TY - JOUR
T1 - The predictive power of the business and bank sentiment of firms
T2 - A high-dimensional Granger causality approach
AU - Wilms, I.
AU - Gelper, S.E.C.
AU - Croux, C.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
U2 - 10.1016/j.ejor.2016.03.041
DO - 10.1016/j.ejor.2016.03.041
M3 - Article
SN - 0377-2217
VL - 254
SP - 138
EP - 147
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 1
ER -