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Re: st: Remedy for serial correlation in Panel Data
From
San K <[email protected]>
To
[email protected]
Subject
Re: st: Remedy for serial correlation in Panel Data
Date
Fri, 13 Apr 2012 23:54:12 +1000
I tried the xtregar on models as David suggested.
Model 1: using one lag of the dependant
xtregar ConsDayAvgLN L1.ConsDayAvgLN waitedAvgPrice Rain tempC Evap
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec, fe
Results:
rho_ar | .06241197
sigma_u | .22515903
sigma_e | .15550244
rho_fov | .67705949 (fraction of variance because of u_i)
--------------------------------------------------------------------------------
F test that all u_i=0: F(2510,47692) = 6.24 Prob > F = 0.0000
Model 4: using 4th lag of the dependant (since it is a quarterly metered data)
xtregar ConsDayAvgLN L4.ConsDayAvgLN waitedAvgPrice Rain tempC Evap
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec, fe
rho_ar | .48774083
sigma_u | .36213708
sigma_e | .15382504
rho_fov | .84714912 (fraction of variance because of u_i)
--------------------------------------------------------------------------------
F test that all u_i=0: F(2510,40159) = 8.83 Prob > F = 0.0000
How do I interpret these results?
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