1. Michel Keoula, Researcher, HEC Montreal & IRCCF
Discussion of the paper
DETERMINANTS OF FAILURE OF CREDIT UNIONS AND COMMERCIAL BANKS: SIMILARITIES AND DIFFERENCES Luis Dopico & James WILcox
Michel Keoula, Researcher, HEC Montreal & IRCCF
24 August 2017, IWFSAS, Montreal, QC

2. Research questions and policy implications
“First, large scale, long term analysis of failure of credit unions”
Determinants that have over time endured and other determinants.
May have implications for analysis on efficiency analysis, pricing, portfolio, activities.
Will contribute to the debate on the optimal size of credit unions and banks.

3. Research questions and policy implications
Seminal studies by Meyer & Pifer (1970), Altmann (1977), Kharadia &Collins (1981)
Risk-based capital requirements for credit unions and risk-based deposit insurance premium
Taylor the analysis to the comparison of failure of credit unions and banks
Use: Early Warning System, off-site surveillance

4. Interesting take-aways
Stock ownership vs. mutual ownership
Agency problems in mutuals: managers may not be maximizing value, non-monetary perks, excessively risk-averse in order to show something in their next position (from the lit review in the paper).
Empirical evidence is mix
“Link between smaller size and bank failure has broken down during the financial crisis”

5. Research design: sample
Period: (observations)
Whole period
Credit unions
113,852
94,266
145,287
44,585
18,781
416, 771
Banks
100,733
88,197
121,740
40,391
16,940
368,001
Period: (observations)
Tiny
Smallish
Medium
Large
All
<10 M
10<..<100M
100M<..<1B
>1B
Credit unions
156,384
112,028
31,417
3,090*
302,919
Banks
2,402
122,752
126,599
16,515
268,268

6. Research design: the regression model
Dependent variable
Explanatory variables (15)
Comment
Failure (0-1 dummy)
Constant
Securities
Other assets (N.E.C)
Loans other than res. Mortg./Consumer loans
Residential mortgages
Commercial mortgages
C&I loans
Log real assets
Noninterest expenses
Provision on loan losses/Delinquent loans
Capital
ROA
Unemployment rate
Logit
Chow tests
Expected probability of failure

7. Ideas to improve of the paper
Logit is a nonlinear model; precision needed for what effects are reported as coefficients («averages» to precise).
Full disclosure on what counts as a failure
Explanation of the puzzling result that unemployment rate does not significantly affect credit union failure may be appreciated.

8. Thank you
for your
attention