Table 7: Climate change exposure and the...

Table 7:

Climate change exposure and the costs of high leverage: High-tech vs. manufacturing and retail industries.

Panel A
	High-tech Industry		Manufacturing and Retail Industries
	(1)	(2)	(3)	(4)
CCEXPOt-2 × HLEVt-2	-0.0313* (-1.82)	-0.0324* (-1.79)	-0.0131^*** (-2.93)	-0.0130^*** (-2.92)
CCEXPOt-2	0.0093 (1.14)	0.0098 (1.22)	0.0048 (1.50)	0.0048 (1.49)
CSRt-2 × HLEVt-2		0.0013 (0.22)		0.0053 (1.38)
CSRt-2		-0.0101^*** (-2.93)		-0.0063^** (-2.27)
HLEV t-2	-0.0124 (-1.34)	-0.0124 (-1.31)	-0.0171^*** (-2.61)	-0.0172^*** (-2.61)
SIZEt	0.0387*** (3.69)	0.0399^*** (3.80)	0.0426^*** (4.43)	0.0427^*** (4.45)
COMPETITIONt	0.0735 (0.23)	0.0998 (0.32)	0.1029 (0.50)	0.1133 (0.55)
PROFITt-1	-0.1202^*** (-2.62)	-0.1216^*** (-2.64)	-0.0088 (-0.20)	-0.0102 (-0.23)
PROFITt-2	-0.0377 (-0.90)	-0.0389 (-0.92)	-0.1308^*** (-2.64)	-0.1314^*** (-2.66)
INVESTMENTt_-1	-0.2358^* (-1.86)	-0.2451^* (-1.95)	0.0861 (0.74)	0.0859 (0.74)
INVESTMENTt-2	0.0468 (0.35)	0.0435 (0.33)	-0.1304 (-1.19)	-0.1313 (-1.19)
SELLEXPt-1	0.0529 (1.24)	0.0528 (1.24)	0.0350 (0.85)	0.0352 (0.85)
SELLEXPt-2	0.0127 (0.36)	0.0126 (0.35)	0.0513 (1.02)	0.0511 (1.02)
COGSt-1	-0.4211^*** (-7.14)	-0.4218^*** (-7.10)	-0.3956*** (-9.97)	-0.3966^*** (-10.01)
COGSt-2	0.2387^*** (4.34)	0.2355^*** (4.28)	0.2260^*** (5.65)	0.2244^*** (5.62)
PENALTYt-1	-0.0019^*** (-2.60)	-0.0019^*** (-2.69)	-0.0001 (-0.29)	-0.0001 (-0.33)
PENALTYt-2	-0.0014^** (-1.99)	-0.0014^** (-1.98)	-0.0007 (-1.61)	-0.0007 (-1.59)
CONSTANT	-0.0910 (-0.54)	-0.1170 (-0.70)	-0.4329^*** (-3.66)	-0.4382^*** (-3.72)
N	6,830	6,830	8,342	8,342
R-squared	9.14%	9.31%	21.25%	21.31%
Firm F.E.	Y	Y	Y	Y
Year × Industry F.E.	Y	Y	Y	Y

Panel A
	High-tech Industry		Manufacturing and Retail Industries
	(1)	(2)	(3)	(4)
CCEXPOt-2 × HLEVt-2	-0.0313*(-1.82)	-0.0324*(-1.79)	-0.0131^***(-2.93)	-0.0130^***(-2.92)
CCEXPOt-2	0.0093(1.14)	0.0098(1.22)	0.0048(1.50)	0.0048(1.49)
CSRt-2 × HLEVt-2		0.0013(0.22)		0.0053(1.38)
CSRt-2		-0.0101^***(-2.93)		-0.0063^**(-2.27)
HLEV t-2	-0.0124(-1.34)	-0.0124(-1.31)	-0.0171^***(-2.61)	-0.0172^***(-2.61)
SIZEt	0.0387***(3.69)	0.0399^***(3.80)	0.0426^***(4.43)	0.0427^***(4.45)
COMPETITIONt	0.0735(0.23)	0.0998(0.32)	0.1029(0.50)	0.1133(0.55)
PROFITt-1	-0.1202^***(-2.62)	-0.1216^***(-2.64)	-0.0088(-0.20)	-0.0102(-0.23)
PROFITt-2	-0.0377(-0.90)	-0.0389(-0.92)	-0.1308^***(-2.64)	-0.1314^***(-2.66)
INVESTMENTt_-1	-0.2358^*(-1.86)	-0.2451^*(-1.95)	0.0861(0.74)	0.0859(0.74)
INVESTMENTt-2	0.0468(0.35)	0.0435(0.33)	-0.1304(-1.19)	-0.1313(-1.19)
SELLEXPt-1	0.0529(1.24)	0.0528(1.24)	0.0350(0.85)	0.0352(0.85)
SELLEXPt-2	0.0127(0.36)	0.0126(0.35)	0.0513(1.02)	0.0511(1.02)
COGSt-1	-0.4211^***(-7.14)	-0.4218^***(-7.10)	-0.3956***(-9.97)	-0.3966^***(-10.01)
COGSt-2	0.2387^***(4.34)	0.2355^***(4.28)	0.2260^***(5.65)	0.2244^***(5.62)
PENALTYt-1	-0.0019^***(-2.60)	-0.0019^***(-2.69)	-0.0001(-0.29)	-0.0001(-0.33)
PENALTYt-2	-0.0014^**(-1.99)	-0.0014^**(-1.98)	-0.0007(-1.61)	-0.0007(-1.59)
CONSTANT	-0.0910(-0.54)	-0.1170(-0.70)	-0.4329^***(-3.66)	-0.4382^***(-3.72)
N	6,830	6,830	8,342	8,342
R-squared	9.14%	9.31%	21.25%	21.31%
Firm F.E.	Y	Y	Y	Y
Year × Industry F.E.	Y	Y	Y	Y

