from the Cleveland Fed
Consumption represents approximately 70 percent of GDP as measured by the National Income and Product Accounts, so unsurprisingly it closely follows the overall trend of GDP during business cycles. Still, the two series are not identical; consumption is typically less volatile than GDP, falling by less in downturns and rising by less in recoveries. To understand why, it helps to see how the three main components of consumption – durables, nondurables, and services – have behaved over recent recoveries.
Durables consumption has a long-lived feature that makes it somewhat similar to investment. Just as an investment pays returns over multiple periods, durable goods can be used over and over, returning utility over time. Also like investment, durables consumption is more volatile than the other consumption components. During recessions, consumers tend to limit large and costly purchases due to declines in income or to the increased risk of a decline in income, causing a sharp downturn in durables sales; during recoveries, they come back strongly. Looking at the 1982 recovery, durables growth initially was subdued, growing only at the same pace as GDP in the first quarter. Over the next seven quarters however, durables consumption grew rapidly so that while GDP grew approximately 14 percent over the two years, durables grew by 25 percent. One recent recovery was an exception: During the 2001 to 2007 period, durables growth remained subdued.
Nondurable goods represent a larger share of aggregate consumption than durables, but the share has been falling over time. In 1982 approximately 33 percent of aggregate consumption came from nondurables whereas today it’s only 22 percent. Typically, nondurable consumption rebounds more slowly than durables during recoveries. In the 1991-1996 recovery, nondurables did not experience growth until about four quarters after the trough of the recession. While nondurables consumption did grow more in the two most recent recoveries than in previous expansionary periods, the magnitude of growth has not been large enough, when coupled with the decreasing share of nondurables in aggregate consumption, to have had more than a minimal impact.
Services make up the largest share of aggregate consumption – roughly two-thirds today – and consequently services play a much larger role in determining the level of overall consumption. However, services also tend to be less volatile than GDP. During economic downturns, services are generally much less responsive and remain at prerecession levels. During expansionary periods, services usually follow the increasing trend of GDP very closely. For this reason, services usually explain less of the change in consumption from quarter to quarter. Coming out of the last recession, services consumption has risen a bit more sluggishly than it did in previous recoveries.
Even when durables and nondurables consumption growth is strong, the large share that services now comprise of aggregate consumption means that services largely determine the path for the level of aggregate consumption.
Source for this Post: https://www.clevelandfed.org/en/Newsroom%20and%20Events/Publications/Economic%20Trends/2015/The%20Behavior%20of%20Consumption%20in%20Recoveries.aspx
The views expressed in Federal Reserve Bank of Cleveland publications and working papers are strictly those of the authors. They do not necessarily represent the position of the Federal Reserve Bank of Cleveland, or the Federal Reserve System.
About the Authors
Daniel Carroll is a research economist in the Research Department of the Federal Reserve Bank of Cleveland. His primary research interests are macroeconomics, public finance, and political economy. Currently, he is studying the implications of progressive income taxation for the distributions of wealth and income.
Amy Higgins is a research analyst in the Research Department of the Federal Reserve Bank of Cleveland. Her primary interests include microeconomics, regional, urban, and development economics, labor economics, econometrics, and learning how to apply linear, nonlinear, and dynamic programming and stochastic modeling to economics.