Real GDP is used because it is the most common means to measure the economy. Gross private domestic investment was selected as the forecast target because it reflects the investing habits of the typical consumer and adds to the stock of productive capital available to produce GDP. A forecast decline in GDP would indicate a recession for the year 2000. The year 2000 was chosen as the forecast horizon because of the short time span from the present, therefore producing a more accurate prediction.
The remainder of the paper is organized as follows: Part 2. contains
the data concerning the interest rates and GDP from the past six years,
from 1992 until 1998; Part 3. explains the basis for the forecast; Part
4. includes the regressions and describes how both the interest rates and
GDP relate to GPDI, and the actual forecast for GPDI for the year 2000;
Part 5. demonstrates the importance of the two different forecasts for
the immediate future of the economy; Part 6. determines what the effect
on the economy the forecast will have and what monetary policy the Federal
Reserve must adopt.
All variables are taken from the Federal Reserve Bank of St. Louis Federal Reserve Economic Data (FRED). The measures of Gross Private Domestic Investment and GDP are FRED variables GDPIC92 and GDPC92. Both are real variables and are given in billions of chained 1992 dollars at seasonally adjusted annual rates. The primary source is the U.S. Department of Commerce Bureau of Economic Analysis.
The interest rate data given are the 3-month T–bill (secondary market) rates and the 30-year T–bond rates (FRED variables TB3Ms and GS30), both of which are given as a percent discount. The primary source for this data is the Board of Governors, U.S. Federal Reserve System. These interest rates are both monthly variables. The value given for the third month in each quarter (March, June, September, and December) was taken as the value for the quarter. The sample period runs for the first quarter of 1992 to the end of the last quarter of 1998.
From the sample data two regressions were run. The first was done using both sets of interest rates as the X variables; the second was done using real GDP as the X variable. Both regressions were estimated with the right-hand-side variables lagged two years because the forecast horizon was two years into the future.
The Keynesian Investment Function is assumed to be a simple linear function
used to forecast investment spending. When using the two interest
rate variables (omitting income) the formula becomes:
When using one variable in the function, GDP, (omitting interest
rates,) the formula becomes:
Two different regressions were run, one using interest rates and the other using GDP. This was done to separate the effects due to interest rates from the effects due to income or GDP. Each variable can affect investments independently of the other variable. If SR interest decreases, firms' opportunity cost of investment decreases. Investment can also be an independent function of LR interest. As LR also decreases, the amount of investment firms can afford also increases. LR interest has decreased due to the low inflationary pressures on the economy and peoples' willingness to invest in larger market securities, such as stocks.
There are a few shortcomings of this paper. First, SR and LR interest
may be altered any time the Federal Reserve Board decides interest rates
need to be raised to combat various inflationary conditions. Second,
investment decisions of firms may be hard to track since there are many
people with differing financial positions and various degrees of risk tolerance,
which may prevent them from investing.
After running the first regression with the interest rates (X variables)
to the GPDI (Y variable) it was found that the R–square of the estimate
was 0.7439. The F–statistic was 24.69. The regression estimate
is (t-statistics in parentheses):
where I is investment spending, the short-term interest rate is on 3-month T-bills, and the long-term interest rate is on 30-year T-bonds. All t-statistics are significant at conventional levels.
After running the second regression with the GDP (X variable) to the
GPDI (Y variable) it was found that the R–square of the estimate was 0.937965.
The F–statistic was 272.15. The regression estimate is (with t-statistics
in parentheses):
where I is investment spending and GDP is real GDP.
After running both regressions it is obvious that consumer investment
is explained well by both lagged interest rates and GDP. Annual forecasts
(calculated with four-quarter averages) for 1999 are1244.55 (in billions
of chained 1992 dollars) using the two interest rates and 1444.55 using
GDP. For 2000 the forecasts are 1303.20 using the two interest rates and
1580.96 using GDP.
Quarterly forecasts are reported in table 1.
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A GDPI forecast suggests the amount of individual wealth and income will be used to maintain and increase the capital stock. Comparing GPDI to interest rates and GDP proved that there was a correlation between the three over the data.
The forecast predicts little or no chance of a recession in the near
future. This is apparent when looking at the interest rates and GDP data.
1999 will see a strong economy with an increase of 3.18% (using interest
rates) and 19.75% (using GDP) in consumer investing. In the year 2000 there
will be an increase (decrease) of –2.16% (using interest rates) and 18.64%
(using GDP) in consumer investing. Although this is slightly lower than
the change in 1999 it is not serious and could probably be attributed to
precautionary measures taken by consumers due to the changing of the century.
It is predicted that the economy will move towards an upward trend with a slight decrease in interest rates to offset the decreasing domestic investing in the early part of 2000.