Commercial bank digital transformation, information costs, and corporate financial constraints

Figures & data

Figure 1. Framework of Commercial Bank Digital Transformation Index.

Figure 2. The Digital Transformation Index and sub-indices of commercial banks from Peking University.

Note: The left axis shows the Digital Transformation Index, the organisational sub-index, and the product sub-index; the right axis shows the cognitive sub-index.

Table 1. Variable definitions.

Variables	Definitions
Corporate financial constraints
INV	Corporate investment, the capital expenditure scaled by the lagged total assets. Capital expenditure is calculated as follow: Cash paid to acquire fixed assets, intangible assets and other long-term assets + Cash paid to acquire subsidiaries and other business entities – Cash from disposing of fixed assets, intangible assets and other long-term assets – Cash from disposing of subsidiaries and other business entities – Depreciation of fixed assets – Amortisation of intangible assets – Deferred expenses.
CF	Cash flow, computed as the net cash flow from operating activities scaled by lagged total assets.
Bank digital transformation
BankTech	The degree of bank digital transformation, the Bank Digital Transformation Index weighted by the loan amount at the firm-year level.
BankOrg	The organisational dimension of Bank Digital Transformation Index.
BankPduc	The product dimension of Bank Digital Transformation Index.
BankCon	The cognitive dimension of Bank Digital Transformation Index.
Control variables
SOE	An indicator equal to one if the firm is an SOE, and 0 otherwise.
SIZE	The logarithm of the total market capitalisation of the company.
LEV	Corporate leverage, total liabilities divided by total assets.
TobinQ	Ratio of the market value of equity to the book value of equity.
OPROA	Company performance, operating profits divided by total assets.
PPE	The proportion of fixed assets, fixed assets divided by total assets.
FIRST	Ownership of the first largest shareholder.
INDP	Board independence, the proportion of independent directors.
MktIndex	Total marketability index.
GDPG	GDP growth rate of the city where the company is located.
GDPPer	The logarithm of GDP per capita in the city where the company is located.

Table 2. Summary statistics.

Variables	Mean	Median	SD	P25	P75
INV	0.06	0.04	0.08	0.01	0.09
CF	0.04	0.04	0.08	0.00	0.09
BankTech	76.20	77.60	52.50	36.10	109.60
BankOrg	39.40	41.00	26.20	20.30	57.30
BankPduc	58.80	69.40	35.60	28.50	89.20
BankCon	184.60	153.00	162.20	54.10	268.50
SOE	0.34	0.00	0.47	0.00	1.00
SIZE	15.33	15.27	0.91	14.69	15.90
LEV	0.47	0.47	0.20	0.32	0.62
TobinQ	2.71	2.09	1.95	1.44	3.22
OPROA	0.03	0.03	0.08	0.01	0.06
PPE	0.20	0.17	0.16	0.08	0.29
FIRST	0.33	0.30	0.14	0.22	0.42
INDP	0.38	0.36	0.06	0.33	0.43
MktIndex	8.25	9.14	1.67	7.07	9.77
GDPG	0.09	0.09	0.06	0.07	0.12
GDPPer	11.41	11.51	0.51	11.09	11.82

Table 3. Effects of bank digital transformation on corporate financial constraints.

	(1)	(2)	(3)	(4)
	INV	INV	INV	INV
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF*CF	−0.041^**	−0.043^**	−0.041^**	−0.033^*
	(−2.27)	(−2.23)	(−2.21)	(−1.95)
BF	0.001	0.002	0.001	0.001
	(0.75)	(1.07)	(0.47)	(0.63)
CF	0.075***	0.078***	0.078***	0.075***
	(3.80)	(3.90)	(3.91)	(3.78)
SOE	−0.002	−0.002	−0.002	−0.002
	(−0.29)	(−0.24)	(−0.28)	(−0.29)
SIZE	0.004	0.004	0.004	0.004
	(1.20)	(1.12)	(1.12)	(1.23)
LEV	0.028*	0.029*	0.028*	0.028*
	(1.83)	(1.87)	(1.83)	(1.82)
TobinQ	0.003**	0.003**	0.003**	0.003*
	(2.00)	(2.06)	(2.03)	(1.96)
OPROA	0.086***	0.084***	0.085***	0.086***
	(4.27)	(4.19)	(4.21)	(4.28)
PPE	−0.114***	−0.114***	−0.114***	−0.114***
	(−5.26)	(−5.26)	(−5.24)	(−5.27)
FIRST	0.025	0.025	0.025	0.025
	(1.02)	(1.04)	(1.01)	(1.02)
INDP	−0.043	−0.043	−0.043	−0.043
	(−1.38)	(−1.37)	(−1.39)	(−1.38)
MktIndex	0.006	0.006	0.006	0.006
	(1.50)	(1.47)	(1.50)	(1.50)
GDPG	−0.004	−0.004	−0.004	−0.004
	(−0.23)	(−0.23)	(−0.24)	(−0.22)
GDPPer	0.001	0.000	0.001	0.000
	(0.05)	(0.02)	(0.07)	(0.03)
Constant	0.001	0.007	0.001	0.002
	(0.00)	(0.05)	(0.00)	(0.01)
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.329	0.329	0.329	0.329

