Panel Estimation with GLS Cross Section Weights

[abcxyz]

In estimating Panel Regression equation, I found nearly all the variables to be insignificant but when I used GLS CROSS SECTION WEIGHTS in Panel Options, then the story changed completely and most of the variables became significant but still the Durbin Watson statistics has changed from 1.12 to 1.36.

What does this imply ?? Heteroscedaticity or/and Autocorrelation ?? Or Something else.

I would be obliged if anybody faced with the same problem let me know what is the situation like.

Regards.

[vtodorov]

In estimating Panel Regression equation, I found nearly all the variables to be insignificant but when I used GLS CROSS SECTION WEIGHTS in Panel Options, then the story changed completely and most of the variables became significant but still the Durbin Watson statistics has changed from 1.12 to 1.36.

What does this imply ?? Heteroscedaticity or/and Autocorrelation ?? Or Something else.

I would be obliged if anybody faced with the same problem let me know what is the situation like.

Regards.

I am interested in the answer as well.

[kisumow]

I am interested in this as well. Besides getting more significant variables and higher Durbin-Watson value, my R^2 jumps also.
Here are the results when I do a normal Panel Least Squares:

Dependent Variable: MLEVW-MLEVW(-1)
Method: Panel Least Squares
Date: 11/15/12 Time: 13:13
Sample (adjusted): 1993 2011
Periods included: 19
Cross-sections included: 10348
Total panel (unbalanced) observations: 66241
White cross-section standard errors & covariance (d.f. corrected)

Variable Coefficient Std. Error t-Statistic Prob.

KZCONSTRAINED(-1)*MDEV2 0.009581 0.004592 2.086482 0.0369
MDEV2*MDEV2 0.016816 0.016334 1.029520 0.3032
MTOB(-1)*MDEV2 -5.24E-06 6.27E-06 -0.835260 0.4036
LIQUIDITY(-1)*MDEV2 1.02E-05 1.04E-05 0.982654 0.3258
TANGIBILITY(-1)*MDEV2 0.008468 0.015940 0.531217 0.5953
EBITTA(-1)*MDEV2 1.19E-05 1.24E-05 0.961401 0.3364
LNASSETSDEFLATED(-1)*MDEV2 -0.002317 0.001981 -1.169856 0.2421

R-squared 0.001391 Mean dependent var 0.008193
Adjusted R-squared 0.001300 S.D. dependent var 0.109958
S.E. of regression 0.109887 Akaike info criterion -1.578629
Sum squared resid 799.7806 Schwarz criterion -1.577667
Log likelihood 52291.98 Hannan-Quinn criter. -1.578332
Durbin-Watson stat 2.121004

As you see, all the independent variables are insignificant and R^2 is very low. When I regressed with only one independent variable, I got a negative R^2 (?). When I apply cross-section weights as GLS weights I get the following results:

Dependent Variable: MLEVW-MLEVW(-1)
Method: Panel EGLS (Cross-section weights)
Date: 11/15/12 Time: 13:16
Sample (adjusted): 1993 2011
Periods included: 19
Cross-sections included: 10348
Total panel (unbalanced) observations: 66241
Linear estimation after one-step weighting matrix
White cross-section standard errors & covariance (d.f. corrected)

Variable Coefficient Std. Error t-Statistic Prob.

KZCONSTRAINED(-1)*MDEV2 0.009662 9.49E-05 101.8232 0.0000
MDEV2*MDEV2 0.016657 0.001710 9.744021 0.0000
MTOB(-1)*MDEV2 -5.48E-06 2.08E-06 -2.638492 0.0083
LIQUIDITY(-1)*MDEV2 1.04E-05 1.11E-06 9.295758 0.0000
TANGIBILITY(-1)*MDEV2 0.008213 0.000978 8.397623 0.0000
EBITTA(-1)*MDEV2 1.18E-05 1.32E-06 8.963587 0.0000
LNASSETSDEFLATED(-1)*MDEV2 -0.002346 0.000191 -12.26996 0.0000

Weighted Statistics

R-squared 0.900697 Mean dependent var 0.008739
Adjusted R-squared 0.900688 S.D. dependent var 0.438289
S.E. of regression 0.109843 Sum squared resid 799.1513
Durbin-Watson stat 2.059037

Unweighted Statistics

R-squared 0.001381 Mean dependent var 0.008193
Sum squared resid 799.7880 Durbin-Watson stat 2.121280

Now R^2 is very high, independent variables are significant and Durbin-Watson is higher. What does this imply?