petar sorić, ivana lolić: economic uncertainty and its impact on the croatian economy public sector economics 41 (4) 443-477 (2017)

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This paper analyzes the domestic and external inflation determinants for eight non-eurozone new EU member states (NMS). The empirical literature has been rather silent on the comparison of the relative importance of domestic vs. foreign inflation determinants. This paper aims to fill this gap and add to the literature by several methodological and empirical contributions. Empirical analysis is based on the structural vector autoregression (SVAR) model. It enables the authors to decompose inflation into its domestic and foreign component via historical decomposition analysis. Results indicate that foreign shocks are a major factor in explaining inflation dynamics in the medium run, while the short run inflation dynamics is mainly influenced by domestic shocks. Moreover, the importance of the foreign inflation component has had a rising trend in the pre-crisis period in all NMS, while the start of that trend mostly coincided with their accession to the EU. The global financial crisis seems to have decreased the importance of the foreign inflation component, although the results vary across countries. Since foreign shocks proved to be a very important determinant of inflation in NMS, the main policy implication of this study is the need to augment the classical Taylor rule with foreign factors in case of small open economies.

In the last five decades the European Economic Sentiment Indicator (ESI) has positioned itself as a high-quality leading indicator of overall economic activity. Relying on data from five distinct business and consumer survey sectors (industry, retail trade, services, construction and the consumer sector), ESI is conceptualized as a weighted average of the chosen 15 response balances. However, the official methodology of calculating ESI is quite flawed because of the arbitrarily chosen balance response weights. This paper proposes two alternative methods for obtaining novel weights aimed at enhancing ESI's forecasting power. Specifically, the weights are determined by minimizing the root mean square error in simple GDP forecasting regression equations; and by maximizing the correlation coefficient between ESI and GDP growth for various lead lengths (up to 12 months). Both employed methods seem to considerably increase ESI's forecasting accuracy in 26 individual European Union countries. The obtained results are quite robust across specifications. Key wordsBusiness and Consumer Surveys, Economic Sentiment Indicator, Nonlinear Optimization with Constraints, Leading Indicator JEL classification C53, C61, E32, E37 AbstractIn the last five decades the European Economic Sentiment Indicator (ESI) has positioned itself as a high-quality leading indicator of overall economic activity. Relying on data from five distinct business and consumer survey sectors (industry, retail trade, services, construction and the consumer sector), ESI is conceptualized as a weighted average of the chosen 15 response balances. However, the official methodology of calculating ESI is quite flawed because of the arbitrarily chosen balance response weights. This paper proposes two alternative methods for obtaining novel weights aimed at enhancing ESI's forecasting power. Specifically, the weights are determined by minimizing the root mean square error in simple GDP forecasting regression equations; and by maximizing the correlation coefficient between ESI and GDP growth for various lead lengths (up to 12 months). Both employed methods seem to considerably increase ESI's forecasting accuracy in 26 individual European Union countries. The obtained results are quite robust across specifications.

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