Reconciling Conflicting Evidence on the Elasticity of Intertemporal Substitution
In this paper, we reconcile two opposing views about the elasticity of intertemporal substitution (EIS), a parameter that plays a key role in macroeconomic analysis. On the one hand, empirical studies using aggregate consumption data typically find that the EIS is close to zero (Hall 1988). On the other hand, calibrated macroeconomic models designed to match growth and business cycle facts typically require that the EIS be close to one. We show that this apparent contradiction arises from ignoring two kinds of heterogeneity across individuals. First, a large fraction of households in the U.S. do not participate in stock markets. Second, a variety of microeconomic studies using individual-level data conclude that an individual's EIS increases with his wealth. We analyze a dynamic economy which incorporates both kinds of heterogeneity. We find that limited participation creates substantial wealth inequality matching that in U.S. data. Consequently, the dynamic behavior of output and investment is almost entirely determined by the preferences of the wealthy minority of households. At the same time, since consumption is much more evenly distributed across households than is wealth, estimation using aggregate consumption uncovers the low EIS of the majority of households (i.e., the poor). Our model also matches a number of cross-sectional features of the U.S. data that are otherwise difficult to explain. Finally, using simulated data generated by our heterogeneous-agent model, we show that the econometric methods used by Hall and others produce biased estimates of the average EIS across individuals. In particular, ignoring the correlation of instruments with (the omitted) conditional variances in the log-linearized Euler equation biases the estimate of the EIS downward by as much as 60%.
Year of publication: |
2000-10
|
---|---|
Authors: | Guvenen, Muhammet Fatih |
Institutions: | Carnegie Mellon University, Tepper School of Business |
Saved in:
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