20002001
Forecast: U.S. Gross Domestic Product
Using Real
Private Nonresidential Fixed Investment
BRENDA LUTHER
Western
Carolina University
College of
Business
Western
Carolina University
This is a forecast of U S
Gross Domestic Product (GDP) for 2000 through 2001. (Lagged government
expenditures and gross investment were chosen as a combined explanatory
variable used to forecast future GDP.) The forecast is based on the Keynesian
Aggregate Expenditure Model which relies on the accounting identity expressing
that aggregate expenditure or GDP has the following components: consumption,
investment, government expenditure, and net exports. The MPC and MPI are 56
percent and 23 percent, estimated from quarterly data. This implies a historically low Keynesian
autonomous expenditures multiplier of 1.52.
The interest elasticity of investment is 16 percent also estimated from
the data used. Investment spending is projected into the future with a
horizontal time trend, as all the other components of aggregate expenditures
are held constant. The GDP forecast
predicts a gradual and steady, increase in the growth of the economy over the
next two years. (This conclusion is drawn from the fact that GDP continues to
steadily rise between the first quarter of 2000 and the fourth quarter of
2001.) The U S government and the Fed need to be concerned about the
possibility of an increase in inflation rising in the future so they can begin
counteractive measures. If the Fed has
a suspicion that an inflationary period may occur, it could take measures to
slow the economy. (JEL: E120, H50)
This
paper forecasts U S Gross Domestic Product for the years 2000 and 2001. The key explanatory variable is real lagged
private nonresidential fixed investment. The projection is based on the
Keynesian Aggregate Expenditure Model using new estimates of marginal
propensity to consume (MPC) and marginal propensity to import (MPI) based on
data from 1993.1 – 1999.4. The Keynesian investment function is estimated, and
this approach utilizes the role of private investment expenditures as a guiding
force in the aggregate economy.
Real
Gross Domestic Product is the most thorough measure of United States economic
income and output. A growing GDP indicates a strong economy. An increase in GDP
would result in continued growth for the nation’s economy. In an effort to
minimize unforeseen factors, a twoyear horizon was chosen. The forecast
horizon is relatively short, in order to avoid overstating or understating
future GDP.
The
remainder of this paper is arranged in the following order: Part 2 presents the
data gathered to forecast GDP; Part 3 explains the economic theory for which
the forecast is based; Part 4 presents the GDP forecast for 2000 and 2001; Part
5 indicates the importance of GDP with regard to the U.S. economy; Part 6 details
the conclusions for an economic policy.
The
data used to predict U S GDP was taken from the Federal Reserve Bank of St.
Louis Federal Reserve Economic Data (FRED) web site. The FRED variables used
are GDPC96, GCEC96 and GPDIC96, respectively. The variables are reported in
billions of chained 1996 dollars, which have been seasonally adjusted at annual
rates (SAAR) and are reported quarterly.
The forecast horizon is two years from the last reported data.
Gross
Domestic Product is one of the most important measures of a country’s economic
activity. The purpose of this forecast is to predict economic activity into the
future, with lagged government expenditure and gross investment as the
explanatory variables. Lagged government expenditures and gross investment were
chosen to forecast GDP because they are key components of GDP. It is
conceivable that government expenditures and gross investment should be simple
and reliable variables to forecast future GDP.
This forecast assumes the interest
rate will remain constant for the next two years and will have no impact on
investment spending or GDP. The annual growth rates for investment spending
will be calculated over the sample period of the data. The average annual
growth rate will be used to project investment spending into the future for the
eight quarters of 2000 and 2001 to provide a shortterm projection of
investment. The values for projected future investment will be used to
calculate GDP forecasts for each future quarter using the Keynesian autonomous
expenditures multiplier:
DY = DI/[MPS + MPI]
This is a simple model appropriate for forecasting shortterm GDP growth. The forecast should be interpreted as trend GDP in the absence of a recession. This model is probably not adequate to forecast a recession, especially one caused by unanticipated real aggregate supply shocks. The marginal propensity to save (MPS) is 0.43, from a Keynesian Consumption Function estimated from the quarterly data gathered.
This forecast assumes the interest rate will remain constant for the next two years. It also assumes the interest rate will have no effect on government expenditures, gross investment, or GDP. Quarterly GDP will be calculated for two years into the future. Government expenditures and gross investment data were taken from data reported from 1993.1 through 1999.4.
The
Keynesian Aggregate Expenditure Model is an appropriate approach to use to
forecast GDP because the model supports the notion that government expenditures
and gross investment influence the amount of GDP the United States produces in
a given year. One problem with using government expenditures and gross
investment is they are independent of GDP because the government sets the
amount of expenditures within the budget each year. This means that GDP has little effect on the amount of government
expenditures and gross investment, even though government expenditures directly
influence GDP.
National
consumption, investment, government expenditures, and net exports are aggregate
components of GDP, and these components influence the level of GDP for any
given year. These components actually are responsible for the amount of GDP
produced each year. The accounting identity that supports this theory is
written as:
GDP = AE = C +
I + G + X,
where
AE is aggregate expenditure, C is consumption, I is investment, G is government
expenditure, and
X
is net exports for a country.
In
the forecast, government expenditure was taken from the above equation and used
in a regression with past GDP figures to calculate future GDP for the United
States. The above equation is not actually used in the forecast; it merely
supports the theory that government expenditures and gross investment
influence,
or
drive future GDP.
The
foundation of this forecast is based upon the regression and trend analysis.
There has to be a relationship between GDP, government expenditures, and gross
investment in order for the forecast to be plausible. The Keynesian model
provides that support.
Lagging the righthandside by two years, removing the other variables, and allowing intercept and error term yields:
Y_{t }=
a + b (G_{t2}) + c (I_{t2}) + d (Y_{t2}) + e_{t}
This
is the equation mentioned in Part 4, and it forms the basis of the forecast
calculations.
Government
expenditures, gross investment, and GDP are measured in billions of
1996chained dollars, and the figures are seasonally adjusted at annual rates.
Table 1Regression Estimate of GDP
Forecasting Equation 1: 1993.11999.4 

