+ Reply to Thread
Results 1 to 2 of 2

Thread: Does endogeneity affect the R-squared estimated in variance partitioning?

  1. #1
    Points: 7, Level: 1
    Level completed: 13%, Points required for next Level: 43

    Posts
    1
    Thanks
    0
    Thanked 0 Times in 0 Posts

    Does endogeneity affect the R-squared estimated in variance partitioning?




    Hi,

    I have a likely very simple question but I can’t get my head around the answer. I want to estimate which part of the variance in a firm's return on asset (ROA) can be attributed to year effects, industry effects, firm effects and finally CEO effects. I run an OLS regression to which I sequentially add each group (first year dummies, then industry dummies, firm dummies, CEO dummies). I use the incremental increase in R-squared as the measure of the variance of ROA a group explains. I got the comment today that because there are many time varying factors on the industry (e.g., industry specific temporary shocks), firm (e.g., change in firm size) or CEO (age) level that I don’t include in the model, endogeneity from an omitted variable is present and the coefficients are biased. While this is certainly true, I don't see how it would affect the incremental R-squared attributed to each group (year, industry, firm, CEO). More generally, is endogeneity an issue at all for variance partitioning?

    Many thanks in advance and my apologies for the simplicity of the question

    Peter
    Last edited by Peter Schmid; 05-02-2017 at 06:16 PM.

  2. #2
    TS Contributor
    Points: 22,359, Level: 93
    Level completed: 1%, Points required for next Level: 991
    spunky's Avatar
    Location
    vancouver, canada
    Posts
    2,135
    Thanks
    166
    Thanked 537 Times in 431 Posts

    Re: Does endogeneity affect the R-squared estimated in variance partitioning?


    Quote Originally Posted by Peter Schmid View Post
    .... endogeneity from an omitted variable is present and the coefficients are biased. While this is certainly true, I don't see how it would affect the incremental R-squared attributed to each group (year, industry, firm, CEO). More generally, is endogeneity an issue at all for variance partitioning?
    Well, OLS multiple regression's R-squared can be expressed as a function of the regression coefficients and the correlations among the dependent and independent variables. To be more specific:



    Where r_{xy} is the vector containing the pairwise correlations between the dependent variable Y and each predictor X and \beta is the vector containing the regression coefficients. Since endogeneity biases correlations and regression coefficients I can't see how it wouldn't negatively affect R2, with the exception of the extremely contrived cases where for some reason the biases are just going in the exact opposite directions for the exact amount so that they end up cancelling out.
    for all your psychometric needs! https://psychometroscar.wordpress.com/about/

+ Reply to Thread

           




Tags for this Thread

Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts






Advertise on Talk Stats