Production-based Asset Pricing Model Research Articles

Disaster learning and aggregate investment

We extend a production-based asset pricing model by introducing learning about disaster risk. The information is not perfect, and Bayesian learning is adopted to update beliefs about the likelihood of rare disasters. We show that disaster learning reconciles key stylized facts about macroeconomic quantities and financial markets. For macroeconomic quantities, during the crisis, the decline in aggregate investments is much worse than that of output, whereas the decline in aggregate consumption is moderate relative to that of output. Additionally, the model endogenously features lower consumption volatility and higher investment volatility than that of output. For financial markets, belief updating over a rare disaster produces a higher equity premium, lower risk-free rate, and more volatile stock returns. Finally, we show that jump intensity uncertainty accounts for a substantial fraction of the total welfare cost of rare disasters.

The equity premium puzzle and two assets: GMM estimation

ABSTRACT We quantify a production-based asset pricing model with fixed and variable capitals based on the GMM structural estimation. The estimation results match the stylized characteristics of the U.S. stock market return and help enlighten the equity premium puzzle. In addition, the model performance is reliable throughout the business cycle.

Learning and the capital age premium

Imperfect information and learning are introduced into a production-based asset pricing model. Our model features slow learning about firms’ exposure to aggregate productivity shocks over time. In contrast to a full information case, our framework provides a unified explanation for the stylized empirical features of the cross-section of stocks that differ in capital age: old capital firms (1) have higher capital allocation efficiency; (2) are more exposed to aggregate productivity shocks and, hence, earn higher expected returns, which we refer to as capital age premium; and (3) have shorter cash-flow duration, when compared with young capital firms.

Job postings and aggregate stock returns

The job openings-to-employment ratio (JOE), defined as the number of job postings divided by the employment level, is among the strongest known predictors of the equity premium. We find that JOE outperforms a broad set of over two dozen popular predictor variables in both in-sample and out-of-sample forecasting tests. Forecasts based on JOE also produce gains of 2.91% in annualized certainty equivalent return and 0.20 in annualized Sharpe ratio relative to forecasts based on the historical mean equity premium. The empirical results are consistent with a standard production-based asset pricing model with labor inputs and search frictions.

Long-term discount rates do not vary across firms

Long-term expected returns do not appear to vary in the cross section of stocks. We show that even negligible persistent differences in expected returns, if they existed, would be easy to detect. Markers of such differences, however, are absent from actual stock returns. Our results are consistent with behavioral models and production-based asset pricing models in which firms’ risks change over time. Consistent with the lack of long-term differences in expected returns, persistent differences in firm characteristics do not predict the cross section of stock returns. Our results imply that stock market anomalies have only a limited effect on firm valuations.

Financial Uncertainty with Ambiguity and Learning

We examine a production-based asset pricing model with regime-switching productivity growth, learning, and ambiguity. Both the mean and volatility of the growth rate of productivity are assumed to follow a Markov chain with an unobservable state. The agent’s preferences are characterized by the generalized recursive smooth ambiguity utility function. Our calibrated benchmark model with modest risk aversion can match moments of the variance risk premium in the data and reconcile empirical relations between the risk-neutral variance and macroeconomic quantities and their respective volatilities. We show that the interplay between productivity volatility risk and ambiguity aversion is important for pricing variance risk in returns. This paper was accepted by Tomasz Piskorski, finance.

Average crossing time: An alternative characterization of mean aversion and reversion

This study compares and contrasts the multiple characterizations of mean reversion in financial time series as regards the restrictions they imply. This is accomplished by translating them into statements about an alternative measure, the “Average Crossing Time” or ACT. We argue that the ACT measure, per se, provides not only a useful benchmark for the degree of mean reversion/aversion, but also an intuitive, and easily quantified sense of one time series being “more strongly mean‐reverting/averting” than another. We conclude our discussion by deriving the ACT measure for a wide class of stochastic processes and detailing its statistical characteristics. Our analysis is principally undertaken within a class of well‐understood production based asset pricing models.

