Month: March 2015

What’s a pension band?

A pension band is a figure that is used when calculating the monthly benefit for a defined benefit pension program.  A pension band figure, which is typically changes each year, is generally a dollar amount that the person will receive monthly for each year of service with the employer when they retire..  The pension band generally varies by job title/grade level/occupation covered by a pension plan.. Once assigned, the job title, grade level and occupation will generally remain in that band unless the job title, grade level and occupation (by location) are later reclassified to a different pension band.

Example of Basic Monthly Benefit Calculation.

The following hypothetical example shows how a basic monthly benefit is calculated assuming: •

You are in pension band 115.

The monthly benefit for pension band 115 is $55.49

In this example, the monthly benefit for a person with 30 years of credited service would be

Monthly benefit for pension band 115 ($ 55.49 Multiplied by 30 years of net credited service x 30 Basic monthly benefit =  $1,664.70

Comparsion of CPS matched data sets – Millmet et al (2002) to Steward and Gaylor (2015)

Big Data. Bureau of Labor Statistics. Survey data. Employment Big Data.  Those are all things that calculating worklife expectancy for U.S. workers requires.  Worklife expectancy is similar to life expectancy and indicates how long a person can be expected to be active in the workforce over their working life.  The worklife expectancy figure takes into account the anticipated to time out of the market due to unemployment, voluntary leaves, attrition, etc.

Overall the goal of our recent work is to update the Millimet et al (2002) worklife expectancy paper and account for more recent CPS data. Their paper uses data from  the 1992 to 2000 time period. Our goal is to update that paper using data from 2000 to 2013. The main goal of the paper is to see if estimating the Millimet et al (2002) econometric worklife models with more recent data changes the results in the 2002 paper in any substantive way.

 

Our approach is two fold.  First we matched the BLS data cohorts based on the Millimet et al. (2002) and Peracchi and Welch (1995) papers. In a nutshell the CPS matching routine involves matching incoming and outgoing cohorts across a given year.  Once the data is matched, we then look at the work status of the individuals to determine if they were active or in active across the year that they were interviewed by the BLS. . We were able to create a match CPS data set of 201,797 individuals where as the Millimet et al. (2002) found 200,916 matched individuals.

Table 1. Comparsion of CPS cohort matched data sets
Year Millimet et al.  (2002) Steward and Gaylor (2015)
1992/93 37,709 36,652
1994/95 34,418 33,377
1996/97 31,691 32,739
1997/98 32,276 32,972
1998/99 32,083 32,893
1999/2000 32,739 33,164
Total 200,916 201,797

Notes:

The CPS data was matched using the algorithm similar to Millimet et al (2002) and Peracchi and Welch (1995).  Households in rotation 1-4 were matched using the household identifier number to the same household in rotations 5-8 of the following year. Individuals had to have the same sex, race and be a year older in rotation 5-8 to be determined a match.

 

CPI falls faster than medical care commodities while medical services rise from Dec to Jan

cpi

general_inflation_2015_1

The consumer price index (CPI) went down from 236.284 in December 2014 to 234.677 in January 2015, an annualized rate of 8.16%.

medical_commodities_2015_1medical_services_2015_1

The price index for medical care commodities went down at an annualized rate of 3.37% from December 2014 to January 2015. During the same period, the price index increased for medical care services (0.98%), hospital and related services (0.59%), and professional services (2.09%).

Source: BLS

Image source: http://www.shutterstock.com/pic-54762670/stock-photo-background-concept-illustration-consumer-price-index.html