Need HELP with my model!! PLEASE

#1
Hi everyone,
I am stuck in my model, it's been more than two years that I have not had any econometric courses and I have forgotten some parts...
So, here's the thing: I want to see the effect of the farmland values on the urban sprawl and as a proxy of sprawl, I am using the "land permits" data on county level for Kansas.
as explanatory variable, I have income, density of population, farmland price and a dummy variable, 1 for a county being adjacent to the metropolitan area and 0 for the opposite case.
When I run the model with the dummy, the dummy turns out to be insignificant and the model seems good without it, (Rsquared, pvalue and the signs are correct) BUT

1- My datas are not normally distributed (but quite large sample)
2- httest shows I have the heteroscedasity problem.
3- my residuals are not normally distributed.
4- ovtest shows that my model has some omitted variables (I tried to add some others but they are not statically significant! :( )

I know its awful :shakehead but I have no idea WHERE I should start, I need some help,

here is the result of regression:

****
reg permits nilv income density dummy

Source | SS df MS Number of obs = 105
-------------+------------------------------ F( 4, 100) = 45.51
Model | 1642023.55 4 410505.888 Prob > F = 0.0000
Residual | 901959.21 100 9019.5921 R-squared = 0.6455
-------------+------------------------------ Adj R-squared = 0.6313
Total | 2543982.76 104 24461.3727 Root MSE = 94.972

------------------------------------------------------------------------------
permits | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
nilv | -.0356831 .0147927 -2.41 0.018 -.0650313 -.0063349
income | .0052909 .0016778 3.15 0.002 .0019622 .0086197
density | .958824 .127327 7.53 0.000 .7062109 1.211437
dummy | 31.06607 20.52525 1.51 0.133 -9.655439 71.78757
_cons | -186.5026 70.08598 -2.66 0.009 -325.5512 -47.45402
------------------------------------------------------------------------------

and here it is without dummy:

****
reg permits nilv income density

Source | SS df MS Number of obs = 105
-------------+------------------------------ F( 3, 101) = 59.16
Model | 1621361.06 3 540453.687 Prob > F = 0.0000
Residual | 922621.701 101 9134.86832 R-squared = 0.6373
-------------+------------------------------ Adj R-squared = 0.6266
Total | 2543982.76 104 24461.3727 Root MSE = 95.577

------------------------------------------------------------------------------
permits | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
nilv | -.0343146 .0148591 -2.31 0.023 -.063791 -.0048382
income | .0052326 .0016881 3.10 0.003 .0018839 .0085813
density | .9651885 .1280682 7.54 0.000 .7111357 1.219241
_cons | -176.8083 70.23728 -2.52 0.013 -316.1401 -37.47641
------------------------------------------------------------------------------

** ovtest

Ramsey RESET test using powers of the fitted values of permits
Ho: model has no omitted variables
F(3, 98) = 22.88
Prob > F = 0.0000


** hettest

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Ho: Constant variance
Variables: fitted values of permits

chi2(1) = 533.52
Prob > chi2 = 0.0000

* sktest r, noadj

Skewness/Kurtosis tests for Normality
------- joint ------
Variable | Obs Pr(Skewness) Pr(Kurtosis) chi2(2) Prob>chi2
-------------+---------------------------------------------------------------
r | 105 0.0000 0.0000 65.22 0.0000

Any idea where I should start?