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From |
Andrea Bennett <mac.stata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Your opinion on income groups and inflation |

Date |
Sat, 7 Jun 2008 20:00:43 +0200 |

Thank you both for you suggestions! So, I will use NO dummies for income since there is no/I have no theoretical expectation that the effects should be different within each specific level of income, rather I do expect one direction of the effect of income on y, only. I might test for an interaction dummy with the highest income class, though. In the case of the "trust" variable I will NOT use dummies, too (for the above reason).

Many thanks for you little helper!

On Jun 7, 2008, at 7:40 PM, SamL wrote:

Making ordered categories dummy variables vs. making them one ordered variable by assigning values are both okay. The dummy variable approach is most flexible, allowing the effect to be different across categories. But, if you have no theoretical expectation for that, nor any reason to believe those particular categorical lines match the lines you'd draw if you could, then I agree with Martin below.

Sam

On Sat, 7 Jun 2008, Martin Weiss wrote:

The obsession with dummies in some posts is a little bewildering. If you

already have an ordered variable recording trust in government it is hard to

see why you would want to throw away this information and let the resulting

dummies eat up your df. Just include the variable in the regression as it

is. If you absolutely want to, -tabulate, generate- could be helpful. Be

sure to omit one dummy in the regression to dodge the famous dummy trap...

Martin Weiss

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-----Original Message-----

From: owner-statalist@hsphsun2.harvard.edu

[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Andrea Bennett

Sent: Saturday, June 07, 2008 7:19 PM

To: statalist@hsphsun2.harvard.edu

Subject: st: Your opinion on income groups and inflation

Dear Statalisters,

I wonder what you do think about the following issues:

1.

I have a cross-sectional panel data set with a time span of 10 years

(5 complete surveys). The survey does NOT ask for (more or less)

precise income but instead for income groups (e.g. between 3000 and

4000 $). As this does cluster the income quite a bit I was wondering

of how much use it would be to control for the inflation rate (which

was rather low, about 1-2% p.a.)? Still, I tend to control for

inflation since there is a gradual shift from lower income groups to

higher income groups. Would you include the inflation adjustments or

not?

2.

Do I need to treat these income groups as categorical data and

therefore generate dummies for each income category? Do I also need to

control for the highest income group with an additional dummy since it

measures income>=10'000$? This just affects the df quite a bit, I

think. How would you deal with such a variable?

3.

Related to the above question, I wonder how one usually deals with

interval variables. I have a variable measuring the trust/confidence

in the national government on a scale of 0-10 (1-point steps). Again,

as I have learned it, I would have to include a dummy for each trust-

level. Again, losing df is what brings me to ask you again. Do I need

to generate dummies here or not?

Kind regards and many thanks for your consideration,

Andrea

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**Follow-Ups**:**Re: st: RE: Your opinion on income groups and inflation***From:*bmilanovic@worldbank.org

**References**:**st: Your opinion on income groups and inflation***From:*Andrea Bennett <mac.stata@gmail.com>

**st: RE: Your opinion on income groups and inflation***From:*"Martin Weiss" <martin.weiss@uni-tuebingen.de>

**Re: st: RE: Your opinion on income groups and inflation***From:*SamL <saml@demog.berkeley.edu>

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