The t-statistics, calculated using robust standard errors clustered at the firm level, are reported in parentheses. *, **, and *** represent significance at the 10%, 5%, and 1% levels, respectively. The same as below.

Table 4. Endogeneity tests to solve measurement error issue.

	(1)	(2)	(3)	(4)
	INV	INV	INV	INV
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
Resid_BF*CF	−0.083^**	−0.162^*	−0.165^**	−0.031^*
	(−2.09)	(−1.78)	(−2.36)	(−1.88)
Resid_BF	0.001	0.008	−0.006	0.001
	(0.12)	(1.10)	(−0.73)	(0.41)
CF	0.078***	0.077***	0.079***	0.075***
	(3.90)	(3.83)	(3.97)	(3.79)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.329	0.329	0.329	0.329

Table 5. Instrumental variable test.

	(1)		(2)
	First stage		Second stage
	BankTech		INV
IT_Index	0.242**	BankTech_hat*CF	−0.045**
	(2.05)		(−2.36)
College20	0.065**	BankTech_hat	0.001
	(2.04)		(0.86)
BankSIZE	0.110***	CF	0.076***
	(10.62)		(3.85)
BankROA	−0.475	SOE	−0.002
	(−1.36)		(−0.27)
BankLEV	−1.607	SIZE	0.004
	(−0.46)		(1.17)
HHI	−0.129	LEV	0.028*
	(−0.81)		(1.84)
CityTech	0.215***	TobinQ	0.003**
	(6.16)		(2.03)
Third	−0.665***	OPROA	0.086***
	(−4.80)		(4.24)
		PPE	−0.114***
			(−5.26)
		FIRST	0.025
			(1.03)
		INDP	−0.043
			(−1.38)
MktIndex	0.005	MktIndex	0.006
	(0.79)		(1.52)
GDPG	0.204	GDPG	−0.004
	(0.87)		(−0.21)
GDPPer	−0.051	GDPPer	0.001
	(−1.57)		(0.07)
Constant	−1.833***	Constant	−0.001
	(−4.02)		(−0.01)
Year	YES	Year & Firm	YES
N	1,345	N	9,437
Adj R^2	0.478	Adj R^2	0.330

Table 6. Cross-sectional tests based on corporate contract intensity.

	(1)	(2)	(3)	(4)
	INV	INV	INV	INV
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF*CF*MoreContract	−0.115**	−0.117**	−0.099*	−0.108**
	(−2.09)	(−2.06)	(−1.84)	(−1.96)
BF*CF	0.046	0.024	0.029	0.057
	(1.10)	(0.58)	(0.71)	(1.36)
CF*MoreContract	−0.033	−0.030	−0.028	−0.036
	(−0.56)	(−0.51)	(−0.47)	(−0.60)
BF*MoreContract	0.007	0.004	0.003	0.008
	(1.31)	(0.86)	(0.71)	(1.55)
MoreContract	−0.069**	−0.070**	−0.069**	−0.069**
	(−2.31)	(−2.34)	(−2.31)	(−2.29)
BF	−0.004	−0.002	−0.003	−0.004
	(−1.04)	(−0.60)	(−0.91)	(−1.07)
CF	0.051	0.049	0.048	0.055
	(1.05)	(1.01)	(1.00)	(1.11)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	4,224	4,224	4,224	4,224
Adj R^2	0.339	0.340	0.339	0.338

The industry contract intensity index is derived from Nunn (2007). Since this index is only for the manufacturing industry, the sample observations in Table 6 are less than that in the main test.

