Tradability and Productivity Growth Differentials Across EU Member States

Abstract

This study examines the lack of convergence among EU countries from a structural perspective. We apply the tradable-non-tradable framework (T-NT) to evaluate the heterogeneity in labour productivity before and after the great recession. We find that, across all countries, non-tradables were less relevant for aggregate productivity. The low productivity growth in peripheral EU countries was accompanied by a specific structural change pattern: there was a sharp production increase of non-tradables before the crisis relative to other EU countries. For most peripheral countries concerns about unfavourable sector structures remain, implying a continuation of unsustainable growth patterns. This has implications for the European Commission's macroeconomic imbalance procedures, since it allows identifying patterns of real divergence on a disaggregated level. Finally, we identify a link between sectoral growth asymmetries and the quality of domestic governance institutions. Especially differences in the legal system help to explain the observed productivity growth differentials.

Structural Modeling and Forecasting Using a Cluster of Dynamic Factor Models

“…Moreover, structural change might turn a previously tradable sector into a nontradable one, and vice versa. We follow the approach to the sectoral classification in Friesenbichler and Glocker (2019), determine the nominal value added for tradable goods and nontradable goods and calculate the corresponding deflators, which allows us to determine the real value added of these two categories.…”

Nontradable Goods and Fiscal Multipliers

“…We classify sectors according to their level of tradability making use of the work of Friesenbichler and Glocker (2019). Utilising input-output (IO) data within an approach that allows for a change in the classification for sectors over time, Friesenbichler and Glocker (2019) construct quarterly data for the share of nontradable goods (τ , the value added of nontradable goods producing sectors relative to total value added) for the period ranging from 1999 to 2019.…”

“…We classify sectors according to their level of tradability making use of the work of Friesenbichler and Glocker (2019). Utilising input-output (IO) data within an approach that allows for a change in the classification for sectors over time, Friesenbichler and Glocker (2019) construct quarterly data for the share of nontradable goods (τ , the value added of nontradable goods producing sectors relative to total value added) for the period ranging from 1999 to 2019. 1 Figure 1 shows the share of nontradable goods for EU28 countries in relation to different measures of openness: (i) the sum of exports and imports relative to GDP multiplied by one half (ϑ), (ii) the export share (ξ), and (iii) the import share (ν).…”

“…Data. The data used to construct the quarterly measures for tradable and nontradable goods production, as well as for sectoral price deflators, are from the EURO-STAT database (further details are provided by Friesenbichler and Glocker, 2019) the GDP deflator is used as price measure. The trade balance is defined as the ratio between exports (Exports of goods and services at constant prices (ESA 2010-code: P.6))…”