Panel B
	High-tech Industry		Manufacturing and Retail Industries
	(1)	(2)	(3)	(4)
REGEXPOt-2 × HLEVt-2	-0.0302^* (-1.78)		-0.0123^** (-2.37)
REGEXPOt-2	0.0109 (1.11)		0.0057^* (1.82)
PHYEXPOt-2 × HLEVt-2		-0.0053 (-1.62)		-0.0230^* (-1.86)
PHYEXPOt-2		0.0031 (0.62)		0.0009 (0.28)
CSRt-2 x HLEVt-2	0.0022 (0.36)	0.0024 (0.40)	0.0028 (0.77)	0.0030 (0.81)
CSRt-2	-0.0101^*** (-2.90)	-0.0100^*** ( -2.87)	-0.0044^* (-1.65)	-0.0045^* (-1.70)
HLEVt-2	-0.0138 (-1.43)	-0.0144 (-1.48)	-0.0205^*** (-3.17)	-0.0198^*** (-3.05)
SIZE_t	0.0411^*** (3.84)	0.0408*** (3.82)	0.0538^*** (5.42)	0.0542^*** (5.45)
COMPETITIONt	0.1048 (0.33)	0.1066 (0.34)	0.1017 (0.49)	0.1027 (0.49)
PROFITt-1	-0.1245^*** (-2.68)	-0.1244^*** (-2.68)	-0.0053 (-0.12)	-0.0068 (-0.16)
PROFITt-2	-0.0473 (-1.08)	-0.0469 (-1.07)	-0.1500^*** (-3.16)	-0.1509^*** (-3.16)
INVESTMENTt-1	-0.2419^* (-1.90)	-0.2407^* (-1.89)	0.1003 (0.85)	0.1037 (0.89)
INVESTMENTt_-2	0.0518 (0.38)	0.0516 (0.38)	-0.1526 (-1.40)	-0.1470 (-1.34)
SELLEXPt-1	0.0539 (1.29)	0.0539 (1.29)	0.0399 (1.02)	0.0375 (0.97)
SELLEXPt-2	0.0066 (0.19)	0.0067 (0.19)	0.0396 (0.91)	0.0402 (0.91)
COGSt-1	-0.4304^*** (-7.10)	-0.4299*** (-7.11)	-0.4046^*** (-10.55)	-0.4019^*** (-10.49)
COGSt-2	0.2371^*** (4.24)	0.2369^*** (4.24)	0.2354^*** (6.07)	0.2358^*** (6.08)
PENALTYt-1	-0.0021^*** (-2.94)	-0.0021^*** (-2.91)	0.0001 (0.16)	0.0001 (0.16)
PENALTYt-2	-0.0013^* (-1.90)	-0.0013^* (-1.90)	-0.0008^* (-1.78)	-0.0008^* (-1.78)
CONSTANT	-0.0856 (-0.52)	-0.0833 (-0.51)	-0.2183^* (-1.76)	-0.2195^* (-1.77)
Observations	6,694	6,694	8,968	8,968
R-squared	9.10%	9.07%	20.15%	20.12%
Firm F.E.	Y	Y	Y	Y
Year × Industry F.E.	Y	Y	Y	Y

