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UP539 March 10, 2009. Employers “buy” labor power from workers. Supply-side. demand-side. Workers “sell” their labor power to employers. Workforce development. Economic development. Employers “buy” labor power from workers. Supply-side. demand-side.
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Employers “buy” labor power from workers Supply-side demand-side Workers “sell” their labor power to employers Workforce development Economic development
Employers “buy” labor power from workers Supply-side demand-side Workers “sell” their labor power to employers Bringing jobs and local residents together Workforce development Economic development
Career ladders: institutional and human capital ladders • Within and across firms, within and across regions, within (and across) occupations • Relate to specific vs. general human capital
whatshould we invest in (i.e., sustain)? NATURE (natural capital) ECONOMY (capital) LABOR (human capital) SOCIETY (social capital) Capital = creates the capacity to generate new capital in the future the ability to reproduce / sustain
Persons Not in the Labor Force (Household Survey Data) • About 2.1 million persons (not seasonally adjusted) were marginally attached to the labor force in February, 466,000 more than a year earlier. These individuals wanted and were available for work and had looked for a job sometime in the prior 12 months. They were not counted as unemployed because they had not searched for work in the 4 weeks preceding the survey. Among the marginally attached, there were 731,000 discouraged workers in February, up by 335,000 from a year earlier. Discouraged workers are persons not currently looking for work because they believe no jobs are available for them. The other 1.3 million persons marginally attached to the labor force in February had not searched for work in the 4 weeks preceding the survey for reasons such as school attendance or family responsibilities.
1 Data refer to persons who have searched for work during the prior 12 months and were available to take a job during the reference week. 2 Includes thinks no work available, could not find work, lacks schooling or training, employer thinks too young or old, and other types of discrimination. 3 Includes those who did not actively look for work in the prior 4 weeks for such reasons as school or family responsibilities, ill health, and transportation problems, as well as a small number for which reason for nonparticipation was not determined
Other concepts 1 • Labor force = employed + unemployed • Labor force participation rates (LFPR) = labor force / civilian non-institutional population • Civilian non-institutional population • Included are persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces. (Current Population Survey) • Unemployed: • Persons aged 16 years and older who had no employment during the reference week, were available for work, except for temporary illness, and had made specific efforts to find employment sometime during the 4-week period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed. • Unemployment rate = unemployed / labor force Labor force Under 16 Employed unemployed Not in LF Institutional pop or active duty Total population Civilian non-institutional population
Source: U.S. Bureau of Labor Statistics, Employment and Earnings, monthly, January 2008 issue; Monthly Labor Review, November 2007; and unpublished data.
Table 788. Individuals Employed in Science and Engineering (S&E) Occupations as Share of Workforce, 2007. Source: U.S. Bureau of Labor Statistics, May 2007 National Occupational Employment and Wage Estimates
Table 788. Individuals Employed in Science and Engineering (S&E) Occupations as Share of Workforce, 2007. Source: U.S. Bureau of Labor Statistics, May 2007 National Occupational Employment and Wage Estimates
The Spatial Division of Labor on a Regional Scale BLOOMFIELD HILLS Family Income: $200,000+ Families in Poverty: 2% Management, professionals: 71% Production, transport, material moving: 2% FLINT Family Income: $31,424 Families in Poverty: 23% Management, professionals: 21% Production, transport, material moving: 25% ANN ARBOR Median Family Income (1999): $71,293 Percent of Families in Poverty (1999): 5% Occupation: Management, professionals (in percent, 2000): 61% Occupation: Production, transport, material moving (in percent, 2000): 4% DETROIT Family Income: $33,853 Families in Poverty: 22% Management, professionals: 22% Production, transport, material moving: 23% YPSILANTI Family Income: $40,793 Families in Poverty: 17% Management, professionals: 30% Production, transport, material moving: 10% Source: U.S. Census Bureau, Census 2000 Summary File 3, Matrices P49, P50, and P51;
FLINT Family Income: $31,424 Families in Poverty: 23% Management, professionals: 21% Production, transport, material moving: 25% DETROIT Family Income: $33,853 Families in Poverty: 22% Management, professionals: 22% Production, transport, material moving: 23% BLOOMFIELD HILLS Family Income: $200,000+ Families in Poverty: 2% Management, professionals: 71% Production, transport, material moving: 2% The Spatial Division of Labor on a Regional Scale Source: U.S. Census Bureau, Census 2000 Summary File 3, Matrices P49, P50, and P51; ANN ARBOR Median Family Income (1999): $71,293 Percent of Families in Poverty (1999): 5% Occupation: Management, professionals (in percent, 2000): 61% Occupation: Production, transport, material moving (in percent, 2000): 4% YPSILANTI Family Income: $40,793 Families in Poverty: 17% Management, professionals: 30% Production, transport, material moving: 10% http://www.metroresearch.org/
Two data tables* BLS: OCCUPATIONAL PAY COMPARISONS AMONG METROPOLITAN AREAS, 2007 [two pages]* BLS: Unemployed persons by occupation and sex, 2007-8 [1 page]Answer these questions:1. What occupations seem to have the lowest and highest unemployment levels? Is there a difference by gender?2. Are there geographic patterns in occupational pay? (e.g., big metro vs. small metro areas?). 3. Do metro areas in general seem to reward (i.e., have higher pay for) some occupations over others? (i.e., the metropolitan return on human capital….). If so, what is the pattern?