HELEN CALLAHAN

College of Business

Western Carolina University

Abstract

This paper forecasts U.S. inflation rates for the years 2000 and 2001. The explanatory variable is the seasonally adjusted unemployment rate. The approach is based on the New Classical School interpretation of the Phillips Curve. The Phillips Curve was used because it asserts a short-run theoretical relationship between inflation and unemployment rates. It is important to have a forecast that will allow us to see the inflation rates for the next two years. Future inflation can be used to predict future employment rates, given static expectations. With expectations held constant, the short-run Phillips Curve intersects the natural rate of unemployment curve. The government, the Fed, and firms should continue present measures to maintain the low unemployment level. (JEL: E240).

Part 1. Introduction

This paper forecasts U.S. inflation rates for the years 2000 and 2001. The explanatory variable is the seasonally adjusted unemployment rate. The approach is based on the New Classical School interpretation of the Phillips Curve. The Phillips Curve was used because it is a simple model appropriate for forecasting short-term unemployment rates. The New Classical interpretation of the Phillips curve is that it is vertical in the long run, but upward sloping in the short run. This provides the inflation-unemployment trade-off Phillips identified. Future inflation can be used to predict future employment rates, given static expectations. The forecast is for the next two years with expectations held constant; the short-run Phillips Curve intersects the natural rate of unemployment curve (approximately 6%) at the expected inflation rate (Thomas 1997, p. 442).

This forecast assumes the inflation rates for the next two years will decline throughout the forecast period creating an impact on unemployment. Monthly unemployment rates will be calculated over the sample period of the data. The average monthly inflation rates will be used to project unemployment into the future for the years of 2000 and 2001 to provide a short-term projection. Forecasts for each future month will be projected using the New Classical interpretation of the Phillips curve:

The rest of this paper is organized as follows: Part 2. presents the data used to forecast inflation rates; Part 3. presents the theoretical basis for the approach adopted in forecasting inflation rates; Part 4. presents forecasts of inflation rates for 1999 and 2000; Part 5. evaluates the importance of the forecast for the economy; and Part 6. discusses conclusions for economic policy.

Part 2. Data

The first variable is inflation. The rates are computed from the Consumer Price Index: Total; All Urban Consumers. This data was taken from the Federal Reserve Bank of St. Louis Federal Reserve Economic Data (FRED). The FRED descriptor is CPIAUCSL. The inflation rate was computed as the annualized percent change in the CPI. The rates used for the sample period were seasonally adjusted annual rates for each month from 1990 to 1999. The second variable was unemployment. The FRED descriptor for the unemployment rate is UNRATE. The rates taken for the sample period were from every month from years 1990 to 1999. The forecast horizon is two years into the future. This data was used because it clearly shows the relationship between the inflation rate and unemployment. Inflation and unemployment are essential parts of the Phillips Curve so they had to be used to complete the forecast.

Part 3. The New Classical Phillips Curve as a Forecasting Instrument

The Phillips Curve and variables were used because of the relationship that exists between them. Data was found on unemployment and inflation. The forecast takes advantage of the short-run relationship between these variables.

u = f(i),

Where i = inflation and u = unemployment. The regression model used is the basic univariate model. Solving for inflation, the forecast target, the equation is written as:

i_t = a+ bu_t

The constants (a) and (b) are computed in the regression and are given as the intercept coefficient (a) and X variable coefficient (b). Lagging the right-hand-side of the Phillips Curve by twenty-four months yields the following forecasting equation:

i_t = a+ bu_t-24

This equation is estimated in Part 4 and is used to calculate the inflation forecast.

Part 4. A Forecast of U.S. Inflation Rates, 2000-2001

Unemployment was lagged twenty-four months to forecast inflation. The R-square is 0 and the adjusted R-square is –0.043478, indicating approximately 4% of the variation in inflation is explained by variation in unemployment from two years earlier. The regression estimate is (with t-statistics in parentheses):

i_t =2699(8.21) +-170.7 (-2.13)u_t-24

This equation will give the expected inflation rates when unemployment rates from the past two years are put in. The following equation is for the forecast inflation rate for December 1999 and the X variable is unemployment from the month of December in 1999:

1947.92 = 2699 + -170.7 (4.4)

This equation is shown as an example of how the inflation forecast was computed for each month in 2000 and 2001. Forecast inflation rates are given in Table 1.

Table 1 Forecast of Inflation Rates, 2000-2001
*2000 month*	*Forecast inflation*	*2001 month*	*Forecast inflation*
2000.01	1.94%	2001.01	1.95%
2000.02	1.94%	2001.02	1.98%
2000.03	1.93%	2001.03	1.96%
2000.04	1.93%	2001.04	1.98%
2000.05	1.93%	2001.05	1.96%
2000.06	1.93%	2001.06	1.98%
2000.07	1.94%	2001.07	1.98%
2000.08	1.96%	2001.08	2.00%
2000.09	1.90%	2001.09	2.00%
2000.10	1.91%	2001.10	2.00%
2000.11	1.90%	2001.11	2.00%
2000.12	1.96%	2001.12	2.00%

This forecast predicts declining inflation throughout the year 2000. The inflation rates forecast for 2000 are almost 1% higher than recent inflation. In two years the rates are expected to decline throughout the year2001, before leveling off to 2.00% by August 2001. Using the relationship between inflation and unemployment, this forecast suggests the fluctuation in inflation will create a fluctuation in unemployment over 2000, with a slight increase in unemployment by December 2000.

Part 5. Forecast Implications

If the predicted results of the forecast are correct inflation and unemployment should remain rather low for the next two years. The unemployment rate now is at 4% for 2000. Since the unemployment rate and inflation rate are inversely related in the short run, the forecast implies unemployment rates will be about the same, with a possibility of unemployment being even lower throughout 2000. Then unemployment will rise back to 2.00 percent by August 2001, as inflation rises back to recent levels. However, employers may find it difficult to fill job vacancies should it moderate. Low forecast inflation suggests anyone thinking of buying any large purchase such as a home or car should do so within the next couple of years while inflation rates are still relatively low.

Part 6. Policy Conclusions

This forecast predicts higher than current inflation over the next year, but predicts declining inflation throughout the forecast period. With the lower unemployment rate, the state governments will have higher tax revenues. This will give the government more flexibility to spend on assorted programs. Furthermore lower unemployment levels should promote consumer spending. In the financial service industry there could be more jobs for professional money managers because of increased wealth accumulation. Assuming the forecast turns out to be correct, firms, government, and the Fed should continue current policy measures.

References

Economist Resources for Economists, Economic Time Series Page, and Consumer Price Index: Total; All Urban Consumers SA, http://bos.uab.edu/browse/cgi-bin/data.exe/fedstl/cpiaucsl+1/.

Federal Reserve Bank of St. Louis, Federal Reserve Economic Data (FRED), http://www.stls.frb.org/fred/.

Mueller, M.G., ed., Readings in Macroeconomics, New York: Holt, Rinehart, & Winston, 1966.

Thomas, Lloyd B., Money, Banking, and Financial Markets, New York: McGraw-Hill, 1997.