Real Business Cycle Theory

Background

After the stagflation of the 1970s and the Lucas critique, macroeconomics was pressed to build models grounded in microeconomic optimization and rational expectations. Robert Lucas (1977) argued that business cycles should be understood as equilibrium phenomena. Extending this, Kydland and Prescott (1982), in "Time to Build and Aggregate Fluctuations," presented a model explaining business cycles within the neoclassical growth model, and Long and Plosser (1983) named the approach real business cycles. Its claim that a model with no money at all could reproduce many key features of postwar US fluctuations made a large impact.

Core mechanism and method

In an RBC model a representative household allocates consumption and leisure optimally over time and firms produce with capital and labor. The main source of fluctuations is random change in total factor productivity, a technology shock, measured by the residual from Solow's (1957) growth accounting, the Solow residual. A positive technology shock temporarily raises wages and returns to capital, so households work more now (intertemporal labor substitution) and firms invest more, sharply raising output. Investment and capital accumulation spread the shock's effects over many periods. Prescott (1986) championed calibration: setting parameters from micro studies and long-run data, then comparing the standard deviations and correlations the model generates with actual data. The Hodrick–Prescott (HP) filter was used to separate trend from cycle (Hodrick and Prescott, 1997). Because fluctuations in this framework are efficient responses to shocks, stabilization policy may be unnecessary or even harmful.

Critiques and legacy

Lawrence Summers (1986) objected that there is no evidence of large technological regress causing recessions and that the assumed intertemporal elasticity of labor supply far exceeds micro estimates. Gregory Mankiw (1989) noted that recessions such as the Great Depression are hard to explain by technological regress and that the theory ignores evidence that money affects real activity. Jordi Galí (1999) found empirically that technology shocks reduce employment in the short run, challenging RBC's core mechanism, and critics noted that the Solow residual mixes in factors such as labor hoarding. Even so, RBC's methodological legacy is immense. Its framework of microfoundations, rational expectations, dynamic optimization and general equilibrium, combined with Keynesian frictions such as sticky prices in New Keynesian models, became the dynamic stochastic general equilibrium (DSGE) models central banks use today (King and Rebelo, 1999; Smets and Wouters, 2007).

FAQ

What is real business cycle theory in simple terms?

Booms and busts happen not because of money or weak demand but because changes in technology and production conditions lead people and firms to rationally adjust how much they work and invest.

How does it relate to DSGE models?

Today's DSGE models used by central banks take the microfoundations and dynamic optimization framework that RBC pioneered and add Keynesian elements such as sticky prices.

Sources reviewed: 2026-10-26

References

1. Kydland, F. E., & Prescott, E. C. (1982). Time to build and aggregate fluctuations. Econometrica, 50(6), 1345–1370.
2. Long, J. B., & Plosser, C. I. (1983). Real business cycles. Journal of Political Economy, 91(1), 39–69.
3. Prescott, E. C. (1986). Theory ahead of business cycle measurement. Federal Reserve Bank of Minneapolis Quarterly Review, 10(4), 9–22.
4. Summers, L. H. (1986). Some skeptical observations on real business cycle theory. Federal Reserve Bank of Minneapolis Quarterly Review, 10(4), 23–27.
5. Plosser, C. I. (1989). Understanding real business cycles. Journal of Economic Perspectives, 3(3), 51–77.
6. Mankiw, N. G. (1989). Real business cycles: A new Keynesian perspective. Journal of Economic Perspectives, 3(3), 79–90.
7. Solow, R. M. (1957). Technical change and the aggregate production function. Review of Economics and Statistics, 39(3), 312–320.
8. Lucas, R. E. (1977). Understanding business cycles. Carnegie-Rochester Conference Series on Public Policy, 5, 7–29.
9. King, R. G., & Rebelo, S. T. (1999). Resuscitating real business cycles. In Handbook of Macroeconomics (Vol. 1B, pp. 927–1007). Amsterdam: Elsevier.
10. Galí, J. (1999). Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? American Economic Review, 89(1), 249–271.
11. Hodrick, R. J., & Prescott, E. C. (1997). Postwar U.S. business cycles: An empirical investigation. Journal of Money, Credit and Banking, 29(1), 1–16.
12. Smets, F., & Wouters, R. (2007). Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review, 97(3), 586–606.
13. Cooley, T. F. (Ed.). (1995). Frontiers of Business Cycle Research. Princeton: Princeton University Press.