Academic journal article Federal Reserve Bank of St. Louis Review

Trends in Hours, Balanced Growth, and the Role of Technology in the Business Cycle

Academic journal article Federal Reserve Bank of St. Louis Review

Trends in Hours, Balanced Growth, and the Role of Technology in the Business Cycle

Article excerpt

This paper revisits a property embedded in most dynamic macroeconomic models: the stationarity of hours worked. First, the author argues that, contrary to what is often believed, there are many reasons why hours could be nonstationary in those models, while preserving the property of balanced growth. Second, the author shows that the postwar evidence for most industrialized economies is clearly at odds with the assumption of stationary hours per capita. Third, he examines the implications of that evidence for the role of technology as a source of economic fluctuations in the G7 countries.


Business cycles have long been associated with highly procyclical fluctuations in labor input measures. In the mind of the common man, the recurrent ups and downs in employment (or unemployment) observed in modern economies are arguably more of a defining feature of the business cycle than the accompanying fluctuations in gross domestic product (GDP). (1) Understanding the factors underlying the joint variation of output and labor input measures remains a key item in macroeconomists' research agenda.

This paper focuses on a dimension of those joint fluctuations that is generally ignored by macroeconomists, in theoretical as well as in empirical analysis: the long-run behavior of hours worked. In particular, the paper revisits a property common to the majority of intertemporal equilibrium models used in macroeconomic applications, namely, that of stationarity of hours worked per capita. First, I argue that, contrary to what is often believed, stationarity of (per capita) hours is not a necessary condition for those models to generate a balanced-growth path. Second, and perhaps most importantly, I show that the evidence for the G7 economies is generally at odds with the key equilibrium relationship that underlies the stationarity of hours in those models. In fact, that evidence suggests that both margins of labor utilization (i.e., hours per worker and the employment rate) display some nonstationarity features in most G7 countries.

The evidence of nonstationarity in hours per worker points to the importance of using an hours-based measure of productivity when estimating the effects of technology shocks under the approach proposed in Gali (1999), in which technology shocks are identified as the only source of nonstationarity in labor productivity. The reason is straightforward: Shocks unrelated to technology that have a permanent effect on hours per worker (but not on output per hour) would be a source of nonstationarity in employment-based measures of productivity and would thus be mislabeled as technology shocks. I revisit here the international evidence on the effects of technology shocks using an hours-based measure of productivity and find little evidence in support of a major role of technology as a source of business cycles.

The paper is organized as follows. Section 2 discusses the relationship between the stationarity of hours and the balanced-growth hypothesis. Section 3 provides some evidence on the behavior of the two margins of labor utilization for the G7 countries and discusses the implications of that evidence. Section 4 presents new estimates of the effects and role of technology shocks in the G7 countries.


Since the seminal work by Kydland and Prescott (1982) and Prescott (1986), most business cycle models have adopted a neoclassical growth framework (augmented with a consumption-leisure choice) as a "core structure," on which stochastic disturbances and frictions of different sorts are added. The choice of a specification for preferences and technology in the resulting models has been generally guided by the requirement that the underlying deterministic model is consistent with some "stylized facts" of growth. It is generally argued that imposing such a requirement facilitates calibration of the model on the basis of information unrelated to the business cycle phenomena that the model seeks to explain. …

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