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  • Beta coefficient in fixed effect model

    Hi there,

    This might be a very easy question but I would like to report the beta ('β' -standardised coefficient) results for the fixed-effect model in panel data analysis (longitudinal dataset from Time 1 to 4). I know for the regular linear regression model we use "regress y x, beta" syntax but when I tried the same technique here, it does not work and I am not actually sure that I should use the same approach in the panel data fixed model with robust standard error. I have red published papers reporting standard coefficient- β- using STATA software.

    Can someone helps me with the syntax, please?

    Thanks in advance,
    Liyu
    I use STATA 15.1

  • #2
    As I wrote in an earlier post on this same topic today, using standardized coefficients in a fixed-effects regression takes a bad idea and makes it much worse.

    I won't trouble you with my usual rant on why standardized coefficients in ordinary regression are rarely useful and almost always serve to obfuscate the results. Instead, I'll focus here on the additional problems that arise in the context of panel data.

    What does "standardized" mean in the context of panel data? In a fixed effects regression, we are estimating exclusively within-panel effects. So using the standard deviation of a variable in the entire sample makes no sense--it would be an irrelevant "standard" at best, and in some situations would be dominated by the between-panel variation that is explicitly excluded from consideration in fixed-effects models. But that still leaves ambiguity. Do you want to standardize within each panel separately, or do you want to calculate a pooled standard deviation across the panels? How will you explain or justify this choice to your audience? What does it even mean? With either approach, nobody but you will have any clue what the standard deviation(s) used actually is(are), so it follows that nobody will have any idea what your regression coefficients mean.

    If you are thinking that you need standardization so that you can "compare" the effects of different variables in your model, that notion is discredited and illusory even in the context of non-hierarchical data (ordinary beta coefficients), and it is even farther from reality with panel data.

    There is no built-in command or option in Stata to do this. If you really have a compelling reason to go down this rabbit hole, you will have to simply standardize the variables (in whichever way you think is less nonsensical) yourself using the usual data management commands and then run the panel regression with them.
    Last edited by Clyde Schechter; 15 Nov 2018, 00:23.

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    • #3
      Realised that I didn't reply, sorry and thank you Clyde. That was usual.

      Liyu

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