# [Limdep Nlogit List] F-test question

William Greene wgreene at stern.nyu.edu
Tue Apr 21 04:52:16 AEST 2020

```Bill.  It is not a feature.  Try something like this:
create;fed=female*educ ; med=educ-fed ; male=1-female\$\$
regr;lhs=income;rhs=female,fed,male,med
;cls:b(1)-b(3)=0,b(2)-b(4)=0\$\$
regr;lhs=income;rhs=one,educ\$
Please see below for results.
/Bill Greene

-----------------------------------------------------------------------------
Restricted   least squares regression ............
LHS=INCOME   Mean                 =         .44476
Standard deviation   =         .21659
----------   No. of observations  =           3377  DegFreedom   Mean square
Regression   Sum of Squares       =        11.3623           1      11.36229
Residual     Sum of Squares       =        147.004        3375        .04356
Total        Sum of Squares       =        158.367        3376        .04691
----------   Standard error of e  =         .20870  Root MSE          .20864
Fit          R-squared            =         .07175  R-bar squared     .07147
Model test   F[  1,  3375]        =      260.86136  Prob F > F*       .00000
Restrictions F[  2,  3373]        =        1.74597  Prob F > F*       .17463
--------+--------------------------------------------------------------------
|                  Standard            Prob.      95% Confidence
INCOME|  Coefficient       Error       z    |z|>Z*         Interval
--------+--------------------------------------------------------------------
FEMALE|     .16692***      .01757     9.50  .0000      .13248    .20136
FED|     .02415***      .00150    16.15  .0000      .02122    .02708
MALE|     .16692***      .01757     9.50  .0000      .13248    .20136
MED|     .02415***      .00150    16.15  .0000      .02122    .02708
--------+--------------------------------------------------------------------
***, **, * ==>  Significance at 1%, 5%, 10% level.
Model was estimated on Apr 20, 2020 at 02:47:40 PM
-----------------------------------------------------------------------------

|-> regr;lhs=income;rhs=one,educ\$

-----------------------------------------------------------------------------
Ordinary     least squares regression ............
LHS=INCOME   Mean                 =         .44476
Standard deviation   =         .21659
----------   No. of observations  =           3377  DegFreedom   Mean square
Regression   Sum of Squares       =        11.3623           1      11.36229
Residual     Sum of Squares       =        147.004        3375        .04356
Total        Sum of Squares       =        158.367        3376        .04691
----------   Standard error of e  =         .20870  Root MSE          .20864
Fit          R-squared            =         .07175  R-bar squared     .07147
Model test   F[  1,  3375]        =      260.86136  Prob F > F*       .00000
--------+--------------------------------------------------------------------
|                  Standard            Prob.      95% Confidence
INCOME|  Coefficient       Error       z    |z|>Z*         Interval
--------+--------------------------------------------------------------------
Constant|     .16692***      .01757     9.50  .0000      .13248    .20136
EDUC|     .02415***      .00150    16.15  .0000      .02122    .02708
--------+--------------------------------------------------------------------
***, **, * ==>  Significance at 1%, 5%, 10% level.
Model was estimated on Apr 20, 2020 at 02:49:10 PM
-----------------------------------------------------------------------------

On Mon, Apr 20, 2020 at 2:36 PM William Spitz <bills at gra-inc.com> wrote:

> I am doing an F-test for equality of coefficients in a simple linear model.
>
> Base model is y = a + b X
> I am testing whether the observations should be split into Groups 1 and 2:
> y = a1 + b1 X + a2 + b2 X
>
> But when I run the restricted model (using CLS: b(1)=b(3), b(2)=b(4)), I
> don't get the same restricted coefficient values as I do when running
> the Base model.
> They're pretty close, but not the same -- and it seems to be off by more
> than just rounding error.
>
> Is this a "feature" of imposing restrictions via CLS?
>
> Thanks in advance.
> /Bill Spitz
>
> _______________________________________________
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> Limdep at mailman.sydney.edu.au
> http://limdep.itls.usyd.edu.au
>
>

--
William Greene
Department of Economics, emeritus
Stern School of Business, New York University
44 West 4 St.
New York, NY, 10012
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Email: wgreene at stern.nyu.edu
Ph. +1.646.596.3296
Editor in Chief: Journal of Productivity Analysis
Editor in Chief: Foundations and Trends in Econometrics
Associate Editor: Economics Letters
Associate Editor: Journal of Business and Economic Statistics
```