We propose a modelling approach based on a set of small-scale factor models linked together in a cluster with linkages derived from Granger causality tests. GDP forecasts are produced using a disaggregated approach across production, expenditure and income accounts. The method combines the advantages of large structural macroeconomic models and small factor models, making our cluster of dynamic factor models (CDFM) useful for large-scale model-consistent forecasting. The CDFM has a simple structure, and its forecasts outperform those of a variety of competing models and professional forecasters. In addition, the CDFM allows forecasters to use their own judgment to produce conditional forecasts.

We present an uncertainty measure that is based on a business survey in which uncertainty is captured directly by a qualitative question on subjective uncertainty regarding expectations. Uncertainty perceptions display persistence at the firm level and changes are associated with past business assessments and expectations. While our uncertainty measure correlates with commonly used alternatives, it is superior in forecasting and suggests a larger role of uncertainty shocks for aggregate fluctuations. Its informational content is highest when considering smaller firms or firms with a low growth rate. Our results confirm the feasibility of constructing uncertainty measures from business survey questions that elicit information on uncertainty of respondents directly.

This study assesses the effects of reserve requirements on the probability of bank failure and compares them to those of capital requirements. While both requirements affect banks' balance sheets and lending rates similarly, their effects on financial stability can differ markedly. When adjustment in deposit rates is constrained, the cost effect arising from higher reserve requirements may incentivise banks to choose riskier assets rendering worse financial conditions. Borrowers' moral hazard problem augments these adverse effects. They are mitigated when considering imperfectly correlated loan-default as higher interest revenues from non-defaulting loans curb losses from defaulting loans.

We apply the tradable-nontradable framework to evaluate the lack of convergence in labour productivity among EU Member States. Our results show that increases in overall productivity are primarily due to the tradable and not the nontradable sectors of production. The low productivity growth in peripheral EU countries before the crisis was accompanied by a sharp increase in the production of nontradables (i.e., nontradable goods and services) relative to other EU countries. We identify differences in the legal systems and the quality of public institutions, among others, as factors relevant for explaining the observed productivity growth differentials. Our findings have implications for the European Commission's macroeconomic imbalance procedures since the tradable-nontradable approach allows identifying patterns of real divergence on a disaggregated level.

While all EU economies witnessed a sharp decline in output during the financial crisis, the peripheral EU countries were particularly hard hit. This is surprising, given their sound macroeconomic performance prior to the crisis. It became obvious that imbalances had been building up underneath a seemingly tranquil macroeconomic surface. We argue that the underlying mechanisms are mirrored by productivity developments in a tradable-non-tradable framework. Countries that were severely affected not only exhibited low productivity growth in tradables (e.g., manufacturing), but also experienced a sharp increase in the production of non-tradables (e.g., real estate) before the crisis.