Using the time change method we show how to construct a solution to the stochastic equation   $d{{X}_{t}}\,=\,b({{X}_{t}}\_)d{{Z}_{t}}\,+\,a({{X}_{t}})dt$  with a nonnegative drift a provided there exists a solution to the auxililary equation
 $d{{X}_{t}}\,=\,b({{X}_{t}}\_)d{{Z}_{t}}\,+\,a({{X}_{t}})dt$  with a nonnegative drift a provided there exists a solution to the auxililary equation   $d{{L}_{t}}=[{{a}^{-1/\alpha }}b]({{L}_{t}}\_)d\overline{{{Z}_{t}}}+dt$  where
 $d{{L}_{t}}=[{{a}^{-1/\alpha }}b]({{L}_{t}}\_)d\overline{{{Z}_{t}}}+dt$  where   $Z,\,\overline{Z}$  are two symmetric stable processes of the same index
 $Z,\,\overline{Z}$  are two symmetric stable processes of the same index   $\alpha \,\in \,(0,\,2]$ . This approach allows us to prove the existence of solutions for both stochastic equations for the values
 $\alpha \,\in \,(0,\,2]$ . This approach allows us to prove the existence of solutions for both stochastic equations for the values   $0\,<\,\alpha \,<\,1$  and only measurable coefficients
 $0\,<\,\alpha \,<\,1$  and only measurable coefficients   $a$  and
 $a$  and   $b$  satisfying some conditions of boundedness. The existence proof for the auxililary equation uses the method of integral estimates in the sense of Krylov.
 $b$  satisfying some conditions of boundedness. The existence proof for the auxililary equation uses the method of integral estimates in the sense of Krylov.