It is often argued that changes in expectation are an important driving force of the business cycle. However, it is well known that changes in expectations cannot generate positive co-movement between consumption, investment and employment in the most standard neo-classical business cycle models. This gives rise to the question of whether changes in expectation can cause business cycle fluctuations in neo-classical setting or whether such a phenomenon is inherently related to market imperfections. This paper offers a systematic exploration of this issue. Our finding is that expectation driven business cycle fluctuation can arise in neo-classical models when one allows for a sufficient rich description of the inter-sectorial production technology, however such a structure is rarely allowed in macro-models. In particular, the key characteristic which we isolate as giving rise to the possibility of Expectation Driven Business Cycles is that intermediate good producers exhibit cost complementarities (i.e., economies of scope) when supplying intermediate goods to different sectors of the economy.

"This paper uses aggregate Japanese data and sectoral U.S. data to explore the properties of the joint behavior of stock prices and total factor productivity (TFP) with the aim of highlighting data patterns that are useful for evaluating business cycle theories. The approach used follows that presented in Beaudry and Portier [2004b]. The main findings are that (i) in both Japan and the U.S., innovations in stock prices that are contemporaneously orthogonal to TFP precede most of the long run movements in total factor productivity and (ii) such stock prices innovations do not affect U.S. sectoral TFPs contemporaneously, but do precede TFP increases in those sectors that are driving U.S. TFP growth, namely durable goods, and among them equipment sectors"--National Bureau of Economic Research web site.

In this paper we show that the joint behavior of stock prices and TFP favors a view of business cycles driven largely by a shock that does not affect productivity in the short run -- and therefore does not look like a standard technology shock -- but affects productivity with substantial delay -- and therefore does not look like a monetary shock. One structural interpretation we suggest for this shock is that it represents news about future technological opportunities which is first captured in stock prices. We show that this shock causes a boom in consumption, investment and hours worked that precede productivity growth by a few years. Moreover, we show that this shock explains about 50\% of business cycle fluctuations.

There is a long tradition in macroeconomics suggesting that market imperfections may explain why economies repeatedly go through periods of booms and busts, with booms sowing the seeds of the subsequent busts. This idea can be captured mathematically as a limit cycle. For several reasons, limit cycles play almost no role in current mainstream business cycle theory. In this paper we present both a general structure and a particular model with the aim of giving new life to this mostly dismissed view of fluctuations. We begin by showing why and when models with strategic complementarities -- which are quite common in macroeconomics -- give rise to unique equilibrium dynamics characterized by a limit cycle. We then develop and estimate a fully-specified dynamic general equilibrium model that embeds a demand complementarity to see whether the data favors a configuration supportive of a limit cycle. Booms and busts arise endogenously in our setting because agents want to concentrate their purchases of goods at times when purchases by others are high, since in such situations unemployment is low and therefore taking on debt is perceived as being less risky. A key feature of our approach is that we allow limit-cycle forces to compete with exogenous disturbances in explaining the data. Our estimation results indicate that US business cycle fluctuations in employment and output can be well explained by endogenous demand-driven cycles buffeted by technological disturbances that render those fluctuations irregular.

Business cycles reflect changes over time in the amount of trade between individuals. In this paper we show that incorporating explicitly intra-temporal gains from trade between individuals into a macroeconomic model can provide new insight into the potential mechanisms driving economic fluctuations as well as modify key policy implications. We first show how a "gains from trade" approach can easily explain why changes in perceptions about the future (including "news" about the future) can cause booms and bust. We then turn to fiscal policy, and discuss under what conditions fiscal multipliers can be observed. While much of our analysis is conducted in a flexible price environment, we also present implications of our model for a sticky price environments, as it allows to understand stable-inflation boom-bust cycles. The source of the explicit gains from trade in our setup derives from simply assuming that in the short run workers are not perfect mobile across all sectors of the economy. We provide evidence from the PSID in support of this modeling assumption.