1 / 19

Discussion of: Credit Availability. Identifying Balance-Sheet Channels with Loan Applications

This paper examines the connection between financial institutions and the real economy by analyzing the impact of shocks to banks' funding sources on their lending. It uses loan applications as a proxy for potential loan demand and explores the heterogeneous effects across different banks and firms. The findings highlight the transmission of shocks from the financial sector to lending activities.

jmohammed
Télécharger la présentation

Discussion of: Credit Availability. Identifying Balance-Sheet Channels with Loan Applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Discussion of:Credit Availability. Identifying Balance-Sheet Channels with Loan Applications Nicola Cetorelli Federal Reserve Bank of New York Fourth BI-CEPR Conference on Money, Banking and Finance Rome, October 2-3, 2009 The views expressed in this paper do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System.

  2. Framing this paper in the literature • There is a vast literature exploring the connections between the financial sector and the real economy

  3. Do shocks to financial institutions transmit to the real sector? Firms’ balance sheet Banks balance sheet !! !! Funding Capital Liquid assets Loans Cash Assets Funding Capital 3 1 !! !! !! 2 4 e.g., Khwaja and Mian, AER 2008 Paravisini, JF 2008 e.g. Kashyap and Stein, AER 2000 3

  4. Main contributions of this paper • Go at the heart of the demand/supply identification problem • Unit of observation is an actual loan application

  5. Potential loan demand Firms not asking for a loan Firms in need of a loan

  6. Main contributions of this paper • Empirical strategy based on determinants of likelihood application is approved • Identification coming from heterogeneous impact across banks of different characteristics and firms of different characteristics

  7. Do shocks to financial institutions transmit to the real sector? Firms’ balance sheet Banks balance sheet !! !! Funding Capital Liquid assets Loans Cash Assets Funding Capital 3 1 !! !! !! 2 4 7

  8. Findings • Banks are affected by “shocks” to their funding sources • Shocks are transmitted to banks’ lending

  9. Comments Potential demand Apply but banks do not request info. Not in dataset Apply and banks request info. In dataset In need of funds but do not apply. Not in dataset Not in dataset

  10. Potential loan demand The composition between observable and non-observable demand may change with macro conditions. Not sure which way it goes. Not in dataset In dataset Not in dataset

  11. Potential loan demand • In bad times, better firms may choose not to apply if at the margin bank funding becomes more expensive. • Left in dataset is a disproportionately “worse” pool. • May lead to overestimate of effects. Not in dataset In dataset Not in dataset

  12. Potential loan demand • In bad times, better firms may choose to apply to obtain quality certification from bank loans. • Leads to dataset of disproportionately “better” pool. • May imply under-estimate of effects. Not in dataset In dataset Not in dataset

  13. Potential loan demand Apply but banks do not request info. In this unobservable group we have the current bank clients. In bad times banks may choose to shift resources more toward old clients. Effect found still legitimate, but it requires qualifications. Not in dataset In dataset Not in dataset

  14. Should be able to delve deeper • May be able to get info on the unobservable components of demand (at least some). • Spanish Credit Register has info on all credit exposures of existing bank clients vis-à-vis all banks. You could observe to what extent they are getting (new) credit while others apply and get denied.

  15. Should be able to delve deeper • Likewise, may be able to say something about firms not applying (harder task). At least in aggregate terms? (Not sure what is the data source for the characteristics of the firms).

  16. Should be able to delve deeper • Encouragement to push further. With the identity of the firms should be able to address part “3” and “4” of the big picture.

  17. Do shocks to financial institutions transmit to the real sector? Firms’ balance sheet Banks balance sheet !! !! Funding Capital Liquid assets Loans Cash Assets Funding Capital 3 1 !! !! !! 2 4 17

  18. Should be able to delve deeper • Encouragement to push further. With the identity of the firms should be able to address part “3” and “4” of the big picture. • Use firm data to measure overall change in funding positions. • Use firm data to hopefully gauge ultimate impact on their asset side (impact on capital investment, growth, etc.).

More Related