How do local banks respond to natural disasters?

Figures & data

Figure 1. Summary of natural disasters in the US from 2000 to 2019.

Table 1. Descriptive statistics.

Variable	Obs.	Mean	Std. Dev.	Min	Max
Bank stability
ln_Z1	24,266	4.779	0.951	−4.753	10.427
ln_Z2	25,520	4.707	0.963	−4.753	10.833
EA	24,419	0.112	0.041	−0.129	0.910
ROA	24,712	0.002	0.004	−0.136	0.128
Provision of Loan Asset losses	24,788	0.824	1.194	−6.908	9.257
Volatility of total equity	24,012	3.536	1.889	−3.448	12.559
Volatility of total deposits	23,869	3.410	1.877	−7.254	12.162
Climate risks
Natural disaster	27,504	0.549	0.498	0.000	1.000
CO2 Emissions (1000 tons) (log)	27,210	8.112	1.031	0.693	10.171
Retail gas Consumption (Mcf) (log)	25,514	20.216	0.987	14.777	22.147
Records of hazards	27,494	1.189	1.342	0.000	8.000
Records of severe hazards	27,494	1.089	1.280	0.000	7.000
Total Damage (log)	4,300	10.974	3.088	0.000	23.026
Bank characteristics
Bank age	27460	2.571	0.945	0.000	5.263
Bank size	26013	7.464	1.588	−1.155	15.014
Growth	24731	0.019	0.075	−5.078	7.607
Capital intensity	22491	1.055	1.123	−4.017	9.212
Tier 1 leverage	22597	0.015	0.030	−0.018	1.743
Change of cash	22750	0.002	0.140	−15.047	0.956
Dividend	22712	1.375	1.523	−1.245	9.449
Financial cash flow	22750	0.022	0.141	−0.530	18.985
Investment cash flow	22750	−0.026	0.229	−33.139	1.331
Operating cash flow	20384	2.698	1.880	−5.809	11.653
ΔSpread	31,693	−0.008	0.100	−3.733	1.229
ΔLoan_deposit	32,687	−0.007	0.021	−0.277	0.370
ΔLLP	32,630	0.014	0.138	−2.597	4.266
ΔExpense_ratio	32,882	0.001	0.204	−7.415	7.307
ΔNonInterest_income	32,887	−0.003	0.053	−0.483	0.481
ΔNPL	32,236	0.001	0.002	−0.042	0.036
ΔAllowance_adequacy	33,048	0.774	0.285	0.067	2.802
SGR	32,887	−0.002	0.109	−1.479	0.765
LGR	32,688	0.009	0.039	−0.198	0.936
Macroeconomic variables
House price	20,059	0.008	0.021	−0.053	0.086
GDP growth	26,590	0.004	0.019	−0.137	0.105
Inflation	25,514	4.601	0.095	4.436	4.782
Unemployment	27,504	1.808	0.358	0.693	2.632
Interest rate	26,023	0.531	0.749	0.010	2.400
Governance variables
Female ratio	15,897	0.133	0.102	0.000	0.562
STDEV.Age	15,898	7.612	2.344	0.000	17.800
Busyness	15,898	0.377	0.215	0.000	1.000
Boardsize	15,898	10.962	3.327	1.000	33.000
Network size (log)	15,898	6.456	0.904	2.691	8.887

Notes: This table reports summary statistics for all variables used. All variable descriptions are in Table A1.

Figure 2. Hydrological disasters in the US from 2000 to 2019.

Figure 3. Meteorological disasters in the US from 2000 to 2019.

Figure 4. Geophysical disasters in the US from 2000 to 2019.

Figure 5. Climatic disasters in the US from 2000 to 2019.

Table 2. How do natural disasters affect banking financial stability? (baseline result).