Panel B
	High-tech Industry		Manufacturing and Retail Industries
	(1)	(2)	(3)	(4)
REGEXPOt-2 × HLEVt-2	-0.0302^*(-1.78)		-0.0123^**(-2.37)
REGEXPOt-2	0.0109(1.11)		0.0057^*(1.82)
PHYEXPOt-2 × HLEVt-2		-0.0053(-1.62)		-0.0230^*(-1.86)
PHYEXPOt-2		0.0031(0.62)		0.0009(0.28)
CSRt-2 x HLEVt-2	0.0022(0.36)	0.0024(0.40)	0.0028(0.77)	0.0030(0.81)
CSRt-2	-0.0101^***(-2.90)	-0.0100^***( -2.87)	-0.0044^*(-1.65)	-0.0045^*(-1.70)
HLEVt-2	-0.0138(-1.43)	-0.0144(-1.48)	-0.0205^***(-3.17)	-0.0198^***(-3.05)
SIZE_t	0.0411^***(3.84)	0.0408***(3.82)	0.0538^***(5.42)	0.0542^***(5.45)
COMPETITIONt	0.1048(0.33)	0.1066(0.34)	0.1017(0.49)	0.1027(0.49)
PROFITt-1	-0.1245^***(-2.68)	-0.1244^***(-2.68)	-0.0053(-0.12)	-0.0068(-0.16)
PROFITt-2	-0.0473(-1.08)	-0.0469(-1.07)	-0.1500^***(-3.16)	-0.1509^***(-3.16)
INVESTMENTt-1	-0.2419^*(-1.90)	-0.2407^*(-1.89)	0.1003(0.85)	0.1037(0.89)
INVESTMENTt_-2	0.0518(0.38)	0.0516(0.38)	-0.1526(-1.40)	-0.1470(-1.34)
SELLEXPt-1	0.0539(1.29)	0.0539(1.29)	0.0399(1.02)	0.0375(0.97)
SELLEXPt-2	0.0066(0.19)	0.0067(0.19)	0.0396(0.91)	0.0402(0.91)
COGSt-1	-0.4304^***(-7.10)	-0.4299***(-7.11)	-0.4046^***(-10.55)	-0.4019^***(-10.49)
COGSt-2	0.2371^***(4.24)	0.2369^***(4.24)	0.2354^***(6.07)	0.2358^***(6.08)
PENALTYt-1	-0.0021^***(-2.94)	-0.0021^***(-2.91)	0.0001(0.16)	0.0001(0.16)
PENALTYt-2	-0.0013^*(-1.90)	-0.0013^*(-1.90)	-0.0008^*(-1.78)	-0.0008^*(-1.78)
CONSTANT	-0.0856(-0.52)	-0.0833(-0.51)	-0.2183^*(-1.76)	-0.2195^*(-1.77)
Observations	6,694	6,694	8,968	8,968
R-squared	9.10%	9.07%	20.15%	20.12%
Firm F.E.	Y	Y	Y	Y
Year × Industry F.E.	Y	Y	Y	Y

Note: Panel A reports the results of the effect of climate exposure on high leverage costs in different business sectors. Models 1 and 2 report regression results for a sample of firms in the high-tech sector; Models 3 and 4 report regression results for a sample in the manufacturing and retail sectors. Following Kile and Phillips (2009), we identify high-tech sectors with 3-digit SIC codes 283, 357, 366, 367, 382, 384, 481, 482, 489, 737, and 873. Following Ho et al. (2005) and McGurr and DeVaney (1998), we identify manufacturing sectors with 2-digit SIC codes ranging from 20 to 39 (excluding firms classified as high-tech industries), and retail sectors with 4-digit SIC codes ranging from 5200 to 5999. The main variable of interest is the interaction term between industry-adjusted climate change exposure (CCEXPO) and a dummy variable that equals 1 if, in that year, the firm’s long-term debt-to-assets ratio ranks in the top three deciles of the overall sample (HLEV). Panel B reports the results of the effect of regulatory climate exposure or physical climate exposure on high leverage costs in different business sectors, respectively. Models 1 and 2 report the regression results for a sample of firms in the high-tech sector; Models 3 and 4 report the regression results for a sample in the manufacturing and retail sectors. The dependent variable is industry-adjusted sales growth (SALES_G). The main variables of interest in Models 1 and 3 are the interaction term between industry-adjusted regulatory exposure (REGEXPO) and a dummy variable that equals 1 if, in that year, the firm’s long-term debt-to-assets ratio ranks in the top three deciles of the overall sample (HLEV). The main variables of interest in Models 1 and 3 are the interaction term between industry-adjusted physical exposure (PHYEXPO) and a dummy variable that equals 1 if, in that year, the firm’s long-term debt-to-assets ratio ranks in the top three deciles of the overall sample (HLEV). Additional variable definitions are in the Appendix. All control variables are adjusted to their industry-year means and are winsorized at the 1st and 99th percentiles. Further, we require that each industry-year contains at least four firms to be qualified in the analysis so that the industry-year mean is not biased toward outliers. The sample period is 2004—2020. The t-statistics based on heteroskedasticity-robust standard errors and clustered at the firm level are reported in parentheses. Asterisks denote statistical significance at the 1% (***), 5% (**), or 10% (*) level.

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