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. 89-131). The Keynesian consumption function can be written as:
 
Ct = C0 + (MPC x Yt), (1.

where C0 is autonomous consumption and MPCxYt is induced consumption. Yt 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:

 
Ct = C0 + C1 x Ct-2 +C2 x Yt-2, (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 t-statistics in parentheses):

 
Ct = 1459.5(29.37) + 27.659(64.27) x Yt,
 
The adjusted R-square of the estimate is 0.9803, indicating approximately 98.0% of the variation of consumption can be linked to changes in industrial production. The t-statistics are very high, which indicates strong rejection of the null hypotheses that coefficients equal zero.

The regression estimate of the forecasting equation is (with t-statistics in parentheses):

 
Ct = 328.03(1.18) + .5536(3.30) x Ct-2 + 18.05(4.07) x Yt-2,

The t-statistic of the y intercept is less than 2, which indicates failure to reject the null hypothesis that the intercept equals zero. The t-statistics for the slopes reject the null hypotheses that the coefficients on lagged consumption and lagged income are zero. The coefficient of determination, or R2, is 0.9827, indicating the estimated line fits the data points closely. The high R-square 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