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Hi everyone. I hope there is someone out there that can answer my question :)

Im currently writing my thesis about the price-setting on the real estate market, where im making a hedonic model to estimate the price of individual houses, with time on market, physical attributes, locational attributes and trend as independable variables.
I have come to the conclusion that heteroskedasticity is present in my model, why the t-statistic and F-statistic is biased. As far as i know Ramseys RESET test, Wald test and Davidson-MacKinnon test cannot be used with the presence of heteroskedasticity because they rely on the t-statistic and F-statistic. My question is : how can these test be made robust to heteroskedasticity and can it be done in eviews?

My own thought for the Wald test and Davidson-MacKinnon test is first to make the model robust for heteroskedasticity with Whites heteroskedasticy-constant standard error & covariance method and afterwards make the tests. Making the tests without or with Whites heteroskedasticy-constant standard error & covariance, gives different test result, but this doesn't necessarily imply that this is the right way of doing it.
Making the Ramseys RESET test without or with heteroskedasticy-constant standard error & covariance makes no difference in the test results, why i don't think this is the way to go.

Anyway please give me your feedbacks and thoughts on this issue.

Thanks in advance
Martin

There must be someone out there knowing the solution Please share...

Hi,

The procedure you have followed (make estimators robust) I think is correct. When doing the Ramsey test you also have to include the option to make the estimators of the expanded model robust. This will produce a robust F-statistic. I think this is the way.
You can check this book: "Introductory Econometrics, A Modern Approach" by J. Wooldridge. This matter you can find in chapter 9 (third edition).

I hope I have helped somewhat.