A small quarterly multi-country projection model with financial-real linkages and oil prices /

Saved in:
Bibliographic Details
Imprint:Washington, D.C. : International Monetary Fund, ©2008.
Description:1 online resource (74 pages) : illustrations
Language:English
Series:IMF working paper ; WP/08/280.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/14153386
Hidden Bibliographic Details
Other authors / contributors:Carabenciov, Ioan, author.
International Monetary Fund. Research Department.
ISBN:1462388078
9781462388073
1452735956
9781452735955
1282391658
9781282391659
9786613820082
6613820083
1451999356
9781451999358
Notes:At head of title: Research Dept.
"December 2008."
Includes bibliographical references (pages 36-38).
Electronic reproduction. [Place of publication not identified] : HathiTrust Digital Library, 2011.
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212
English.
digitized 2011 HathiTrust Digital Library committed to preserve
Print version record.
Summary:This is the third of a series of papers that are being written as part of a larger project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit for studying both own-country and cross-country linkages. In this paper, we estimate a small quarterly projection model of the US, Euro Area, and Japanese economies that incorporates oil prices and allows us to trace out the effects of shocks to oil prices. The model is estimated with Bayesian techniques. We show how the model can be used to construct efficient baseline forecasts that incorporate judgment imposed on the near-term outlook.
Other form:Print version: Small quarterly multi-country projection model with financial-real linkages and oil prices. Washington, D.C. : International Monetary Fund, ©2008
Table of Contents:
  • I. Introduction; II. Benchmark Model; A. Background; B. The Specification of the Model; B.1. Observable variable and data definitios; B.2. Stochastic processes and model definitions; B.3 Behavioral equations; B.4. Cross corelations of disturbances; III. Extending the Model to Include Financial-Real Linkages; A. Background; B. Model Specification Incorporating the US Bank Lending Tightening Variable; IV. Extending the Model to Include Oil Prices; A. Background; B. Model Specification Incorporating Oil Price; V. Confronting The Model with The Data; A. Bayesian Estimation; B. Results.
  • B.1. Estimates of coefficientsB. 2. Estimates of standard deviation of structural shocks and cross correlations; B.3. RMSEs; B.4. Impulse response functions; C. Forecasting with Bayesian Estimates; VI. Concluding Remarks; References; Appendix: GPM Data Definitions; Figures; 1. Comparison between Output Gap and BLT indicator; 2. Real Oil Price; Tables; 1. Results from posterior maximization (1); 2. Results from posterior maximization (2); 3. Results from posterior maximization (3); 4. Results from posterior parameters (standard deviation of structural shocks).
  • 5. Results from posterior parameters (correlation of structural Shocks)6. Root Mean Squared Errors; 3 Demand shock in the US (1); 4. Demand shock in the US (2); 5. Demand shock in the US (3); 6. Demand shock in Europe (1); 7. Demand shock in Europe (2); 8. Demand shock in Europe (3); 9. Demand shock in Japan (1); 10. Demand shock in Japan (2); 11. Demand shock in Japan (3); 12. Financial (BLT) shock in the US (1); 13. Financial (BLT) shock in the US (2); 14. Financial (BLT) shock in the US (3); 15. Growth rate shock in the US (1); 16. Growth rate shock in the US (2).
  • 17. Growth rate shock in the US (3)18. Oil Price Shock (1); 19. Oil Price Shock (2); 20. Oil Price Shock (3); 21. Oil Price Shock (4); 22. Oil Price Shock Permanent (1); 23. Oil Price Shock Permanent (2); 24. Oil Price Shock Permanent (3); 25. Oil Price Shock Permanent (4); 26. Forecast Results (1); 27. Forecast Results (2); 28. Forecast Results (3); 29. Forecast Results (4).