Since the population of the U.S. is continually increasing, and consumption is a major component of GDP, it is important to understand the relationship among these variables. Also, since the forecast is a considerable amount of time into the future, the probability of accuracy leaves a wide margin for error.
The rest of the paper is organized as follows: Part 2. presents the
data used to forecast GDP, consumption, and estimates of the population;
Part 3. presents the theoretical basis for the approach taken in forecasting
GDP; Part 4. presents the forecast for GDP, the two variables, and the
methods used in determining these values; Part 5. evaluates the importance
of these projections for the economy; Part 6. discusses the conclusions
for economic policy.
The Bureau of Economic Analysis and the Census Bureau, U.S. Department of Commerce, are the primary sources of the data. The sample period for the data is 1983-1998. The forecast horizon is twelve years into the future. The data was chosen for the forecast because the information is the actual historical values of the variables, recorded by the appropriate government authorities.
Real GDP is the sum of consumption expenditures, investment expenditures, government expenditures, and the total of net exports less net imports. This is show by the aggregate expenditures model where AE = GDP = C + I + G + X. Since consumption is a major component of GDP, it is useful to understand the effect it can have in determining GDP. However, consumption is just one of the variables that can be used to forecast GDP. Any one of the components of the aggregate expenditure model can be used in determining GDP based on the Keynesian theory. Government spending, investment, and net exports can be used as a linear function in determining GDP, assuming the rest of the variables remain constant. It is important to note that although all of the variables can fluctuate independently of one another, fluctuations in GDP result from fluctuations of all the other variables.
Graph 1 shows the percent change from the year to year forecast by the
Census Bureau. Notice population is estimated to increase at a decreasing
rate in the future. This is important to note in determining the effect
this will have on consumption in the future.
Graph 2 shows the changes of actual GDP and Forecast GDP.
The equation used to estimate consumption for the year 2010 was done by an ordinary least squares regression formula for the years 1983-1998. The data input was actual population and consumption for these years. The R-squared of the estimate is 0.970. This indicates that approximately 97% of the variations in population are explained by the variation of consumption. The regression estimate is (t-statistics in parentheses):
Table 1 shows the forecasts for GDP, consumption, and population for
the forecast period.
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As shown in Table 1, population and consumption are increasing each year, with the exception of 1999. As the equations show, GDP follows the same pattern as the two variables, and is also increasing for the forecast years with the exception of 1999. The negative change in 1999 does not imply a recession for the year. When using ordinary least square regression the forecast is a linear function, and the negative shift is a result of the calculation. It is an artifact of the regression estimate which occurs whenever positive regression residuals are found for the last period of the regression.
Another important item of information is per capita real GDP. Per capita
real GDP is the amount each consumer will contribute to real GDP on average.
As shown in Table 2, per capita GDP is rising for the forecast horizon.
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GDP is important to forecast because it indicates the nation’s output for a given year. The forecast of increasing GDP indicates economic activity will grow steadily in the future. Along with a growing economy, certain economic needs can be determined. There will be a growing need for labor services, leading to a lower unemployment rate if the labor force grows more slowly than GDP. Lower unemployment and increased demand for labor will increase consumer income, which may increase the marginal propensity to consume.
With higher demand for consumer goods and services, manufacturers can use these trends to estimate inventory needed to maintain the levels of consumption. Depending on the predicted outcome, surpluses and shortages can be avoided. This also allows businesses to maximize the cash flow provided by current resources. These trends can also help determine the level of employment needed, decreasing business expenses.
The fact that per capita real GDP is forecast to increase up to 2010
indicates an increase in real income, real wealth, and a rising standard
of living, for the U.S. throughout the forecast period.
A rise in real GDP will affect all sectors of the economy. The individual sectors will have to anticipate consumer demand for their particular area, and plan accordingly. Determining the changing demand of consumers will help companies adjust to these changes in the areas of production and employment. This will be helpful in evaluating when to increase or decrease production, and when more or less employment is needed to fulfill these requirements.
This forecast assumes government spending will remain a constant fraction
of real GDP during the forecast period. For now, the government should
not change any of its policies. The forecast predicts the economy will
remain strong well into the future. However, if the economy becomes stagnant
the government may want to intervene in order to stimulate the economy
as needed.