STATISTICAL BULLIES IN WASHINGTON USE PHONY MATH TO REDUCE SOCIAL SECURITY AND OTHER BENEFITS IMPORTANT TO SENIORS & THE POOR*

My last post – January 9th – generally explained some of the statistical gimmicks utilized by the Bureau of Labor Statistics to suppress the consumer price index and consequently reduce cost of living increases for a broad array of retirement programs.  Redefining how the CPI is calculated amounts to a cut in benefits for retirees – including veteran retirement, disability, and Social Security.  This is a big deal.  The cuts we are talking about are not small.

According to my fellow activists and good friends Nancy Altman and Eric Kingson of Social Security Works, the decrease resulting from a so-called “chained CPI” will impact Social Security beneficiaries thusly:  the typical beneficiary will lose $500 by age 75, $1,000 by age 85, and $1500 by age 90 (see their Huff Post article at http://www.huffingtonpost.com/eric-kingson/chained-cpi-social-security_b_2376108.html).  Nancy and Eric are both nationally recognized leaders in the field of Social Security.  Nancy has written one of the two leading histories of the Social Security system and is considered one of the three leading contenders for the Social Security Administrator position.  She will be guest on Sharon Lockhart’s KKFI program “Every Woman” at 3:00 PM on Saturday, January 12th.

This post explains the current methodology for calculating the CPI.  Even without further unfair suppression of cost of living through the chained CPI gimmick, the working classes, poor, and seniors are now losing ground due to unfair and invalid methods for calculating price increases and their impacts on subgroups of the population.

The Current CPI:  Bad Math Foisted on the American Public by Statistical Bullies

I am not approaching the issue of the CPI from the vantage point of a “mainstream economist,” but rather as a statistician. It is obvious to me that the statistical approaches to calculation of the CPI are invalid and seriously disadvantage the elderly, the poor, and to a lesser, but still serious, extent middle income workers. I will explain how certain categories of goods are weighted and how this is one of the major reasons the CPI calculation is unfair to particular groups of Americans.

It seems as though BLS officials and a group of conservative economists have engaged in some “inside the beltway wankery” to snow the public with abstruse “hedonic regression models” and other forms of mathematical dissimulation.  This is in actuality a form of bullying.  Economists and public officials pushing their agenda with patently absurd pseudoscience know that only a very tiny proportion of the population will have the expertise and mathematical wherewithal to counter what seems to them (the public) to be illogical on its face.

People know what they are paying for housing, food, health care, utilities, and a broad array of other goods and services necessary for meeting basic needs.  A large segment of the U.S. population – especially those at the lower income levels – know that their costs of living increased more than the official 1.8% in 2012.

Statistical bullies use abstruse mathematical concepts to foist unfair public policy on the poor and middle income wage/salary classes and seniors.  Manipulating the CPI and keeping it artificially low works to the advantage of the super-rich and mega-corporations, i.e. the power elite. This is a much bigger deal for the economic well-being of the masses than is commonly understood by most people.

This blog post will discuss math that most everyone understands.  What I present below should be devastating to any argument for reducing Social Security benefits through manipulation of the CPI.  This type of material is a real “eye glazer” for most people.  However, as I said, it is a big deal and push back is critical for stopping the economic deterioration of the middle and low income classes and retirees.  Please let me know if you have any questions in the comments sections below.

The Market Basket & the Weight Given to Categories of Goods & Services by the BLS

For the most part, the BLS determines prices of goods and services through a massive data collection process (mainly through a survey of businesses).  Prices are collected on thousands of goods and services, which are grouped into categories such as “food,” “energy,” “apparel,” “shelter,” “medical care services,” “transportation services,” and “education” – to name a few.

Within each of these general categories are more specific goods and services.  For instance, within “transportation service,” one will find public transportation, within which one will find “intercity bus fare.” Each category is assigned a weight.  All weights must sum to 100.  For instance, food is weighted 14.175; energy is weighted 10.184.  The weight for “medical care services” is 5.387.  These weights also provide a clear idea of what the BLS thinks is the proportion of each good or service in a consumer’s budget.

