Heterogeneous effects of competitiveness shocks on macroeconomic performance across euro area countries

Abstract

This paper considers how competitiveness impacts macroeconomic performance in 11 euro area countries. VAR models are estimated for the individual countries using quarterly data from 1995Q4 to 2013Q4. Besides unit labour costs as a competitiveness measure, the models include GDP, the current account balance and domestic credit. The empirical analyses show that changes in unit labour costs help explain GDP dynamics in the short and medium term in most countries, whereas they have little explanatory power for the current account balance or domestic credit for most countries. Overall, the effects of the unit labour costs vary substantially across the countries in the euro area. The heterogeneity suggests that policy measures aiming to improve economic growth, correct current account imbalances and ensure financial stability need to take country‐specific features into account.

Convergence towards a single economic model? Italy and Germany in the interconnected euro system

“…Moreover, the trajectory of NULC in Italy primarily is the effect of larger price increases, in particular in the sheltered sector, and does not reflect excessive wage pressures (Hopkin 2015, Molina & Rhodes 2007. Given these measurement issues, it is not too surprising that research has failed to detect a clear relation between export performance and the development of NULC (Gaulier & Vicard 2013;Staehr & Vermeulen 2018). Table 4 reviews the OECD's indicators for labour market and product market reform since the mid-1980s in Italy and Germany.…”

The export performance of the euro area: A panel quantile regression approach

“…They consider that wage cuts are relatively ineffective in dealing with a current account deficit, as productivity growth triggers wage growth. Staehr and Vermeulen (2019) analyse the impact of competitiveness on the macroeconomic performance of 11 euro-area countries. The VAR models for individual countries are estimated using quarterly data for the period 1995Q4 to 2013Q4.…”