Table 6

Nonbank entry: Further tests

Dependent variable: Nonbank Share|$_{it}$|
Robustness test:Syndicate aggregationCapital measurement
Syndicate aggregation:VWMedianDominantLeadEWEW
 [1][2][3][4][5][6]
Tier 1 Capital/RWA|$_{t-1}$|-4.323***-0.962***-2.083***-0.563***
 (0.548)(0.438)(0.410)(0.169)
Tier 1 Gap|$_{t-1}$|-1.830***
(0.452)
Total Capital/RWA|$_{t-1}$|-1.349***
(0.304)
Bank controlsYYYYYY
Loan controlsYYYYYY
Year fixed effectsYYYYYY
Observations29,12129,12129,12129,12129,12129,121
(R2)0.5420.5450.5490.5400.4190.419
Dependent variable: Nonbank Share|$_{it}$|
Robustness test:Syndicate aggregationCapital measurement
Syndicate aggregation:VWMedianDominantLeadEWEW
 [1][2][3][4][5][6]
Tier 1 Capital/RWA|$_{t-1}$|-4.323***-0.962***-2.083***-0.563***
 (0.548)(0.438)(0.410)(0.169)
Tier 1 Gap|$_{t-1}$|-1.830***
(0.452)
Total Capital/RWA|$_{t-1}$|-1.349***
(0.304)
Bank controlsYYYYYY
Loan controlsYYYYYY
Year fixed effectsYYYYYY
Observations29,12129,12129,12129,12129,12129,121
(R2)0.5420.5450.5490.5400.4190.419

This table shows robustness checks for the effects of bank regulatory capital for loan acquisition by nonbanks. The unit of observation in each regression is a loan-year. The dependent variable is the fraction of the loan held by nonbanks. Columns [1] to [4] use alternative methods to aggregate independent variables—bank controls shown in Table 3—up to the loan syndicate level. In particular, we consider the loan share value-weighted average, the median value, the simple average among the three (“dominant”) banks with the largest loan shares, and the lead arranger’s bank characteristics. Columns [5] and [6] examine alternative measures of bank regulatory capital as independent variables. The sample period is from 1993 to 2014. Where indicated, the columns include controls for bank, loan, and year fixed effects, and loan controls (a regulatory pass/fail dummy and the natural logarithm of loan maturity). All variables are defined in Table A1. Standard errors (in parentheses) are clustered at the year level. ***, **, and * denote 1%, 5%, and 10% statistical significance, respectively.

Table 6

Nonbank entry: Further tests

Dependent variable: Nonbank Share|$_{it}$|
Robustness test:Syndicate aggregationCapital measurement
Syndicate aggregation:VWMedianDominantLeadEWEW
 [1][2][3][4][5][6]
Tier 1 Capital/RWA|$_{t-1}$|-4.323***-0.962***-2.083***-0.563***
 (0.548)(0.438)(0.410)(0.169)
Tier 1 Gap|$_{t-1}$|-1.830***
(0.452)
Total Capital/RWA|$_{t-1}$|-1.349***
(0.304)
Bank controlsYYYYYY
Loan controlsYYYYYY
Year fixed effectsYYYYYY
Observations29,12129,12129,12129,12129,12129,121
(R2)0.5420.5450.5490.5400.4190.419
Dependent variable: Nonbank Share|$_{it}$|
Robustness test:Syndicate aggregationCapital measurement
Syndicate aggregation:VWMedianDominantLeadEWEW
 [1][2][3][4][5][6]
Tier 1 Capital/RWA|$_{t-1}$|-4.323***-0.962***-2.083***-0.563***
 (0.548)(0.438)(0.410)(0.169)
Tier 1 Gap|$_{t-1}$|-1.830***
(0.452)
Total Capital/RWA|$_{t-1}$|-1.349***
(0.304)
Bank controlsYYYYYY
Loan controlsYYYYYY
Year fixed effectsYYYYYY
Observations29,12129,12129,12129,12129,12129,121
(R2)0.5420.5450.5490.5400.4190.419

This table shows robustness checks for the effects of bank regulatory capital for loan acquisition by nonbanks. The unit of observation in each regression is a loan-year. The dependent variable is the fraction of the loan held by nonbanks. Columns [1] to [4] use alternative methods to aggregate independent variables—bank controls shown in Table 3—up to the loan syndicate level. In particular, we consider the loan share value-weighted average, the median value, the simple average among the three (“dominant”) banks with the largest loan shares, and the lead arranger’s bank characteristics. Columns [5] and [6] examine alternative measures of bank regulatory capital as independent variables. The sample period is from 1993 to 2014. Where indicated, the columns include controls for bank, loan, and year fixed effects, and loan controls (a regulatory pass/fail dummy and the natural logarithm of loan maturity). All variables are defined in Table A1. Standard errors (in parentheses) are clustered at the year level. ***, **, and * denote 1%, 5%, and 10% statistical significance, respectively.

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