Nasty tricks with inflation in Japan

Consumer price index is a common measure of the overall price change in modern economies, which represents a broader indicator of the cost of living. For Japan, this measure has become extremely important during the last decade because of its very low if not negative value. Economists usually panic when cost of living decreases. Price deflation is a major danger for long term economic growth since bank credits (read investments) are highly suppressed.  Everybody knows: no investment -  no growth.  Hence, any news about positive inflation is welcome and no tricks are bed to get this news.

Figure 1 shows the evolution of two integral inflation measures for Japan: the cumulative CPI inflation and the cumulative GDP deflator (DGDP).  The latter covers all prices in a given economy, while the CPI only a part of them related to consumer goods and services. By definition, the DGDP should nest all CPI items, but the CPI is calculated in a different way based on a basket of goods and products with their shares fixed over a few years. In that sense, the CPI does not follow all economic changes up.

The graphs in Figure 1 are different from inflation indices expressing the absolute change in price level. The cumulative inflation time series describes the relative change in the overall price.  The difference between the DGDP and CPI is dramatic and increases since 1974. From 1974 to 2012, the difference between the cumulative inflation reached 0.37, and the rise in CPI inflation is by ~50%  larger than that in the DGDP.

What is the reason?

The DGDP plays a different role in economics. This is the most important value for real GDP growth. Real GDP is not a measured macroeconomic variable, but rather the ratio of the nominal GDP and the GDP price deflator. Larger DGDP values give smaller real GDP. 

So, this is very important to keep the DGDP as low as possible and the CPI as high as possible. This is a   nasty trick which, mathematically, must result in negative absolute prices of all goods and services not in the CPI.  Do not trust the CPI estimates in Japan. Figure 2 shows two countries without such a dramatic difference between CPI and DGDP: Austria and France. In the USA, the difference between CPI and DGDP has been also increasing since 1978 (Figure3). But the FRB prefers to use Purchase Consumer Expenditures (PCE) instead of the CPI to characterize consumer prices. Figure 4 shows that the DGDP and PCE are similar in the USA. 

Figure 1. The evolution of cumulative rate of CPI inflation and GDP deflator in Japan. 

 

 

  

Figure 2.  The evolution of cumulative rate of CPI inflation and GDP deflator in Austria and France.

Figure 3.  The evolution of cumulative rate of CPI inflation and GDP deflator in the USA.

Figure 4.  The evolution of cumulative rate of PCE inflation and GDP deflator in the USA.

Inflation, unemployment, and labour force. Phillips curves and long-term projections for Austria

Paper in PDF is avilable on IDEAS

Abstract

We model the rate of inflation and unemployment in Austria since the early 1960s within the Phillips/Fisher framework. The change in labour force is the driving force representing economic activity in the Phillips curve. For Austria, this macroeconomic variable was first tested as a predictor of inflation and unemployment in 2005 with the involved time series ended in 2003. Here we extend all series by nine new readings available since 2003 and re-estimate the previously estimated relationships between inflation, unemployment, and labour force. As before, a structural break is allowed in these relationships, which is related to numerous changes in definitions in the 1980s. The break year is estimated together with other model parameters by the Boundary Element Method with the LSQ fitting between observed and predicted integral curves. The precision of inflation prediction, as described by the root-mean-square (forecasting) error is by 20% to 70% better than that estimated by AR(1) model. The estimates of model forecasting error are available for those time series where the change in labour force leads by one (the GDP deflator) or two (CPI) years. For the whole period between 1965 and 2012 as well as for the intervals before and after the structural break (1986 for all inflation models) separately, our model is superior to the naïve forecasting, which in turn, is not worse than any other forecasting model. The level of statistical reliability and the predictive power of the link between inflation and labour force imply that the National Bank of Austria does not control inflation and unemployment beyond revisions to definitions. The labour force projection provided by Statistic Austria allows foreseeing inflation at a forty-year horizon: the rate of CPI inflation will hover around 1.3% and the GDP deflator will likely sink below zero between 2018 and 2034.

Inflation, unemployment, and labor force. Phillips curves and long-term projections for Japan

PDF paper is available on arxiv.org

Abstract

The evolution of the rate of price inflation and unemployment in Japan has been modeled within the Phillips curve framework. As an extension to the Phillips curve, we represent both variables as linear functions of the change rate of labor force. All models were first estimated in 2005 for the period between 1980 and 2003. Here we update these original models with data through 2012. The revisited models accurately describe disinflation during the 1980s and 1990s as well as the whole deflationary period started in the late 1990s. The Phillips curve for Japan confirms the original concept that growing unemployment results in decreasing inflation. A linear and lagged generalized Phillips curve expressed as a link between inflation, unemployment, and labor force has been also re-estimated and validated by new data. Labor force projections allow a long-term inflation and unemployment forecast: the GDP deflator will be negative (between -0.5% and -2% per year) during the next 40 years. The rate of unemployment will increase from 4.3% in 2012 to 5.5% in 2050.

What is so important in 36-year-olds?

Figure 1 below compares the evolution of employment-population ratio (EPR) and the number of 36-year-olds in the U.S.  What can be so important in this number? I do not understand. Moreover, why this number is not important since 2010, as the projection from the number of 21-year-old shows in Figure 2? 

I do not say the 36-year-olds drive the EPR, but mere coincidence is rather unlikely.

