Forecasting Private Consumption by Consumer Surveys

Dreger, Christian; Kholodilin, Konstantin A.

doi:10.2139/ssrn.1691590

Cited by 3 publications

(2 citation statements)

References 17 publications

(10 reference statements)

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“…Sentiment indicators are often considered to be among the most important leading indicators of the real economy (Dreger and Kholodilin, 2013) and are therefore closely followed by business cycle analysts, central banks and business owners (Vuchelen, 2004, Claveria et al, 2007, Martinsen et al, 2014. However, studies on the predictive power of sentiment indicators find mixed results.…”

Section: Introductionmentioning

confidence: 99%

“…However, studies on the predictive power of sentiment indicators find mixed results. While many studies find that sentiment indicators have predictive power for future economic developments (Kumar et al, 1995, Hansson et al, 2005, Lemmens et al, 2005, Abberger, 2007, Klein and Oezmucur, 2010, Christiansen et al, 2014, others conclude that sentiment indicators provide only limited information for predicting economic variables (Cotsomitis and Kwan, 2006, Claveria et al, 2007, Dreger and Kholodilin, 2013and Bruno, 2014).…”

Section: Introductionmentioning

confidence: 99%

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

Wilms

Gelper

Croux

2016

European Journal of Operational Research

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Wilms

Gelper

Croux

2016

European Journal of Operational Research

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Consumer sentiments across G7 and BRICS economies: Are they related?

Gil-Alana,

Abakah,

Carmona-González

et al. 2024

J Econ Finan

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This paper utilizes fractional integration and cointegration techniques to investigate the stochastic properties of the bilateral linkages between the Consumer Sentiment Index (CSI) of eight developed economies, Australia, Canada, France, Germany, Italy, Japan, the UK and the US and five emerging economies comprising Brazil, Russia, India, China and South Africa, for the time period from 15th January 2010 to 15th July 2019. The univariate results support fractional integration with mean reverting behaviour, with many of the series displaying orders of integration in the interval (0, 1), which connotes that shocks to consumer sentiment have significant long-lasting though reverting effects. From the covariate results and testing for cointegration, we found evidence of cointegration for Australia versus Italy, and France versus Italy. For the BRICS, the only evidence of fractional cointegration is found between Russia and India. Some policy implications of the results obtained are also mentioned at the end of the article.

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