* NONLINEAR LEAST SQUARES AND TESTING FOR AUTOCORRELATED ERRORS
*
* Example: Estimation of a CES production function
* 
* Data set: Table 22.4, page 724 of Griffiths, Hill and Judge,
*     LEARNING AND PRACTICING ECONOMETRICS, Wiley, 1993.
*
SAMPLE 1 30
READ L K Q 
      0.228      0.802      0.256918
      0.258      0.249      0.183599
      0.821      0.771      1.212883
      0.767      0.511      0.522568
      0.495      0.758      0.847894
      0.487      0.425      0.763379
      0.678      0.452      0.623130
      0.748      0.817      1.031485
      0.727      0.845      0.569498
      0.695      0.958      0.882497
      0.458      0.084      0.108827
      0.981      0.021      0.026437
      0.002      0.295      0.003750
      0.429      0.277      0.461626
      0.231      0.546      0.268474
      0.664      0.129      0.186747
      0.631      0.017      0.020671
      0.059      0.906      0.100159
      0.811      0.223      0.252334
      0.758      0.145      0.103312
      0.050      0.161      0.078945
      0.823      0.006      0.005799
      0.483      0.836      0.723250
      0.682      0.521      0.776468
      0.116      0.930      0.216536
      0.440      0.495      0.541182
      0.456      0.185      0.316320
      0.342      0.092      0.123811
      0.358      0.485      0.386354
      0.162      0.934      0.279431
GENR LOGQ=LOG(Q)
* Estimate the CES production function
NL 1 / NCOEF=4 PCOV ZMATRIX=Z COEF=BETA PREDICT=YHAT 
EQ LOGQ=GAMMA-(ETA/RHO)*LOG(DELTA*L**(-RHO)+(1-DELTA)*K**(-RHO)) 
COEF  RHO 1  DELTA .5  GAMMA 1  ETA 1
END 
* Estimate the elasticity of substitution
TEST 1/(1+RHO)
* Generate the linear pseudomodel and compute the DURBIN-WATSON p-value
MATRIX YBAR=LOGQ-YHAT+Z*BETA
OLS YBAR Z / NOCONSTANT DWPVALUE
STOP