U.S. Consumption Expenditure and Gross Domestic
Product
SHAWN TIGNOR
College of Business
Western Carolina University
Abstract
U.S. consumption expenditures are forecast to grow approximately 2%
annually in 1999 and 2000. The forecast is based on a Keynesian aggregate
consumption function. Consumption is found to be a function of lagged consumption
and lagged GDP, allowing a forecast to be extended two years into the future.
Current levels of consumption, aggregate output, and employment indicate
the possibility of future inflation. If consumption increases, unemployment
will decrease, creating inflation by bidding up wages. If consumption does
increase, it is possible that unemployment would fall far under the natural
rate of unemployment, causing inflation. (JEL: E22)
Part 1. Introduction
This paper forecasts U.S. consumption spending for the years 1999 and 2000.
U.S. gross domestic product (GDP) is the explanatory variable used to predict
consumption. The forecasting approach is based on the Keynesian aggregate
expenditure model. In this model, real GDP is the sum of consumption spending,
investment, government spending and net exports. Consumption spending is
a function of real income, measured as real GDP.
The rest of this paper is organized as follows: Part 2 presents data
used to forecast consumption; Part 3 explains the theoretical basis for
the approach adopted in forecasting with the Keynesian consumption function;
Part 4 presents the forecast of consumption in regression and lagged regression
form; Part 5 evaluates the importance of the forecast for the economy;
and Part 6 discusses conclusions for economic policy.
Part 2. Data
The data used to predict U.S. consumption was found on the St. Louis Federal
Reserve Economic Data (FRED) web site. U.S. consumption (PCEC92) is forecast
for 1999 and 2000. PCEC92 is a real variable measured in billions of chained
1992 dollars. The explanatory variable is the index of industrial production
(INDPRO) and is used as a proxy for real GDP. INDPRO is also a real variable
measured as a percent of 1992 real industrial output.
Part 3. The Keynesian Consumption Function
This model assumes consumption expenditures depend on total real income
(Keynes 1936, pp. 89131). The Keynesian consumption function can be written
as:
C_{t} = C_{0} + (MPC x Y_{t}),
(1.
where C_{0} is autonomous consumption and MPCxY_{t}
is induced consumption. Y_{t} is real GDP. In estimating the consumption
function, the industrial production index was used to proxy real GDP. GDP
is only observed quarterly; consumption and the index of industrial production
are observed monthly. Lagging the right hand side of the consumption function
by two years and adding lagged consumption provides the following forecasting
equation:
C_{t} = C_{0} + C_{1 }x C_{t2}
+C_{2 }x Y_{t2}, (2.
Estimate of equations 1 and 2 and forecasts based on the regressions
are presented in Part 4.
Part 4. Empirical Results
The regression estimate of the consumption function is (with tstatistics
in parentheses):
C_{t} = 1459.5(29.37) + 27.659(64.27) x Y_{t},
The adjusted Rsquare of the estimate is 0.9803, indicating approximately
98.0% of the variation of consumption can be linked to changes in industrial
production. The tstatistics are very high, which indicates strong rejection
of the null hypotheses that coefficients equal zero.
The regression estimate of the forecasting equation is (with tstatistics
in parentheses):
C_{t} = 328.03(1.18) + .5536(3.30) x C_{t2}
+ 18.05(4.07) x Y_{t2},
The tstatistic of the y intercept is less than 2, which indicates failure
to reject the null hypothesis that the intercept equals zero. The tstatistics
for the slopes reject the null hypotheses that the coefficients on lagged
consumption and lagged income are zero. The coefficient of determination,
or R^{2}, is 0.9827, indicating the estimated line fits the data
points closely. The high Rsquare for the lagged U.S. consumption function
indicates the data points lie very close to the regression line. In other
words, predicted values of consumption will be close to actual values for
the sample period.
Part 5. Stabilized Times
Consumption is forecast to increase 3.5% in 1999 and 4.1% in 2000. The
forecast period is January 1999 to December 2000. Within the forecast period,
projected annual growth rates range from 2.87% for June 1999 to 4.98% for
May 2000.
Table 1: A Forecast of U.S. consumption Spending for 1999 and
2000

Month/Year

Forecast U.S. consumption,
billions of chained 1992 dollars

Annualized percent change

January 1999.01

5233.14399

4.015901

February 1999.02

5251.26758

3.786145

March 1999.03

5260.5851

3.671149

April 1999.04

5274.85793

3.609396

May 1999.05

5286.21417

2.976861

June 1999.06

5314.43951

2.871402

July 1999.07

5357.19581

3.873964

August 1999.08

5372.8032

3.786184

September 1999.09

5388.50341

3.402353

October 1999.10

5407.1578

3.529865

November 1999.11

5431.49378

3.914247

December 1999.12

5448.31703

3.507362

January 2000.01

5464.48498

4.420688

February 2000.02

5478.1511

4.320548

March 2000.03

5495.87198

4.472637

April 2000.04

5516.85037

4.587658

May 2000.05

5549.83297

4.986911

June 2000.06

5545.93169

4.35591

July 2000.07

5538.17346

3.378216

August 2000.08

5582.99129

3.912075

September 2000.09

5592.88274

3.792877

October 2000.10

5608.50971

3.723803

November 2000.11

5608.70359

3.262635

December 2000.12

5634.14708

3.410779

Part 6. Conclusions on Policy
There will be relatively little change in growth of GDP and consumption
spending. However, consumption spending has grown at a rate nearly one
percent faster than GDP, and the forecast suggests this will continue for
at least the next two years. Assuming the forecast is correct, increasing
growth in consumption will strain U.S. resources to produce new output.
Some of the increased demand forecast for consumption goods may be satisfied
by increased imports. The increase in consumption spending may drive up
output prices, creating inflation. It seems that America is consuming so
much right now that domestic producers are having difficulties hiring enough
people to supply enough consumption goods to meet demand. If consumption
were to increase much beyond current levels, there would not be enough
people to produce the goods to feed the new demand. It appears this would
cause salaries, and thus the price of goods, to increase because labor
would be so scarce. Inflation would result, and the dollar would lose value.
References
Federal Reserve Bank of St. Louis, Federal Reserve Economic Data (FRED),
http://www.stls.frb.org/fred/
Keynes, John Maynard, The General Theory of Employment Interest and
Money, New York: Harcourt Brace and World, 1936.