INTRODUCTORY ECONOMETRICS – REPLICATING EXAMPLES

Chapter 3. Multiple Regression – Examples

-------------------------------------------------------------------------------------
      name:  SN
       log:  ~Wooldridge\intro-econx\iexample3.smcl
  log type:  smcl
 opened on:   5 Jan 2019, 23:46:37
. **********************************************
. * Solomon Negash - Replicating Examples
. * Wooldridge, Jeffery (2016). Introductory Econometrics: A Modern Approach. 6th ed.  
. * STATA Program, version 15.1. 

. * Chapter 3  - Multiple Regression Analysis 
. * Computer Exercises (Examples)
. ******************** SETUP *********************

. *example3.1  Determinants of College GPA
. u gpa1.dta, clear
. eststo: reg colG hsGP ACT

      Source |       SS           df       MS      Number of obs   =       141
-------------+----------------------------------   F(2, 138)       =     14.78
       Model |  3.42365506         2  1.71182753   Prob > F        =    0.0000
    Residual |  15.9824444       138  .115814814   R-squared       =    0.1764
-------------+----------------------------------   Adj R-squared   =    0.1645
       Total |  19.4060994       140  .138614996   Root MSE        =    .34032
------------------------------------------------------------------------------
      colGPA |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       hsGPA |   .4534559   .0958129     4.73   0.000     .2640047    .6429071
         ACT |    .009426   .0107772     0.87   0.383    -.0118838    .0307358
       _cons |   1.286328   .3408221     3.77   0.000      .612419    1.960237
------------------------------------------------------------------------------
(est3 stored)

. eststo: reg colG  ACT
      Source |       SS           df       MS      Number of obs   =       141
-------------+----------------------------------   F(1, 139)       =      6.21
       Model |  .829558811         1  .829558811   Prob > F        =    0.0139
    Residual |  18.5765406       139  .133644177   R-squared       =    0.0427
-------------+----------------------------------   Adj R-squared   =    0.0359
       Total |  19.4060994       140  .138614996   Root MSE        =    .36557
------------------------------------------------------------------------------
      colGPA |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         ACT |    .027064   .0108628     2.49   0.014     .0055862    .0485417
       _cons |   2.402979   .2642027     9.10   0.000     1.880604    2.925355
------------------------------------------------------------------------------
(est4 stored)

. esttab, se
------------------------------------------------
             (1)             (2)                
            colGPA          colGPA             
------------------------------------------------
hsGPA       0.453***                
            (0.0958)                   
ACT         0.00943          0.0271*  
            (0.0108)        (0.0109)   
_cons       1.286***        2.403***
            (0.341)         (0.264)   
--------------------------------------------------
N           141             141   
--------------------------------------------------
Standard errors in parentheses
* p<0.05, ** p<0.01, *** p<0.001
. est clear

. *example3.2. Wage equation
. u wage1.dta, clear
. reg lwage educ exper tenure

      Source |       SS           df       MS      Number of obs   =       526
-------------+----------------------------------   F(3, 522)       =     80.39
       Model |  46.8741776         3  15.6247259   Prob > F        =    0.0000
    Residual |  101.455574       522  .194359337   R-squared       =    0.3160
-------------+----------------------------------   Adj R-squared   =    0.3121
       Total |  148.329751       525   .28253286   Root MSE        =    .44086
-----------------------------------------------------------------------------
       lwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        educ |    .092029   .0073299    12.56   0.000     .0776292    .1064288
       exper |   .0041211   .0017233     2.39   0.017     .0007357    .0075065
      tenure |   .0220672   .0030936     7.13   0.000     .0159897    .0281448
       _cons |   .2843595   .1041904     2.73   0.007     .0796756    .4890435
------------------------------------------------------------------------------

. *example3.3. Participation in 401(k) pension plans 
. u 401k.dta, clear
. reg prate mrate age

      Source |       SS           df       MS      Number of obs   =     1,534
-------------+----------------------------------   F(2, 1531)      =     77.79
       Model |  39517.1118         2  19758.5559   Prob > F        =    0.0000
    Residual |  388868.428     1,531   253.99636   R-squared       =    0.0922
-------------+----------------------------------   Adj R-squared   =    0.0911
       Total |  428385.539     1,533  279.442622   Root MSE        =    15.937
------------------------------------------------------------------------------
       prate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       mrate |   5.521289   .5258844    10.50   0.000     4.489759    6.552819
         age |   .2431466   .0446999     5.44   0.000     .1554671     .330826
       _cons |   80.11905   .7790208   102.85   0.000     78.59099    81.64711
------------------------------------------------------------------------------

. *example3.4. Determinants of College GPA, R-squared. See example3.1.
. u gpa1.dta, clear
. reg colG hsGP ACT

