Table 7

Robustness test using entropy balancing - The effects of politically-connected boards (PCBs) on over-(under-)investment in labor (OVER_LAB or UNDER_LAB)

OVER_LABUNDER_LAB
Coefficientt-valuesCoefficientt-values
#1#2#3#4
PCBsit−0.046***(−5.14)0.002(1.47)
TOP5it−0.015(−0.61)0.009**(2.36)
LEVit−0.106***(−4.07)0.007*(1.86)
ROAit−0.404***(−5.21)−0.010(−0.97)
DPRit−0.028**(−2.47)−0.003(−1.59)
TANGit0.084***(5.45)−0.006***(−3.89)
OPER_CCit0.027***(4.83)−0.004***(−3.53)
Qit0.012**(2.53)0.001(1.22)
Constant0.255***(4.83)0.096***(12.69)
Observations1,439 1,017 
F14.5*** 28.6*** 
R20.280 0.431 

Note(s): Entropy balancing regression model. Over-(under)investment in labor (OVER_LABit or UNDER_LABit) in firm i occurs when the ratio of the number of employees at the end of financial year t to the annual sales of firm i during year t is greater (lower) than the ratio of the total number of employees of all firms in the same industry sector in year t to the total annual sales for all firms in the same industry sector in year t. In the sub-sample of over-investment in labor, a higher (lower) positive number indicates a higher (lower) over-investment in labor. For ease of interpretation, the negative signs of the sub-sample for under-investment in labor are multiplied by −1 to obtain a positive number. Hence, a higher (lower) positive number indicates a higher (lower) under-investment in labor. The presence of PCBsit is a dummy variable set to 1 if firm i in year t has politically-connected board member(s) and zero (0) otherwise. Columns 1 and 2 report the OVER_LAB regression coefficients and t-values in parentheses, columns 3–4 report the UNDER_LAB regression coefficients and t-values in parentheses. *, **, and *** indicate statistical significance at the 10, 5 and 1% levels, respectively (two-tailed). The definitions of variables are presented in  Appendix

Source(s): Table 7 by authors

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