Dependent variable: Ln_Z1
	(1)	(2)	(3)	(4)	(5)
L.ln_Z1	0.495***	0.492***	0.493***	0.505***	0.505***
	(0.014)	(0.014)	(0.015)	(0.015)	(0.016)
L2.ln_Z1	0.370***	0.371***	0.372***	0.362***	0.365***
	(0.017)	(0.017)	(0.016)	(0.019)	(0.020)
Natural hazard	0.000	−0.007	−0.002	−0.003	−0.013
	(0.013)	(0.014)	(0.014)	(0.013)	(0.014)
L.Natural hazard	−0.081**	−0.079**	−0.073**	−0.058**	−0.072***
	(0.027)	(0.026)	(0.023)	(0.018)	(0.018)
L2.Natural hazard	0.069**	0.072**	0.074**	0.051*	0.061*
	(0.023)	(0.023)	(0.022)	(0.020)	(0.024)
Bank age			−0.013*	−0.020*	−0.018*
			(0.006)	(0.008)	(0.008)
Size			0.033***	0.121***	0.119***
			(0.007)	(0.023)	(0.020)
Growth			−0.287**	−0.138	−0.331+
			(0.099)	(0.141)	(0.178)
Capital intensity			−0.052***	−0.027**	−0.023*
			(0.012)	(0.010)	(0.009)
Tier1 leverage				0.102	0.331
				(0.401)	(0.386)
Change of Cash				0.831	1.356+
				(0.830)	(0.733)
Dividend				0.018+	0.028**
				(0.010)	(0.010)
Financial cash flow				−0.959	−0.989
				(0.918)	(0.844)
Investment cash flow				−0.893	−1.355+
				(0.871)	(0.802)
Operating cash flow				−0.103***	−0.105***
				(0.016)	(0.016)
House price					1.123
					(0.747)
GDP growth					−2.742**
					(0.819)
Inflation					0.005
					(0.067)
Unemployment					−0.060+
					(0.034)
Interest rate					−0.247***
					(0.058)
Constant	0.651***	0.395***	0.227*	−0.148	0.023
	(0.055)	(0.067)	(0.093)	(0.180)	(0.335)
Year Fixed Effects	N	Y	Y	Y	Y
Err. clustered by state	Y	Y	Y	Y	Y
Observations	22,364	22,364	19,582	16,854	12,657
R-squared	0.672	0.675	0.681	0.686	0.701

Notes: This table reports the baseline OLS results of how natural disasters affect banking financial stability. L.ln_Z1 and L2.ln_Z1 are lag 1 and lag 2 of ln_Z1, respectively. The same notion goes for natural hazard. All variable descriptions are in Table A1. The corresponding robust standard errors are reported in parentheses. +, *, ** and *** and correspond to the 10%, 5%, 1% and 0.1%, respectively

Table 3. How do natural disasters affect banking financial stability? (IV-GMM results).

Dependent variable: Ln_Z1
	Model 1	Model 2	Model 3
Natural hazard	1.200***	1.020	1.166*
	(0.000)	(0.212)	(0.012)
L.Natural hazard	−1.483+	−2.744	−1.127
	(0.056)	(0.752)	(0.103)
L.ln_Z1	0.393***	0.409*	0.482***
	(0.000)	(0.034)	(0.000)
L2.ln_Z1	0.465***	0.490	0.381***
	(0.000)	(0.152)	(0.000)
Bank age		−0.073	−0.017
		(0.744)	(0.421)
Bank size		0.067	0.100**
		(0.334)	(0.003)
Growth		−0.518	−0.418*
		(0.708)	(0.037)
Capital intensity		0.061	−0.012
		(0.856)	(0.698)
Tier 1 leverage		1.474	0.613
		(0.755)	(0.361)
Change of cash		3.492	2.254*
		(0.661)	(0.042)
Dividend		0.045	0.036*
		(0.363)	(0.012)
Financial cash flow		−4.058	−2.066+
		(0.646)	(0.088)
Investment cash flow		−3.825	−2.238+
		(0.665)	(0.051)
Operating cash flow		−0.065	−0.100***
		(0.512)	(0.000)
House			−5.912*
			(0.028)
GDP growth			−2.331
			(0.218)
Inflation			−0.002
			(0.981)
Unemployment			−0.066
			(0.458)
Interest rate			0.185
			(0.385)
Constant.	0.864	1.368	0.079
	(0.120)	(0.798)	(0.889)
Year Fixed Effects	Y	Y	Y
Err. clustered by state	Y	Y	Y
Observations	21,578	16,402	12,471
R-squared	0.9644	0.9235	0.9706
Hansen test	0.0295	0.8141	0.0677
Endogeneity test	0.0157	0.0100	0.0083

