Real Durable Goods Expenditures as a
Predictor of Future Consumption Spending
 
JONATHAN ESSER and RYAN FINLEY
College of Business
Western Carolina University
 
Abstract
 
As the stock market surges to new highs in the current economic boom, the equally booming increases in personal wealth fuel a consumption binge that pushes the labor force’s limits. There is concern that future increases in consumption spending may exhaust the capabilities of the already stretched labor force and thus bring about inflation. It is for this reason a forecast of consumption will aid in determining the chances for such a condition. If consumption appears to be threatening an inflationary period over the next year or two, it will be up to the government and the Federal Reserve to discourage the growth of consumption. Some available means include: raising interest rates, which decreases the amount of capital firms acquire; establishing tariffs and quotas on imports, which tends to counter the superior purchasing power of the dollar versus weakened overseas currencies, and thus lower consumption; and raising corporate taxes in order to siphon off firms' excess investment expenditures which allows firms to continue produce the quantities of goods which are available for consumption. (JEL: E22, E37)
 
Part 1. Introduction
 
This paper forecasts real personal consumption expenditures for the years 1999 and 2000. The explanatory variables are the index of U.S. industrial production, used as a proxy for Gross Domestic Product (GDP), and real personal consumption of durable goods, for 1992-1998. It is necessary to use industrial production rather than real GDP as a measure of real output and income because of the reporting frequency. Industrial production, consumption, and expenditures on durable goods are measured in monthly periods whereas GDP is measured quarterly. Since the Federal Reserve Index of Industrial Production and GDP both measure production (Oyen, p. 18), using one for the other is an acceptable substitution.

According to the Keynesian consumption function, personal consumption expenditures of households, referred to as consumption in this paper, is a function of GDP (Keynes, pp. 89-134). In recent years, "consumer expenditures have accounted for nearly 70% of aggregate expenditures in the United States," (Thomas, pg. 588). Services, nondurable goods, and durable goods are the factors of consumption. These expenditures may be influenced through a number of channels, such as interest rates affecting spending on durable goods, a change in wealth affecting all factors of consumption, and the effect of a change in liquidity on spending for durable goods.

Durable goods, a factor of consumption, represents spending on such long lasting items as cars, airplanes, televisions, etc. As consumption gradually rose through the decades, expenditures on durable goods remained relatively constant at around 8.3% of GDP throughout the 1980’s and 1990’s. Recent favorable conditions in the equity and bond markets reassure consumers of increases in expected average future income and expected future wealth. Feeling confident they will not need to convert savings portfolios to cash in the near term, consumers are demanding more durable goods. Durable goods are not easily convertible to cash. Purchase of these long lasting big-ticket items represents consumer confidence in future earnings.

Inflation is the weakening of purchasing power. Consumers fear this condition because it dilutes their wealth and ability to consume. The labor market "is at a drum-tight 4.3%, and that is taking its toll on firms’ ability to find suitable workers" (Naroff and White, p. 1). As demand for consumption increases, so does the pressure to meet that demand, creating an induced demand for labor services. As labor becomes scarce, the price of labor increases.

When firms pay more for labor, they lose profits and must pass the higher costs of production to consumers, fueling inflation. This forecast will hopefully predict a slowing in consumption and thus ease concern over future inflationary times.

The rest of the paper is organized as follows: Part 2 presents the data used to forecast cosumption; Part 3 presents the theoretical basis for the approach adopted in forecasting consumption; Part 4 presents forecasts of consumption for 1999 and 2000; Part 5 evaluates the importance of the forecast for the economy; and Part 6 presents conclusions.
 

Part 2. Data

Data were obtained for real expenditures for durable goods (PCEDGC92), industrial production (INDPRO1992=100), and consumption spending (PCEC92). The consumption function of the Keynesian Aggregate Expenditures Model is used to explain the relationship of consumption to aggregate expenditures and expenditures on durable goods. The Federal Reserve Bank of St. Louis Federal Reserve Economic Data (FRED) is the source for variables used in this project. Data sets begin the first month of 1992, ends the twelfth month of 1998, and forecasts to the twelfth month of 2000. All data are measured in billions of chained 1992 dollars with seasonally adjusted annual rates. Though expenditures on nondurable items and services could also be used in the equation, movement in these areas is more volatile than durable goods. The relatively constant portion of expenditures on durable goods should act as a stabilizing agent in the forecast.
 

Part 3. Economic Theory

This forecast assumes expenditures on durable goods will be a predictor of future consumption spending as a whole. Durable goods expenditures indicate disposable income and consumer confidence. A further assumption is that recent growth rates in industrial production will remain relatively stable. This assumption allows for an accurate forecast over the next 24 months, into the years 1999 and 2000. The Keynesian consumption function is:
 

Ct = Co +MPC x Yt
 
In this equation, C is real aggregate consumption expenditures and Y is real GDP.

