Download or read book The Inter-Industry Effect of Productivity on Employment written by Jin Woong Kim and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of technology improves the efficiency of the production process and increases the competitiveness of the commodity produced in general. Considering an open economy, technology raises a price and a quality competitiveness of domestic goods in the international market. Therefore, technology innovation is known to be one of the most essential factors in economic growth. However, there are two different views regarding to the effects of technology on employment. A negative insight of technology on employment insists that a simple labor-saving technology innovation like the introduction of automated equipment increases value-added at the expense of unskilled labor. On the contrary, technology innovation in some industries causes ultimate growth in the industry, and subsequently requires more employment. This is the income effect of technology innovation. Besides technology innovation in some industries spills over into other industries, leads to their growth, and brings about positive inter-industry effects from the technology. These two insights regarding to the technology effect on employment have been cited in the previous literature. First, with the negative aspects, Gali (1999) shows that positive technology innovation reduced U.S. total work hours in the short run. Francis and Ramsey(2005) and Basu, Fernald, and Kimball(2006) also suggest that an aggregate technology shock can reduce the use of labor, investment and real interest rates, even in the short run. And Canova, Lopez-Salido, and Michelacci(2007) suggest that a possible reason for this mechanism is “search friction” in the labor market. Kim, Choi, and Lee (2007) investigate the effects of labor productivity shocks on employment in aggregate, manufacturing, services, ICT, and non-ICT industries using 1993~2006 data in Korea. They show that a productivity shock in an industry reduces employment of the industry in the short run, but the positive transmission effects of productivity on employment exist from non-ICT innovation to ICT employment. Choi and Lee(2008) provide that employment was reduced, especially in for unskilled jobs, by technological development and globalization during the years 1991~2007 in Korea. They estimate that the reduction was 11,000 job positions as an annual average.6) Kim(2008b) insists that the technology innovation in Korea has had a labor saving feature. As empirical evidence, he showed the negative relationship between productivity and employment using panel model with 1993~2007 data.However, some studies show that the effect of technology on employment can be positive. The idea is based on the theory of RBC(Real Business Cycle), of which technology innovation increases employment as well as production. Related past studies are summarized in Christiano et al.(2003) and Uhlig (2004).8) Kim(2001)9) provides that there has been no significant employment reduction effect in Korea since 1970 using the empirical method of Gali (1999). Also, Kang(2006)10) uses the same empirical method with Gali(1999) and shows that the effects of technology innovation on employment can be different across industries. The effects were significantly positive in manufacturing, but insignificant in services.This paper investigates the effect of productivity on employment and also tests whether the effect has changed from the year 2000. In particular, the paper attempts to include the inter-industry effect of productivity on employment. The initiative of considering inter-industrial effect of productivity starts from Kim and Kim(2008)11) which investigates the effect of total factor productivity on investment and employment and shows two different empirical results by model specification; the effect was positive using national level data, but was negative using industry panel data. We have outlined the purpose of the paper and related studies in this first section. In section 2, the data for the empirical analysis is described. Section 3 and section 4 show the empirical model specifications for analysis and the subsequent results. Section 5 provides the conclusion and implications from the empirical results.