Unexpectedly Intriguing!
07 April 2009

Kitov, March 2009, U.S. CPI Annual Rates and Cumulative Rates since 1965 What if all you needed to project the rate of inflation within a nation was to simply know how the size of its labor force changed?

That's the intriguing concept we're following up on today, as we've constructed a tool to do the math originally developed by Ivan Kitov, which he finds might be applied to several nations. To use the tool, you'll need to collect the following information for your nation of interest:

  1. Historic or projected civilian labor force data spanning two consecutive years.
  2. Nation-specific coefficients (equivalent to the slope and y-intercept of a linear equation).
  3. The corresponding time lag between change in labor force and change in inflation observed for the nation in question.

And that's it! We've set the tool up with data for the United States, including civilian labor force data for 2006 and 2007, which we obtained from the BLS, which is a bit different from that available from the OECD that Kitov used to build his regression model. We'll have additional comments below the tool.

Civilian Labor Force Data
Input Data Values
Year of More Recent Average Civilian Labor Force Data
Average Civilian Labor Force for Year Indicated [thousands]
Preceding Year's Average Civilian Labor Force [thousands]
Country-Specific Data
Multiplier [Equivalent of Slope]
Base [Equivalent of y-Intercept]
Observed Time Lag [years]

Projected Value of Inflation
Calculated Results Values
Projected Rate of Inflation
Year for Projection

Earlier this year, Ivan and Oleg Kitov published a paper that presents the coefficient data for a number of different countries: Unemployment and in ation in Western Europe: Solution by the Boundary Element Method. The table below provides the country-specific data that might be used in the tool above:

Country Specific Data
Nation Inflation Measure Multiplier Intercept Typical Time Lag [years]
Austria (since 1986) GDP Deflator 1.25 0.0075 0.0
Austria (1965-1987) GDP Deflator 2.0 0.033 0.0
Canada CPI (OECD) 2.58 -0.0043 2.0
Germany CPI (OECD) -1.71 0.41 6.0
Japan GDP Deflator 1.31 0.0007 0.0
Netherlands* GDP Deflator 3.5 -0.03 3.0
Sweden CPI (OECD) -1.3 0.13 0.0
Switzerland (since 1986) CPI (OECD) 1.1 0.005 2.0
Switzerland (1965-1987) CPI (OECD) 2.01 0.055 2.0
United States CPI (OECD) 4.5 -.031 2.0
United States GDP Deflator -4.0 -0.03 2.0
* Data might be improved by applying a 3-year moving average to calculated values.

Using this method for projecting the future rate of inflation, Kitov finds that the quality of the forecast is highly dependent upon the quality of the underlying data. Over time, changes in how this data is measured can produce significant deviations between forecast and realized values. In the paper cited above, Kitov also finds that forecasts might be improved if unemployment rate data is incorporated into the formulation, which the tool we've presented above does not do.

We observe that the time lag between labor force change and a corresponding change in the inflation rate is not necessarily stable over time. For example, in looking at the U.S. data, for which a 2-year lag typically applies, we find that this lag may vary anywhere from 0 to 3 years.

We'll conclude this post by noting that while the rate of inflation may have a strong demographic component to it, a nation's monetary policy may also influence its rate of inflation. The relevance of that concept is especially true today given the extreme actions taken by many of the world's central banks. In a paper from March 2006, Ivan Kitov offered the following observation that really stands out given today's circumstances. (In the following quotation, "PID" refers to Personal Income Distribution, and the two year lead time he references applies for the U.S.; we've added the boldface emphasis):

Labor force change is a potential candidate for describing the process of personal attempts to advance in the PID. The second section describes the process and provides empirical facts supporting this concept. One of the findings is that the labor force change leads inflation by two years. Therefore, this causality principle excludes the current inflation value from being controlled by some contemporary means including monetary ones. One cannot exclude "insane" behavior of some monetary authorities, however, such as flooding an economy with money. This is not the case for the USA, but it happens sometimes in countries in transition. In our opinion, the driving force for such "strange" behavior is the redistribution of personal incomes in a new way after failure of the old economic and social organization. One can observe a fast evolution of PID in former socialist countries during the last 15 years from a truncated "socialist" version to a wide "capitalist" one.

Since Kitov lived through the transition of the Soviet Union to modern Russia, I don't think he ever expected such "strange behavior" by monetary authorities ever would apply to the U.S. These would then appear to be very strange times.

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Welcome to the blogosphere's toolchest! Here, unlike other blogs dedicated to analyzing current events, we create easy-to-use, simple tools to do the math related to them so you can get in on the action too! If you would like to learn more about these tools, or if you would like to contribute ideas to develop for this blog, please e-mail us at:

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