Re: st: Question: Ordered logit- suspicious odds ratio

[Richard Williams <richardwilliams.ndu@gmail.com>]

At 06:12 AM 4/16/2012, Stefanie Kneer wrote:
> Dear Statalist
>
> I am encountering running an ordered logit regression with the
> following panel data ranging from 1992-2010.
>
> describe  p11101 regionunempl unempl_empl interaction
>
>
>
> storage  display  value
>
> variable name   type   format label variable label
>
>
>
> p11101          byte   %8.0g        life satisfaction -discrete from 0-10
>
> regionunempl    float  %9.0g        Region unempl. %
>
> unempl_empl     float  %9.0g        dummy for being 1=unemployed and 
> 0=employed
>
> interaction     float  %9.0g        regionalunemployment 
> rate*unemployment dummy
>
> I am trying to identify the link between unemployment and happiness
> and in particular whether there exists a social norm effect. P11101 is
> thus my dependent variable and as it is discrete I was planning to run
> an ordered logit but I am encountering difficulties when trying to
> calculate the odds ratio. As can be seen the social norm effect, and
> thus whether you feel more comfortable when other people around you
> are not working, too is massively big (27). That looks kind of
> suspicious to me.  Could you give me an advice on why this is the case
> and what I should do about it?

I think it is hard to say that an effect is "massively big" without 
knowing something about the scaling. If you rescale the variables, 
e.g. measure income in dollars rather than 1000s of dollars, the 
coefficients will get rescaled too. If regionunempl is coded on a 
scale that ranges from 0 to 1, then a 1 unit increase is a HUGE 
increase (100 percentage points), indeed probably a much bigger 
increase than actually occurs in your data. If it is coded 0-100, 
then a 1 unit increase is just a 1 percentage point increase, which 
is much smaller. So, consider rescaling your variables so a 1 pt 
increase is a meaningful number. Or, compute the predicted values, or 
use -adjust- or -margins- to compute predicted values for various 
combinations of values, and see if the results seem plausible to you.


-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
WWW:    http://www.nd.edu/~rwilliam

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