The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach

Ines Wilms, Sarah Gelper and Christophe Croux

No 504661, Working Papers of Department of Decision Sciences and Information Management, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven

Abstract: We study the predictive power of industry-specific economic sentiment indicators for future macro-economic developments. In addition to the sentiment of firms towards their own business situation, we study their sentiment with respect to the banking sector - their main credit providers. The use of industry-specific sentiment indicators results in a high-dimensional forecasting problem. To identify the most predictive industries, we present a bootstrap Granger Causality test based on the Adaptive Lasso. This test is more powerful than the standard Wald test in such high-dimensional settings. Forecast accuracy is improved by using only the most predictive industries rather than all industries.

Keywords: Bootstrap; Granger Causality; Lasso; Sentiment surveys; Time series forecasting (search for similar items in EconPapers)
Date: 2015
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Published in FEB Research Report KBI_1520

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Related works:
Journal Article: The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:ete:kbiper:504661

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