Explanatory Variable 
Estimated
Coefficient 
tratio 
Intercept (a) 
2682.544 
2.542 
G coefficient (b) 
1.307 
1.708 
I coefficient (c) 
1.896 
4.961 
GDP coefficient (d) 
1.969 
14.394 
R Square = .996 
F (zero
slopes) = 1193.233 
Probability
(F) 0.000 
Table
1 summarizes the regression used to forecast GDP. The intercept and the X
variable were the variables used in the regression equation to forecast GDP.
The Rsquare is .996, which means that approximately 99.6 % of the variation in
GDP is explained by variation in government expenditures and gross investment.
The tstatistic for the intercept is equal to –2.542, and this indicates
rejection of the null hypothesis. The tstatistic for the coefficient of
government spending and the Fstatistic for zero slope (which is the square of
the tstatistic when there is only one righthandside variable) are also
listed above.
The first part of the projected twoyear period of GDP is relatively stable and resembles the current GDP figures. Toward the end of the period, it appears as if there will be continued growth in the economy. GDP rises through the forecast period. The 2000 to 2001 GDP forecasts are shown in table 2.
Table 2 Forecast GDP 2000.12001.4 (Billions of Chained 1996 dollars, SAAR) 

Quarter 
Forecast 
Annual % D 
2000.1 
9071.201 
 
2000.2 
9165.629 
0.010 
2000.3 
9242.496 
0.008 
2000.4 
9390.192 
0.016 
2001.1 
9493.633 
0.011 
2001.2 
9593.378 
0.009 
2001.3 
9703.173 
0.013 
2001.4 
9847.040 
0.015 
This
forecast predicts growth through 2001.4, since GDP activity is on an upswing.
The
forecast GDP is favorable in the sample period. The Federal Reserve would have
to implement some policies to counterattack the effects of a rapidly growing
economy, which could cause inflation. One measure the Federal Reserve may
introduce is an increase in interest rates. This would be in an effort to slow
down the economy. The Federal Reserve should be concerned with the possibility
of growth occurring too rapidly, which could cause inflation to rise. It can
have devastating effects on everyone in the economy. The past actual GDP and
the forecast GDP are shown in the attached graph in order to demonstrate the
prediction.
GDP
is projected to continue to increase at a moderate rate over the next two
years. GDP is predicted to increase in 2000. In 2001, GDP is projected to
moderately increase, as well. This was
concluded based on government expenditures and gross investment as the
explanatory variables.
Industries will continue to enjoy steady growth in the economy over the next two years. According to the forecast data, it appears GDP is going to moderately increase in the near future. This will have little effect on U.S. industries. The industries will have to wait and see what policies the government will implement during this election year.
The
United States government needs to be concerned with the possibility of high
inflation due to GDP rising too rapidly.
If inflationary problems are suspected, the Fed should consider
increasing nominal interest rates to slow the economy. This will allow the Fed to impact key
components of GDP.
Federal
Reserve Bank of St. Louis, Federal Reserve Economic Data (FRED), http://www.stls.frb.org/fred/, 1 Mar
2000.
Thomas,
Lloyd B. Money, Banking, and Financial Markets. New York: McGrawHill
Companies, Inc., 1997
GDP EXPLAINED BY
LAGGED GDP, LAGGED GOVERNMENT, LAGGED INVESTMENT 













Regression Statistics 








Multiple R 
0.998 







R Square 
0.996 







Adjusted R Square 
0.995 







Standard Error 
36.029 







Observations 
20 
















ANOVA 









df 
SS 
MS 
F 
Significance F 



Regression 
3 
4646845.667 
1548948.556 
1193.233 
0.000 



Residual 
16 
20769.779 
1298.111 





Total 
19 
4667615.446 
















Coefficients 
Standard Error 
t Stat 
Pvalue 
Lower 95% 
Upper 95% 
Lower 95.0% 
Upper 95.0% 
Intercept 
2682.544 
1055.466 
2.542 
0.022 
4920.030 
445.057 
4920.030 
445.057 
GDP 
1.969 
0.137 
14.394 
0.000 
1.679 
2.260 
1.679 
2.260 
G 
1.307 
0.765 
1.708 
0.107 
2.928 
0.315 
2.928 
0.315 
I 
1.896 
0.382 
4.961 
0.000 
2.706 
1.086 
2.706 
1.086 