Housing, credit and consumer expenditure: commentary

Mortgages ; Housing ; Consumer behavior

The Empirical Risk-Return Relation: a factor analysis approach

Financial economists have long been interested in the empirical relation between the conditional mean and conditional volatility of excess stock market returns, often referred to as the risk-return relation. Unfortunately, the body of empirical evidence on the risk-return relation is mixed and inconclusive. A key criticism of the existing empirical literature relates to the relatively small amount of conditioning information used to model the conditional mean and conditional volatility of excess stock market returns. To the extent that financial market participants have information not reflected in the chosen conditioning variables, measures of conditional mean and conditional volatility--and ultimately the risk-return relation itself--will be misspecified and possibly highly misleading. We consider one remedy to these problems using the methodology of dynamic factor analysis for large datasets, whereby a large amount of economic information can be summarized by a few estimated factors. We find that several estimated factors contain important information about one-quarter ahead excess returns and volatility that is not contained in commonly used predictor variables. Moreover, the factor-augmented specifications we examine predict an unusual 16-20 percent of the one-quarter ahead variation in excess stock market returns, and exhibit remarkably stable and strongly statistically significant out-of-sample forecasting power. Finally, in contrast to several pre-existing studies that rely on a small number of conditioning variables, we find a positive conditional correlation between risk and return that is strongly statistically significant, whereas the unconditional correlation is weakly negative and statistically snginficantpredictability, conditioning information, large dimension factor models

How important is the stock market effect on consumption?

Many argue that the astonishing growth in Americans' stock portfolios in the 1990s has been a major force behind the growth of consumer spending. This article reviews the relationship between stock market movements and consumption. Using various econometric techniques and specifications, the authors find that the propensity to consume out of aggregate household wealth has exhibited instability over the postwar period. They also show that the dynamic response of consumption growth to an unexpected change in wealth is extremely short-lived, implying that forecasts of consumption growth one or more quarters ahead are not typically improved by accounting for changes in existing wealth. Finally, the impact effect of a wealth shock on consumption growth, while statistically positive, is found to be uncertain. Although recent market gains have provided support for consumer spending, the authors' findings are too limited to encourage reliance on estimates of the stock market effect in macroeconomic forecasts.Stock market ; Consumption (Economics)

Does consumer confidence forecast household expenditure? a sentiment index horse race

This article is the first formal investigation of consumer attitudes that compares the forecasting power of the University of Michigan's Index of Consumer Sentiment and the Conference Board's Consumer Confidence Index. The authors find that measures available from the Conference Board have both economically and statistically significant explanatory power for several categories of consumer spending. By contrast, measures available from the University of Michigan generally exhibit weaker forecasting power for most categories of spending. As part of their analysis, the authors examine the ways in which the surveys underlying these measures differ and test whether certain types of survey questions are particularly important for predicting consumer spending.Consumer behavior ; Consumption (Economics)

Understanding Trend and Cycle in Asset Values: Reevaluating the Wealth Effect on Consumption

Both textbook economics and common sense teach us that the value of household wealth should be related to consumer spending. At the same time, movements in asset values often seem disassociated with important movements in consumer spending, as episodes such as the 1987 stock market crash and the contraction in equity values that occurred in the fall of 1998 suggest. An important first step in understanding the consumption-wealth linkage is determining how closely the two variables are actually correlated, and whether there exist important movements in asset values that are not associated with changes in consumption. This paper provides evidence that a surprisingly small fraction of the variation in household net worth is related to variation in aggregate consumer spending. We use empirical techniques that allow us to quantify the relative importance of permanent and transitory innovations in the variation of consumer spending and wealth and find that transitory shocks dominate post-war variation in wealth, while permanent shocks dominate variation in aggregate consumption. Although transitory innovations are found to have little influence on consumer spending, they have long-lasting effects on wealth , exhibiting a half-life of a little over two years. The findings suggest that most macro models which make no allowance for transitory variation in wealth that is orthogonal to consumption are likely to misstate both the timing and magnitude of the consumption-wealth linkage.

