Hi -
I have a simple model where I am trying to understand the impact of a firm's geographical diversification (Ln_GSD) on the firm's performance (Ln_EBIT_ROA.) I am using a fixed effect regression model.
I need to run a Pearson residual model for validating goodness of fit. I am not able to get the stata commands for this. Any help would be much appreciated. Thanks in advance!
For your reference, I am sharing the original fe regression below:
I have a simple model where I am trying to understand the impact of a firm's geographical diversification (Ln_GSD) on the firm's performance (Ln_EBIT_ROA.) I am using a fixed effect regression model.
I need to run a Pearson residual model for validating goodness of fit. I am not able to get the stata commands for this. Any help would be much appreciated. Thanks in advance!
For your reference, I am sharing the original fe regression below:
Code:
. xtreg Ln_EBIT_ROA Ln_Revenue Ln_LTD_to_Sales Ln_Intangible_Assets CoAge wGDPpc wCPI wDCF wExpgr w
> GDPgr wCons Ln_PS_RD c.l1.Ln_GSD c.l1.Ln_GSD_Asset if CoAge>=0 & NATION=="UNITED STATES" & NATION
> CODE==840 & FSTS>=10 & FSTS<=100 &GENERALINDUSTRYCLASSIFICATION ==1 & Year_<2020 & Year_<YearInact
> ive & Discr_GS_Rev!=1, fe cluster(n_WSID)
Fixed-effects (within) regression Number of obs = 926
Group variable: n_WSID Number of groups = 188
R-sq: Obs per group:
within = 0.1412 min = 1
between = 0.0050 avg = 4.9
overall = 0.0006 max = 18
F(11,187) = .
corr(u_i, Xb) = -0.8922 Prob > F = .
(Std. Err. adjusted for 188 clusters in n_WSID)
--------------------------------------------------------------------------------------
| Robust
Ln_EBIT_ROA | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
Ln_Revenue | .6213811 .1665789 3.73 0.000 .2927657 .9499965
Ln_LTD_to_Sales | -.1556032 .0594701 -2.62 0.010 -.2729216 -.0382847
Ln_Intangible_Assets | -.1654777 .0597661 -2.77 0.006 -.2833801 -.0475753
CoAge | -.024804 .0129604 -1.91 0.057 -.0503714 .0007634
wGDPpc | .0000398 .0000231 1.72 0.087 -5.77e-06 .0000853
wCPI | -.0217982 .0244759 -0.89 0.374 -.0700825 .0264861
wDCF | 1.53e-13 1.29e-13 1.18 0.238 -1.02e-13 4.08e-13
wExpgr | -.0021509 .0117711 -0.18 0.855 -.025372 .0210702
wGDPgr | .032427 .0352196 0.92 0.358 -.0370519 .1019058
wCons | -2.38e-14 4.52e-14 -0.53 0.598 -1.13e-13 6.53e-14
Ln_PS_RD | -.0598333 .0754722 -0.79 0.429 -.2087198 .0890531
|
Ln_GSD |
L1. | -.513574 .1632796 -3.15 0.002 -.8356807 -.1914673
|
Ln_GSD_Asset |
L1. | -.0604326 .0880181 -0.69 0.493 -.2340687 .1132034
|
_cons | -12.64825 2.90528 -4.35 0.000 -18.37958 -6.916913
---------------------+----------------------------------------------------------------
sigma_u | 1.6031898
sigma_e | .59408415
rho | .87926191 (fraction of variance due to u_i)
--------------------------------------------------------------------------------------
