- Thread starter Mistermishka
- Start date
- Tags autocorrelation regression analysis t-statistic

Now, your Durbin-Watson test is small, which means that there is a positive correlation i.e. that means the assumption of independence is not valid.

This means, your regression output won't be reliable.

One generic solution to address auto-correlation is to use lagged values as your explanatory variable.

ledzep said:

Does your data have time as a variable? Autocorrelation is common in spatial and temporal data, as the measurements which are close together in time would be more similar than the measurement further apart in time.

Now, your Durbin-Watson test is small, which means that there is a positive correlation i.e. that means the assumption of independence is not valid.

This means, your regression output won't be reliable.

One generic solution to address auto-correlation is to use lagged values as your explanatory variable.

Apologies, I made a mistake: my durbin-watson statistic is greater than upper critical value, so there is an evidence that error terms are not positively correlated. Also when I plot ACF for errors it looks like there is no correlation there and Ljung-Box statistic is smaller than critical value.

I was hoping I could avoid lagging as I don't really understand how to do it.