According to Keynesian theory, "the economy tends toward an ‘equilibrium’ level of production dictated by aggregate spending" (Oyen, pg. 168). This statement is commonly known as the aggregate expenditures model and it underlines the assumption that when aggregate expenditures is greater than production, production increases.

Durable goods are an accurate indicator of the consumer's confidence in the economy and their perceptions of its continued performance. The average annual growth rates for industrial production and consumption of durable goods will be used to project consumption over our forecast horizon of two years. The level of consumption in the predicted years will signal whether or not to expect inflation.

Adding real durable goods consumption as an explanatory variable, substituting the index of industrial production for real GDP, and lagging the right-hand-side variables 24 months (two years), and the consumption function can be written as a forecasting equation:
 

Ct = C0 + C1xDGt-24 + C2xIPt-24

This equation is the basis for the forecast presented in Part 4.
 

Part 4. A Short Term Forecast of Consumption, 1999-2000

 The forecasting equation based on the consumption function was estimated with 1992.1 through 1998.12 monthly data. The regression estimate is (t-statistics in parentheses):
 

(Ct ) = 131.9(13.51) + 0.908(2.09)x(DGt-24) + 26.471(8.88)x(IPt-24)
 
where durable goods is DG, industrial production is IP and the lag is 24 months.
 
The adjusted R-square of the estimate is .980169, indicating approximately 98% of the variation of consumption is explained by variation in the right-hand-side variables. The t-statistic of durable goods (2.092) is greater than two, rejecting the null hypothesis that C1 = 0. The t-statistic of industrial production is also greater than two (8.876), indicating strong rejection of the null hypothesis that C2 = 0. The t-statistic of the intercept (13.51) is greater than 2, rejecting the null hypothesis that the intercept equals zero. If the slopes were zero, it would indicate there is no relationship between the left and right-hand-side variables whereas t-statistics greater than 3 indicate strong rejection. Table 1 provides the forecast for consumption over the next two years.
 
Table 1
Forecast Consumption, 1999-2000
 
Month
Projected Consumption Expenditures
(billions of chained 1992 dollars)
Annual Percent Change
Jan-1999
Feb-1999
Mar-1999
Apr-1999
May-1999
Jun-1999
Jul-1999
Aug-1999
Sep-1999
Oct-1999
Nov-1999
Dec-1999
Jan-2000
Feb-2000
Mar-2000
Apr-2000
May-2000
Jun-2000
Jul-2000
Aug-2000
Sep-2000
Oct-2000
Nov-2000
Dec-2000
5236.2
5256.3
5268.2
5282.5
5294.0
5321.8
5361.5
5385.3
5397.3
5415.7
5445.2
5461.4
5478.5
5474.7
5480.4
5497.9
5539.0
5521.1
5489.0
5548.6
5555.1
5577.1
5570.7
5609.3
4.08%
3.89%
3.82%
3.76%
3.13%
3.01%
3.96%
4.03%
3.57%
3.69%
4.18%
3.75%
4.63%
5.05%
5.09%
4.97%
5.10%
3.59%
2.71%
3.56%
2.64%
2.38%
1.81%
1.70%
 
This forecast projects consumption spending to rise 3.53% in 1999 and 3.35% in 2000. This indicates a slight cooling in economic growth, which will be beneficial in keeping inflationary pressures down. Analysts accept a figure of 3% for long-term GDP growth, and these consumption growth rates are consistent with that figure. This forecast suggests the U.S. economy will continue to grow moderately, all other factors held constant.
 
Part 5. Forecast Implications
 
Consumption forecasts can be viewed as predictors of future economic expansion and indicate consumer confidence in the economy. This forecast predicts a mild slowing of economic growth over the next two years, but still indicates a strong economy and high consumer confidence. Even though growth is predicted to slow slightly over the next two years, it will still be at a rate that is high enough to sustain a very strong economy.

The slowing increase in consumption spending indicates consumers are taking a more realistic approach towards economic growth. The slight slowdown may not be noticeable to the average person because the gain will still be above average and is indicative of a strong and stable economy.
 

Part 6. Conclusion

Real consumption is predicted to rise at approximately 3.4 % per year. Assuming the forecast turns out to be correct, increasing durable goods consumption indicates a higher level of future output. An outside factor to consider would also be the wealth effect, which suggests higher durable goods spending may result from greater personal wealth. As the stock market booms along, people find their net worth increasing and have more wealth to finance consumption.
 

References