[R] Non-Linear Regression (Cobb-Douglas and C.E.S)

[James Wettenhall]

Mohammed,

> For estimating Cobb-Douglas production Function [ Y = ALPHA * 
> (L^(BETA1)) * (K^(BETA2))  ], i want to use nls function 
> (without linearizing it). But how can i get initial values? 

This might be a dumb question, but why do you need nonlinear 
regression for that model?  It is linear after taking logs:

log Y = log ALPHA + BETA1 log L + BETA2 log K

> 2. How can i estimate C.E.S Production Function [  Y = GAMA * 
> ((DELTA*K^(-BETA)) + ((1-DELTA)*L^(-BETA)))^(-PHI/BETA)  ] 

Your second model (C.E.S. Prod. Fcn) does indeed look nonlinear, 
and I'm sorry I can't think how to find a good point 
around which to linearize. Can you guess some approximate 
parameter values for some "typical" Y,L,K data?  

If it's too hard to estimate parameters 
for a model, maybe it's time to come up with a new model :)

Regards,
James