Durbin-Watson difference, between, values

Andreas42

What is the difference between DL and DU values on a DW table?

yodacaia

On the table you take the two values and they make up your line bare used to determine whether you accept or reject the hypothesis that auto correlation is present



0 ----- DLower --- Dupper ---- 4 - DUpper ------ 4 - DLower -----4

If your calculated D stat is below Dlower, then Positive A/C is present

Between DL and DU - inconclusive - you can't reject and can't not reject

Greater than Dupper than positive A/C is not present

And similar for negative A/c


So its

positive A/C - inconclusive - no A/C - inconclusive - negative A/C

RMontgomery

thank you very much.

flyinggirl

And its corrected with Hansen Std Errors

tobeornottobe

keep adding lags until the residual slopes are no longer significant

hassan

U tesit for AR model, test for corrolation, still exists, test for AR2, if it doesnt exist, add a seasonality lag, then ARCH ..


Get st error = 1 / square root of number of observations

t = AC / st error if its greater than t table, then it needs adjustment..

if not then u fail to reject null and model is correctly specified.

benbenxiong

thanks all, I was just quizzing to see who is interested.

Kapie

true enough ..


Can you explain more on cointegration .. I have no clue what that is .. All i know is both v should not have unit root OR if they have unit root but must be cointegrated (long term economic relation) .. And it has a reliable t test.

giorgio10

for AR use dickey fuller test.
H0: b1-1 =0
if rejected, then time is covariant stationary.
If fail to reject, then b1 is indeed 1/has unit root.


To correct unit root, do first differencing.
A) Calculate yt = error = xt - x(t-1)
B) Then state yt = b0 + b1 y(t-1) + e where b0=b1=0

lucasg85

Cointegration -- just like you do differencing to get rid of the rising or falling trend, cointegration says if the two series are bad (not cov station), then it's ok, if the two series are relared to each other...they are both going wild, but if you take the difference between them, you get a stable mean, etc.