Figure 1.  The employment-population ratio and the number of 36-year-olds  (blue line) between 1950 and 2013.

 

Figure 2. A 15-year ahead  projection (red line) of 36-year-olds from the number of 21-year-olds.

Price of nonferrous metals on a mid-term decline

This is a regular revision. We have been following the evolution of several price indices of metals since 2008. Our general approach is based on the presence of long-term sustainable (linear and nonlinear) trends in the evolution of the CPI and PPI in the United States [1, 2]. The difference between various components of these indices is not a random one but is rather a predetermined process. Using these trends, one can predict consumer and producer price indices for select goods, services and commodities.

 

Yesterday, we revisited the index of steel and iron. In this post, we revisit the trends in the PPI of nonferrous metals. Originally, we reported on this item in 2008 and then revisited in 2010 and February 2012. The index for non-ferrous metals (102) shows an example of the absence of sustainable trends in the difference (see Figure 1). The curve is rather a comb with teeth of varying width. Although varying, the distance between consecutive troughs is several years at least. 

We predicted that the index of nonferrous metals had to fluctuate with large amplitude around the PPI and grew at a lower rate than PPI during 2012 and 2013:  “Considering the observation that the rate of growth was approximately 3 points per month since February 2012 one may expect the level of -10 in approximately 10 to 12 months, i.e. in September 2013.” 

In reality, this difference was at -38.5 in June 2013. There was a short term fall during the summer of 2012. Therefore, despite there is three months to grow, the difference is slightly behind the schedule. This delay does not change the trend, however, and we expect the price of nonferrous metals to fall through 2016.  

The producer price index of aluminum base scrap has to follow the same trend up, as Figure 2 shows. The price of aluminum will be decreasing as well.

Figure 1.  The evolution of the difference between the PPI and the index of nonferrous metals from 1985 and June 2013. There are no linear trends in the difference, but its behavior demonstrates a clear periodic structure with relatively deep but short troughs, which reflect the fast growth in the PPI for nonferrous metals.

 

Figure 2.  The evolution of the difference between the PPI and the index of aluminum base scrap from 1985 and June 2013.

Long term problems of the labor force market

A month ago we presented a prediction of the labor force participation rate, LFPR, measured by the Bureau of Labor Statistics. The LFPR (the portion of people in labor force) for the working age population (16 years of age and over) has been on a long-term decline since 1995. We predicted the fall down to 59% by 2025. Here we use a different approximation to project the future evolution of the LFPR. Following the Kondratiev wave approach (the Russian economist Kondratiev introduced long-period (50 to 60 years) waves in economic evolution – see Figure 1) we interpolated the observed LFPR curve by a sinus function with a period of ~70 years. The result is shown in Figure 2. The trough of the model function is 2030 and the bottom rate in 58.5%.

 

Another interesting feature is shown in Figure 3. The rate of unemployment also has some long period (~35 years)  oscillation in amplitude together with short-period ( 7 to 11 years) fluctuations. The period of 35 years is a half of the labor force period. The rate of unemployment is sensitive to the peaks and inflection points of the labor force curve. One may expect the following unemployment peak to be higher than in 2010.  

 

Figure 1. The Kondratiev wave

 

Figure 2. The actual LFPR curve (red) and that predicted by sinus function with a period of ~70 years. 

Figure 3.  The rate of unemployment. 

Price of steel and iron will be declining

Eight months ago we revisited the previously predicted fall in the producer price index of steel and iron in the fourth quarter of 2012 and formulated the hypothesis on the evolution in 2013: “One may foresee the difference to fluctuate around the green line in the near future. The price of iron and steel will likely be declining.”  It’s time to revisit our prediction.

 

Originally, we reported on the difference between the overall PPI and the PPI of steel and iron in 2008. Then we revisited the difference in 2010, February 2012, and December 2012. We predicted the index of steel and iron to return to the long term trend, which express a higher rate of growth of the producer price index than that of steel and iron. Our general approach is based on the presence of long-term sustainable (linear and nonlinear) trends in the evolution of the CPI and PPI in the United States [1, 2]. The difference between various components of these indices is not a random one but is rather a predetermined process. Using these trends, one can predict consumer and producer price indices for select goods, services and commodities.

 

Figure 1 (the upper panel is from December 2012 and the lower one is its updated version with data through June 2013) compares the difference between the PPI and the index for iron and steel (BLS code 101). The difference is characterized by the presence of a sharp decline between 2001 and 2008. Between 1985 and 2000, the curve fluctuates around the zero line, i.e. there was no linear trend in the absolute difference. In 2008, our main assumption was that the negative trend observed before 2008 should start transforming into a positive one after 2008. In Figure 1, the (expected) new trend is shown by green line. This trend suggests that the PPI grows faster than the index of steel and iron by approximately 2 units of index per year.

 

Figure 2 (same two panels) demonstrates the most recent period and confirms that our prediction for 2013 was correct – the difference has touched the green line. We foresee that the difference will be growing fluctuating around the green line till 2016. The price of iron and steel will be declining further before the difference reach ~10 to 20.

 

 

Figure 1. The difference of the PPI and the index of steel and iron updated (lower panel) for the period between November 2012 and June 2013. 

 

Figure 2. Same as in Figure 1 for the period between January 2005 and June 2013. Green line predicts the evolution of the difference after 2008. Red circles represent the difference between April 2009 and June 2013.