Notes: This table reports the main stage of 2SLS-GMM regression results of the interaction between CO₂ Emissions and natural disasters affect bank stability (The first stage result is reported in Appendix Table A6, see also the IV-GMM version without lag of natural hazard in Table A7). L.ln_Z1 and L2.ln_Z1 are lag 1 and lag 2 of ln_Z1, respectively. The same notion goes for natural hazard. All variable descriptions are in Table A1. The corresponding robust standard errors are re- ported in parentheses. +, *, ** and *** and correspond to the 10%, 5%, 1% and 0.1%, respectively

Table 4. How natural disasters affect banking Z-score through various channels?.

	Dependent variable: Ln_Z1
	Profitability channel				Prudence channel			Growth channel
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
L1.ln_Z1	0.479***	0.503***	0.505***	0.507***	0.505***	0.498***	0.503***	0.506***	0.503***
	(0.021)	(0.016)	(0.016)	(0.015)	(0.015)	(0.016)	(0.016)	(0.015)	(0.016)
L2.ln_Z1	0.392***	0.365***	0.365***	0.364***	0.365***	0.370***	0.364***	0.364***	0.365***
	(0.022)	(0.020)	(0.020)	(0.019)	(0.019)	(0.020)	(0.020)	(0.020)	(0.020)
L1. Natural hazard	−0.049*	−0.061***	−0.061***	−0.061***	−0.063***	−0.061***	−0.093***	−0.060***	−0.067***
	(0.022)	(0.017)	(0.017)	(0.017)	(0.017)	(0.017)	(0.020)	(0.017)	(0.017)
L1. Natural hazard #Spread	−0.076+
	(0.040)
L1. Natural hazard #Loans_Deposits		0.234
		(0.208)
L1. Natural hazard #Noninterest_Income			−0.052
			(0.053)
L1. Natural hazard #Expense_Ratio				0.161***
				(0.028)
L1. Natural hazard #LLP					0.199***
					(0.034)
L1. Natural hazard #N P L						−1.010*
						(0.483)
L1. Natural hazard #Allowance_Adequacy							0.047**
							(0.015)
L1. Natural hazard #SGR								−0.088*
								(0.042)
L1. Natural hazard#LGR									0.331*
									(0.127)
Constant	0.293	0.028	0.037	0.039	0.045	−0.066	0.081	0.050	0.036
	(0.315)	(0.343)	(0.343)	(0.343)	(0.342)	(0.345)	(0.360)	(0.343)	(0.341)
Control variables	Y	Y	Y	Y	Y	Y	Y	Y	Y
Year Fixed Effects	Y	Y	Y	Y	Y	Y	Y	Y	Y
Err. Clustered by state	Y	Y	Y	Y	Y	Y	Y	Y	Y
Observations	8,148	12,589	12,651	12,651	12,515	12,212	12,500	12,644	12,589
R-squared	0.710	0.700	0.700	0.703	0.702	0.699	0.699	0.701	0.700

Notes: This table illustrates the results for channels of which natural disaster affect bank risk. L.ln_Z1 and L2.ln_Z1 are lag 1 and lag 2 of ln_Z1, respectively. The same notion goes for natural hazard. For the definitions of all the control variables and the details of their construction, see Appendix. The corresponding robust standard errors are reported in parentheses. Significance levels are indicated by +, *, ** and *** and correspond to the 10%, 5%, 1% and 0.1% significance levels, respectively.

