Dear all!!

 I estimated the following OLS model with R 2.5.6:

Output R 2.5.6

Call:

lm(formula = UN ~ log(x) + time2, data = dati)



Residuals:

   Min     1Q Median     3Q    Max

-5.649 -2.753 -1.015  1.225 16.199



Coefficients:

              Estimate Std. Error t value Pr(>|t|)

(Intercept)  7.3036294  0.6871025  10.630   <2e-16 ***

log(x)      -0.0028542  0.0270730  -0.105    0.916

time2       -0.0002670  0.0003823  -0.698    0.487

---

Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Residual standard error: 4.323 on 87 degrees of freedom

Multiple R-Squared: 0.02933,    Adjusted R-squared: 0.007017

F-statistic: 1.314 on 2 and 87 DF,  p-value: 0.2739

is significant only the intercept

After I estimated the same model with R 2.7 and this is the new output:

Output R 2.7

regressione14<-lm(UN ~ log(x)+ time2,data=dati)

> summary(regressione14)



Call:

lm(formula = UN ~ log(x) + time2, data = dati)



Residuals:

   Min     1Q Median     3Q    Max

-8.825 -2.094 -0.861  2.233 12.664



Coefficients:

             Estimate Std. Error t value Pr(>|t|)

(Intercept) 22.724208   3.304670   6.876 8.89e-10 ***

log(x)      -7.117981   1.499482  -4.747 8.05e-06 ***

time2        0.002051   0.000523   3.922 0.000175 ***

---

Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Residual standard error: 3.853 on 87 degrees of freedom

Multiple R-Squared: 0.2289,     Adjusted R-squared: 0.2112

F-statistic: 12.91 on 2 and 87 DF,  p-value: 1.227e-05


Well, how you can see the two outputs are very differents, so i try to
estimated the same model with another package and i show the

output:





*Variabile*

*Coefficiente*

*Errore Std.*

*Statistica t*

*p-value*



const

22,7242

3,30467

6,8764

<0,00001

***

logx

-7,11798

1,49948

-4,7470

<0,00001

***

time2

0,00205144

0,000523012

3,9224

0,00017

***



            Media della variabile dipendente = 6,47833

            Scarto quadratico medio della variabile dipendente = 4,33827

            Somma dei quadrati dei residui = 1291,58

            Errore standard dei residui = 3,85302

            R2 = 0,228922

            R2 corretto = 0,211196

            Statistica F (2, 87) = 12,9145 (p-value = 1,23e-005)

            Log-verosimiglianza = -247,576

            Criterio di informazione di Akaike = 501,152

            Criterio bayesiano di Schwarz = 508,652

            Criterio di Hannan-Quinn = 504,176

  How you can see this package show the same output of the R 2.7

 My question is where is the bug?



 Kind regards

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