How to add heteroskedasticity transformation in my model result?

[yann]

I've heteroskedasticity in my model result,so my residus are very large. I would like to transform and add them in my model result.That's means, to have results with low residus. I'm using Pooling model. Here my R result:

plm(formula = sp ~ lag(debt) + lag(I(debt^2)) + outgp + +bcour + 
gvex + tradeop, data = bdata, model = "pooling", index = c("country", 
"year"))

Balanced Panel: n = 15, T = 20, N = 300

Residuals:
     Min.   1st Qu.    Median   3rd Qu.      Max. 
-14.06754  -2.00112  -0.43568   1.83239  39.87933 

Coefficients:
                  Estimate  Std. Error t-value  Pr(>|t|)    
(Intercept)    -2.66988469  1.22336253 -2.1824   0.02987 *  
lag(debt)       0.13411803  0.02180357  6.1512 2.517e-09 ***
lag(I(debt^2)) -0.00057832  0.00010127 -5.7105 2.762e-08 ***
outgp           0.01986735  0.01620570  1.2259   0.22120    
bcour           0.23662511  0.03926279  6.0267 5.018e-09 ***
gvex           -0.52866311  0.12588780 -4.1995 3.553e-05 ***
tradeop        -3.57865159  1.58891292 -2.2523   0.02505 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Total Sum of Squares:    8996.6
Residual Sum of Squares: 6660.6
R-Squared:      0.25965
Adj. R-Squared: 0.24449
F-statistic: 17.1269 on 6 and 293 DF, p-value: < 2.22e-16