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YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

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Page 1: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

YES 2011 DiscussionsDubrovnik Economic Conference

Paul WachtelStern School of Business. New York University

Page 2: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Are some banks more lenient in implementation of placement classification rule?

Tomislav Ridzak

Page 3: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Overview

A fascinating piece of applied banking research

Will be of interests to bank regulators, policy makers and, of course, the banks themselves.

Simple idea with big implications that need to be explored

Page 4: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Idea

Companies have more than one banking relationship.

Do different banks rate the same bank differently? There is going to be some random variation.

Can be important tool for bank examiners. Can be informative about bank behavior

But… more to do…relate it back to policy

Page 5: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Policy implications to explore

Do banks with less capital rate loans more leniently?

Do banks that are less profitable rate loans more leniently?

If answers are yes, then Banks are ‘gaming’ the regulators.Risk regulations of unclear value

Page 6: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Data

Loans to non financial companies by 33 Croatian banks 2006-09

Need to ‘prepare’ dataDefine defaultHandle collateral

SINCE THERE IS SOME ARBITRARINESS, ROBUSTNESS TO DEFINTIONS SHOULD BE EXAMINED.

Page 7: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Method from educational stats

BANKS (or Graders)

__________________

COMPAN IES

(or Students)

WHICH BANK IS GRADING IN A SIGNIFICANTLY DIFFERENT WAY?

Page 8: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Method from educational stats

BANKS (or Graders)

__________________

COMPAN IES

(or Students)

WHICH BANK IS GRADING IN A SIGNIFICANTLY DIFFERENT WAY?

Page 9: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

RESULTS

There are differences – 2-6 banks are significantly grading away from the pack

But, how much should we expect? I need a benchmark of some kind. How

much behavioral variation is ‘normal’?Appendix figures hint at some answers.

Small, insignificant relationship between relative leniency and coverage ratio (is that average for all of banks’ loans?) Collateral correction should be for each loan

Page 10: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

CONCLUSION

Imaginative application.But, what is the goal

So, regulators know more about banksOr, research on bank behavior

Page 11: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

The role of demand and supply in cyclical fluctuations of household debt in Coratia

Ivana Herceg

Page 12: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

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Overview

Nice paper are a really important issue (not just a Croatia issue)

But, I am not sure why I can understand what the paper sets out to

do But, it is hard to figure out from the paper

what was actually done.Which makes it hard to know what the

results are

Page 13: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

13

The issue

It is common (lots of references shown) to attribute credit booms / crises to easy bank lending standards – supply shift

But credit booms occur when economy is growing and the income elasticity of the demand for credit is high – So it could be a demand shift.

So, which is it? S or D?

Page 14: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

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Approach

Standard econometrics – identify S and D curves and see which is moving more in the boom.

Hard to find identifying restrictions Not clear what data to use other than aggregates

Use information from Croatia household survey to infer bank supply behavior and household demand behavior.

Paper bogs down in confusing explanations of the econometrics and never tells us what it can accomplish.

Page 15: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Infer supply

Look at households who took at loans (this is the bank’s product) and estimate a production frontier – standard application of stochastic frontier analysis

Page 16: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Understanding Frontier

Two inputs – efficient frontier

Extent to which individual is below frontier – weakness of demand

Extent to which frontier moves over time – change in supply.

In crisis – Did frontier shift in or did demand [inefficiency so to speak] increase?

Page 17: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Frontier results

2008 and 2009 – are estimates (overall) significantly different? Seem to unstable to be so.

Frontier estimation does not include existing loans outstanding as a control.

Page 18: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Alternative approach

Quantile regression estimates?Give me some intuition about what this does.

The results are shown in figures – and I have no idea what the figures show.

Page 19: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Fig. 6 Usage of available credit limits

6

7

8

9

10

11

12

13

14

15

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321

household

ln(n

ew lo

an)

credit limit new ly granted loan amount

WHAT AM I LOOKING AT?

What is on each axis?1 to 321 Householdswith loans? How ordered?Resutls from SFA or QR? How presented?

Page 20: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Probability of loan and supply

Some kind of probit estimates for S and D (same 0-1 variable for both)Never see the specificationOr the estimatesOr any tests of the identifying variables (in

footnote 14). Too big an issue for a footnote. And, existence of prior loan seems relevant to both S and D

Page 21: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Little puzzles

“Creditoworthiness….deteriorated”Can we really treat 2008 and 2009 as

different? The one comparison does not answer

original question – does S or D drive credit boom?When is survey conducted?Are othere waves available?

Page 22: YES 2011 Discussions Dubrovnik Economic Conference Paul Wachtel Stern School of Business. New York University

Conclusion

In crisis/recession, banks tightened selection of households to offer loans.

Banks offered selected households larger loans

Households took down less.

Important result – Need to clarify methodology And show how you got the results