*
* HAUSMAN.RPF
* RATS Version 8, Users' Guide, Example 3.7
* Hausman test for simultaneous equations
*
cal(a) 1920
allocate 1941:1
open data klein.prn
data(org=columns,format=prn) / cons $
  profit privwage invst klagged1 prod govtwage govtexp taxes
set wagebill = privwage+govtwage
set trend    = t-1931:1
set capital  = klagged1+invst
smpl 1921:1 1941:1
instruments constant  trend govtwage govtexp taxes  profit{1} $
    capital{1}  prod{1}
*
equation   conseq cons
# constant  profit{0 1}   wagebill
equation   invseq invst
# constant  profit{0 1}   capital{1}
equation   wageeq privwage
# constant  prod{0 1}  trend
*
group klein conseq invseq wageeq
*
* Compute 2SLS estimates using SUR. Save the covariance matrix of
* residuals in VCV2SLS, the coefficients and %XX matrix in BETA2SLS and
* COV2SLS.
*
sur(model=klein,inst,cv=%identity(3),cvout=vcv2sls)
compute [symmetric] cov2sls=%xx
compute [vector] beta2sls=%beta
*
* Compute covariance matrix of 2SLS.  Apply SUR with CV=INV(VCV2SLS),
* then compute the matrix expression from the preceding page.
*
sur(model=klein,inst,nosigma,cv=inv(vcv2sls),noprint)
compute cov2sls=%mqform(inv(%xx),cov2sls)
*
* Compute 3SLS estimates.
*
sur(model=klein,inst)
*
test(all,vector=beta2sls,covmat=cov2sls-%xx)