We model consumption and dividend growth rates as containing (i) a small long-run predictable component and (ii) fluctuating economic uncertainty (consumption volatility). These dynamics, for which we provide empirical support, in conjunction with Epstein and Zin’s (1989) preferences, can explain key asset markets phenomena. In our economy, financial markets dislike economic uncertainty and better long-run growth prospects raise equity prices. The model can justify the equity premium, the risk-free rate, and the volatility of the market return, risk-free rate, and the price-dividend ratio. As in the data, dividend yields predict returns and the volatility of returns is time-varying.

In a financially integrated global market, the conditionally expected return on a portfolio of securities from a particular country is determined by the country's world risk exposure. This paper measures the conditional risk of 17 countries. The reward per unit of risk is the world price of covariance risk. Although the tests provide evidence on the conditional mean variance efficiency of the benchmark portfolio, the results show that countries' risk exposures help explain differences in performance. Evidence is also presented which indicates that these risk exposures change through time and that the world price of covariance risk is not constant.

This paper explores the ability of conditional versions of the CAPM and the consumption CAPM—jointly the (C)CAPM—to explain the cross section of average stock returns. Central to our approach is the use of the log consumption–wealth ratio as a conditioning variable. We demonstrate that such conditional models perform far better than unconditional specifications and about as well as the Fama-French three-factor model on portfolios sorted by size and book-to-market characteristics. The conditional consumption CAPM can account for the difference in returns between low-book-to-market and high-bookto-market portfolios and exhibits little evidence of residual size or book-to-market effects. We are grateful to Eugene Fama and Kenneth French for graciously providing the

In this paper we examine the dynamic resolution of technological adoption in \hardware/software" systems. We are interested in determining to what extent software availability a®ects hardware sales and/or vice-versa. We ¯st develop a dynamic model for estimating demand when costs (and hence prices) are declining over time. We then estimate it empirically for the case of compact disc players. We ¯nd that there is \two-way " feedback between hardware and software for compact disc players. The result that the availability of compatible software (the CDs) plays a signi¯cant role in determining the adoption of compact disc players is likely due in part to the fact that compact disc players were not compatible with any existing audio standard.

Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other complications such as introducing infinite dimensional parameter spaces that may not be compact. The method of sieves provides one way to tackle such complexities by optimizing an empirical criterion function over a sequence of approximating parameter spaces, called sieves, which are significantly less complex than the original parameter space. With different choices of criteria and sieves, the method of sieves is very flexible in estimating complicated econometric models. For example, it can simultaneously estimate the parametric and nonparametric components in semi-nonparametric models with or without constraints. It can easily incorporate prior information, often derived from economic theory, such as monotonicity, convexity, additivity, multiplicity, exclusion and non-negativity. This chapter describes estimation of semi-nonparametric econometric models via the method of sieves. We present some general results on the large sample properties of the sieve estimates, including consistency of the sieve extremum estimates, convergence rates of the sieve M-estimates, pointwise normality of series estimates of regression functions, root-n asymptotic normality and efficiency of sieve estimates of smooth functionals of infinite dimensional parameters. Examples are used to illustrate the general results.

This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a time-varying pricing kernel, which we call the empirical pricing kernel (EPK). We estimate the EPK on a monthly basis from 1991 to 1995, using S&P 500 index option data and a stochastic volatility model for the S&P 500 return process. We find that the EPK exhibits countercyclical risk aversion over S&P 500 return states. We also find that hedging performance is significantly improved when we use hedge ratios based the EPK rather than a time-invariant pricing kernel.

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In parametric models a sufficient condition for local identification is that the vector of momentconditionsisdifferentiable at the true parameter with full rank derivative matrix. We show that additional conditions are often needed in nonlinear, nonparametric models to avoid nonlinearities overwhelming linear effects. We give restrictions on a neighborhood of the true valuethataresufficient for local identification. We apply these results to obtain new, primitive identification conditions in several important models, including nonseparable quantile instrumental variable (IV) models, single-index IV models, and semiparametric consumption-based asset pricing models. JEL Classification: C12, C13, C23

We show that the external habit-formation model economy of Campbell and Cochrane ~1999! can explain why the Capital Asset Pricing Model ~CAPM! and its extensions are better approximate asset pricing models than is the standard consumptionbased model. The model economy produces time-varying expected returns, tracked by the dividend--price ratio. Portfolio-based models capture some of this variation in state variables, which a state-independent function of consumption cannot capture. Therefore, though the consumption-based model and CAPM are both perfect conditional asset pricing models, the portfolio-based models are better approximate unconditional asset pricing models. THE DEVELOPMENT OF CONSUMPTION-BASED ASSET PRICING THEORY ranks as one of the major advances in financial economics during the last two decades. The classic papers of Lucas ~1978!, Breeden ~1979!, Grossman and Shiller ~1981!, and Hansen and Singleton ~1982, 1983! show how a simple relation between consumption ...

The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data. It amounts to treating the data as if they were the population for the purpose of evaluating the distribution of interest. Under mild regularity conditions, the bootstrap yields an approximation to the distribution of an estimator or test statistic that is at least as accurate as the