Table 5. Sub-sample analyses.

	Dependent variable: Ln_Z1
	Frequently exposed to natural hazard		Nonperforming loan		ROE
	Less exposed (1)	More exposed (2)	Less (3)	More (4)	Lower (5)	Higher (6)
L1.ln_Z1	0.518***	0.488***	0.536***	0.481***	0.529***	0.471***
	(0.027)	(0.020)	(0.021)	(0.021)	(0.017)	(0.026)
L2.ln_Z1	0.380***	0.352***	0.333***	0.382***	0.341***	0.385***
	(0.026)	(0.028)	(0.034)	(0.024)	(0.027)	(0.029)
L1. Natural hazard	−0.101***	−0.032	−0.026	−0.084***	−0.031+	−0.099***
	(0.011)	(0.027)	(0.016)	(0.019)	(0.016)	(0.020)
Constant	−0.474	0.309	0.180	0.220	0.003	0.277
	(0.516)	(0.409)	(0.368)	(0.452)	(0.348)	(0.516)
Control variables	Y	Y	Y	Y	Y	Y
Year Fixed Effects	Y	Y	Y	Y	Y	Y
Err. Clustered by state	Y	Y	Y	Y	Y	Y
Observations	6,180	6,477	5,333	7,324	7,219	5,438
R-squared	0.748	0.655	0.708	0.689	0.697	0.688

Notes: This table reports the sub-sample results. L.ln_Z1 and L2.ln_Z1 are lag 1 and lag 2 of ln_Z1, respectively. The same notion goes for natural hazard. All variable descriptions are in Table A1. +, *, ** and *** and correspond to the 10%, 5%, 1% and 0.1%, respectively

Table 6. Which kind of board mitigate better climate risks?

	Dependent variable: Ln_Z1
	(1)	(2)	(3)	(4)	(5)
L.Natural disaster	−0.089**	−0.089**	−0.073*	−0.139**	−0.233**
	(0.028)	(0.032)	(0.032)	(0.047)	(0.066)
Female ratio in board	−0.112
	(0.067)
L.Natural disaster # Female_ratio	0.270*
	(0.113)
STDEV.Age		−0.006*
		(0.002)
L.Natural disaster # STDEV.Age		0.005
		(0.004)
Busyness			−0.064
			(0.038)
L.Natural disaster # Busyness			0.055
			(0.060)
Boardsize				0.002
				(0.002)
L.Natural disaster # Boardsize				0.008*
				(0.003)
Network size					−0.035***
					(0.008)
L.Natural disaster # Network size					0.028**
					(0.010)
Constant	0.321***	0.345***	0.309**	0.340***	0.489***
	(0.086)	(0.093)	(0.091)	(0.087)	(0.116)
Control variables	Y	Y	Y	Y	Y
Year Fixed Effects	Y	Y	Y	Y	Y
Err. clustered by state	Y	Y	Y	Y	Y
Observations	14,039	14,040	14,040	14,040	14,040
R-squared	0.698	0.697	0.697	0.698	0.698

Notes: This table reports the regression results about which kind of board mitigate better climate risks. L.Natural hazard is the lag 1 of natural hazard occurrence. All variable descriptions are in Table A1. +, *, ** and *** and correspond to the 10%, 5%, 1% and 0.1%, respectively.

Table 7. Non-linear effect of natural disaster on banking stability.

