عمر مهني (مصطلح)

التعمر المهني من مقالة Occupational Age Structure and Access for Older Workers. Barry T. Hirsch, David A. Macpherson, Melissa A. Hardy. Industrial and Labor Relations Review, Vol. 53, No. 3 (Apr., 2000), pp. 401-418 http://www2.gsu.edu/~ecobth/PaperReprints/AgeStructure_OlderWorkers.pdf

حسب مرحلة وظيفية محددة مثل الوصول لمنصب كبير أو التقاعد. وتتواجد عدة معايير علمية لحساب التعمر المهني.

• The static age distribution can be readily measured. For descriptive purposes, we use worker age at the 90th (P90), 50th (P50), and 10th (PIO) percentiles to identify "old" and "young" occupations. Although median age is a standard measure, it provides limited information about the age distribution of workers
• Age5O+, representing the proportion of workers in an occupation who are 50 or over. Age5O+ = Compmixc(x + SkillsI3a + Conditionst + XV + e .
• Hire5O+ (proportion of older new hire) represents the proportion of workers by occupation who are "new" hires in a company, defined here as workers with 5 or fewer years of company tenure who are age 50 and over. HireSO+ provides a measure of the age structure among recent hires. Hire50+ = Compmixax +Skillsfib + Conditionst b + Xrb + eb
• Open50+ (the ratio of the proportions of older new hires to older workers) equal to Hire50+/Age50+, it represents an index measuring the openness or accessibility of an occupation to older new hires, relative to the number of existing older workers
• age dispersion (CV(Age))
• size, number of old or young workers (P90 or Pl0), occupations with the oldest workers (a high P90) etc

• نتيجة هامة: Among men, occupations with the oldest workers (a high P90) tend to be those requiring few physical demands, flexible hours and schedules, and, for the most part, low skill and training requirements (for example, crossing guards, messengers, private guards, and taxi and bus drivers). Chief executives andjudges are exceptions to the generalization regarding skills, presumably because skills in these occupations depreciate slowly. Most of the occupations with high P9Os also hire a high proportion of older workers, as compared to the economy-wide mean for Hire5O+, which is .10. Interestingly, many "old" occupations (for example, messengers, parking lot attendants, and private guards) have high age dispersion and many young workers, PIO being below the economy-wide mean of 23. Occupations with low training requirements and high physical demands or undesirable hours tend to employ young but not older workers (for example, stock handlers and baggers, cooks). Well-paidjobs requiring lengthy training tend to have few young and few old workers, the latter result owing to retirement combined with little new hiring of older workers. For example, skilled administrative and managerial occupations have low age dispersion. The accessibility measure Open5O+ (the ratio of the proportions of older new hires to older workers) is largely unrelated to age (the correlation of Open50+ and P90 is .03), and obtains some of its highest values in occupations with few older workers (for example, recreation workers and food counter workers). Occupations requiring substantial training tend to have low accessibility for older workers (the correlation of Open5O+ and firm training is -.26). We obtain similar patterns among women

• A striking result is the statistically significant effect of wage tilt on the age structure. Occupationswith steeper profiles, aln W/alnEXP, are less likely to have a high proportion of older workers (Age5O+) and less likely to hire older workers (Hire5O+).
• Wage tilt also is associated with occupations that are less open or accessible to older new hires, measured by the ratio of older new hires to older incumbents (Open5O+). This finding provides support for implicit contract theories predicting relative underpayment of young and overpayment of older workers relative to productivity (see, relatedly, Hutchens 1986). It also helps explain both the barriers older workers face in obtaining employment and the substantial earnings losses among older displaced workers. As predicted, higher wage occupations are found to be associated with older work forces, but with substantially less age dispersion.
• Skill variables are systematically related to the age structure, but the type of skill matters. As seen above, the occupational wage (skill) level is associated positively with age and negatively with age dispersion. Occupations with firm-provided training, those requiring high numerical aptitude, and those with high computer use have fewer older male workers. Although higher skill requirements are generally associated with lower age dispersion, computer use and numerical aptitude (among men) are exceptions, being associated with greater dispersion due to a large concentration of young workers. Occupations requiring computer use not only employ few older workers, but also are less accessible to older workers, at statistically significant levels, than are other occupations (that is, lower Open5O+, as well as Age5O+ and Hire5O+). Occupations requiring high numerical aptitude exhibit the same pattern, but only among men, not women.
• A broad generalization that emerges is that the older work force is relatively highskilled, but not strong in quantitative skills. Older workers are unlikely to select or be selected for jobs providing substantial onthe-job training or requiring computerbased skills.
• Occupations with a high proportion of employees working long hours (more than 42 hours a week) have male and female work forces that are older but less age-dispersed. Occupations with high proportions of part-time male and female workers tend to have a more dispersed age distribution, and higher proportions of older workers and older hires
• Variable Definitions and Sources
  • P90 Age at the 90th percentile of the age distribution. CPS-ORG, 1983-95.
  • P50 Age at the 50th percentile of the age distribution. CPS-ORG, 1983-95.
  • P1O Age at the 10th percentile of the age distribution. CPS-ORG, 1983-95.
  • Age5O+ Proportion of workers who are age 50 or over. CPS-ORG, 1983-95.
  • CV(Age) Coefficient of variation of the age distribution (100 times the standard deviation divided by the mean). CPS-ORG, 1983-95.
  • HireSO+ Proportion of workers with 5 years or less of company tenure who are ages 50 and over. Six CPS supplements containing information on company tenure (time with current employer): January 1983, May 1983, January 1987, May 1988, January 1991, and April 1993.
  • Open5O+ Ratio Hire50+/Age50+.
  • ln(Wage) Mean of log wage in 1995 dollars. CPS-ORG Male W&S, 1983-95.
  • alnW/alnExp Wage equation regression coefficient on log of potential experience (Age-Schooling-6), estimated by occupation. Schooling and other premarket control variables included in the regression. Represents wageexperience elasticity. CPS-ORG Male W&S, 1983-95.