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Tobit Regression with unbalanced Panel Data

Thank you for your answers.

I have just replaced pdata.frame with plm.data and it worked.

tobit1<- plm.data(T1, index = c("firm", "year"))

But I have two more questions, maybe someone could help:

summary(Tob)

Call:
censReg(formula = Imp ~ Bath + CEOTurnover + ChangeOCF + E +
    Sales + ROE + GTA + Size, data = tobit1, method = "BHHH")

Observations:
         Total  Left-censored     Uncensored Right-censored
           606            469            137              0

Coefficients:
              Estimate Std. error    t value  Pr(> t)
(Intercept)  1.110e-03  5.648e-04      1.965   0.0494 *
Bath         7.442e-03  6.780e-03      1.098   0.2724
CEOTurnover -1.500e-03  2.742e-04     -5.472 4.45e-08 ***
ChangeOCF   -6.738e-03  1.272e-03     -5.297 1.18e-07 ***
E           -5.515e-02  5.304e-03    -10.398  < 2e-16 ***
Sales        8.009e-03  3.487e-04     22.971  < 2e-16 ***
ROE          2.921e-03  5.896e-06    495.331  < 2e-16 ***
GTA         -3.509e-03  1.174e-03     -2.989   0.0028 **
Size        -5.688e-04  1.220e-04     -4.662 3.13e-06 ***
logSigma    -5.401e+00  2.746e-04 -19668.028  < 2e-16 ***
---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

BHHH maximisation, 150 iterations
Return code 4: Iteration limit exceeded.
Log-likelihood: -66915.77 on 10 Df

How can I calculate McFadden's adjusted  R2 in R?
How could I reduce iteration?

Thank you,
Vanessa



2017-01-04 13:25 GMT+01:00 PIKAL Petr <petr.pikal at precheza.cz>: