Evidence on Wage Inequality, Worker Education, and Technology

To explain these patterns, a variety of theories have been advanced, including those stressing the growth of international trade, changes in institutions (e.g., declining unionization and real minimum wage), rising immigration, and technological change. Growing levels of imports into the United States, for instance, may have hit workers in tradesensitive industries (e.g., textiles and apparel) particularly hard as domestic labor demand and, consequently, wages have dropped.3 Rising immigration since the 1960s may also have contributed to these trends by increasing the supply of lessskilled workers in the U.S. labor market (Borjas, Freeman, and Katz, 1997). In addition, because unionization is often associated with wage compression (Fortin and Lemieux, 1997), declining rates of union membership in the United States may have contributed to rising earnings disparity.4 T he rapid rise of U.S. wage inequality in recent decades has produced a sizable literature both documenting the empirical trends and theorizing about their causes.1 The main empirical findings can be summarized by three basic patterns. First, the overall distribution of hourly and weekly earnings across all workers in the economy has grown wider. Second, consistent with this rise, the wage gaps between workers with different levels of education, especially between college graduates and workers with no more than a high school diploma, have also increased. This rise in “betweeneducation-group” earnings disparity, however, accounts for only a modest fraction of the rise in overall wage dispersion because of the third pattern: The variance of wages among workers with the same level of education has also grown.2 The rise in U.S. wage inequality over the past two decades is commonly associated with an increase in the use of “skill-biased” technologies (e.g., computer equipment) in the workplace, yet relatively few studies have attempted to measure the direct link between the two. This paper explores the relationship among inequality, worker education levels, and workplace computer usage using a sample of 230 U.S. industries between 1983 and 2002. The results generate two primary conclusions: First, this rising inequality in the United States has been caused predominantly by increasing wage dispersion within industries rather than between industries. Second, within-industry inequality is strongly tied to both the frequency of computer usage among workers and the fraction of total employment with a college degree. Both results lend support to the idea that skill-biased technological change has been an important element in the rise of U.S. wage inequality.