Table 7. Cross-sectional tests based on corporate intangible assets.

	(1)	(2)	(3)	(4)
	INV	INV	INV	INV
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF*CF*MoreInt	−0.085^**	−0.065^*	−0.078^**	−0.082^**
	(−2.40)	(−1.73)	(−2.19)	(−2.44)
BF*CF	−0.010	−0.019	−0.013	−0.003
	(−0.44)	(−0.77)	(−0.56)	(−0.14)
CF*MoreInt	−0.063*	−0.057	−0.058	−0.065*
	(−1.73)	(−1.56)	(−1.62)	(−1.80)
BF*MoreInt	0.003	0.003	0.002	0.003
	(1.08)	(1.17)	(0.80)	(1.07)
MoreInt	−0.002	−0.002	−0.002	−0.002
	(−0.56)	(−0.70)	(−0.65)	(−0.53)
BF	0.000	0.001	0.000	0.000
	(0.13)	(0.30)	(0.07)	(0.00)
CF	0.098***	0.098***	0.099***	0.098***
	(4.15)	(4.13)	(4.17)	(4.18)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.331	0.331	0.331	0.331

Table 8. Cross-sectional tests based on corporate external information environment.

	(1)	(2)	(3)	(4)
	INV	INV	INV	INV
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF*CF*LessAnalyst	−0.240^**	−0.149^*	−0.154^*	−0.324^**
	(−2.05)	(−1.65)	(−1.82)	(−2.07)
BF*CF	−0.032*	−0.035*	−0.031	−0.026
	(−1.75)	(−1.79)	(−1.63)	(−1.53)
CF*LessAnalyst	−0.121*	−0.089	−0.066	−0.174**
	(−1.84)	(−1.34)	(−0.99)	(−2.36)
BF*LessAnalyst	0.004	0.002	0.001	0.006
	(0.60)	(0.42)	(0.27)	(0.76)
LessAnalyst	−0.017***	−0.018***	−0.018***	−0.016***
	(−3.32)	(−3.74)	(−3.75)	(−2.80)
BF	0.001	0.001	0.001	0.001
	(0.56)	(0.81)	(0.30)	(0.51)
CF	0.082***	0.084***	0.084***	0.082***
	(4.12)	(4.17)	(4.15)	(4.13)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.334	0.334	0.334	0.334

Table

Panel B: New short-term loans
	(1)	(2)	(3)	(4)
	△STLOAN	△STLOAN	△STLOAN	△STLOAN
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF	−0.001	−0.001	−0.001	−0.000
	(−0.55)	(−1.00)	(−0.50)	(−0.27)
CF	−0.236***	−0.236***	−0.236***	−0.236***
	(−14.35)	(−14.34)	(−14.35)	(−14.35)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.098	0.098	0.098	0.098

Table

Panel C: The cost of debt financing
	(1)	(2)	(3)	(4)
	Cost of debt	Cost of debt	Cost of debt	Cost of debt
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF	−0.000	−0.000	−0.000	0.000
	(−0.19)	(−0.19)	(−0.48)	(0.05)
CF	0.007	0.007	0.007	0.007
	(1.18)	(1.18)	(1.18)	(1.18)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.470	0.470	0.470	0.470

Table 9. Mechanism tests.

Panel A: New long-term loans
	(1)	(2)	(3)	(4)
	△LTLOAN	△LTLOAN	△LTLOAN	△LTLOAN
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF	0.003^**	0.002^**	0.001	0.003^**
	(2.15)	(2.18)	(0.90)	(2.15)
CF	−0.074***	−0.074***	−0.074***	−0.074***
	(−5.11)	(−5.10)	(−5.09)	(−5.10)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.256	0.256	0.256	0.256

Table 10. Effects of bank digital transformation on bank market structure.