Panel A: Using polynomial form for total damages of natural hazard
	Dependent variable: ln_Z1
	(1)	(2)	(3)
L.ln_Z1	0.4912***	0.5037***	0.5042***
	(0.0150)	(0.0144)	(0.0156)
L2.ln_Z1	0.3737***	0.3630***	0.3645***
	(0.0163)	(0.0191)	(0.0196)
L.Total damages	−0.0096**	−0.0091**	−0.0150***
	(0.0035)	(0.0030)	(0.0036)
L.Total damages # L.Total damages	0.0005*	0.0005**	0.0009***
	(0.0002)	(0.0002)	(0.0002)
Bank characteristics	N	Y	Y
Macro economics	N	N	Y
Year Fixed Effects	Y	Y	Y
Err. clustered by state	Y	Y	Y
Observations	19,582	16,854	12,657
R-squared	0.6795	0.6856	0.7005
Panel B: Using bin of total damages
	Dependent variable: ln_Z
	(1)	(2)	(3)
L.ln_Z1	0.4913***	0.5038***	0.5046***
	(0.0150)	(0.0144)	(0.0156)
L2.ln_Z1	0.3735***	0.3627***	0.3649***
	(0.0163)	(0.0190)	(0.0195)
Bin 2	−0.0198	−0.0077	−0.0143
	(0.0256)	(0.0229)	(0.0298)
Bin 3	−0.0561*	−0.0490**	−0.0745***
	(0.0221)	(0.0175)	(0.0192
Bin 4	−0.0353+	−0.0305+	−0.0405*
	(0.0204)	(0.0166)	(0.0177)
Bank characteristics	N	Y	Y
Macro economics	N	N	Y
Year Fixed Effects	Y	Y	Y
Err. clustered by state	Y	Y	Y
Observations	19,582	16,854	12,657
R-squared	0.6796	0.6856	0.7005

Notes: This table reports the OLS regression results on non-linear relation- ship between natural disasters and banking stability. L.ln_Z1 and L2.ln_Z1 are lag 1 and lag 2 of ln_Z1, respectively. The same notion goes for natural hazard and total damages. Panel A displays the model with the square term of total damage caused by natural disasters. Panel B shows the model with 4 different bins of total damage caused by natural disasters. Bin = 1 if L.ln_totaldmg = 0. Bin = 2 if L.ln_totaldmg>0 & L.ln_totaldmg<p(50). Bin = 3 if L.ln_totaldmg> = p(50) & L.ln_totaldmg<p(75). Bin = 4 if L.ln_totaldmg> = p(75). All variable descriptions are in Table A1. The corresponding robust standard errors are reported in parentheses. +, *, ** and *** and correspond to the 10%, 5%, 1% and 0.1%, respectively.

Table 8. Non-linear effect of indemnity on banking stability.

Panel A: Difference in Z-score between two groups (high damage vs. low damage)
	Low damage	High damage	Difference
ln_Z1	4.797	4.761	0.036***
Panel B: OLS regression (sub-sample: high damage vs. low damage)
	Dependent variable: ln_Z1
	High damage (1)	Low damage (2)
L.ln_Z1	0.6421***	0.4473***
	(0.0500)	(0.0433)
L2.ln_Z1	0.2762***	0.3834***
	(0.0556)	(0.0370)
L.Indemnity	0.0726+	0.0486
	(0.0373)	(0.0312)
L.Indemnity # L.Indemnity	−0.0034+	−0.0020
	(0.0017)	(0.0013)
Bank characteristics	Y	Y
Macro economics	Y	Y
Year Fixed Effects	Y	Y
Err. clustered by state	Y	Y
Observations	3,878	2,682
R-squared	0.7539	0.6597

Notes: This table reports the OLS regression results on non-linear relationship between indemnity and banking stability in two sub-samples. L.ln_Z1 and L2.ln_Z1 are lag 1 and lag 2 of ln_Z1, respectively. The same notion goes for natural hazard and indemnity. All variable descriptions are in Table A1. The corresponding robust standard errors are reported in parentheses. +, *, ** and *** and correspond to the 10%, 5%, 1% and 0.1%, respectively