<p>If you want to do unit-fixed effects (so eliminating any unobserved variable that varies cross-sectionally but remains the same over time), this should not be a problem, at least assuming that your explanatory variable varies over time (be it a dummy that is 1 in the year the policy was administered and 0 otherwise, or a continuous variable that changes over time according to the intensity of the policy treatment). </p>

<p>It does not matter that the variable is on state level, as long as the policy varies over time. However, if you only have individual observations for the one state that introduced the policy, you will not be able to interpret your results counterfactually. For that you would need similar individuals observed over the same period of time in a state that did not introduce the policy (and apply difference-in-difference or something of the sort). </p>

CC BY-SA 4.0
2019-01-18T14:51:27.217Z
Thank you for your answer. Every state in my dataset introduced the policy, but to varying degrees. The policy varies over time and state. The aim of my analysis is to find out the effect of the extent of policy intervention on the behavior of individuals.
R-User
CC BY-SA 4.0
2019-01-18T18:24:01.760Z
Then it should not be a problem to introduce unit-fixed effects. You can code an ordinal variable that reflects the varying degrees of the policy introduction.
hrrrrrr5602
CC BY-SA 4.0
2019-01-18T14:28:34.657Z
2019-01-18T14:28:34.657Z
hrrrrrr5602
<p>I am planing a panel data analysis evaluating a continuous policy intervention. I do have individual level data. I would like to account for individual fixed-effects. However, the explanatory variable does not vary on individual level, but only on state level. The response variable is on individual level. Is that a problem?</p>

CC BY-SA 4.0
2019-01-18T11:50:56.640Z
So to be clear, I'm guessing this is a policy introduced by the state that affects individuals differentially?
hrrrrrr5602
CC BY-SA 4.0
2019-01-18T14:12:16.870Z
Yes, that is correct.
R-User
<fixed-effects>
Fixed-Effects on individual level with explanatory variable on state level
R-User
# Fixed-Effects on individual level with explanatory variable on state level

(Asked by: username_0 on 2019-01-18)

I am planing a panel data analysis evaluating a continuous policy intervention. I do have individual level data. I would like to account for individual fixed-effects. However, the explanatory variable does not vary on individual level, but only on state level. The response variable is on individual level. Is that a problem?

**Tags:** fixed-effects
> **Comments:**
> **username_1**: So to be clear, I'm guessing this is a policy introduced by the state that affects individuals differentially?  
> **username_0**: Yes, that is correct.  

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## 1 answers

### Answer by username_1 on 2019-01-18. Score: 1

If you want to do unit-fixed effects (so eliminating any unobserved variable that varies cross-sectionally but remains the same over time), this should not be a problem, at least assuming that your explanatory variable varies over time (be it a dummy that is 1 in the year the policy was administered and 0 otherwise, or a continuous variable that changes over time according to the intensity of the policy treatment).

It does not matter that the variable is on state level, as long as the policy varies over time. However, if you only have individual observations for the one state that introduced the policy, you will not be able to interpret your results counterfactually. For that you would need similar individuals observed over the same period of time in a state that did not introduce the policy (and apply difference-in-difference or something of the sort).

> **Comments:**
> **username_0**: Thank you for your answer. Every state in my dataset introduced the policy, but to varying degrees. The policy varies over time and state. The aim of my analysis is to find out the effect of the extent of policy intervention on the behavior of individuals.  
> **username_1**: Then it should not be a problem to introduce unit-fixed effects. You can code an ordinal variable that reflects the varying degrees of the policy introduction.  

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