I am working on determinants of corporate cash holdings with a panel dataset of ~700 firms across 16 years. Having gone through related literature, Roodman (2009), content on internet and posts on Statalist etc., I have developed the following model using xtabond2 for finding factors that influence cash holdings.
Code:
xtabond2 CashHoldings1 L.CashHoldings1 Size1 Leverage1 Liquidity1 Profitability4 GrowthPotential2 OperatingCashflow Dividend2 CapitalExpenditure1 CashFlowVol15years WPromoterSharesin1 i.Year, twostep small robust cluster(CompanyID) orthogonal artests(2) gmm(L.CashHoldings1, lag(2 2) eq(d)) gmm(Leverage1 Liquidity1 GrowthPotential2 Dividend2 CapitalExpenditure1, lag(2 5) eq(d) collapse) iv(Size1 Profitability4 WPromoterSharesin1 CashFlowVol15years OperatingCashflow i.Year, eq(l))
Code:
Dynamic panel-data estimation, two-step system GMM
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Group variable: CompanyID Number of obs = 6991
Time variable : Year Number of groups = 671
Number of instruments = 53 Obs per group: min = 1
F(27, 670) = 173.51 avg = 10.42
Prob > F = 0.000 max = 15
(Std. Err. adjusted for clustering on CompanyID)
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| Corrected
CashHoldings1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
------------------------+----------------------------------------------------------------
CashHoldings1 |
L1. | .5456747 .0595597 9.16 0.000 .4287286 .6626207
|
Size1 | -.0016775 .0008491 -1.98 0.049 -.0033447 -.0000103
Leverage1 | .0217131 .0190564 1.14 0.255 -.0157043 .0591306
Liquidity1 | -.0248853 .0120496 -2.07 0.039 -.0485448 -.0012257
Profitability4 | .1125777 .0334868 3.36 0.001 .046826 .1783294
GrowthPotential2TobinsQ | -.0092466 .0050835 -1.82 0.069 -.0192282 .0007349
OperatingCashflow | .073043 .0137996 5.29 0.000 .0459473 .1001386
Dividend2 | -.0210518 .0327112 -0.64 0.520 -.0852806 .0431771
CapitalExpenditure1 | -.1112026 .0363169 -3.06 0.002 -.1825111 -.039894
CashFlowVol15years | .135721 .0454753 2.98 0.003 .0464297 .2250123
WPromoterSharesin1 | -.0124934 .0049304 -2.53 0.012 -.0221743 -.0028125
|
Year |
2001 | 0 (empty)
2002 | .0419119 .0326967 1.28 0.200 -.0222884 .1061122
2003 | .0433601 .0324212 1.34 0.182 -.0202994 .1070196
2004 | .0472348 .0324283 1.46 0.146 -.0164385 .1109082
2005 | .0527746 .0326891 1.61 0.107 -.0114108 .11696
2006 | .0579921 .0328381 1.77 0.078 -.0064859 .1224701
2007 | .0584495 .0329269 1.78 0.076 -.0062029 .1231018
2008 | .0486299 .032612 1.49 0.136 -.0154041 .1126639
2009 | .0518934 .032595 1.59 0.112 -.0121073 .115894
2010 | .0532916 .0322942 1.65 0.099 -.0101183 .1167016
2011 | .0455951 .030552 1.49 0.136 -.014394 .1055842
2012 | .0459586 .031354 1.47 0.143 -.0156054 .1075225
2013 | .0408918 .0296378 1.38 0.168 -.0173024 .0990859
2014 | .0441315 .0301533 1.46 0.144 -.0150748 .1033378
2015 | .0482326 .0313953 1.54 0.125 -.0134124 .1098777
2016 | .0482783 .0322953 1.49 0.135 -.0151339 .1116905
|
_cons | 0 (omitted)
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Instruments for orthogonal deviations equation
GMM-type (missing=0, separate instruments for each period unless collapsed)
L(2/5).(Leverage1 Liquidity1 GrowthPotential2TobinsQ Dividend2
CapitalExpenditure1) collapsed
L2.L.CashHoldings1
Instruments for levels equation
Standard
Size1 Profitability4 WPromoterSharesin1 CashFlowVol15years
OperatingCashflow 2001b.Year 2002.Year 2003.Year 2004.Year 2005.Year
2006.Year 2007.Year 2008.Year 2009.Year 2010.Year 2011.Year 2012.Year
2013.Year 2014.Year 2015.Year 2016.Year
_cons
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Arellano-Bond test for AR(1) in first differences: z = -7.88 Pr > z = 0.000
Arellano-Bond test for AR(2) in first differences: z = 1.40 Pr > z = 0.161
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Sargan test of overid. restrictions: chi2(25) = 49.40 Prob > chi2 = 0.003
(Not robust, but not weakened by many instruments.)
Hansen test of overid. restrictions: chi2(25) = 32.88 Prob > chi2 = 0.134
(Robust, but weakened by many instruments.)
Difference-in-Hansen tests of exogeneity of instrument subsets:
gmm(L.CashHoldings1, eq(diff) lag(2 2))
Hansen test excluding group: chi2(12) = 13.17 Prob > chi2 = 0.357
Difference (null H = exogenous): chi2(13) = 19.71 Prob > chi2 = 0.103
gmm(Leverage1 Liquidity1 GrowthPotential2TobinsQ Dividend2 CapitalExpenditure1, collapse eq(diff) lag
> (2 5))
Hansen test excluding group: chi2(5) = 8.40 Prob > chi2 = 0.136
Difference (null H = exogenous): chi2(20) = 24.48 Prob > chi2 = 0.222
iv(Size1 Profitability4 WPromoterSharesin1 CashFlowVol15years OperatingCashflow 2001b.Year 2002.Year
> 2003.Year 2004.Year 2005.Year 2006.Year 2007.Year 2008.Year 2009.Year 2010.Year 2011.Year 2012.Year 2
> 013.Year 2014.Year 2015.Year 2016.Year, eq(level))
Hansen test excluding group: chi2(6) = 6.29 Prob > chi2 = 0.391
Difference (null H = exogenous): chi2(19) = 26.59 Prob > chi2 = 0.115
1. Is it fine to provide the lag range for lagged dependent variable as (2 2) and for endogenous variables (gmm style) as (2 5)? I ask this because I have arrived at these lag ranges after a lot of experimentation to ensure AR(2) and Hansen tests are within acceptable limits.
2. Are the results of all Hansen/Sargan tests reported in this output within acceptable limits? I ask this because Roodman (2009) mentions that one should look out for p values of Hansen tests close to 0.25. Moreover, I would also like to know the range for which p values of Hansen tests are deemed ideal.
3. Does the overall output of the model seem statistically valid? Specifically, is the instrument count within acceptable limits? Are the results for time dummies correct with reference to the bug in xtabond2 which omits/drops time dummies?
Help regarding the abovementioned issues is highly appreciated. Thanks!
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