Untangling the Value Premium with Labor Shares

Abstract This paper quantifies the relative importance of labor-induced operating leverage at explaining the value premium. I extend a traditional variance decomposition methodology using labor shares to disentangle labor leverage from the value premium and from the value spread and from the variation in profitability levels and growth. My extended decomposition shows that labor leverage explains approximately 50% of the value premium, whereas profitability and growth-based mechanisms explain the other 50%. I propose a tractable production-based asset-pricing model that qualitatively and quantitatively explains this finding, as well as the relation between book-to-market ratios, discount rates, profitability, and future growth.

Production, Consumption, and Time Varying Expected Returns

This paper develops an empirical test of the q-theory production based asset pricing model. In general equilibrium, with habit utility and adjustment costs of investment, it must be the case that when the consumption surplus predicts stock returns corresponding investment patterns must predict investment returns to the same extent. The no arbitrage condition also implies investment patterns must predict stock returns in the same way as the consumption surplus. Using this insight, we find strong empirical support for the production based model without encountering the difficulties of calculating investment returns. Consequently, previous rejections of the model most likely stem from the failure of one or more of the many assumptions that are needed to construct investment returns.

Government Debt, Dividend Growth, and Stock Returns

This paper documents that the increase in public debt can lead to higher dividend payout to shareholders, which suggests public debt can be a strong cash flow predictor which helps better predict future stock returns. Specifically, the higher public debt-to-GDP ratio can predict both higher dividend growth and higher stock returns, and the predicted changes are in the same magnitudes. The finding is consistent with Lettau and Ludvigson's (2005) argument that there exists a common component among stock returns and dividend growth. We argue that i) public debt can drive the co-movement among returns and dividend growth, and the existence of a common component can resolve the US asset pricing puzzle as emphasized by Cochrane (2007, 2011) that the dividend-price ratio can only predict discount rates but not cash flows; ii) the strong cash flow predictability of the public debt-to-GDP ratio can not be consumed by the popular consumption-to-wealth ratio (cay) and many other macroeconomic states variables; iii) future stocks returns can be better out-of-sample predicted after controlling for public debt. The empirical evidence documented in the US aggregate market can also be extended to the US cross-section and the international markets, especially for the advanced financial markets, which helps to explain the weak cash flow predictability recently documented by Rangvid et al. (2014) and Maio et al. (2015). To rationalize the finding, we propose a production-based asset pricing model incorporating cash-retention friction on the corporate sector. The model can produce testable predictions that the increase in public debt moves both dividend payment and the cost of capital in the same direction, resulting in the capture of the common component.

Computational Methods for Production-Based Asset Pricing Models with Recursive Utility

Abstract We compare local and global polynomial solution methods for DSGE models with Epstein- Zin-Weil utility. We show that model implications for macroeconomic quantities are relatively invariant to choice of solution method but that a global method can yield substantial improvements for asset prices and welfare costs. The divergence in solution quality is highly dependent on parameters which affect value function sensitivity to TFP volatility, as well as the magnitude of TFP volatility itself. This problem is pronounced for calibrations at the extreme of those accepted in the asset pricing literature and disappears for more traditional macroeconomic parameterizations.

Correlations, Value Factor Returns, and Growth Options

This paper documents that the average equity market correlation is informative about the value of growth options and the correlation dynamics of growth and value stocks and, in turn, forecasts changes in growth options and the returns on the value factor. Consistently, a production-based asset-pricing model shows that correlations are homogeneous among stocks with similar growth characteristics and increasing in the value of growth options. Therefore, the expected average equity correlation serves as a leading procyclical state variable and drives the value premium. Correlations extracted from an equity value index improve the predictability of value-related factors in-sample and out-of-sample.

Can ambiguity about rare disasters explain equity premium puzzle?

We study the effects of ambiguity aversion to diffusion risk and jump risk on asset prices in a production-based asset pricing model and find that ambiguity aversion to jump risk can resolve equity premium puzzle and risk-free rate puzzle.

