Shock Hunting: The Relative Importance of Industry‐Specific, Region‐specific and Aggregate shocks in the OECD Countries

Abstract

A common argument against monetary union is that it precludes stabilization of economies through monetary and exchange rate policy. We address this point by calculating the relative empirical importance of industry-speci¢c, country-speci¢c and aggregate disturbances using a comparable international data set comprising annual data from 1971 to 1993 for 19 OECD countries and 25 two-digit industries. The evidence seems to suggest that the country-speci¢c shocks have declined over the last 20 years.

Real and Monetary Challenges to Wage Policy in Germany at the Turn of the Millennium: Technical Progress, Globalization and European Monetary Union

“…The study by Karras (1996) analyzes European OECD countries for the time period from 1951 to 1990 and concludes that country-specific shocks were more important than common ones. In contrast to this result, Funke et al (1999) show that the relevance of countryspecific shocks has decreased while world-wide shocks gained in importance.…”

Monetary Union and the Economic Geography of Europe

“…According to Funke, Hall and Ruhwedel (1999) country specific shocks are far more important than common international and industry-specific shocks, suggesting that the degree of volatility introduced to an economy through industry specific shocks is quite low.…”

The sources of decentralised output fluctuations in France

“…Using the same methodology and annual one‐digit sectoral data for eight European countries, Bayoumi and Prasad (1997) estimate variance shares of 19%, 16%, 18%, and 47% for European, country‐specific, industry‐specific, and idiosyncratic shocks. With a data set comprising annual data for 19 OECD countries and 25 two‐digit industries, Funke et al. (1999) estimate that the international, country‐specific, industry‐specific and idiosyncratic effects explain 12%, 25%, 11%, and 52%, respectively, of nation‐industry variation.…”

“…Many papers use error‐component models to evaluate the influence of regional and industrial factors on output movements (see for instance Bayoumi and Prasad 1997;De Nardis et al. 1996; Funke et al. 1999; Ramos et al.…”