOG(EX)| -0.936270| 1.097771| -0.852883| 0.4063|
LOG(LF)| -0.339816| 0.195877| -1.734848| 0.1020|
R-squared| 0.895152| Mean dependent volt-ampere| 7.926808|
Adjusted R-squared| 0.868940| S.D. dependent var| 1.010853|
S.E. of regression| 0.365950| Akaike info criterion| 1.031619|
Sum squared residual oil| 2.142715| Schwarz criterion| 1.280315|
Log likelihood| -5.831999| F-statistic| 34.15059|
Durbin-Watson stat| 0.781840| Prob(F-statistic)| 0.000000|
Individual partial coefficient test
a) study of intercept
* Ho: ?1 = 0
H1: ?1 ? 0
* Test nurse: t = ?1^- 0Se(?1) = 5.725779-08.800845 = 0.651
* Decision rule: worsen Ho if |t| > tc = tc0.025, 11 = 2.201
* Since t = 0.651 < 2.
201 Do not discard Ho
Conclusion: in that location is insufficient evidence to infer that ?1 is statistically significant
b) Holding log(CPI) constant: Whether log(GPDR), log(LF), log(EX) has the power on FDI
* Ho: ?2 = 0
H1: ?2 ? 0
* Test value: t = ?2^- 0Se(?2) = 3.428861-00.612231 = 5.6
* Decision rule: Reject Ho if |t| > tc = tc0.025, 11 = 2.201
* Since t = 5.6 > 2.201 reject Ho
Conclusion: There is sufficient evidence to infer that ?2
c) Holding log(GDPR) constant: Whether log(IFL), log(EX), log(LF) has the effect on FDI
* Ho: ?3 = 0
H1: ?3 ? 0
* Test value: t = ?3^- 0Se(?3^) = 0.892895-00.465065 = 1.92
* Decision rule : Reject Ho if |t| > tc = tc0.025,...If you want to get a full essay, order it on our website: Ordercustompaper.com
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