published in: Journal of Labor Economics, 2004, 22 (2), 397-430
By exploiting establishment-level data, this paper sheds new light on the sources of the changes in the structure of production, wages, and employment that have occurred over the last several decades. We investigate the following two related hypotheses. First, that most of the recent increase in the dispersion of wages and productivity has occurred across establishments and these changes are linked. Second, that the increased dispersion in wages and productivity across establishments is linked to differential rates of technological adoption across establishments. Our findings are largely supportive of these hypotheses. Specifically, we find that (1) the between-plant component of wage dispersion is an important and growing part of total wage dispersion; (2) much of the between plant increase in wage dispersion is within industries; (3) the between-plant measures of wage and productivity dispersion have increased substantially over the last few decades; and (4) a significant fraction of the rising dispersion in wages and (to a lesser extent) productivity is accounted for by changes in the distribution of computer investment across plants as well as changes in the wage and productivity differentials associated with the computer investment.
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.