Dear all,
I'm performing a Hausman test on panel data to determine whether to choose Random Effects or Fixed Effects for my analysis with AR(1). After performing the test I get a negative chi2 such as:
hausman fixed random
Note: the rank of the differenced variance matrix (11) does not equal the number of coefficients being tested
(13); be sure this is what you expect, or there may be problems computing the test. Examine the output
of your estimators for anything unexpected and possibly consider scaling your variables so that the
coefficients are on a similar scale.
---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| fixed random Difference S.E.
-------------+----------------------------------------------------------------
....deleted
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtregar
B = inconsistent under Ha, efficient under Ho; obtained from xtregar
Test: Ho: difference in coefficients not systematic
chi2(11) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= -13.34 chi2<0 ==> model fitted on these
data fails to meet the asymptotic
assumptions of the Hausman test;
see suest for a generalized test
What does this mean? Is this result OK, and it simply means that I should use random effects or something is terribly wrong here?
I have tried to invert the order, but I guess that it is not make sense...
hausman random fixed
Note: the rank of the differenced variance matrix (11) does not equal the number of coefficients being tested
(13); be sure this is what you expect, or there may be problems computing the test. Examine the output
of your estimators for anything unexpected and possibly consider scaling your variables so that the
coefficients are on a similar scale.
---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| random fixed Difference S.E.
-------------+----------------------------------------------------------------
...deleted
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtregar
B = inconsistent under Ha, efficient under Ho; obtained from xtregar
Test: Ho: difference in coefficients not systematic
chi2(11) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 13.34
Prob>chi2 = 0.2719
(V_b-V_B is not positive definite)
For the xtregar it is not possible to use sigmamore option or the xtoverid routine but they work only for the xtreg...
Should I reject the null hypothesis, and use the random effects estimator?
I'm performing a Hausman test on panel data to determine whether to choose Random Effects or Fixed Effects for my analysis with AR(1). After performing the test I get a negative chi2 such as:
hausman fixed random
Note: the rank of the differenced variance matrix (11) does not equal the number of coefficients being tested
(13); be sure this is what you expect, or there may be problems computing the test. Examine the output
of your estimators for anything unexpected and possibly consider scaling your variables so that the
coefficients are on a similar scale.
---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| fixed random Difference S.E.
-------------+----------------------------------------------------------------
....deleted
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtregar
B = inconsistent under Ha, efficient under Ho; obtained from xtregar
Test: Ho: difference in coefficients not systematic
chi2(11) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= -13.34 chi2<0 ==> model fitted on these
data fails to meet the asymptotic
assumptions of the Hausman test;
see suest for a generalized test
What does this mean? Is this result OK, and it simply means that I should use random effects or something is terribly wrong here?
I have tried to invert the order, but I guess that it is not make sense...
hausman random fixed
Note: the rank of the differenced variance matrix (11) does not equal the number of coefficients being tested
(13); be sure this is what you expect, or there may be problems computing the test. Examine the output
of your estimators for anything unexpected and possibly consider scaling your variables so that the
coefficients are on a similar scale.
---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| random fixed Difference S.E.
-------------+----------------------------------------------------------------
...deleted
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtregar
B = inconsistent under Ha, efficient under Ho; obtained from xtregar
Test: Ho: difference in coefficients not systematic
chi2(11) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 13.34
Prob>chi2 = 0.2719
(V_b-V_B is not positive definite)
For the xtregar it is not possible to use sigmamore option or the xtoverid routine but they work only for the xtreg...
Should I reject the null hypothesis, and use the random effects estimator?
Comment