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Inflation

Copyright © 1998-2000, 2003-2017 by David E. Ross

In planning for my retirement, one important factor I considered is how inflation impacts both my pre-retirement income — which determines my future Social Security benefits, my employer's pension benefits, and how much I can afford to invest — and my need for post-retirement income. I hear on the news about inflation, but I never hear how it is measured. Therefore, I created my own measure — something tied both to the national economy and to the local cost of living.

To measure inflation, I use both the consumer price index (CPI, which tracks how much money I will need to maintain some standard of living) and the producer price index (PPI, which tracks the underlying costs of bringing goods to the retail market). I obtain these from the U. S. Bureau of Labor Statistics (BLS).

I view both current inflation (over the past 12 months) and long-term inflation (over the entire period in which comparable indices are available).

Living in southern California, I am affected by local economic trends in Los Angeles. Thus, besides considering national indices, I also consider the local CPI for Los Angeles. For those not living in this area, the table below includes the latest month's national inflation based on the same methodology that I use for local inflation.

Inflation Computed From BLS Statistics for January 2017, a Year Earlier, and July 1986
Current Inflation (annual rate over the past 12 months) Long-Term Inflation (annual rate since 1986) Combined
PPICPI USCPI LA Infl USInfl LA PPICPI USCPI LA Infl USInfl LA Infl USInfl LA
4.4%2.5%2.1%3.4%3.3% 2.1%2.6%2.7%2.4%2.4% 2.9%2.9%

Recent values of current and long-term U.S. inflation are plotted below.

plot of recent values of current and long-term U.S. inflation

Methodology

Current Inflation is computed from non-adjusted indices over a one-year span (i.e.: to the report month from the corresponding month in the prior year). By using year-to-year data, I eliminate the need for seasonal adjustments, which are sometimes questionable.

Long-Term Inflation is computed from non-adjusted indices from July 1986. For all three indices, I use the rate that would yield the current value if compounded annually from the base period. NOTE WELL: As the time-span for Long-Term Inflation gradually increases in one-month increments, the results gradually show less variability than does Current Inflation.

In July 2008, I changed the computation of LA Infl values when I noticed a very large increase in the PPI caused the local rate of inflation in the Los Angeles metropolitan area to be smaller than the national rate of inflation even though the CPI-LA index had a larger increase than the CPI-US index. Obviously, this was wrong. I now use the following:

In September 2014, I changed the computation of the long-term Los Angeles CPI. I had been using a base of February 1969 with a value of 36.0. This was a 45-year-old base. Instead, I now use the same July 1983 with the same value of 100 that I use for the long-term PPI and national CPI, a 31-year-old base. This caused long-term inflation for Los Angeles to approximate more closely long-term national inflation.

In June 2016, I changed the computation of all long-term factors. Having a span of 33 years masked systemic, non-short-term changes in the United States economy. I now use a base of July 1986, which still gives less variability than the year-to-year values. In the chart, this change results in an imperceptible discontinuity in the long-term plot between May and June, marked with a vertical blue line in the plot.

I use geometric means because they are usually a better representation of the "average" of percentages than the more common arithmetic means.

The PPI index (WPU00000000) is for all commodities. Generally, this is initially reported as preliminary and subject to revision. My tabulation is not revised if the final value does indeed change. Many estimates of inflation ignore producer prices, using only consumer prices. However, the PPI index reflects future changes in consumer prices; it is also a component of inflation in the national economy even if it is not a component of inflation currently seen by consumers.

The CPI indices are for all urban consumers for all items. The CPI-US index (CUUR0000SA0) is the U. S. city average. The CPI-LA index (CUURA421SA0) is for Los Angeles, Orange, and Riverside Counties in California. It was suggested that I use CWUR0000SA0 and CWURA421SA0, which include housing components, instead of CUUR0000SA0 and CUURA421SA0, which do not. However, the CWUR series are for "Urban Wage Earners and Clerical Workers" and thus exclude spending patterns of the self-employed, salaried workers, and retirees. The CUUR series are for "All Urban Consumers". The CUUR series is thus more reflective of my own situation — formerly salaried and now retired. The omission of housing components from the CUUR series has negligible impact on my situation since I have owned my house for over 40 years and do not plan to move.

Interpreting the Results

Because of this methodology, Current Inflation reports what happened over the past 12 months; it cannot be used to project future inflation. Long-Term Inflation, however, reports what happened over more than 30 years; while it cannot be used to project near-term future inflation, it may be used to project long-term future inflation since month-to-month fluctuations in PPI and CPI values have only minor effects. Combined Inflation might be used for a very approximate projection of intermediate-term future inflation since it smoothes the fluctuations in near-term values by combining them with stable long-term values; nevertheless, such a projection should be used only with caution. I use Combined Inflation when I need a single estimate that covers both the near-term and far-term.

Manipulating the Indices

The BLS is an agency within the Department of Labor, part of the President's cabinet. Thus, there are occasional pressures to "adjust" the indices for political purposes.

The most frequently discussed adjustment for the CPI is substitution. This involves monitoring how consumers change their spending habits in response to inflation, changing the way the CPI is computed accordingly. For example, if the rising costs of food mean that we are forced to eat more hamburger and less steak, the significance of steaks in the CPI is reduced while the significance of hamburgers is increased. As a result, the CPI does not rise as much. This manipulation would hide the degradation of our standard of living caused by inflation. A recent (2011) version of this is called chained CPI and is being proposed for use in adjusting Social Security benefits. This, of course, would subject seniors to an ongoing reduction in their standard of living. Michael Hiltzik, a columnist for the Los Angeles Times wrote a lengthy criticism of chained CPI.

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CPI values are now reported to six significant digits. Given the fact that these indices are based on surveys of fluctuating costs and then subjected to seasonal adjustments, knowing the values to 1 part in 1,000,000 is not possible. This is just an example of an attempt to give more credence to statistics than can be justified.

In recognition of the fact that accuracy to even three significant digits is problematical, the table above reports only to the nearest tenth of a percent instead of the previous hundredth.

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Such manipulations are not the only way politics becomes involved with the indices. The President's administration (all Presidents, not merely the current one) will sometimes select the most favorable index when discussing the nation's economy. Thus, during soaring prices for food or fuel, only the core CPI (which omits those two items) is mentioned. During a decline in the real estate markets, the CWUR CPI series is cited because it makes inflation appear less; conversely, during a real estate boom, the administration may tend to cite the CUUR series, which omits the inflationary impact of rising housing costs.

An article on the front page of the Los Angeles Times "Business" section on 20 May 2010 raised the spectre of deflation. It cited a month-to-month (March to April 2010) decrease of 0.1% in the CPI and a year-to-year (April 2009 to 2010) increase of 0.9%. From March 2010 to April 2010, however, the CWUR0000SA0 increased 0.2%; the year-to-year increase was 2.24%. Both of those CWUR0000SA0 changes clearly did not indicate deflation. The statistics in the Los Angeles Times article were taken from a BLS press release in which core CUUR CPI changes were reported after seasonal adjustments. Thus, the article fostered fear over deflation by citing statistics that are doubly flawed: they involve highly subjective seasonal adjustments and they omit food and fuel costs, which are among the most significant recurring expenses for consumers.

There is no perfect measure of inflation.


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While the data from the US BLS seems to be in the public domain, my copyright on this page applies to the text, the table and computed values therein, and the graphic plot.

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