Reversing the financial accelerator : credit conditions and macro-financial linkages /

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Bibliographic Details
Author / Creator:Bayoumi, Tamim A., author.
Imprint:[Washington, D.C.] : International Monetary Fund, ©2011.
Description:1 online resource (36 pages)
Language:English
Series:IMF working paper ; WP/11/26
IMF working paper ; WP/11/26.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12499086
Hidden Bibliographic Details
Other authors / contributors:Darius, Reginald, author.
International Monetary Fund. Strategy, Policy, and Review Department, issuing body.
ISBN:1283554283
9781283554282
9781455263981
1455263982
9781455216734
1455216739
Notes:Includes bibliographical references.
Summary:This paper examines the role of credit markets in the transmission of U.S. macro-financial shocks through the prism of a financial conditions index (FCI) based on a vector autoregression (VAR) methodology. It explores the relative predictive power of market variables compared to credit standards/conditions. The main conclusion is that under plausible specifications credit conditions dominate market variables, highlighting the importance of credit supply. The fact that direct measures of credit conditions anticipate future movements in asset prices has an extremely important implication. Most models of the credit channel see it as an amplifier of underlying changes in financial wealth. The impact of credit conditions on growth compared to other market variables implies that credit supply drives other financial variables rather than responding to them.
Other form:Print version: Bayoumi, Tamim. Reversing the Financial Accelerator: Credit Conditions and Macro-Financial Linkages. Washington : International Monetary Fund, ©2011 9781455216734
Table of Contents:
  • Cover Page; Title Page; Copyright Page; Contents; I. Introduction and Literature Review; A. Introduction: Turning the Credit Channel on its Head; B. Literature Review; II. Model and Estimation Method; A. The basic model and survey data; B. Role of senior loans survey of credit conditions (SLOS): Baseline model; 1. Response of GDP to financial variables including SLOS; 2. VDC Baseline Model; III. Does the small business survey of credit conditions (SBS) add information?; 3. Response of GDP to financial variables including SLOS and SBS; 4. VDC of GDP in model including SLOS and SBS.
  • 5. Response of GDP to financial variables in model with SBS6. VDC of GDP in model with only SBS; IV. Timing and Ordering of Credit Variables; 7. Response of GDP in model with period average asset prices (baseline; 8. VDC of GDP in model with period average asset prices (baseline; 9. Response of GDP in model with period average asset prices (SLOS; 10. VDC of GDP in model with period average asset prices (SLOS; V. Why does credit matter so much and what does it imply?; 11. Variance Decomposition of Policy and market Variables; 12. Response of market and financial variables to credit shocks.
  • 13. Response of credit to market and financial shocksVI. Conclusions; A1. Decomposition for growth in baseline VAR; A2. Decomposition for growth in VAR with both credit variables; A3. Decomposition for growth in various VARs; A4. Variance decomposition for policy rate and REER in baseline VAR; A5. Variance decomposition for market variables in baseline VAR; References; Footnotes.