Real business-cycle theory (RBC theory) is a class of new classical macroeconomics models in which business-cycle fluctuations are accounted for by real, in contrast to nominal, shocks. RBC theory sees business cycle fluctuations as the efficient response to exogenous changes in the real economic environment. That is, the level of national output necessarily maximizes expected utility.

In RBC models, business cycles are described as "real" because they reflect optimal adjustments by economic agents rather than failures of markets to clear. As a result, RBC theory suggests that governments should concentrate on long-term structural change rather than intervention through discretionary fiscal or monetary policy. These ideas are strongly associated with freshwater economics within the neoclassical economics tradition, particularly the Chicago School of Economics.

If we were to take snapshots of an economy at different points in time, no two photos would look alike. This occurs for two reasons:

A common way to observe such behavior is by looking at a time series of an economy's output, more specifically gross national product (GNP). This is just the value of the goods and services produced by a country's businesses and workers.

Figure 1 shows the time series of real GNP for the United States from 1954 to 2005. While we see continuous output growth, it is not a steady increase. There are times of faster growth and times of slower growth. Figure 2 transforms these levels into growth rates of real GNP and extracts a smoother growth trend. The Hodrick–Prescott filter is a common method to obtain this trend. The basic idea is to find a balance between the extent to which the general growth trend follows the cyclical movement (since the long-term growth rate is not likely to be perfectly constant) and how smooth it is. The HP filter identifies the longer-term fluctuations as part of the growth trend while classifying the more jumpy fluctuations as part of the cyclical component.

Observe the difference between this growth component and the jerkier data. Economists refer to these cyclical movements about the trend as business cycles. Figure 3 explicitly captures such deviations. Note the horizontal axis at 0. A point on this line indicates that there was no deviation from the trend that year. All other points above and below the line imply deviations. Using log real GNP, the distance between any point and the 0 line roughly equals the percentage deviation from the long-run growth trend. Also, note that the Y-axis uses very small values. This indicates that the deviations in real GNP are comparatively small and might be attributable to measurement errors rather than real deviations.

We call large positive deviations (those above the zero axis) peaks. We call relatively large negative deviations (those below the zero axis) troughs. A series of positive deviations leading to peaks are booms, and a series of negative deviations leading to troughs are recessions.

At a glance, the deviations look like a string of waves bunched together—nothing about it appears consistent. To explain the causes of such fluctuations may seem rather difficult, given these irregularities. However, considering other macroeconomic variables, we will observe patterns in these irregularities. For example, consider Figure 4, which depicts fluctuations in output and consumption spending, i.e., what people buy and use at any given period. Observe how the peaks and troughs align at almost the same places and how the upturns and downturns coincide.