	(1)	(2)	(3)	(4)
	Loan	Loan	Loan	Loan
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF*BigBank	0.055^***	0.023^*	0.043^***	0.061^***
	(3.98)	(1.75)	(3.55)	(4.20)
BF	−0.049***	−0.028**	−0.010	−0.054***
	(−3.28)	(−2.26)	(−0.84)	(−3.63)
CF	−0.074	−0.076	−0.077	−0.073
	(−1.19)	(−1.22)	(−1.22)	(−1.17)
Controls	YES	YES	YES	YES
Bank & Year & Firm	YES	YES	YES	YES
N	59,212	59,212	59,212	59,212
Adj R^2	0.491	0.491	0.491	0.491

The bank fixed effects absorb the effect of BigBank, so the coefficients on BigBank are not reported.

Table 11. The impact of ‘Internet Finance’ policy.

	(1)		(2)
	INV		INV
Post*HighBF*CF	−0.128**	Yr2013_2014*HighBF*CF	−0.127
	(−2.01)		(−1.50)
Post*CF	0.079	Yr2015*HighBF*CF	−0.245*
	(1.60)		(−1.80)
Post*HighBF	0.004	Yr2016*HighBF*CF	−0.366**
	(0.90)		(−2.45)
HighBF*CF	0.010	Aft2017*HighBF*CF	−0.138
	(0.24)		(−1.43)
CF	0.059*	Yr2013_2014*CF	0.086
	(1.92)		(1.24)
SOE	−0.002	Yr2015*CF	0.185*
	(−0.31)		(1.73)
SIZE	0.009**	Yr2016*CF	0.177
	(2.57)		(1.47)
LEV	0.027	Aft2017*CF	0.104
	(1.48)		(1.30)
TobinQ	0.003**	Yr2013_2014*HighBF	0.011
	(2.26)		(1.50)
OPROA	0.076***	Yr2015*HighBF	0.012
	(2.90)		(1.22)
PPE	−0.088***	Yr2016*HighBF	0.016
	(−4.07)		(1.40)
FIRST	0.014	Aft2017*HighBF	0.011
	(0.50)		(1.35)
INDP	−0.050	HighBF*CF	0.101
	(−1.57)		(1.32)
MktIndex	0.006	CF	−0.004
	(1.50)		(−0.07)
GDPG	−0.000
	(−0.02)
GDPPer	0.014
	(1.07)
Constant	−0.242	Constant	−0.227
	(−1.62)		(−1.50)
Year & Firm	YES	Year & Firm & Controls	YES
N	5,041	N	5,041
Adj R^2	0.336	Adj R^2	0.337

(1) The firm fixed effects absorb the effect of HighBF, while the year fixed effects absorb the effect of Post. Therefore, the coefficients on HighBF and Post are not reported. (2) In order to distinguish the treatment and control group, we only retain the observations with bank digital transformation data in 2014, so the sample observations in Table 11 are less than that in the main test.

Table 12. Economic consequences of bank digital transformation.

	(1)	(2)	(3)	(4)
	INV	INV	INV	INV
	BF = BankTech	BF = BankOrg	BF = BankPduc	BF = BankCon
BF*CF*Zombie	0.144^**	0.135^**	0.125^**	0.132^**
	(2.42)	(2.15)	(2.01)	(2.28)
BF*CF	−0.072***	−0.071***	−0.065***	−0.062***
	(−3.95)	(−3.54)	(−3.56)	(−3.71)
CF*Zombie	0.039	0.024	0.030	0.044
	(0.64)	(0.39)	(0.49)	(0.72)
BF*Zombie	−0.011***	−0.008**	−0.007**	−0.011***
	(−3.29)	(−2.26)	(−2.32)	(−3.57)
Zombie	−0.012***	−0.011***	−0.012***	−0.013***
	(−3.08)	(−2.81)	(−2.94)	(−3.11)
BF	0.004**	0.004**	0.003*	0.004**
	(2.50)	(2.41)	(1.69)	(2.46)
CF	0.067***	0.072***	0.072***	0.066***
	(3.37)	(3.57)	(3.57)	(3.32)
Controls	YES	YES	YES	YES
Year & Firm	YES	YES	YES	YES
N	9,437	9,437	9,437	9,437
Adj R^2	0.333	0.333	0.333	0.332

Nunn, N. (2007). Relationship-specificity, incomplete contracts, and the pattern of trade. The Quarterly Journal of Economics, 122(2), 569–600. https://doi.org/10.1162/qjec.122.2.569

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