Chapter 11 - Examples

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      name:  SN
       log:  ~Wooldridge\intro-econx\iexample11.smcl
  log type:  smcl
 opened on:  15 Jan 2019, 11:10:19

. **********************************************
. * Solomon Negash - Replicating Examples
. * Wooldridge (2016). Introductory Econometrics: A Modern Approach. 6th ed.  
. * STATA Program, version 15.1. 

. * Chapter 11 Further Issues in Using OLS with Time Series Data
. * Computer Exercises (Examples)
. ******************** SETUP *********************

. *Example 11.1. Static Model
. //NA

. *Example 11.2.  Finite Distributed Lag Model
. //NA

. *Example 11.3.  AR(1) Model
. //NA

. *Example 11.4.  Efficient Markets Hypothesis
. u nyse, clear
. reg return return_1

      Source |       SS           df       MS      Number of obs   =       689
-------------+----------------------------------   F(1, 687)       =      2.40
       Model |  10.6866231         1  10.6866231   Prob > F        =    0.1218
    Residual |  3059.73817       687  4.45376735   R-squared       =    0.0035
-------------+----------------------------------   Adj R-squared   =    0.0020
       Total |  3070.42479       688  4.46282673   Root MSE        =    2.1104

------------------------------------------------------------------------------
      return |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    return_1 |   .0588984   .0380231     1.55   0.122    -.0157569    .1335538
       _cons |    .179634   .0807419     2.22   0.026     .0211034    .3381646
------------------------------------------------------------------------------

. //Equation [11.18]
. g return_2 = return[_n-2]
(3 missing values generated)
. reg return return_1 return_2

      Source |       SS           df       MS      Number of obs   =       688
-------------+----------------------------------   F(2, 685)       =      1.66
       Model |  14.7922358         2  7.39611792   Prob > F        =    0.1912
    Residual |  3054.64167       685   4.4593309   R-squared       =    0.0048
-------------+----------------------------------   Adj R-squared   =    0.0019
       Total |   3069.4339       687   4.4678805   Root MSE        =    2.1117

------------------------------------------------------------------------------
      return |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    return_1 |   .0603152   .0381775     1.58   0.115    -.0146437    .1352741
    return_2 |  -.0380748   .0381425    -1.00   0.319    -.1129651    .0368154
       _cons |   .1857481   .0811501     2.29   0.022     .0264153    .3450808
------------------------------------------------------------------------------
. test return_1 return_2
 ( 1)  return_1 = 0
 ( 2)  return_2 = 0
       F(  2,   685) =    1.66
            Prob > F =    0.1912

. *Example 11.5.  Expectations Augmented Phillips Curve
. u phillips, clear
. d
Contains data from phillips.dta
  obs:            49                          
 vars:            11                          17 Aug 1999 21:42
 size:         2,058                          
------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
------------------------------------------------------------------------------------------
year            int     %9.0g                 1948-1996
unem            float   %9.0g                 civilian unem. rate
inf             float   %9.0g                 CPI inflation rate
unem_1          float   %9.0g                 unem lagged once
inf_1           float   %9.0g                 inf lagged once
unem_2          float   %9.0g                 unem lagged twice
inf_2           float   %9.0g                 inf lagged twice
cunem           float   %9.0g                 unem - unem_1
cinf            float   %9.0g                 inf - inf_1
cunem_1         float   %9.0g                 cunem lagged once
cinf_1          float   %9.0g                 cinf lagged once
------------------------------------------------------------------------------------------
Sorted by: 
. reg cinf unem

      Source |       SS           df       MS      Number of obs   =        48
-------------+----------------------------------   F(1, 46)        =      5.56
       Model |  33.3830007         1  33.3830007   Prob > F        =    0.0227
    Residual |  276.305134        46  6.00663335   R-squared       =    0.1078
-------------+----------------------------------   Adj R-squared   =    0.0884
       Total |  309.688135        47  6.58910925   Root MSE        =    2.4508

------------------------------------------------------------------------------
        cinf |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        unem |  -.5425869   .2301559    -2.36   0.023    -1.005867    -.079307
       _cons |   3.030581    1.37681     2.20   0.033     .2592061    5.801955
------------------------------------------------------------------------------