      Source |       SS           df       MS      Number of obs   =       141
-------------+----------------------------------   F(2, 138)       =     14.78
       Model |  3.42365506         2  1.71182753   Prob > F        =    0.0000
    Residual |  15.9824444       138  .115814814   R-squared       =    0.1764
-------------+----------------------------------   Adj R-squared   =    0.1645
       Total |  19.4060994       140  .138614996   Root MSE        =    .34032
------------------------------------------------------------------------------
      colGPA |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       hsGPA |   .4534559   .0958129     4.73   0.000     .2640047    .6429071
         ACT |    .009426   .0107772     0.87   0.383    -.0118838    .0307358
       _cons |   1.286328   .3408221     3.77   0.000      .612419    1.960237
------------------------------------------------------------------------------

. *example3.5 Arrest records
. u crime1.dta, clear
. eststo: reg narr86 pcnv  ptime86 qemp86

      Source |       SS           df       MS      Number of obs   =     2,725
-------------+----------------------------------   F(3, 2721)      =     39.10
       Model |  83.0741941         3   27.691398   Prob > F        =    0.0000
    Residual |  1927.27296     2,721  .708295833   R-squared       =    0.0413
-------------+----------------------------------   Adj R-squared   =    0.0403
       Total |  2010.34716     2,724  .738012906   Root MSE        =     .8416
------------------------------------------------------------------------------
      narr86 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        pcnv |  -.1499274   .0408653    -3.67   0.000    -.2300576   -.0697973
     ptime86 |  -.0344199    .008591    -4.01   0.000    -.0512655   -.0175744
      qemp86 |   -.104113   .0103877   -10.02   0.000    -.1244816   -.0837445
       _cons |   .7117715   .0330066    21.56   0.000      .647051     .776492
------------------------------------------------------------------------------
(est1 stored)

. eststo: reg narr86 pcnv avgsen ptime86 qemp86
      Source |       SS           df       MS      Number of obs   =     2,725
-------------+----------------------------------   F(4, 2720)      =     29.96
       Model |  84.8242895         4  21.2060724   Prob > F        =    0.0000
    Residual |  1925.52287     2,720  .707912819   R-squared       =    0.0422
-------------+----------------------------------   Adj R-squared   =    0.0408
       Total |  2010.34716     2,724  .738012906   Root MSE        =    .84138
------------------------------------------------------------------------------
      narr86 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        pcnv |  -.1508319   .0408583    -3.69   0.000    -.2309484   -.0707154
      avgsen |   .0074431   .0047338     1.57   0.116    -.0018392    .0167254
     ptime86 |  -.0373908   .0087941    -4.25   0.000    -.0546345   -.0201471
      qemp86 |   -.103341   .0103965    -9.94   0.000    -.1237268   -.0829552
       _cons |   .7067565   .0331515    21.32   0.000     .6417519     .771761
------------------------------------------------------------------------------
(est2 stored)

. esttab, se r2
--------------------------------------------
                      (1)             (2)   
                   narr86          narr86   
--------------------------------------------
pcnv               -0.150***       -0.151***
                 (0.0409)        (0.0409)   
ptime86           -0.0344***      -0.0374***
                (0.00859)       (0.00879)   
qemp86             -0.104***       -0.103***
                 (0.0104)        (0.0104)   
avgsen                            0.00744   
                                (0.00473)   
_cons               0.712***        0.707***
                 (0.0330)        (0.0332)   
--------------------------------------------
N                    2725            2725   
R-sq                0.041           0.042   
--------------------------------------------
Standard errors in parentheses
* p<0.05, ** p<0.01, *** p<0.001
. est clear

. *example3.6 Wage equation
. u wage1.dta, clear
. reg lwage educ 

      Source |       SS           df       MS      Number of obs   =       526
-------------+----------------------------------   F(1, 524)       =    119.58
       Model |  27.5606288         1  27.5606288   Prob > F        =    0.0000
    Residual |  120.769123       524  .230475425   R-squared       =    0.1858
-------------+----------------------------------   Adj R-squared   =    0.1843
       Total |  148.329751       525   .28253286   Root MSE        =    .48008
------------------------------------------------------------------------------
       lwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        educ |   .0827444   .0075667    10.94   0.000     .0678796    .0976091
       _cons |   .5837727   .0973358     6.00   0.000     .3925563    .7749891
------------------------------------------------------------------------------

. log close
      name:  SN
       log:  ~Wooldridge\intro-econx\iexample3.smcl
  log type:  smcl
 closed on:   5 Jan 2019, 23:46:37
-------------------------------------------------------------------------------------




0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply

Your email address will not be published. Required fields are marked *




RSS Solomon Negash