Long-Term Discount Rates Do Not Vary Across Firms

Long-term expected returns appear to vary little, if at all, in the cross section of stocks. We devise a bootstrapping procedure that injects small amounts of variation into expected returns and show that even negligible differences in expected returns, if they existed, would be easy to detect. Markers of such differences, however, are absent from actual stock returns. Our estimates are consistent with production-based asset pricing models such as Berk, Green, and Naik (1999) and Gomes, Kogan, and Zhang (2003) in which firms' risks change over time. We show that long-term reversals in stock returns are the consequence of the rapid convergence in expected returns. Our results imply stock market anomalies have only a limited effect on firm valuations. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Investment, Consumption and Asset Pricing Model with Ambiguity Aversion

In this paper, we incorporate ambiguity aversion into production-based asset-pricing model of Eberly and Wang (2009b). We derive explicitly the optimal investment, consumption, Tobin’s q, equity premium, equilibrium interest rate and growth rate of capital. We examine the impact of ambiguity aversion on the solutions of model. This paper shows that the relationship between optimal investment, consumption, Tobin’s q and the growth rate of capital and ambiguity aversion is affected by the elasticity of intertemporal substitution. The equilibrium interest rate increases with ambiguity aversion. We separate the impact of risk aversion from the risk aversion on equity premium.

Government debt and the returns to innovation

Elevated levels of government debt raise concerns about their effects on long-term growth prospects. Using the cross-section of US stock returns, we show that (i) high-R&D firms are more exposed to government debt and pay higher expected returns than low-R&D firms, and (ii) higher levels of the debt-to-GDP ratio predict higher risk premiums for high-R&D firms. Furthermore, rises in the cost of capital for innovation-intensive firms predict declines in subsequent productivity and economic growth. We propose a production-based asset pricing model with endogenous innovation and fiscal policy shocks that can rationalize key aspects of the empirical evidence. Our study highlights a novel and distinct risk channel shaping the link between government debt and future growth.

Labor Market Frictions and Aggregate Stock Returns

A standard production-based asset pricing model with labor frictions implies a negative relation between job postings and expected stock market returns. As the discount rate rises in recessions, the present value of hiring declines and firms optimally post fewer job openings. We confirm this prediction in our empirical analysis. The job openings-to-employment ratio (JOE) is a strong time-series predictor of aggregate stock returns and outperforms an array of popular forecasting variables in both in-sample and out-of-sample tests. Forecasts based on JOE also lead to large gains in certainty equivalent returns for investors making asset allocation decisions.

Learning and the Capital Age Premium

We introduce imperfect information and parameter learning into a production-based asset pricing model. Our model features slow learning about firms' exposure to aggregate productivity shocks over time. In contrast to a full information case, our framework provides a unified explanation for the stylized empirical features of the cross-section of stocks that differ in capital age: old capital firms (1) have higher capital allocation efficiency; (2) are more exposed to aggregate productivity shocks and, hence, earn higher expected returns, which we refer to as capital age premium; and (3) have shorter cash-flow duration, when compared to young capital firms.

Untangling the Value Premium with Labor Shares

This paper quantifies the relative importance of labor-induced operating leverage at explaining the value premium. I extend a traditional variance decomposition methodology using labor shares to disentangle labor leverage from the value premium and from the value spread and from the variation in profitability levels and growth. My extended decomposition shows that labor leverage explains approximately 50% of the value premium whereas profitability and growth based mechanisms explain the other 50%. I propose a tractable production-based asset-pricing model that qualitatively and quantitatively explains this finding, as well as the relation between book-to-market ratios, discount rates, profitability, and future growth.

Time-inconsistent preferences, investment and asset pricing

In this paper, we present a production-based asset pricing model in which agents have time-inconsistent preferences. We find that the time-inconsistent preferences lead to under-investment, over-consumption, and higher interest rate. These variables are distorted more in the economy with naive agent than the economy with sophisticated agent. In particular, the sophisticated agent invests more and consumes less than the naive agent, but invests less and consumes more than the time-consistent agent. The interest rate in the sophisticated agent economy is lower than that in the naive agent economy, but higher than that in the time-consistent agent economy.