1. ## Log regressions

So between these two log regressions:
1) transform y into log but keep X normal
2) transform both the y and x into log

When or what would be a logical explanation for only transforming y and not c over transforming them both?

2. ## Re: Log regressions

The functional relationship between them may only require one to be transformed in order to normalize the residuals or get a linear relationship.

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Jazz3 (04-08-2017)

4. ## Re: Log regressions

Originally Posted by hlsmith
The functional relationship between them may only require one to be transformed in order to normalize the residuals or get a linear relationship.
I've also heard that it depends on your research, for example if you expect diminishing returns? Are there more underlying reasons than just in order to normalize the residuals and to get a lineair relationship?

5. ## Re: Log regressions

What matters is if the model fits to the data. If the model does not fit, then the model is rejected.

I've also heard that it depends on your research, for example if you expect diminishing returns?
If you have an hypothesis of "diminishing returns" then that is something that can be tested with the data. Models are not sacrosanct, holy scriptures. They can and should be tested.

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Jazz3 (04-18-2017)

7. ## Re: Log regressions

Agreed. Some fields prefer to talk about relationships on relative instead of absolute terms. Though, regardless of the model used it must fit data and meet assumptions.

8. ## Re: Log regressions

Just to make it more clear, what hlsmith said about the functional form:

1. if you only transform Y you have a relationship like log Y = a1*x1+ a2*x2 -> Y=exp(a1*x1+a2*x2)
2. if you transform both then logY = a1*log(x1)+a2*log(x2) -> Y = x1**a1*x2**a2

regards

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Jazz3 (04-18-2017)

10. ## Re: Log regressions

Thanks for all the information! Really helpful

But to come back to diminishing returns to scale I know this applies for log log regression, but also for log linear regressions?

11. ## Re: Log regressions

Originally Posted by Jazz3
Thanks for all the information! Really helpful

But to come back to diminishing returns to scale I know this applies for log log regression, but also for log linear regressions?
Or does the log linear only e.g. explains the marginal effect?

12. ## Re: Log regressions

In economics I think, where this type of analysis is most common I believe, there are theoretical reasons commonly for which to log.

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Jazz3 (04-18-2017)

14. ## Re: Log regressions

I've been going through some economics book but I can't find anything about diminishing returns and a log linear. I guess it only applies for log-log

Can anyone confirm this?

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