We provide evidence showing, for the first time, that the sensitivity of real wages to the business cycle is much stronger for higher-wage workers than for lower-wage workers. Using matched employer-employee data for Portugal covering the period 1986-2021, we show that a one percentage point increase in the unemployment rate is associated with a decrease in real hourly wages of workers in the 90th percentile of the conditional wage distribution of around 1.3%, contrasted with 0.8% for those in the 10th percentile. This gap is even larger for newly hired workers – the estimates for the 90th percentile workers are double of those in the bottom decile. This pattern also holds for bargained wages and the wage cushion.
These results can be explained by composition effects and heterogeneous sensitivities of firms and collective bargaining agreements (CBAs) to the cycle. First, the considerable gap in new hires' cyclicality arises mostly from match quality fluctuations over the business cycle and is sharply attenuated after we account for job match composition. Second, by estimating cyclicality coefficients for each firm/CBA, we find that firms and CBAs tend to provide a lower degree of insurance against aggregate cyclical fluctuations to higher paid individuals. These findings provide strong empirical evidence on the role of business cycles as amplifiers of inequality trends.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.