Précis
Welfare, work, and location
Analyzing skill content
Measuring ‘core’ inflation
There are many obstacles to the transition from welfare to work. A recent study by Harry J. Holzer and Michael A. Stoll under the auspices of the Brookings Center on Urban & Metropolitan Policy explore the impact of the often-divergent locations of low-skill jobs and welfare recipients seeking work. Their paper, "Meeting the Demand: Hiring Patterns of Welfare Recipients in Four Metropolitan Areas," describes this "spatial mismatch" as most typically a case of the welfare-recipient population living in segregated inner-city neighborhoods, while jobs are most plentiful in suburban neighborhoods.
Holzer and Stoll use data from the Census Bureau and the results of a survey of employers in Chicago, Cleveland, Milwaukee, and Los Angeles to overlay the locations of new low-skill jobs and the location of populations at highest risk of welfare receipt. They found that, despite the facts that welfare recipients are often located far from the suburban locations of jobs and that suburban employers were more willing to hire recipients, in fact "employers in the central city and near public transit fill higher proportions of their low-skill jobs with welfare recipients."
In general, the willingness of employers to hire welfare recipients in either case is not very high in absolute terms—neither suburban nor central city employers reported more than 2 percent of job openings to be available to welfare recipients. Holzer and Stoll observe, however, that these opportunities represent "considerable demand" for such workers relative to the number of welfare recipients actually entering the labor force.
Many examinations of the demand for skills in the labor market depend on measures of the educational attainment of job incumbents to measure the level of skills needed for a particular occupation. David A. Autor, Frank Levy, and Richard J. Murnane provide a task-based analysis of skill demands in their NBER working paper, "The Skill Content of Recent Technological Change: An Empirical Exploration."
By measuring skills in terms of tasks as defined in the Dictionary of Occupational Titles rather than in terms of credentials, they are able to examine more directly how computerization affects work content. This examination is used to show "the mechanisms undergirding the widely-documented observation that computers and education are relative complements." In general, the computer allows the more rapid and efficient completion of the routine procedures of the information processing or cognitive tasks that require relatively high degrees of educational attainment.
The task-based metrics also are used to understand how technical change has changed the balance between the cognitive and manual content of jobs since 1960. They report, "The proportion of the labor force employed in occupations that made intensive use of non-routine cognitive tasks—both interactive and analytic—increases substantially." These are the tasks that generally require the skills represented by credentials of higher education. Autor, Levy, and Murnane also quantify a sizable impact of these changes in the increased demand for workers with relatively high levels of educational attainment.
Policymakers and economic analysts need good current measures of the underlying trend in inflation. The overall Consumer Price Index (CPI) may sometimes include unusual price changes in some components that might obscure the underlying trend. Thus is born the need for a measure of "core" inflation that ignores short-term relative price changes and focuses on the common, persistent components that are necessary for more accurate inflation forecasts.
In the Federal Reserve Bank of Kansas City’s Economic Review, Todd E. Clark evaluates five such measures of core inflation based on CPI data. The measures he studies are the CPI excluding food and energy, the CPI excluding energy only, the median CPI, a "trimmed" mean CPI (the components largest and smallest changes for the month are excluded), and a CPI excluding the eight components with the histories of highest volatility.
While Clark admits that none of these indicators are perfect, his analysis suggest that the CPI excluding energy and the trimmed mean CPI best meet the joint requirements of tracking current trend inflation, predicting future inflation at 1- and 2-year horizons, and being easy to communicate to the public. The trimmed mean was the most accurate tracker of current trend inflation and a powerful predictor of future inflation, but would be somewhat more difficult to explain to the public. The CPI excluding energy would be much more transparent and is also a powerful predictor of future inflation, but does not track current trend inflation as well as the trimmed mean.
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