-----------------------------------------------------------------------------------------------------
. * CCAPMmudeli jaoks vajalike tunnuste loomine, osa 1.


. gen y=ln(1+(price-L.price+L.div)/L.price)
(1 missing value generated)

. gen cg=ln(cons/L.cons)
(1 missing value generated)


* CCAPM mudeli hindamine OLS-i abil. Osa 2.

. regress y cg

      Source |       SS           df       MS      Number of obs   =        65
-------------+----------------------------------   F(1, 63)        =     20.01
       Model |  .392968563         1  .392968563   Prob > F        =    0.0000
    Residual |  1.23700489        63  .019634998   R-squared       =    0.2411
-------------+----------------------------------   Adj R-squared   =    0.2290
       Total |  1.62997345        64  .025468335   Root MSE        =    .14012

------------------------------------------------------------------------------
           y | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          cg |   3.644356   .8146242     4.47   0.000     2.016459    5.272253
       _cons |  -.0191633   .0259828    -0.74   0.464    -.0710858    .0327591
------------------------------------------------------------------------------

. gen dp=ln(div/price)


. * Instrumenttunnuste kasutamine, osa 3.

. ivregress 2sls y (cg = L. i L.dp), first

First-stage regressions
-----------------------

                                                        Number of obs =     65
                                                        F(2, 62)      =   4.66
                                                        Prob > F      = 0.0131
                                                        R-squared     = 0.1306
                                                        Adj R-squared = 0.1025
                                                        Root MSE      = 0.0204

------------------------------------------------------------------------------
          cg | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
           i |
         L1. |   .2036788   .0668061     3.05   0.003     .0701352    .3372223
             |
          dp |
         L1. |   .0033859   .0061172     0.55   0.582    -.0088423    .0156141
             |
       _cons |    .032856   .0202778     1.62   0.110    -.0076787    .0733908
------------------------------------------------------------------------------


Instrumental variables 2SLS regression            Number of obs   =         65
                                                  Wald chi2(1)    =       8.87
                                                  Prob > chi2     =     0.0029
                                                  R-squared       =          .
                                                  Root MSE        =     .16546

------------------------------------------------------------------------------
           y | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
          cg |    7.92602   2.662015     2.98   0.003     2.708566    13.14347
       _cons |  -.1206773   .0663665    -1.82   0.069    -.2507532    .0093986
------------------------------------------------------------------------------
Instrumented: cg
 Instruments: L.i L.dp


. * Endogeensuse testimine, osa 4.

. estat endog

  Tests of endogeneity
  H0: Variables are exogenous

  Durbin (score) chi2(1)          =  4.28033  (p = 0.0386)
  Wu-Hausman F(1,62)              =  4.37059  (p = 0.0407)

-----------------------------------------------------------------------------------------------------