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AbstractDeparting from the mainstream literature on European monetary integration, we acknowledge the interdependence of economic sentiment synchronisation and business cycle co‐movements for 17 European countries and the euro area (EA). Building on national accounts and survey data, we find non‐negligible evidence that sentiment cycles are the driving force behind general economic cycle synchronization. We demonstrate that recent EA acquisitions have witnessed an intensification of cycle synchronization with the EA core after the introduction of a common currency, corroborating the beneficial effects of the Eurosystem. Our results show a certain degree of dependence on the business cycle. The synchronization of 17 examined countries vis‐à‐vis the EA is mostly of equal magnitude or even more intensive during recessions than in expansions. In other words, the common monetary policy of the European Central Bank (ECB) should be able to effectively act as a countercyclical tool when an individual economy is facing a recession.

The literature on the political business cycle (PBC) suggests that politicians systematically manipulate economic conditions in order to increase their chances of re-election. The list of variables that have been found to have a significant effect on the probability of re-election includes macroeconomic (inflation rate, unemployment rate, output growth rate) and fiscal (budget balance, level of expenditures and tax revenues) outcomes. This paper focuses on the question whether price and non-price competitiveness indicators together with consumer confidence index have a statistically significant effect. Thus, this paper addresses two empirical questions. First, in light of the globalisation process and on-going comparisons among national economies, could price and non-price indicators serve as a proxy for voters when deciding on whether to penalise or reward the incumbent? And second, based on the economic theory of voting, is consumer confidence index a better indicator of re-election probability compared to unemployment and output growth rates? Using a dataset of EU member states over the 2000-2015 period and by applying probit/logit analysis we test both questions.

This paper is a follow-up on the Economic Policy Uncertainty (EPU) index, developed in 2011 by Baker, Bloom, and Davis. The principal idea of the EPU index is to quantify the level of uncertainty in an economic system, based on three separate pillars: news media, number of federal tax code provisions expiring in the following years, and disagreement amongst professional forecasters on future tendencies of relevant macroeconomic variables. Although the original EPU index was designed and published for the US economy, it had instantly caught the attention of numerous academics and was rapidly introduced in 15 countries worldwide. Extensive academic debate has been triggered on the importance of economic uncertainty relating to the intensity and persistence of the recent crisis. Despite the intensive (mostly politically-motivated) debate, formal scientific confirmation of causality running from the EPU index to economic activity has not followed. Moreover, empirical literature has completely failed to conduct formal econometric testing of the Granger causality between the two mentioned phenomena. This paper provides an estimation of the Toda-Yamamoto causality test between the EPU index and economic activity in the USA and several European countries. The results do not provide a general conclusion: causality seems to run in both directions only for the USA, while only in one direction for France and Germany. Having taken into account the Great Recession of 2008, the main result does not change, therefore casting doubt on the index methodology and overall media bias.

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.