The Predictive Power of the Business and Bank Sentiment of Firms: A High-Dimensional Granger Causality Approach

26 Pages Posted: 4 Sep 2015

See all articles by Ines Wilms

Ines Wilms

KU Leuven - Department of Applied Economics

Sarah Gelper

KU Leuven - Faculty of Business and Economics (FEB)

Christophe Croux

KU Leuven - Faculty of Business and Economics (FEB)

Date Written: 2015

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

Suggested Citation

Wilms, Ines and Gelper, Sarah and Croux, Christophe, The Predictive Power of the Business and Bank Sentiment of Firms: A High-Dimensional Granger Causality Approach (2015). Available at SSRN: https://ssrn.com/abstract=2655559 or http://dx.doi.org/10.2139/ssrn.2655559

Ines Wilms (Contact Author)

KU Leuven - Department of Applied Economics ( email )

Leuven, B-3000
BELGIUM

Sarah Gelper

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Christophe Croux

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

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