As already mentioned, the BLS calculation of the overall increase in consumer prices between November 2011 and November 2012 was 1.8%.  Also, as already discussed, not all items in the market basket contributed equally to this “overall” increase in the CPI.  Here’s how it works:

“Medical care services” are weighted by the BLS at 5.378, which is .05378 or 5.378% of the total.  Health care services increased 3.7%.  The contribution of this 3.7% increase to the overall increase is (.05378 * 3.7)/1.8 = .12 or 12% of the overall increase.

How were the 5.378 weight and 3.7% increase in medical care services derived?  Within medical care services one will find three major subcategories: “professional services,” “hospital and related services,” and “health insurance,” weighted 2.987, 1.749, and .651 respectively.  These weightings sum to the overall weight for medical care services of 5.378.  The percentage price increases were as follows: professional services = 2.0, hospital and related services = 4.4, and health insurance = 11.2.

The 3.7% increase in medical services is derived as follows:

[(2.987/5.378) * 2.0] + [(1.749/5.378) * 4.2] + [(.651/5.378) * 11.2] = 3.7.

The problem with this methodology is this:  different subsets of a population have very different budgets, which do not reflect the BLS market basket based on an aggregated total.  A senior on Medicare must spend $300 per month on premiums for Part B, Medigap, and Part D or have co-pays and deductibles. The increase in the Part B deductible from Social Security checks has been practically double the rate of inflation for the past 10 years.  Furthermore, as discussed next in this post, some of the commodities and services such as city services, public transportation, child care, tuition, and others that have had the highest percentage increases are weighted low by the BLS but loom large in the budgets of the working classes and seniors.

Why Is the BLS CPI So Low When You Feel So Much Pain From Price Increases?

The low CPI of 1.8% for the past year was low for four reasons:

  1. The BLS weights categories based on the ratio of purchases in each category to the quantity of purchases overall.  For instance, energy purchases accounted for 10.184% of all purchases but had a low percentage annual increase of .3 or three tenths of 1%
  2. Goods and services with the highest percentage increases had the lowest weightings.  For instance, health insurance increased by 11% – the highest of any category (it is actually a subcategory of “medical care services) – but has been assigned a weight of .651% by the BLS.
  3. The weights assigned to each category are based on aggregated data and do not consider subsets of the population.  A poor person’s budget (as well as a senior citizen’s on a fixed income) will reflect far different proportions (weights) for high percentage increase items such as bus fare, tuition, child care, and city services (sewer, water, and trash pickup).
  4. In a down economy – which we have had in the past year – sales of apparel items, new vehicles, appliances, and other commodities are slow.  Retail outlets will be more likely to move these commodities through sales and other mechanisms for keeping prices low.Indeed prices for transportation commodities (less motor fuel) increased only .1% or one-tenth of one percent.  These mostly big ticket items are not as likely to be in the market basket of poorer Americans and retirees dependent upon Social Security.  And yet, these commodities comprise approximately 20% of the market basket weights.

Consider the following market basket categories:  “water, sewer, and trash collection,” “intercity bus fare,” “elementary and high school tuition & fees,” and “child care and nursery school,” which had price increases of 6.9%, 4.8%, 3.5%, and 2.6% respectively.  Along with medical care and health insurance mentioned above, these expenditures have a major impact on working family and retiree budgets.  However, they are weighted 1.187% (“water, sewer, and trash collection), .147% (intercity bus fare), .368% (tuition & fees), and .386% (child care).

Summary

The explanation of the CPI in this post focuses on only one facet of mathematical problems with calculation of the overall increase in prices.  However, the weighting of various commodities and services is a much bigger cause of unfairness of the CPI relative to poorer people and retirees on fairly low fixed incomes than the current brouhaha over the chained CPI – although that is a serious problem.

I was inspired to begin a discussion and explanation of the CPI by members of Jobs & Justice – a progressive activist group comprised of economic faculty, labor leaders, business persons, and other activists who have joined together to develop a strategy for economic justice.  At a meeting the other night, members of the group discussed a need for helping the public understand what the BLS methodologies are doing to their economic well-being.

Hopefully, this post will provide some clarity to the issue.  It is not easy to reduce the CPI to a short post.  The Tallgrass Activist will continue to explicate the basics of the CPI and their implications for working families and retirees.

*CPI data referenced in this post can be found at http://www.bls.gov/news.release/pdf/cpi.pdf