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AI 根据所提供的论文材料归类:摘要研究跨国宏观预测面板,并明确使用 VAR 分析预测修正。

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关注这篇论文的作者
Gultekin Isiklar
Kajal Lahiri
Prakash Loungani

预测者多快吸收新信息?跨国调查证据

研究问题
实际 GDP 增长预测是否及时吸收新信息?作者以预测修正是否相关检验效率,并进一步考察国外信息利用不足的作用。
方法与思路
作者分析十八国、多预测月份及目标年份的调查数据,在面板估计中处理跨国协方差,并对七国集团的预测修正估计 VAR。
材料陈述的贡献
摘要称十八国预测修正均存在较强序列相关,拒绝效率假说;框架进一步指出,对国外新信息吸收不足是部分低效率的来源。
阅读关注点
应核对效率检验的信息集与误差结构、跨国冲击相关性的处理,以及 VAR 如何区分信息吸收迟缓和其他预测修正机制。
阅读边界
仅据所给 Crossref 摘要,无法判断国外信息来源解释的识别强度;增加国外信息可改善预测的幅度和样本外表现未说明。

原文摘要

Abstract Using forecasts from Consensus Economics Inc., we provide evidence on the efficiency of real GDP growth forecasts by testing whether forecast revisions are uncorrelated. As the forecast data used are multi‐dimensional—18 countries, 24 monthly forecasts for the current and the following year and 16 target years—the panel estimation takes into account the complex structure of the variance–covariance matrix due to propagation of shocks across countries and economic linkages among them. Efficiency is rejected for all 18 countries: forecast revisions show a high degree of serial correlation. We then develop a framework for characterizing the nature of the inefficiency in forecasts. For a smaller set of countries, the G‐7, we estimate a VAR model on forecast revisions. The degree of inefficiency, as manifested in the serial correlation of forecast revisions, tends to be smaller in forecasts of the USA than in forecasts for European countries. Our framework also shows that one of the sources of the inefficiency in a country's forecasts is resistance to utilizing foreign news. Thus the quality of forecasts for many of these countries can be significantly improved if forecasters pay more attention to news originating from outside their respective countries. This is particularly the case for Canadian and French forecasts, which would gain by paying greater attention than they do to news from the USA and Germany, respectively. Copyright © 2006 John Wiley & Sons, Ltd.

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