Academic journal article Federal Reserve Bank of St. Louis Review

Granger Causality and Equilibrium Business Cycle Theory

Academic journal article Federal Reserve Bank of St. Louis Review

Granger Causality and Equilibrium Business Cycle Theory

Article excerpt

Postwar U.S. data show that consumption growth "Granger-causes" output and investment growth, which is puzzling if technology is the driving force of the business cycle. The author asks whether general equilibrium models with information frictions and non-technology shocks can rationalize the observed causal relationships. His conclusion is they cannot. (JEL E13, E32)

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There is a "causal" relationship among consumption, output, and investment. Postwar U.S. data show that consumption growth "Granger-causes" gross domestic product (GDP) growth but not vice versa and that GDP growth in turn Granger-causes business investment growth but not vice versa. (1) This unidirectional causal chain suggests that consumption contains better information about the source of shocks hitting the economy than does output, and output in turn contains better information about such shocks than does investment.

This causal relationship cannot be explained by standard real business cycle (RBC) models. For example, under technology shocks, output contains the best information possible for the source of shocks; hence, it will not appear to be "Granger-caused" by consumption once the history of output is taken into account. To rationalize the causal relationship found in the U.S. data, it seems natural to consider demand shocks and to add a richer information structure into standard models such that demand shocks can affect consumption before affecting output and investment. (2)

I investigate whether existing equilibrium business cycle models driven by demand shocks (in particular, government spending shocks) can rationalize the observed causal relationship when the following information structure is embedded: (i) Employment and output cannot respond to demand shocks immediately; they can do so only with a lag behind consumption. And (ii) investment cannot respond to demand shocks immediately; it can do so only with a lag behind output. (3)

Under these ad hoc assumptions, I first show that standard general equilibrium business cycle models do predict the existence of a causal chain from consumption to output and investment, but with the wrong sign. Namely, consumption growth negatively causes output growth, and output growth in turn negatively causes investment growth. (4) In the U.S. data, however, these causal relationships are strictly positive. The negative causal chain emerges from standard models because of the crowding-out effect among components of aggregate demand in general equilibrium.

I then choose to mitigate the crowding-out problem by allowing for variable capacity utilization and production externalities in standard models, following Baxter and King (1990), Benhabib and Farmer (1994), Burnside and Eichenbaum (1996), Wen (1998), and Benhabib and Wen (2004). Variable capacity utilization and mild production externalities mitigate the crowding-out problem by creating short-run increasing returns to labor, which permit the expansion of output to meet aggregate demand with little increase in marginal costs in the short run. These modifications, however, bring about only limited success. The model now predicts that output growth positively causes investment growth, but it fails to predict that consumption growth positively causes output growth. The source of failure is still the crowding-out effect: Demand shocks crowd out consumption at the impact period during which neither output nor investment is able to respond.

There seem to be no simple remedies for the problems identified. More fundamental modifications to existing models are required to fully explain the causal aspects of the business cycle in general equilibrium. One possible remedy is to allow for inventory accumulation, so as to further mitigate the crowding-out effect on consumption. Because general equilibrium business cycle models with inventories are still at an early stage of development, this channel is left as a future research topic. …

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