.-
help for ^durbinh^ (SSC distribution 11 August 2002)
.-
Calculate the Durbin-Watson h statistic after @regress@ or @newey@
--------------------------------------------------------------
^durbinh^ [, force]
^durbinh^ is for use after ^regress^ or ^newey^; see help @regress@ or @newey@.
^durbinh^ is for use with time-series data. You must ^tsset^ your data before
using ^durbinh^; see help @tsset@.
Description
-----------
^durbinh^ computes the Durbin (1970) 'h' statistic to test for first-order serial
correlation in the disturbances after @regress@ when the regressor list contains
one or more lagged values of the dependent variable. In this case, the Durbin-
Watson statistic (@dwstat@) is inappropriate, as it is biased toward 2.0 (non-
rejection). Likewise, the Box-Pierce portmanteau test (@wntestq@) is not
appropriate in the presence of stochastic regressors. The Durbin "h" test
regresses the OLS residuals on their own lags and the original regressor list.
The coefficient on the lagged residual series, in ratio to its estimated
standard error, is distributed 't' under the null of zero autocorrelation
in the error process. This test (a special case of the Breusch-Godfrey LM
test @bgtest@) is asymptotically equivalent to the original test proposed by
Durbin, as discussed in Greene (2000, Ch. 13). Unlike the original test,
this test is computable for all data.
The command displays the estimated coefficient, 't-statistic', and P-value,
and places values in the return array. @return list@ for details.
Options
-------
The ^force^ option specifies that the test is to be allowed after
@regress ..., robust@ and @newey@; by default it is not allowed. In
these cases the test statistic is exactly the same as if standard OLS were
performed using @regress@. This is true because the test is based on the
residuals from the regression and they are the same for @regress@,
@regress ..., robust@, and @newey@. There is no way the test can
utilize any of the information used to make the standard errors robust after
estimation with @newey@ or @regress ..., robust@. It is best to view
the test as a test of the OLS disturbances whether estimation is by
@regress@, @regress ..., robust@, or @newey@.
Examples
--------
. ^use http://fmwww.bc.edu/ec-p/data/macro/wgmacro.dta^
. ^regress consumption L.consumption L(1/4).income^
. ^durbinh^
. ^g Lincome = L.income^
. ^g Lconsump = L.consumption^
. ^newey consumption Lconsump Lincome, lag(4)^
. ^durbinh, force^
References
----------
Durbin, J. "Testing for serial correlation in least squares regression when
some of the regressors are lagged dependent variables." Econometrica,
38, 1970, 410-421.
Greene, W. Econmetric Analysis. 4th ed., 2000. New York: Prentice-Hall.
Authors
-------
Christopher F Baum, Boston College, USA
baum@@bc.edu
Vince Wiggins, Stata Corporation
vwiggins@@stata.com
Also see
--------
Manual: ^[R] regress^, ^[R] regression diagnostics^
On-line: help for @regdiag@, @regress@, @time@, @tsset@; @dwtest@, @newey@,
@bgtest@ (if installed)