How does monetary policy work? While one aspect of the investigation has focused on the behaviour of consumers, another has concentrated on the behaviour of companies faced with the kind of financial pressure associated with tight monetary policy. The general focus in this area is on the impact of financial constraints on investment expenditures including fixed capital and inventories. Our purpose is to shift this focus somewhat and to concentrate on the impact of financial pressure on other aspects of company behaviour. We first discuss briefly the theoretical background and the empirical formulation. Then, using panel data on a large number of UK companies, we derive a number of results.
This paper empirically investigates the changes in inter-industry wage differentials between 1995 and 2002 across a number of EU countries: Belgium, Germany, Greece, Hungary, Ireland, Italy, Netherlands, and Spain. Our focus is to investigate the extent to which these inter-industry wage differentials and their evolution have been driven by macroeconomic developments such as competitiveness and exposure to international trade or to labour market institutions. We also investigate the importance of sectors' ability to pay and unobserved workers' ability as potential determinants of inter-industry wage differentials. Wage differentials are estimated using the so called Structure of Earnings Survey data (SES); a unique dataset of matched employer-employee data, collected from a large sample of firms in each country and comparable across countries. The paper provides evidence of the existence and persistence of industry wage differentials in European countries, additionally it does not find any indication of unobserved ability being one of the determinants. The initial regression results attempting to explain the change in the differentials between the two points in time suggest that there is some correlation with labour market developments, but also with the ability of industries to pay higher wages.Keywords: inter-industry wage differentials JEL Classification: J31, J41 * This paper is part of the Wage Dynamic Network (WDN) research. We are very grateful to our WDN colleagues for their comments and support. The support and help of Frank Smets and of our ECB colleagues in DG-Statistics were essential to gain access to five of the SES data sets used in the paper. We are also grateful to Rebekka Christopoulou who provided excellent research assistance and to Andrew McCallum and Ladislav Wintr for initial help with the data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.