Inflation Evaluation Today it is almost impossible to pick up a financial journal without seeing news on the bull market that some consider to be overvalued. Overvalued or fairly valued, only the future will show the truth. Either way, this market is one that has shown greater run ups and returns, than any other market in history. (Reference Appendix #1a) Recently the Dow Jones Industrial Average has reached historical highs and then receded back to previous levels, leaving investors who are used to consistent and record setting gains month after month, baffled. Both the Dow Jones and the S & P 500 indices have seen modest and even flat performances over the past three months. (Reference #1b) A recent article that was published on the front page of the Wall Street Journal emphasized that returns were flat due to the fact that investors were concerned of the possible on set of inflation.
If these concerns are warranted and inflation is thus expected, the Bull market may very well be over. This after all makes sense, inflation has slowed and stopped many run-ups in the past, and the onset of inflation now could very well do the same. While the article introduced some possibilities, it said nothing of the likelihood, the causes of, the Fed.’s reactions to, and the probability of expected inflationary increases in the future. This paper is thus dedicated to expanding on these ideas by exploring the rationality of these concerns by examining the circumstances surrounding inflation. It is my speculation that the Bull market may eventually correct itself in the future, but not in the short term due to immediate inflation. That is, that the market was in fact flat due investors concerns, but actual imperative inflation does not look to be expected in the near future.
In order to begin to understand the nature of market trends and forces, one must first consider the current state of the U.S. economy relative to its’ business cycle. Certain aggregates can be measured that tell us a great deal about this. These aggregates have a strong history of leading, coinciding, or lagging the relative business cycle with a high amount of regular correlation. Appendix 2a contains illustrations, which show graphically the trends of the leading, lagging, and coincident indicators over the past few years.
These graphs are composites of each group, and upon examination it is clear that all the indicators are rising. In fact the composite index of leading indicators shows that they have not experienced a significant downturn since the early 1980’s, and have been increasing rather sharply over the past 3 years. The fact that all of these indicators are currently rising indicate that the economy is in a period of robust growth, or an expansionary phase. The fruits of this expansion have proven to be many, however it is often said that too much of a good thing can be bad. In this regard there are factors associated with the degree and nature of this economy, which could cause slowdown. For example, how is inflation measured, and to what degree should we be concerned with the effects and attributes of cost- push and demand- pull sources of inflation in this robust economy? According the Baye and Jansen, inflation can be measured by considering the growth of the money supply, the growth of M velocity, and the growth of real output. Algebraically this is represented by the equation: inflation = (gm + gv) – gy.
This equation thus considers the monetary, supply-push, and demand-pull factors. When the rate of inflation is measured in this way one can see, that over the last few years inflation has been relatively stable about its’ trend. This is in part, a result of the steady growth of GDP over the same period, and is testimony to the success of the Federal Reserve Board’s monetary and fiscal policies. The rates of inflation over the last 10 years are graphically illustrated in Appendix 3A. Cost-push inflation incurs when the prices of inputs for production increase and thus cause profit margins to diminish. If firms are unwilling or unable to accept the declination in operating income, they will pass these increases on to consumers in the form of increased prices.
In a competitive market it would seem that firms would be unable to raise prices, unless there was uniform pressure affecting the aggregate whole of suppliers. (Examples include per unit costs of production, labor costs, energy prices, etc.) Both the dollar cost per person per hour, and the output per person have been increasing since 1997. These increases are most likely in response to technological advances in the public and private sectors. It is worth noting that the advances in compensation have exceeded those in output. Hence firms may have experienced a decline in marginal revenues. Another important aspect regarding wages and output is that the rates of increase for both have been declining since the second quarter of 1998.
In the third quarter of 1999, real output was increasing more than the rate at which wages are increasing. This correction may be important when considering cost-push inflationary pressures. (Appendix 3b) On an aggregate level one can measure rising producer costs by examining the producer price index. Appendix 3c graphically explores trends related to the PPI over the past three years. Upon examination it is clear that producer costs have been increasing steadily since 1997. This may be due in part to rising costs of compensation along with recent run-ups on crude oil prices.
There is likely a strong correlation between the producer price index and the consumer price index, (The dependent variable) and is therefore important to include when making a forecast of future inflation. There may also be inflationary pressures attributable to demand-pull effects. This occurs when there are too many dollars chasing too few goods. A point to consider here is worker compensation and disposable personal income. The aggregate disposable personal income has been increasing over the recent economic prosperity.
The key here is that the increases in income have been fairly stable. It is because of this stability that there appears to be little correlation when disposable personal income is regressed against inflation. Despite the low R^2 variable it still may be a worthy component to add to an inflation forecast. The growth of this economy has been very great, and this is support by strong consumer confidence. An area that would seem to contribute to this robust growth and inflationary pressure is the savings rate. Regardless of which indices or months one looks at, it is clear that personal saving in 1999 in considerably down from all other years.
This may have an impact on the velocity of money and thus inflation in the future. The cyclical and irregular activity of the business cycle can be determined by detrending and deseasonalizing the real GDP data. (Appendix 4a) In doing so, one can see how the rates of inflation are correlated with that of the business cycle. The cyclical percentage changes in GDP serve as a good variable in inflationary forecasts because; significant amounts of real increase or decrease tend to be correlated with changes in inflation. When inflation is regressed against the cyclical increases in real GDP, the R^2 value is approximately 32%, indicating a moderate and useful amount of correlation.
Therefore I have also include this variable in my forecasting models. Perhaps the most significantly correlated variable that I have come across is percentage changes in monetary velocity. This predictor shows R^2 percentages in excess of 76%. Clearly, fluctuations in the velocity of money have a significant effect on inflation. Once the inflationary pressures of the 1980’s resided the velocity of money began its steady upward climb. Only in the last few years has this rate begun to slow and decline.
It would appear that the current trend in the velocity of money is one that reflects optimistic consumer behavior. (Appendix 5a shows the trends in the velocity of money over the past few decades.) Meanwhile the M2 money stock has been increasing at a fairly consistent rate for some time, with very little variation about its’ trend. (A.5b) Although in the second quarter the M2 money stock increased by a somewhat larger margin than was originally expected. The above considerations were important when I attempted to create a forecast for inflation by applying techniques discussed in Economic Forecasting 470. In order to attain the most accurate forecast I tried several different methods; including a bivariate, a multivariate, a multivariate with dummy variables, an automatic forecast, and a combination of techniques model. The Bivariate model was based on regressing inflation against the cyclical and irregular behavior of gross domestic product in order to see how the business cycle affected the rate of inflation.
This model produced a significant regression statistic near 32%. In other words, roughly one-third of the variation in inflation can be explained by the stage of the business cycle. Both of the multivariate models contained the following predictor variables; detrended seasonally adjusted GDP, changes in the M2 money stock, changes in the velocity of money, changes in the Ppi, and changes in real wages. The most highly correlated variable being percentage changes in the velocity of money (76)%, and the least correlated being changes in the Ppi (4%). The multivariate model was able to produce a regression statistic of approximately 46%. The multivariate with dummy variables actually produce a lower R^2 value, and thus a less dependable model.
The automatic forecasting method with Smart software produced a model, which could explain 79% of the data. The software chose a …