Land of Addicts? An Empirical Investigation of Habit-Based Asset Pricing Models

A leading explanation of aggregate stock market behavior suggests that assets are priced as if there were a representative investor whose utility is a power function of the difference between aggregate consumption and a "habit" level, where the habit is some function of lagged and (possibly) contemporaneous consumption. But theory does not provide precise guidelines about the parametric functional relationship between the habit and aggregate consumption. This makes formal estimation and testing challenging; at the same time, it raises an empirical question about the functional form of the habit that best explains asset pricing data. This paper studies the ability of a general class of habit-based asset pricing models to match the conditional moment restrictions implied by asset pricing theory. Our approach is to treat the functional form of the habit as unknown, and to estimate it along with the rest of the model's parameters. The resulting specification for investor utility is semiparametric in the sense that it contains both the finite dimensional set of unknown parameters that are part of the power function and time-preference, as well as the infinite dimensional unknown habit function that must be estimated nonparametrically. This semiparametric approach allows us to empirically evaluate a number of interesting hypotheses about the specification of habit-based asset pricing models, and to formally test the framework's ability to explain stock return data relative to other models that have proven empirically successful. We find that a flexibly estimated internal habit model can explain a cross-section of size and book-market sorted equity returns better than the Fama-French (1993) three-factor model, better than the Lettau-Ludvigson (2001) scaled consumption CAPM model, better than a flexibly estimated internal habit model, and better than the classic CAPM and consumption CAPM modelsHabit Formation, Asset Returns

Expected Returns and Expected Dividend Growth

We investigate a consumption-based present value relation that is a function of future dividend growth. Using data on aggregate consumption and measures of the dividend payments from aggregate wealth, we show that changing forecasts of dividend growth make an important contribution to fluctuations in the U.S. stock market, despite the failure of the dividend-price ratio to uncover such variation. In addition, these dividend forecasts are found to covary with changing forecasts of excess stock returns. The variation in expected dividend growth we uncover is positively correlated with changing forecasts of excess returns and occurs at business cycle frequencies, those ranging from one to six years. Because positively correlated fluctuations in expected dividend growth and expected returns have offsetting affects on the log dividend-price ratio, the results imply that both the market risk-premium and expected dividend growth vary considerably more than what can be revealed using the log dividend-price ratio alone as a predictive variable.

Euler Equation Errors

The standard, representative agent, consumption-based asset pricing theory based on CRRA utility fails to explain the average returns of risky assets. When evaluated on cross- sections of stock returns, the model generates economically large unconditional Euler equation errors. Unlike the equity premium puzzle, these large Euler equation errors cannot be resolved with high values of risk aversion. To explain why the standard model fails, we need to develop alternative models that can rationalize its large pricing errors. We evaluate whether four newer theories at the vanguard of consumption-based asset pricing can explain the large Euler equation errors of the standard consumption-based model. In each case, we find that the alternative theory counterfactually implies that the standard model has negligible Euler equation errors. We show that the models miss on this dimension because they mischaracterize the joint behavior of consumption and asset returns in recessions, when aggregate consumption is falling. By contrast, a simple model in which aggregate consumption growth and stockholder consumption growth are highly correlated most of the time, but have low or negative correlation in severe recessions, produces violations of the standard model's Euler equations and departures from joint lognormality that are remarkably similar to those found in the data.

The Declining Equity Premium: What Role Does Macroeconomic Risk Play?

Aggregate stock prices, relative to virtually any indicator of fundamental value, soared to unprecedented levels in the 1990s. Even today, after the market declines since 2000, they remain well above historical norms. Why? We consider one particular explanation: a fall in macroeconomic risk, or the volatility of the aggregate economy. We estimate a two-state regime switching model for the volatility and mean of consumption growth, and find evidence of a shift to substantially lower consumption volatility at the beginning of the 1990s. We then show that there is a strong and statistically robust correlation between low macroeconomic volatility and high asset prices: the estimated posterior probability of being in a low volatility state explains 30 to 60 percent of the post-war variation in the log price-dividend ratio, depending on the measure of consumption analyzed. Next, we study a rational asset pricing model with regime switches in both the mean and standard deviation of consumption growth, where the probabilities of a regime change are calibrated to match estimates from post-war data. Plausible parameterizations of the model are found to account for a significant fraction of the run-up in asset valuation ratios observed in the late 1990s.Equity Premium, Macro Volatility

Land of Addicts? An Empirical Investigation of Habit-Based Asset Pricing Behavior

This paper studies the ability of a general class of habit-based asset pricing models to match the conditional moment restrictions implied by asset pricing theory. We treat the functional form of the habit as unknown, and to estimate it along with the rest of the model's finite dimensional parameters. Using quarterly data on consumption growth, assets returns and instruments, our empirical results indicate that the estimated habit function is nonlinear, the habit formation is better described as internal rather than external, and the estimated time-preference parameter and the power utility parameter are sensible. In addition, the estimated habit function generates a positive stochastic discount factor (SDF) proxy and performs well in explaining cross-sectional stock return data . We find that an internal habit SDF proxy can explain a cross-section of size and book-market sorted portfolio equity returns better than (i) the Fama and French (1993) three-factor model, (ii) Lettau and Ludvigson (2001) scaled consumption CAPM model, (iii) an external habit SDF proxy, (iv) the classic CAPM, and (v) the classic consumption CAPM.