1,909
Views
14
CrossRef citations to date
0
Altmetric
FINANCIAL ECONOMICS

Dynamics of bank capital ratios and risk-taking: Evidence from US commercial banks

ORCID Icon & ORCID Icon | (Reviewing editor)
Article: 1838693 | Received 08 Jun 2020, Accepted 09 Oct 2020, Published online: 30 Oct 2020

Figures & data

Table 1. Descriptive statistics

Table 2. Correlation matrix

Table 3. Risk and Capital ratios model (Full sample results): The dependent variable is risk-weighted assets to total assets ratios. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis)

Table 4. Risk and Capital ratios model (overall sample): The dependent variable is loan loss allowances to gross loans ratio. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis)

Table 5. Risk and Capital ratios model (post-crisis and before-crisis results): The dependent variable is risk-weighted assets to total assets. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis): Note Post-crisis (AC) and Before-crisis (BC)

Table 6. Risk and Capital ratios model (post-crisis and before-crisis period results): The dependent variable is loan loss allowances to gross loans ratio. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis): Note Post-crisis (AC) and Before-crisis (BC)

Table 7. Risk and Capital ratios model (Well (W) & Undercapitalized (U) banks results): The dependent variable is risk-weighted assets to total assets. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis)

Table 8. Risk and Capital ratios model (Well (W) & Undercapitalized (U) banks results): The dependent variable is loan loss allowances to gross loans ratio. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis)

Table 9. Risk and Capital ratios model (Nationally chartered member banks (NAT), State-chartered member banks (SMB), State-chartered non-member banks (SNM) results): The dependent variable is risk-weighted assets to total assets. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis)

Table 10. Risk and Capital ratios model (Nationally chartered member banks (NAT), State-chartered member banks (SMB), State-chartered non-member banks (SNM) results): The dependent variable is loan loss allowances to gross loans ratio. Our predictions are the two-step GMM approach. (Robust standard errors are reported in parenthesis)