In the following system GMM model based on a panel dataset of 1696 firms across 16 years, I am interested in calculating the ultimate coefficient for lagged cash holdings (CashHoldings1) and promoter.ownership (WPromoterS).
Code:
xtdpdgmm CashHoldings1 L.CashHoldings1 Size1 Leverage1 WPromoterS c.WPromoterS#c.L.CashHoldings1, gmmiv(L.CashHoldings1, lag(1 4) model(fodev)) gmmiv(Leverage1 c.WPromoterS#c.L.CashHoldings1, lag(1 7) collapse model(fodev)) iv(Size1 WPromoterS, model(level)) teffects twostep vce(cluster CompanyID) nofootnote
Code:
Generalized method of moments estimation Fitting full model: Step 1 f(b) = .00033582 Step 2 f(b) = .06917731 Group variable: CompanyID Number of obs = 21705 Time variable: Year Number of groups = 1676 Moment conditions: linear = 77 Obs per group: min = 1 nonlinear = 0 avg = 12.95048 total = 77 max = 15 (Std. Err. adjusted for 1,676 clusters in CompanyID) --------------------------------------------------------------------------------------- | WC-Robust CashHoldings1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] ----------------------+---------------------------------------------------------------- CashHoldings1 | L1. | .970056 .2444395 3.97 0.000 .4909633 1.449149 | Size1 | -.000663 .0003608 -1.84 0.066 -.0013701 .0000442 Leverage1 | -.029561 .0094004 -3.14 0.002 -.0479854 -.0111365 WPromoterSharesin1 | .0359299 .0162391 2.21 0.027 .0041019 .067758 | c.WPromoterSharesin1#| cL.CashHoldings1 | -.9789452 .4334874 -2.26 0.024 -1.828565 -.1293254 |
1. I am aware that calculation of coefficient of promoter ownership can be calculated for a certain level of lagged cash holdings (say, 0.04) in this way: .0359299 -.9789452*(0.04) = -0.003227908. However, I would like to know a convenient and short way of calculating the t-statistic for this calculated coefficient (specially considering that this is a system GMM regression on an unbalanced panel dataset).
2. Following general practice, I plug in the mean value of lagged cash holdings (i.e. 0.04) in the above calculation. I would like to know if there is another standard practice regarding this. Is there any other alternative than the mean value?
Thanks!
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