Krueger (1997) is the only study in this survey to focus on the 1990s, defined in his data as 1989 through 1994. He follows the methodology of both Lawrence and Slaughter and Sachs and Shatz by regressing industry product-price changes on direct factor employment. Specifically, he follows Sachs and Shatz by using the fraction of production workers by industry, measured as the average over the years 1989, 1990, and 1991. He also runs this regression both with and without a dummy for the computer industry.
In addition, Krueger also follows Leamer and Baldwin and Cain by regressing a set of crossindustry zero-profit conditions expressed as changes to estimate mandated factor-price changes that can then be compared with actual factor-price changes. Unlike Leamer and Baldwin and Cain, Krueger does not attempt in any way to attribute observed product-price changes between trade and non-trade causes. Thus, his mandated-wage specification looks as follows. Electronic Payday Loans Online
Krueger’s data cover the 150 four-digit SIC manufacturing industries which have at least 75 percent of their output going to final consumer demand–i.e., “finished processor” industries. The product prices are the domestic producer prices like those used in many of the earlier studies. In his cost-share matrix Krueger includes more-skilled labor, less-skilled labor, capital, and materials. Thus, like Leamer he accounts for intermediate inputs as suggested by equation (3”). For equation (K-1) Krueger uses the nonproduction-production classification; for robustness he also uses average worker educational attainment by industry merged in from the CPS. To calculate industry cost shares of less-skilled labor in equation (K-2) Krueger multiplies industry total employment by the average annual earnings of a high-school dropout and then divides this product by industry value of shipments. More-skilled cost shares are calculated as total payroll less this product all divided by industry value of shipments. All regressions are estimated with weighted least squares using 1988 value of shipments as weights.