Missing Data

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newbury1
Posts: 2
Joined: Sun Sep 11, 2011 7:09 am

Missing Data

Postby newbury1 » Sun Sep 11, 2011 7:13 am

I am attempting to run an OLS regression for Estonia, however I am missing some data for my variable seconday school enrollment. When i run the regression it is ignoring the missing data (NA) and taking observations from the year in which I have secondary school enrollment data. Is there a way round this? Thanks

startz
Non-normality and collinearity are NOT problems!
Posts: 3798
Joined: Wed Sep 17, 2008 2:25 pm

Re: Missing Data

Postby startz » Sun Sep 11, 2011 7:47 am

I am attempting to run an OLS regression for Estonia, however I am missing some data for my variable seconday school enrollment. When i run the regression it is ignoring the missing data (NA) and taking observations from the year in which I have secondary school enrollment data. Is there a way round this? Thanks
Could you explain what you mean by "taking observations from the year in which I have secondary school enrollment data." EViews just drops observations in which any variable is NA.

newbury1
Posts: 2
Joined: Sun Sep 11, 2011 7:09 am

Re: Missing Data

Postby newbury1 » Sun Sep 11, 2011 1:48 pm

I have 4 variables in the regression starting from 1960 -2010. The other 3 variables have data for every year, however, for secondary school enrollment it begins in 1990. When i run the regression it disregards all the variables from before 1990, so the regression only has 20 observations (1990 - 2010). Is there any way around this because i want the regression to have 50 observations from (1960 - 2010).

Thanks

startz
Non-normality and collinearity are NOT problems!
Posts: 3798
Joined: Wed Sep 17, 2008 2:25 pm

Re: Missing Data

Postby startz » Sun Sep 11, 2011 1:53 pm

Basically, no. The standard approach to regression is to use listwise deletion. That means eliminating an observation if any variable is missing.

There are methods for imputing missing data, but EViews doesn't provide any and they're not widely used in economics.


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