For homothetic time and state separable preferences, the coefficient of relative risk aversion (CRRA) is equal to the reciprocal of the elasticity of intertemporal substitution (EIS). This paper shows that, when the growth rate of consumption is i.i.d., asset pricing models based upon preferences in which the CRRA and the EIS are no longer linked do not have more explanatory power. Further, in these stochastic environments, estimates of the CRRA in the standard preferences are measures of the true CRRA and not the EIS. These results are fairly accurate descriptions of economies calibrated using United States annual data.

Monetary models based on cash-in-advance constraints make strong predictions about the stochastic properties of endogeneous variables such as the velocity of circulation of money, the rate of inflation, and real and nominal interest rates. We develop numerical methods to understand these predictions because the models cannot be characterized analytically. We calibrate some cash-in-advance models using driving processes estimated from U. S. time-series data to generate model predictions that are compared to sample statistics. Formulations of the models that generate variability in velocity corresponding to the U.S. data typically fail along other dimensions.

We compare the empirical performance of a standard incomplete markets asset pricing model with that of a novel model with constrained Pareto‐optimal allocations. We represent the models’ stochastic discount factors in terms of the cross‐sectional distribution of consumption and use these representations to evaluate the models’ empirical implications. The first model is inconsistent with the equity premium in the United States, United Kingdom, and Italy. The second model is consistent with the equity premium and the risk‐free rate in all three countries if the coefficient of relative risk aversion is roughly 5 and the quarterly discount factor is less than 0.5.

In this paper, we consider an environment in which agents ’ productivities are private information, potentially multi-dimensional, and follow arbitrary stochastic processes. We allow for arbitrary incentive-compatible and physically feasible tax schemes. We prove that it is typically Pareto optimal to have positive capital taxes. As well, we prove that in any given period, it is Pareto optimal to tax consumption goods at a uniform rate. All, University of Minnesota and the Federal Reserve Bank of Minneapolis. Kocherlakota acknowledges the

Monetary models based on cash-in-advance constraints make strong predictions about the stochastic properties of endogeneous variables such as the velocity of circulation of money, the rate of inflation, and real and nominal interest rates. We develop numerical methods to understand these predictions because the models cannot be characterized analytically. We calibrate some cash-in-advance models using driving processes estimated from U. S. time-series data to generate model predictions that are compared to sample statistics. Formulations of the models that generate variability in velocity corresponding to the U.S. data typically fail along other dimensions.

We consider an environment in which individuals receive income shocks that are unobservable to others and can privately store resources. We provide a simple characterization of the unique efficient allocation of consumption in cases in which the rate of return on storage is sufficiently high or, alternatively, in which the worst possible outcome is sufficiently dire. We show that, unlike in environments without unobservable storage, the symmetric efficient allocation of consumption is decentralizable through a competitive asset market in which individuals trade riskfree bonds among themselves.

Narayana R. Kocherlakota, Kei-Mu Yi, A Simple Time Series Test of Endogenous vs. Exogenous Growth Models: An Application to the United States, The Review of Economics and Statistics, Vol. 78, No. 1 (Feb., 1996), pp. 126-134