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

Ines Wilms*, Sarah Gelper, Christophe Croux

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Web of Science)

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.
Original languageEnglish
Pages (from-to)138-147
Number of pages10
JournalEuropean Journal of Operational Research
Volume254
Issue number1
DOIs
Publication statusPublished - 1 Oct 2016
Externally publishedYes

Keywords

  • Bootstrap
  • Granger Causality
  • Lasso
  • Sentiment surveys
  • Time series forecasting
  • ECONOMIC TIME-SERIES
  • CONSUMER CONFIDENCE
  • MACROECONOMIC FORECASTS
  • VARIABLE SELECTION
  • GROWTH
  • CRISES
  • INFORMATION
  • CONSUMPTION
  • HYPOTHESIS
  • DIFFUSION

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