<p>I'm not sure what your variable is for LGBTQ, but the regression seems fine.</p>
<p><span class="math-container">$b$</span> would measure the effect of being LGBTQ for the omitted state.</p>
<p><span class="math-container">$f$</span> would measure the difference in the effect of being LGBTQ for state 1 relative to the omitted state.</p>
<p><span class="math-container">$g$</span> would measure the difference in the effect of being LGBTQ for state 2 relative to the omitted state.</p>
<p>So your interpretation is correct, you just need to remember that you are estimating relative effects (to the baseline group) rather than effects in levels.</p>

CC BY-SA 4.0
2022-05-02T14:35:00.513Z
Thank you! I see- so you are estimating relative effects to the baseline group. Then in that case, to then compare different states, could you rank the states by their interaction term?The state with smallest/most negative interaction term has the most lgbtq discrimination?
Bob
CC BY-SA 4.0
2022-05-02T19:23:09.953Z
Yes, and the omitted state has a value of 0.
Michael Gmeiner
CC BY-SA 4.0
2022-05-02T07:28:22.853Z
2022-05-02T07:28:22.853Z
Michael Gmeiner
<p>I'm an undergraduate student writing up a research proposal for a reserach-based class. I'm testing how LGBTQ discrimination in the labor market might vary in each state in the US (that's my research proposal, not actually collecting the data). This would be a correspondence study (bertrand style).
I'm struggling with how my regression equation would work:
Would something like this measure between-state variation or only within-state variation?
probability of getting interview = a + b[being LGBTQ]+c[state 1] + d[state 2]+...+e[state 49] + f[state 1 x being LGBTQ] + g[state 2 x being LGBTQ].
Would the interaction terms represent the discrimination variation by state? Eg is f is very negative, state 1 discriminates a lot by LGBTQ status.</p>
<p>Or should I just do a simple linear regression for each state and compare?</p>

<applied-econometrics><discrimination>
Regression equation to test state variation
Bob
# Regression equation to test state variation

(Asked by: username_0 on 2022-05-02)

I'm an undergraduate student writing up a research proposal for a reserach-based class. I'm testing how LGBTQ discrimination in the labor market might vary in each state in the US (that's my research proposal, not actually collecting the data). This would be a correspondence study (bertrand style).
I'm struggling with how my regression equation would work:
Would something like this measure between-state variation or only within-state variation?
probability of getting interview = a + b[being LGBTQ]+c[state 1] + d[state 2]+...+e[state 49] + f[state 1 x being LGBTQ] + g[state 2 x being LGBTQ].
Would the interaction terms represent the discrimination variation by state? Eg is f is very negative, state 1 discriminates a lot by LGBTQ status.

Or should I just do a simple linear regression for each state and compare?

**Tags:** applied-econometrics, discrimination


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## 1 answers

### Answer by username_1 on 2022-05-02. Score: 1

I'm not sure what your variable is for LGBTQ, but the regression seems fine.

$b$ would measure the effect of being LGBTQ for the omitted state.

$f$ would measure the difference in the effect of being LGBTQ for state 1 relative to the omitted state.

$g$ would measure the difference in the effect of being LGBTQ for state 2 relative to the omitted state.

So your interpretation is correct, you just need to remember that you are estimating relative effects (to the baseline group) rather than effects in levels.

> **Comments:**
> **username_0**: Thank you! I see- so you are estimating relative effects to the baseline group. Then in that case, to then compare different states, could you rank the states by their interaction term?The state with smallest/most negative interaction term has the most lgbtq discrimination?  
> **username_1**: Yes, and the omitted state has a value of 0.  

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