Hi there,
This is Michalzeszen from Brazil.
I'm finishing a study on the 2008 economic crisis, and it's affects on the automotive sales in my state. For that I'm running a regression where the sales numbers are dependent on the interest rate, a index price and the amount of credit released for the purpose of buying a car.
I have a montly set of data from jan 2005 to dez 2012, and to identify the crisis period, I'm using dummies that say 1 to jan 2008 to jun 2009. This is the period the govenment applied anticyclical policies to prevent sales drop on the sector.
My question is really simple: how to run the regression and make the dummies interact with the explanatory variables?
Thank you so much for the help!
Estimation of dummy variables
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- Non-normality and collinearity are NOT problems!
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Re: Estimation of dummy variables
If y is the dependent variable, D the dummy, and X another explanatory variable
Code: Select all
ls y c x d d*x
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Re: Estimation of dummy variables
startz wrote:If y is the dependent variable, D the dummy, and X another explanatory variableCode: Select all
ls y c x d d*x
Thank you, I was guessing it would be something like that, but it's good to be sure!
Can I ask another question? If I want to use log on this estimation:
- should I convert the values of the variables to log prior the estimation, or during it?
- the Index Price have some negative values, how to properly convert it?
thanks again!
-
- Non-normality and collinearity are NOT problems!
- Posts: 3775
- Joined: Wed Sep 17, 2008 2:25 pm
Re: Estimation of dummy variables
It makes no difference whether you convert before or directly during estimation; do whichever is more convenient.
There is no great solution to the log of a negative number. If it's just a few observations, you might leave them out. Or you can add a positive number to all observations that everything is positive, but that may change the results a little.
There is no great solution to the log of a negative number. If it's just a few observations, you might leave them out. Or you can add a positive number to all observations that everything is positive, but that may change the results a little.
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