I am a new user of STATA. I hope somebody give me a light.
Right now, I am trying to estimate system equations with nonlinear in parameters using NLSUR.
Here, I attached the system equations, the stata command and the result.
The Command in Stata
nlsur ( Rc = {s=0.5}*{τ=2.5}*(({δ=0.12}+{theta=0.616})/({δ=0.12}+{s=0.5}*{theta=0.616}))*Nc - {τ=2.5}*xkab) ( Rcu = {s=0.5}*{τ=2.5}*Nc + {s=0.5}*{τ=2.5}*xkab) (Lc = ({s=0.5}*{theta=0.616}/({δ=0.12}+{s=0.5}*{theta=0.616}))*N - ({s=0.5}*{theta=0.616}/({δ=0.12}+{s=0.5}*{theta=0.616}))*Lr) ( jcurban= (({r=0.1}+{δ=0.12}+{β=0.2}*{s=0.5}*{theta=0.616}) / (1-{β=0.2}*({r=0.1}+{δ=0.12}))*({fsc=0.15}*{r=0.1}+{f sc=0.15}*{δ=0.12}) + ({s=0.5}*{theta=0.616}*{τ=2.5}-{s=0.5}*{theta=0.616}*{s=0.5}*{τ=2.5})/({δ=0.12}+{s=0.5}*{theta=0.616})*N - ({s=0.5}*{theta=0.616}*{τ=2.5}-{s=0.5}*{theta=0.616}*{s=0.5}*{τ=2.5})/({δ=0.12}+{s=0.5}*{theta=0.616})*Lr)) (wc=((({β=0.2}*{r=0.1}+{β=0.2}*{δ=0.12}+{β=0.2}*{s =0.5}*{theta=0.616})*({fsc=0.01}*({r=0.1}+{δ=0.12} ))) / (({r=0.1}+{δ=0.12}-{β=0.2}*{r=0.1}-{β=0.2}*{δ=0.12})*{theta=0.616}))+(({r=0.1}+({β=0. 2}*({r=0.1}+{s=0.5}*{theta=0.616}+{δ=0.12}))) + ({δ=0.12}*{τ=2.5}-{δ=0.12}*{s=0.5}*{τ=2.5})) / ({r=0.1}+{δ=0.12}+{β=0.2}*{s=0.5}*{theta=0.616})*( ( {s=0.5}*{theta=0.616})/({δ=0.12}+{s=0.5}*{theta=0.616}))*N-(({r=0.1}+({β=0.2}*({r=0.1}+{s=0.5}*{theta=0.616}+ {δ=0.12}))) + ({δ=0.12}*{τ=2.5}-{δ=0.12}*{s=0.5}*{τ=2.5})) / ({r=0.1}+{δ=0.12}+{β=0.2}*{s=0.5}*{theta=0.616})*( ( {s=0.5}*{theta=0.616})/({δ=0.12}+{s=0.5}*{theta=0.616}))*Lr)
The Result:
Calculating NLS estimates...
Iteration 0: Residual SS = 1.41e+16
Iteration 1: Residual SS = 1.37e+16
Iteration 2: Residual SS = 1.37e+16
Iteration 3: Residual SS = 1.37e+16
Iteration 4: Residual SS = 1.37e+16
Iteration 5: Residual SS = 1.37e+16
Iteration 6: Residual SS = 1.37e+16
Iteration 7: Residual SS = 1.37e+16
Iteration 8: Residual SS = 1.37e+16
Iteration 9: Residual SS = 1.37e+16
Iteration 10: Residual SS = 1.37e+16
Iteration 11: Residual SS = 1.37e+16
Iteration 12: Residual SS = 1.37e+16
Iteration 13: Residual SS = 1.37e+16
Calculating FGNLS estimates...
Iteration 0: Scaled RSS = 2457.553
Iteration 1: Scaled RSS = 2437.816
Iteration 2: Scaled RSS = 2435.802
Iteration 3: Scaled RSS = 2435.8
Iteration 4: Scaled RSS = 2435.8
FGNLS regression
---------------------------------------------------------------------
Equation | Obs Parms RMSE R-sq Constant
----------------+----------------------------------------------------
1 Rc | 492 4 3494019 0.2344* (none)
2 Rcu | 492 2 3959116 0.1811* (none)
3 Lc | 492 3 64264.35 0.9049* (none)
4 jcurban | 492 7 58396.85 0.6779 r
5 wc | 492 7 187692.6 -0.0248 fsc
---------------------------------------------------------------------
* Uncentered R-sq
------------------------------------------------------------------------------
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
/s | .8927031 .0072136 123.75 0.000 .8785646 .9068415
/t | 4.651894 .309321 15.04 0.000 4.045636 5.258152
/d | 4.214471 1.323854 3.18 0.001 1.619764 6.809177
/theta | 2.216726 .7013804 3.16 0.002 .8420457 3.591406
/r | -3.906808 1.240583 -3.15 0.002 -6.338305 -1.475311
/ß | .9887485 .000669 1478.02 0.000 .9874374 .9900597
/fsc | 2956.139 . . . . .
------------------------------------------------------------------------------
My Questions are::
- If I want to know the relationship between variables, It was right what I’ve done?
- If the step is yes, how to make an interpretation in every equation ?
- If the step is wrong, please give me the light how to conduct rightly to estimate non linear in parameters of system equations.
Best Regard
Gidion
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