This paper exploits a data rich environment to provide direct econometric estimates of time-varying macroeconomic uncertainty. Our estimates display significant independent variations from popular uncertainty proxies, suggesting that much of the variation in the proxies is not driven by uncertainty. Quantitatively important uncertainty episodes appear far more infrequently than indicated by popular uncertainty proxies, but when they do occur, they are larger, more persistent, and are more correlated with real activity. Our estimates provide a benchmark to evaluate theories for which uncertainty shocks play a role in business cycles. (JEL C53, D81, E32, G12, G35, L25)

This paper studies the role of f luctuations in the aggregate consumption-wealth ratio for predicting stock returns. Using U.S. quarterly stock market data, we find that these f luctuations in the consumption-wealth ratio are strong predictors of both real stock returns and excess returns over a Treasury bill rate. We also find that this variable is a better forecaster of future returns at short and intermediate horizons than is the dividend yield, the dividend payout ratio, and several other popular forecasting variables. Why should the consumption-wealth ratio forecast asset returns? We show that a wide class of optimal models of consumer behavior imply that the log consumption-aggregate wealth~human capital plus asset holdings! ratio summarizes expected returns on aggregate wealth, or the market portfolio. Although this ratio is not observable, we provide assumptions under which its important predictive components for future asset returns may be expressed in terms of observable variables, namely in terms of consumption, asset holdings and labor income. The framework implies that these variables are cointegrated, and that deviations from this shared trend summarize agents' expectations of future returns on the market portfolio. UNDERSTANDING THE EMPIRICAL LINKAGES between macroeconomic variables and financial markets has long been a goal of financial economics. One reason for the interest in these linkages is that expected excess returns on common stocks appear to vary with the business cycle. This evidence suggests that stock returns should be forecastable by business cycle variables at cyclical frequencies. Indeed, the forecastability of stock returns is well documented. Financial indicators such as the ratios of price to dividends, price to earnings, or dividends to earnings have predictive power for excess returns over a Treasury-bill rate. These financial variables, however, have been most successful at predicting returns over long horizons. Over horizons spanning the 815 length of a typical business cycle, stock returns have typically been found to be only weakly forecastable. 1 Moreover, traditional macroeconomic variables have proven especially dismal as predictive variables.The question of whether expected returns vary at cyclical frequencies and with macroeconomic variables is also pertinent to the debate over why excess returns are predictable. One possibility is that financial markets are inefficient. Alternatively, predictable variation in returns could simply ref lect the rational response of agents to time-varying investment opportunities, possibly driven by cyclical variation in risk aversion~e.g., Sundaresañ 1989!, Constantinides~1990!, Campbell and Cochrane~1999!! or in the joint distribution of consumption and asset returns. If these rational explanations are correct, it is reasonable to expect that key macroeconomic variables should perform an important function in forecasting excess stock returns. As yet, however, there is little empirical evidence that real macroeconomic variables perform ...

This paper explores the ability of theoretically-based asset pricing models such as the CAPM and the consumption CAPM referred to jointly as the (C)CAPM to explain the cross-section of average stock returns. Unlike many previous empirical tests of the (C)CAPM, we specify the pricing kernel as a conditional linear factor model, as would be expected if risk premia vary over time. Central to our approach is the use of a conditioning variable which proxies for fluctuations in the log consumption-aggregate wealth ratio and is likely to be important for summarizing conditional expectations of excess returns. We demonstrate that such conditional factor models are able to explain a substantial fraction of the cross-sectional variation in portfolio returns. These models perform much better than unconditional (C)CAPM specifications, and about as well as the three-factor Fama-French model on portfolios sorted by size and book-to-market ratios. This specification of the linear conditional consumption CAPM, using aggregate consumption data, is able to account for the difference in returns between low book-to-market and high book-to-market firms and exhibits little evidence of residual size or book-to-market effects. (JEL G10, E21) 9 This debate is borne out in several recent papers; for example, see Daniel and Titman (1997, 1998) and Davis, Fama and French (forthcoming). 10 See Harrison and Kreps (1979).

Uncertainty about the future rises in recessions. But is uncertainty a source of business cycles or an endogenous response to them, and does the type of uncertainty matter? We propose a novel SVAR identification strategy to address these questions via inequality constraints on the structural shocks. We find that sharply higher macroeconomic uncertainty in recessions is often an endogenous response to output shocks, while uncertainty about financial markets is a likely source of output fluctuations. But the findings also suggest that macroeconomic uncertainty plays an important role in recessions, by substantially amplifying downturns caused by other shocks.