Table 5

Effect of GPR, CGI and its interaction on investment inefficiency, overinvestment, and underinvestment

Investment inefficiencyOverinvestmentUnderinvestment
VariablesModel 1Model 2Model 3
GPR × CGI−0.0025***−0.0052**−0.0005**
(0.001)(0.003)(0.000)
GPR0.0155**0.02380.0127***
(0.007)(0.019)(0.005)
CGI−0.0008***−0.0012**−0.0002***
(0.000)(0.001)(0.000)
TANG0.0324**0.0595***−0.0210***
(0.015)(0.021)(0.003)
SIZE−0.0056***−0.0147***−0.0016***
(0.002)(0.004)(0.000)
ROA−0.0712−0.1953*−0.0384***
(0.070)(0.116)(0.008)
LEVE0.01310.01890.0172***
(0.015)(0.027)(0.003)
CASH0.0558***0.1772***0.0026
(0.017)(0.034)(0.005)
SLACK0.0002−0.00240.0018***
(0.001)(0.003)(0.000)
Ln_OC−0.0040−0.0104*0.0015
(0.003)(0.006)(0.001)
ROE0.0026−0.0421−0.0003
(0.003)(0.042)(0.001)
CFO−0.0498−0.1108*0.0030
(0.045)(0.065)(0.004)
Ln_Age−0.0139***−0.0306***−0.0017*
(0.005)(0.009)(0.001)
TOBINSQ0.00470.0129*−0.0009**
(0.004)(0.007)(0.000)
GDP_GRO0.0007**0.00090.0442***
(0.000)(0.001)(0.009)
Intercept0.2998***0.6382***0.0080
(0.088)(0.178)(0.021)
Industry FEYESYESYES
Year FEYESYESYES
Observations6,4642,1134,351
Adj. R20.05790.13330.1274

Note(s): All models employing pooled panel OLS estimation. Robust standard errors in brackets are clustered by firm and year to address serial correlation and heteroskedasticity. The measurement of the variables is in  Appendix Table A1. *, **, and *** indicate significance levels of 10%, 5%, and 1%, respectively

Source(s): Authors own work
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