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Forecasting Ability of Confidence Indicators: Evidence for the Czech Republic
 Herrmannová, Lenka ; Horváth, Roman (advisor) ; Mikolášek, Jakub (referee)
This thesis assesses the usefulness of confidence indicators for short term forecasting of the economic activity in the Czech Republic. The predictive power of both the business confidence indicator and the customer confidence indicator is examined using two empirical approaches. First we predict the likelihood of economic downturn defined as a discrete event using logit models, later we estimate GDP growth out of sample forecasts in the framework of vector autoregression models. The results obtained from the downturn probability models confirm the ability of confidence indicators (especially the business confidence indicator) to estimate the current economic situation and to anticipate economic downturn one quarter ahead. Results from the out-of-sample GDP growth value forecasting are ambiguous. Nevertheless the customer confidence indicator significantly improved original forecasts based on a model with standard macroeconomic variables and therefore we conclude in favour of its predictive power. This result was indirectly confirmed by OECD as the Czech customer confidence indicator has been included as a new component in the OECD domestic composite leading indicator since April 2012.
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