Academic journal article Seoul Journal of Economics

Technical Change, Heterogeneity in Skill Demand, and Employment Polarization

Academic journal article Seoul Journal of Economics

Technical Change, Heterogeneity in Skill Demand, and Employment Polarization

Article excerpt

We explore how the rapid adoption of computer-related assets affects the recent polarization of employment in the U.S. labor market, which is inconsistent with the skill-biased technological change hypothesis. Similar to Goos and Manning (2007). we show that the job polarization could be explained by the routinization hypothesis of Autor, Levy, and Mumane (2003). Our empirical analyses confirm that the newly adopted computer-related capitals change the demands for three types of skilled workers heterogeneously, leading to a polarization in employment structure.

Keywords: Computerization, Skill Demand, Polarization

JEL Classification: J21, J24, O30

I. Introduction

In the 1990s, the employment patterns in the U.S. labor market changed dramatically. During the period 1979-1989, employment growth has monotonically increased in terms of occupation rank: the share of employment below the median occupation declined, whereas the employment share above the median occupation increased. The monotonie pattem, however, has changed toward a certain polarized structure in occupational employment growth after that period (Autor 2010).

Autor, Levey and Mumane (2003) and Autor, Katz and Kearney (2006) show that a polarized employment structure exists in the recent U.S. labor market, characterized by the fastest growth of high-skilled jobs, the slowest growth of middle-skilled jobs, and the moderate growth of low-skilled jobs. Specifically, the authors explore how the employment growth measured based on changes in shares of occupations has changed against initial occupational skill in the United States. These measurements demonstrate that the employment growth in the 1980s has monotonically increased with skill distribution as opposed to the employment growth in the 1990s, which presents a polarized pattern of employment.

Before this polarized employment structure in the U.S. labor market emerged in recent years, much research in the literature focused on the effects of technological change on the labor market (Acemoglu 1999; Acemoglu 2002; Allen 2001; Autor, Katz and Kearney; Berman, Bound and Machin 1998; Card and DiNardo 2002: Kim and Min 2006). In particular, the effects of technological change on the labor market (e.g., wage inequality or structural change of employment) have been explained primarily by skill-biased technological change (SBTC). This implies a bias in favor of skilled workers or more educated workers against unskilled workers. Many studies show positive correlations between the capital intensity based on the newly advanced technology and skilled workers (Berman, Bound and Grilliches 1994; Goldin and Katz 1996; Johnson 1997; Levy and Mumane 1996; Machin and Reenen 1998), thus supporting the SBTC hypothesis.

The recent patterns of polarized employment growth, however, significantly differ from the SBTC hypothesis of monotonie shifts in skill demand from a lower skill distribution toward a higher distribution. That is, these monotonie patterns are compatible no longer with the polarized structural changes of employment in the U.S. labor market. Thus, more effective models are required to analyze these new patterns in the labor market. In this regard, Autor et cd. (2003) provide a simple theory to explain how changes in employment structure are related to advances in computer-related technology, claiming that investments in computerization would be the rationale behind the structural changes in polarized employment.

With the questions of what computers do in the workplace, what tasks they would perform efficiently, and whether they complement or substitute for human labor inputs, Autor et cd. (2003, 2006) argue that computer-related assets would displace workers in carrying out the tasks which can be performed by well-programmed rules or specific manuals (what they call routine tasks), and complement workers in con- ducting nonroutine tasks such as problem-solving jobs or abstract tasks. …

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