Table 2

Financial reporting quality and corporate hedging activities

[1][2][3][4]
EQ10.077***   
(5.16)   
EQ2 0.153***  
 (5.22)  
EQ3  0.039*** 
  (3.37) 
EQ4   0.051***
   (4.66)
logasset0.054***0.057***0.054***0.054***
(33.34)(31.60)(33.04)(33.25)
booklev0.097***0.101***0.093***0.093***
(9.48)(8.93)(9.65)(9.68)
cash−0.043***−0.039***−0.041***−0.041***
(−5.50)(−4.09)(−5.65)(−5.68)
MB0.001*0.0010.001**0.001*
(1.78)(0.70)(1.97)(1.74)
profit−0.039***−0.037***−0.046***−0.045***
(−4.05)(−3.38)(−5.01)(−4.91)
tangib−0.024**−0.018−0.026**−0.024**
(−2.12)(−1.32)(−2.46)(−2.21)
RDdummy−0.017***−0.021***−0.016***−0.016***
(−3.42)(−3.46)(−3.35)(−3.38)
RDintens0.051***0.049**0.048***0.049***
(2.89)(2.29)(2.95)(2.99)
Constant0.0470.0630.0580.056
(0.85)(0.94)(1.06)(1.02)
Industry dummyYYYY
Year dummyYYYY
Observations55,05041,43063,04963,049
R-squared0.3330.3370.3300.330

Note(s): This table reports the results on the baseline model. The dependent variable is the hedging intensity proxy constructed based on keyword counting, while the keyword list is from Campello et al. (2011). EQs are the multiple proxies for financial reporting quality, defined by Dechow and Dichev (2002) and Dechow et al. (1995). The higher values in EQs indicate lower financial reporting quality. The model includes industry (based on the Fama and French 48 industry classification) and year fixed effects. t-statistics are reported in parentheses and are based on standard errors adjusted for clustering at the firm and year level. ***, ** and * indicate significance levels of 1, 5 and 10%, respectively

Source(s): The authors

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