-------------------------------------------------------------------------------
       log:  d:\bill\fall2008\econ30331\phillips_curve.log
  log type:  text
 opened on:  29 Oct 2008, 10:50:21

. 
. * there are three variables in the data set
. * year 
. * unemp (annual unemployment rate in %)
. * inflation (annual inflation rate in %)
. 
. 
. * The order of the time series
. * data must be specified by an
. * index.  Here, we use year as the
. * index
. tsset year
        time variable:  year, 1947 to 2007
                delta:  1 unit

. 
. * run classical phillips curve
. 
. reg inflation unemp

      Source |       SS       df       MS              Number of obs =      60
-------------+------------------------------           F(  1,    58) =    4.06
       Model |  33.5634573     1  33.5634573           Prob > F      =  0.0486
    Residual |  479.480783    58  8.26691005           R-squared     =  0.0654
-------------+------------------------------           Adj R-squared =  0.0493
       Total |   513.04424    59  8.69566509           Root MSE      =  2.8752

------------------------------------------------------------------------------
   inflation |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       unemp |   .5138821   .2550362     2.01   0.049     .0033718    1.024392
       _cons |   .9519491   1.474108     0.65   0.521    -1.998798    3.902696
------------------------------------------------------------------------------

. 
. * get durbin watson statistic
. estat dwatson

Durbin-Watson d-statistic(  2,    60) =  .8076584

. 
. * output residual
. predict resid_a, residual
(1 missing value generated)

. 
. * lag the variable 1 period
. gen resid_a1=resid_a[_n-1]
(2 missing values generated)

. 
. * estimate ar(1) term
. reg resid_a resid_a1, noconst

      Source |       SS       df       MS              Number of obs =      59
-------------+------------------------------           F(  1,    58) =   30.13
       Model |  154.739524     1  154.739524           Prob > F      =  0.0000
    Residual |  297.909892    58  5.13637744           R-squared     =  0.3419
-------------+------------------------------           Adj R-squared =  0.3305
       Total |  452.649415    59  7.67202399           Root MSE      =  2.2664

------------------------------------------------------------------------------
     resid_a |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    resid_a1 |    .568224   .1035255     5.49   0.000     .3609952    .7754529
------------------------------------------------------------------------------

. 
. 
. *now estimate augmented Phillips Curve
. * construct difference in inflation
. gen inflation_1=inflation[_n-1]
(1 missing value generated)

. gen d_inf=inflation-inflation_1
(1 missing value generated)

. 
. reg d_inf unemp

      Source |       SS       df       MS              Number of obs =      60
-------------+------------------------------           F(  1,    58) =    3.76
       Model |   21.645692     1   21.645692           Prob > F      =  0.0573
    Residual |  333.612884    58  5.75194628           R-squared     =  0.0609
-------------+------------------------------           Adj R-squared =  0.0447
       Total |  355.258576    59   6.0213318           Root MSE      =  2.3983

------------------------------------------------------------------------------
       d_inf |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       unemp |  -.4126824   .2127343    -1.94   0.057    -.8385164    .0131517
       _cons |   2.116596   1.229603     1.72   0.091    -.3447227    4.577914
------------------------------------------------------------------------------

. estat dwatson

Durbin-Watson d-statistic(  2,    60) =  1.546911

. 
. prais d_inf unemp, corc twostep

Iteration 0:  rho = 0.0000
Iteration 1:  rho = 0.1559

Cochrane-Orcutt AR(1) regression -- twostep estimates

      Source |       SS       df       MS              Number of obs =      59
-------------+------------------------------           F(  1,    57) =    7.13
       Model |   34.338162     1   34.338162           Prob > F      =  0.0099
    Residual |  274.681638    57   4.8189761           R-squared     =  0.1111
-------------+------------------------------           Adj R-squared =  0.0955
       Total |    309.0198    58  5.32792758           Root MSE      =  2.1952

------------------------------------------------------------------------------
       d_inf |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       unemp |  -.5934445   .2223151    -2.67   0.010    -1.038623   -.1482662
       _cons |   3.269425   1.296032     2.52   0.014     .6741659    5.864685
-------------+----------------------------------------------------------------
         rho |   .1559494
------------------------------------------------------------------------------
Durbin-Watson statistic (original)    1.546911
Durbin-Watson statistic (transformed) 1.978150

. 
. 
. 
end of do-file

. log close
       log:  d:\bill\fall2008\econ30331\phillips_curve.log
  log type:  text
 closed on:  29 Oct 2008, 10:51:16
-------------------------------------------------------------------------------