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

Ines Wilms, Sarah Gelper and Christophe Croux

European Journal of Operational Research, 2016, vol. 254, issue 1, 138-147

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: 2016
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Citations: View citations in EconPapers (13)

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Working Paper: The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:254:y:2016:i:1:p:138-147

DOI: 10.1016/j.ejor.2016.03.041

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