. display as text "u_0 = " _b[_cons]/-_b[unem]
u_0 = 5.5854288

. *Example 11.6.  Fertility Equation
. u fertil3, clear
. reg cgfr cpe cpe_1 cpe_2

      Source |       SS           df       MS      Number of obs   =        69
-------------+----------------------------------   F(3, 65)        =      6.56
       Model |  293.259859         3  97.7532864   Prob > F        =    0.0006
    Residual |  968.199959        65   14.895384   R-squared       =    0.2325
-------------+----------------------------------   Adj R-squared   =    0.1971
       Total |  1261.45982        68  18.5508797   Root MSE        =    3.8595

------------------------------------------------------------------------------
        cgfr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         cpe |  -.0362021   .0267737    -1.35   0.181     -.089673    .0172687
       cpe_1 |  -.0139706   .0275539    -0.51   0.614    -.0689997    .0410584
       cpe_2 |   .1099896   .0268797     4.09   0.000     .0563071    .1636721
       _cons |  -.9636787   .4677599    -2.06   0.043     -1.89786   -.0294976
------------------------------------------------------------------------------
. test cpe cpe_1
 ( 1)  cpe = 0
 ( 2)  cpe_1 = 0
       F(  2,    65) =    1.29
            Prob > F =    0.2824

. *Example 11.7.  Wages and Productivity
. u earns, clear
. reg lhrwage loutphr t

      Source |       SS           df       MS      Number of obs   =        41
-------------+----------------------------------   F(2, 38)        =    641.22
       Model |  1.04458064         2  .522290318   Prob > F        =    0.0000
    Residual |  .030951776        38   .00081452   R-squared       =    0.9712
-------------+----------------------------------   Adj R-squared   =    0.9697
       Total |  1.07553241        40   .02688831   Root MSE        =    .02854

------------------------------------------------------------------------------
     lhrwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     loutphr |   1.639639   .0933471    17.56   0.000     1.450668    1.828611
           t |    -.01823   .0017482   -10.43   0.000     -.021769   -.0146909
       _cons |  -5.328454   .3744492   -14.23   0.000    -6.086487   -4.570421
------------------------------------------------------------------------------

. reg ghrwage goutphr

      Source |       SS           df       MS      Number of obs   =        40
-------------+----------------------------------   F(1, 38)        =     21.77
       Model |  .006255013         1  .006255013   Prob > F        =    0.0000
    Residual |   .01091799        38  .000287316   R-squared       =    0.3642
-------------+----------------------------------   Adj R-squared   =    0.3475
       Total |  .017173003        39  .000440333   Root MSE        =    .01695

------------------------------------------------------------------------------
     ghrwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     goutphr |    .809316   .1734537     4.67   0.000     .4581773    1.160455
       _cons |  -.0036621     .00422    -0.87   0.391    -.0122051    .0048808
------------------------------------------------------------------------------

. *Example 11.8.  Fertility Equation
. u fertil3, clear
. reg cgfr cgfr_1 cpe cpe_1 cpe_2 

      Source |       SS           df       MS      Number of obs   =        69
-------------+----------------------------------   F(4, 64)        =      7.46
       Model |  401.286162         4   100.32154   Prob > F        =    0.0001
    Residual |  860.173657        64  13.4402134   R-squared       =    0.3181
-------------+----------------------------------   Adj R-squared   =    0.2755
       Total |  1261.45982        68  18.5508797   Root MSE        =    3.6661

------------------------------------------------------------------------------
        cgfr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      cgfr_1 |   .3002422   .1059034     2.84   0.006     .0886758    .5118086
         cpe |  -.0454721   .0256417    -1.77   0.081    -.0966972     .005753
       cpe_1 |    .002064   .0267776     0.08   0.939    -.0514303    .0555584
       cpe_2 |   .1051346   .0255904     4.11   0.000      .054012    .1562572
       _cons |  -.7021594   .4537988    -1.55   0.127    -1.608727    .2044079
------------------------------------------------------------------------------
. test cpe cpe_1
 ( 1)  cpe = 0
 ( 2)  cpe_1 = 0
       F(  2,    64) =    1.66
            Prob > F =    0.1990
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      name:  SN
       log:  ~Wooldridge\intro-econx\iexample11.smcl
  log type:  smcl
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