This article investigates the determinants of non-performing loans for a panel of EEC countries and the implications for the real economy, covering the period 2005-2017. Among the determinants, the paper proposes macroeconomic factors, banking sector variables, and cost and governance indicators. Additionally, the paper explores the extensive use of macroprudential measures in these countries. Using a panel with fixed effects and a dynamic GMM estimator, the results support the existing findings that adverse macroeconomic developments are generally associated with higher non-performing loans, while increases in NPLs have a rather transitory effect on the real economy and credit. NPL ratios increase if macroeconomic conditions deteriorate, while an improvement in the government effectiveness reduces them. A more profitable and better capitalized banking sector generally leads to lower NPLs. Moreover, countries with higher past credit growth rates witnessed higher NPLs in the periods that followed. These results support the use of macroprudential measures for increasing the resilience of borrowers, such as limits on the indebtedness level (such as debt service-to-income, DSTI or loan-to-value, LTV caps), as tools to temper the credit cycle.
The present paper aims at developing a better understanding of how the industrial sectors in different countries influence each other and how developments on western markets impact the growth rates of emerging economies, with a focus on the CEE region. Applying a framework developed by Diebold and Yilmaz (2009), we assess bilateral spillovers between a large set of EU members' Industrial Production Indices and find that, after the downturn episode of 2009-2011, spillover effects have significantly grown in importance. Therefore, we estimate an Industrial Production Spillover Index and assess whether including the index in a BVAR forecasting framework can lead to an increase in forecast accuracy, for selected CEE states (the Czech Republic, Poland, Hungary and Romania). Using multiple calibration strategies to ensure robustness, we find an overall increase in forecasting accuracy for Hungary, followed by the Czech Republic and Romania, where the results are mostly positive in favor of including the index, but also depend on the choice of the calibration methodology. Conversely, the results for Poland show that the augmented model offers lower forecast accuracy, in all the considered cases. Our main policy recommendation is related to assessing whether information related to industrial sector spillovers is relevant in explaining real growth dynamics and potentially including this information in the overall framework for monitoring macroeconomic policy. The policy implications brought by spillover effects highlight certain fragilities of the CEE economies, which are especially vulnerable in case of a slowdown in industrial activity in the Western EU states.
This paper analyses the volatility of retail fuel prices in nine different EU countries and the spillover effects between fuel prices across selected countries from Central and Eastern Europe and the Eurozone over the 2008-2019 period. In particular, we use the GARCH-GJR model in order to investigate fuel price volatility and identify potential asymmetric dynamics. Moreover, in order to assess the links between fuel prices across countries, we estimate a VAR model and compute spillover measures using the Generalised Forecast Error Variance Decomposition (GFEVD) approach formulated by Diebold and Yilmaz (2009). Our results provide evidence of weak links between retail fuel prices across EU countries, with slightly higher spillovers originating from some developed economies such as France and Italy.
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