Factor-Augmented Bridge Models (FABM) and Soft Indicators to Forecast Italian Industrial Production

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• 作者：Alessandro Girardi ; Barbara Guardabascio and Marco Ventura
• 刊名：Journal of Forecasting
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：35
• 期：6
• 页码：542-552
• 全文大小：150K
• ISSN：1099-131X

文摘

This paper presents a new forecasting approach straddling the conventional methods applied to the Italian industrial production index. Specifically, the proposed method treats factor models and bridge models as complementary ingredients feeding a unique model specification. We document that the proposed approach improves upon traditional bridge models by making efficient use of the information conveyed by a large amount of survey data on manufacturing activity. Different factor algorithms are compared and, under the provision that a large estimation window is used, partial least squares outperform principal component-based alternatives. Copyright