I'm working on an unbalanced panel data from 2004 to 2015, I'm using two-step System Generalized Method of Moments (GMM) estimation (Blundell and Bond's (1998)). I use lagged variables by one year for all my variables except the year and country dummies. the majority of estimations results coefficients are insignificant. I would like to know if that happen because of the min number of observations per groups or there are other reasons?
Thanks
here is my model and estimation results :
Code:
xtabond2 Equity_w lEquity_w lLogTA_w lLLP_w lR_funding_w lLiquidity_R_w lF_Assets_w lNNI_w lLoans_w lCIRR_w lROA_w i.dcountry i.year if dum_unco==1 & estima
> ted==1 , ///
> gmmstyle(lEquity_w, laglimits(2 .) orthogonal ) ///
> ivstyle(lLogTA_w lLLP_w lR_funding_w lLiquidity_R_w lF_Assets_w lNNI_w lLoans_w lCIRR_w lROA_w i.dcountry i.year ) ///
> twostep robust orthogonal
Favoring space over speed. To switch, type or click on mata: mata set matafavor speed, perm.
Warning: Two-step estimated covariance matrix of moments is singular.
Using a generalized inverse to calculate optimal weighting matrix for two-step estimation.
Difference-in-Sargan/Hansen statistics may be negative.
Dynamic panel-data estimation, two-step system GMM
------------------------------------------------------------------------------
Group variable: index Number of obs = 992
Time variable : year Number of groups = 371
Number of instruments = 63 Obs per group: min = 1
Wald chi2(37) = 3663.52 avg = 2.67
Prob > chi2 = 0.000 max = 7
--------------------------------------------------------------------------------
| Corrected
Equity_w | Coef. Std. Err. z P>|z| [95% Conf. Interval]
---------------+----------------------------------------------------------------
lEquity_w | 1.018779 .1125574 9.05 0.000 .7981704 1.239387
lLogTA_w | -.0010497 .0018253 -0.58 0.565 -.0046273 .0025278
lLLP_w | -.0230238 .1218676 -0.19 0.850 -.2618798 .2158323
lR_funding_w | -.0134484 .0059798 -2.25 0.025 -.0251687 -.0017281
lLiquidity_R_w | -.0029254 .0031748 -0.92 0.357 -.0091478 .003297
lF_Assets_w | -.0598307 .0990781 -0.60 0.546 -.2540202 .1343589
lNNI_w | -.003395 .0053708 -0.63 0.527 -.0139217 .0071316
lLoans_w | -.0070741 .0061623 -1.15 0.251 -.0191521 .0050038
lCIRR_w | -.0078305 .0077993 -1.00 0.315 -.0231169 .0074558
lROA_w | -.2553723 .3162681 -0.81 0.419 -.8752464 .3645018
|
dcountry |
0 | 0 (empty)
1 | -.0073125 .0070432 -1.04 0.299 -.0211169 .0064918
3 | -.0050764 .0059401 -0.85 0.393 -.0167188 .006566
4 | -.0091926 .0074593 -1.23 0.218 -.0238125 .0054273
5 | -.0074848 .0060023 -1.25 0.212 -.019249 .0042795
6 | -.0080595 .0059476 -1.36 0.175 -.0197165 .0035976
7 | -.0033882 .0070647 -0.48 0.632 -.0172348 .0104584
9 | -.0090639 .0058458 -1.55 0.121 -.0205214 .0023936
10 | -.0072724 .0081215 -0.90 0.371 -.0231903 .0086455
12 | -.0052087 .0070388 -0.74 0.459 -.0190045 .0085871
13 | -.0077503 .0098533 -0.79 0.432 -.0270624 .0115618
14 | -.0116339 .0069059 -1.68 0.092 -.0251692 .0019015
15 | -.003701 .0064939 -0.57 0.569 -.0164288 .0090267
16 | -.0012636 .0067079 -0.19 0.851 -.0144107 .0118836
17 | -.0180223 .0100687 -1.79 0.073 -.0377565 .0017119
|
year |
2004 | 0 (empty)
2005 | .008281 .0054798 1.51 0.131 -.0024593 .0190212
2006 | .0003877 .0047867 0.08 0.935 -.0089941 .0097695
2007 | .0007485 .005015 0.15 0.881 -.0090807 .0105776
2008 | .0028752 .0050967 0.56 0.573 -.0071142 .0128645
2009 | .0088131 .0052229 1.69 0.092 -.0014236 .0190497
2010 | .0052882 .0049749 1.06 0.288 -.0044624 .0150388
2011 | .0004021 .0050771 0.08 0.937 -.0095489 .010353
2012 | 0 (omitted)
2013 | .0038661 .0063802 0.61 0.545 -.0086388 .0163711
2014 | .0036385 .0053812 0.68 0.499 -.0069084 .0141854
2015 | .0092108 .006609 1.39 0.163 -.0037427 .0221643
|
_cons | .042304 .0401726 1.05 0.292 -.0364328 .1210408
--------------------------------------------------------------------------------
Instruments for orthogonal deviations equation
Standard
FOD.(lLogTA_w lLLP_w lR_funding_w lLiquidity_R_w lF_Assets_w lNNI_w
lLoans_w lCIRR_w lROA_w 0b.dcountry 1.dcountry 3.dcountry 4.dcountry
5.dcountry 6.dcountry 7.dcountry 9.dcountry 10.dcountry 12.dcountry
13.dcountry 14.dcountry 15.dcountry 16.dcountry 17.dcountry 2004b.year
2005.year 2006.year 2007.year 2008.year 2009.year 2010.year 2011.year
2012.year 2013.year 2014.year 2015.year)
GMM-type (missing=0, separate instruments for each period unless collapsed)
BOD.L(2/11).lEquity_w
Instruments for levels equation
Standard
lLogTA_w lLLP_w lR_funding_w lLiquidity_R_w lF_Assets_w lNNI_w lLoans_w
lCIRR_w lROA_w 0b.dcountry 1.dcountry 3.dcountry 4.dcountry 5.dcountry
6.dcountry 7.dcountry 9.dcountry 10.dcountry 12.dcountry 13.dcountry
14.dcountry 15.dcountry 16.dcountry 17.dcountry 2004b.year 2005.year
2006.year 2007.year 2008.year 2009.year 2010.year 2011.year 2012.year
2013.year 2014.year 2015.year
_cons
GMM-type (missing=0, separate instruments for each period unless collapsed)
DL.lEquity_w
------------------------------------------------------------------------------
Arellano-Bond test for AR(1) in first differences: z = -2.02 Pr > z = 0.043
Arellano-Bond test for AR(2) in first differences: z = -1.69 Pr > z = 0.092
------------------------------------------------------------------------------
Sargan test of overid. restrictions: chi2(25) = 49.27 Prob > chi2 = 0.003
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(25) = 32.85 Prob > chi2 = 0.135
(Robust, but weakened by many instruments.)
Difference-in-Hansen tests of exogeneity of instrument subsets:
GMM instruments for levels
Hansen test excluding group: chi2(19) = 30.25 Prob > chi2 = 0.049
Difference (null H = exogenous): chi2(6) = 2.60 Prob > chi2 = 0.857
0 Response to min number of observations per groups (xtabond2)
Post a Comment