The variables used in the empirical literature on the topic of how monetary policy affects the economy are often highly aggregated. Typically, among others, these variables include GDP, inflation, and unemployment. Less frequently, the literature addresses this topic using more disaggregated, sector level variables. As a result, it is a challenge to find estimates of the differential impact that a change in a policy variable, such as the Federal Funds rate, has on the magnitude and time path of unemployment in diverse sectors from manufacturing to services, and in occupations from laborer to manager. This deficit in the literature is problematic because there is evidence that unemployment often falls unevenly across sectors and occupations.
For instance, according to a recent report on the 2001 recession by the Bureau of Labor Statistics (BLS) [2003], after reaching a 30 year low of 3.8 percent in April 2000, unemployment jumped to 6.1 percent by May 2003. After peaking in February 2001, the private sector lost 3.1 million jobs by May 2003. This represented nine million unemployed people. The bulk of these losses occurred in the manufacturing sector, which lost 2.6 million jobs over the same period. On the other hand, the service sector gained more than one half million jobs during this time. Obviously, models that only use aggregate unemployment cannot adequately address this disparity.
To the extent that monetary policy contributes to episodes of higher unemployment, updated models that estimate its disparate impacts should be readily available. The purpose of this paper is to contribute to filling this gap.
The paper is organized as follows. In the next section, a brief literature review is offered. The following section contains a discussion of some of the relevant theory. Then, the empirical results are presented. The last section consists of a summary and conclusions.
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