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E-book
Author Crowe, Christopher, author

Title Consensus forecasts and inefficient information aggregation / prepared by Christopher Crowe
Published [Washington, D.C.] : International Monetary Fund, ©2010

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Description 1 online resource (42 pages)
Series IMF working paper ; WP/10/178
IMF working paper ; WP/10/178.
Contents Cover Page; Title Page; Copyright Page; Contents; B. Assumed Information Structure of Data; C. Empirical Methodology; A. Basic Model and Results; I. Introduction; Table 1. Correlation Coefficients; II. Model and Empirical Strategy; A. Basic Model and Results; B. Efficiency Tests; Table 2. Naive vs. Rational Priors; Table 3. Baseline Efficiency Tests; Table 4. Efficiency Tests: Iterative Error Adjustment; Table 5. In-Sample Efficiency Gains, by Country; C. Efficiency Gains from adjusted Consensus Forecasts; Table 6. In-Sample Efficiency Gains, by Forecast Horizon
Table 7. Out of Sample Efficiency Gains, by CountryTable 8. Out of Sample Efficiency Gains, by Forecast Horizon; D. Robustness Checks; Table 9. Efficiency Tests: Median Forecasts; Table 10. Efficiency Tests: Real Time Growth Data; Table 11. SPF Nominal GDP Forecasts; III. Application to Cross-Country Growth Forecasts; A. Morris and Shin (2002): A Reassessment; B. Groupthink, Bank Behavior and the Credit Crunch; IV. Discussion; V. Conclusions; Appendix; Table A1. Individual Regression Results Summary; Table A2. Individual SPF Regression Results Summary; References; Footnotes
Summary Consensus forecasts are inefficient, over-weighting older information already in the public domain at the expense of new private information, when individual forecasters have different information sets. Using a cross-country panel of growth forecasts and new methodological insights, this paper finds that: consensus forecasts are inefficient as predicted; this is not due to individual forecaster irrationality; forecasters appear unaware of this inefficiency; and a simple adjustment reduces forecast errors by 5 percent. Similar results are found using US nominal GDP forecasts. The paper also discusses the result's implications for users of forecaster surveys and for the literature on information aggregation
Bibliography Includes bibliographical references (pages 41-43)
Notes English
Print version record
Subject Economic forecasting -- Econometric models
Information theory in economics -- Econometric models
Econometrics.
Econometrics
Economic forecasting -- Econometric models
Information theory in economics -- Econometric models
Form Electronic book
Author International Monetary Fund. Research Department, issuing body.
ISBN 9781455276790
1455276790
1282846507
9781282846500
1455201618
9781455201617
1462327486
9781462327485
9786612846502
661284650X
1455201898
9781455201891