UCLA Academic Technology Services HomeServicesClassesContactJobs
Stat Computing > Stata > Textbook Examples > Econometric Analysis of Cross Section and Panel Data
Search

Stata Textbook Examples
Econometric Analysis of Cross Section and Panel Data by Jeffrey M. Wooldridge
Chapter 11: More Topics in Linear Unobserved Effects Models

The data files used for the examples in this text can be downloaded in a zip file from the Stata Web site. You can then use a program such as WinZip to unzip the data files.
Example 11.3 on page 305 using cornwell.dta.
use cornwell, clear

tsset county year
       panel variable:  county, 1 to 197
        time variable:  year, 81 to 87
ivreg d.lcrmrte (d.l.lcrmrte = l2.lcrmrte l3.lcrmrte) if year ==87 | year==88

Instrumental variables (2SLS) regression

      Source |       SS       df       MS              Number of obs =      90
-------------+------------------------------           F(  1,    88) =    0.18
       Model | -1.08714648     1 -1.08714648           Prob > F      =  0.6704
    Residual |  6.18074089    88  .070235692           R-squared     =       .
-------------+------------------------------           Adj R-squared =       .
       Total |  5.09359441    89  .057231398           Root MSE      =  .26502

------------------------------------------------------------------------------
D.lcrmrte    |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
lcrmrte      |
          LD |    .212428   .4973782     0.43   0.670    -.7760066    1.200863
_cons        |   .0646336   .0404458     1.60   0.114    -.0157439     .145011
------------------------------------------------------------------------------
Instrumented:  LD.lcrmrte
Instruments:   L2.lcrmrte L3.lcrmrte
------------------------------------------------------------------------------

reg d.l.lcrmrte l2.lcrmrte l3.lcrmrte if  year ==87 | year==88

      Source |       SS       df       MS              Number of obs =      90
-------------+------------------------------           F(  2,    87) =    3.95
       Model |  .283912416     2  .141956208           Prob > F      =  0.0228
    Residual |  3.12513763    87  .035921122           R-squared     =  0.0833
-------------+------------------------------           Adj R-squared =  0.0622
       Total |  3.40905005    89  .038303933           Root MSE      =  .18953

------------------------------------------------------------------------------
LD.lcrmrte   |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
lcrmrte      |
          L2 |  -.2616013   .0939729    -2.78   0.007    -.4483825     -.07482
          L3 |   .2598239   .0948714     2.74   0.007     .0712568     .448391
_cons        |   .0532431   .1287512     0.41   0.680    -.2026638      .30915
------------------------------------------------------------------------------

test l2.lcrmrte l3.lcrmrte

 ( 1)  L2.lcrmrte = 0
 ( 2)  L3.lcrmrte = 0

       F(  2,    87) =    3.95
            Prob > F =    0.0228

How to cite this page

Report an error on this page

UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services

The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California.