Dividend Dynamics,Learning, and Expected Stock Index Returns

We present a latent variable model of dividends that predicts, out‐of‐sample, 39.5% to 41.3% of the variation in annual dividend growth rates between 1975 and 2016. Further, when learning about dividend dynamics is incorporated into a long‐run risks model, the model predicts, out‐of‐sample, 25.3% to 27.1% of the variation in annual stock index returns over the same time horizon, with learning contributing approximately half of the predictability in returns. These findings support the view that investors' aversion to long‐run risks and their learning about these risks are important in determining stock index prices and expected returns.     

Do Data Revisions Matter for DSGE Estimation?

This paper checks whether the coefficient estimates of a famous dynamic stochastic general equilibrium (DSGE) model are robust to macroeconomic data revisions. The effects of revisions are captured by rerunning the estimation on a real‐time data set compiled using the latest time series available each quarter from 1997 through 2015. Results show that estimates of the structural parameters are generally robust to changes in the data that have occurred over the past 20 years. By comparison, standard error estimates are more sensitive to revisions. The latter implies that judgments about the statistical significance of certain parameters depend on which data vintage is used for estimation.     

Disasters Implied by Equity Index Options

We use equity index options to quantify the distribution of consumption growth disasters. The challenge lies in connecting the risk‐neutral distribution of equity returns implied by options to the true distribution of consumption growth. First, we compare pricing kernels constructed from macro‐finance and option‐pricing models. Second, we compare option prices derived from a macro‐finance model to those we observe. Third, we compare the distribution of consumption growth derived from option prices using a macro‐finance model to estimates based on macroeconomic data. All three perspectives suggest that options imply smaller probabilities of extreme outcomes than have been estimated from macroeconomic data.     

Learning about the Term Structure and Optimal Rules for Inflation Targeting

In this paper, we incorporate the term structure of interest rates in the New Keynesian model and analyze optimal policy under uncertainty about private sector expectations and the degree of inflation persistence. The novel result of our paper is that for large deviations of inflation from its target, the active learning policy is less activist—in the sense of responding less aggressively to the state of the economy—than a myopic policy, which ignores the learning channel. Moreover, for most initial beliefs, the incentive for active learning increases as monetary policy’s leverage over the long‐term interest rate increases.     

The effect of tick size on managerial learning from stock prices

We investigate the effect of tick size, a key feature of market microstructure, on managerial learning from stock prices. Using a randomized controlled tick-size experiment, the 2016 Tick Size Pilot Program, we find that a larger tick size increases a firm's investment sensitivity to stock prices, suggesting that managers glean more new information from stock prices to guide their investment decisions as the tick size increases. Consistently, we also find that changes in managerial beliefs, as reflected in adjustments of forecasted capital expenditures, respond more strongly to market feedback under a larger tick size. Additional evidence suggests the following mechanism through which tick size affects managerial learning: a larger tick size reduces algorithmic trading, in turn encouraging fundamental information acquisition. Increased fundamental information acquisition generates incremental information about growth opportunities, macroeconomic factors, and industry factors, with respect to which the market has a comparative information advantage over management.     

Stock Market Volatility and Learning

We show that consumption‐based asset pricing models with time‐separable preferences generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. Rational investors with subjective beliefs about price behavior optimally learn from past price observations. This imparts momentum and mean reversion into stock prices. The model quantitatively accounts for the volatility of returns, the volatility and persistence of the price‐dividend ratio, and the predictability of long‐horizon returns. It passes a formal statistical test for the overall fit of a set of moments provided one excludes the equity premium.     

Lumpy Investment,Lumpy Inventories

The link between the microenvironment (frictions and heterogeneity) and the macroeconomic dynamics of general equilibrium macromodels is influenced by exactly how general equilibrium closes the model. We make this observation concrete using the recent literature on how nonconvex capital adjustment costs influence aggregate investment dynamics. We introduce inventories into a two‐sector lumpy investment model and find that nonconvex capital adjustment costs dampen and propagate investment impulse responses, more so than without inventories. With two means of transferring consumption into the future, fixed capital and inventories, the tight link between aggregate saving and fixed capital investment is broken.     

Consumption risk and the cross-section of government bond returns

In this paper we provide a consumption-based explanation of risk in nominal US Treasury bond portfolios. We use a consumption-CAPM with Epstein–Zin–Weil recursive preferences. Our model introduces two sources of risk: uncertainty about current consumption (reflected in contemporaneous consumption growth) and uncertainty about prospects of consumption in a long run (reflected in innovations to expectations about future consumption growth). We use a novel approach to estimate pricing factors in our model: we employ a factor-augmented VAR model with common factors, extracted from a large panel of macroeconomic and financial data, as state variables. We find that the important source of risk in US bonds is related to uncertainty in prospects in future consumption and it induces a positive and significant risk premium. We find as well that covariance risk related to innovations in expectations about future consumption growth is greater for long term bond portfolios than for short term bond portfolios, which is consistent with a duration measure of risk and justifies why long term bonds require greater premium than short term bonds. Our model explains well the cross-sectional variation in average excess returns of bonds with different maturities over the period 1975–2011 and compares favorably with competing models.     

Do subjective expectations explain asset pricing puzzles?

The structural uncertainty model with Bayesian learning, advanced by Weitzman (AER 2007), provides a framework for gauging the effect of structural uncertainty on asset prices and risk premiums. This paper provides an operational version of this approach that incorporates realistic priors about consumption growth volatility, while guaranteeing finite asset pricing quantities. In contrast to the extant literature, the resulting asset pricing model with subjective expectations yields well-defined expected utility, finite moment generating function of the predictive distribution of consumption growth, and tractable expressions for equity premium and risk-free return. Our quantitative analysis reveals that explaining the historical equity premium and risk-free return, in the context of subjective expectations, requires implausible levels of structural uncertainty. Furthermore, these implausible prior beliefs result in consumption disaster probabilities that virtually coincide with those implied by more realistic priors. At the same time, the two sets of prior beliefs have diametrically opposite asset pricing implications.     

Income Insurance and the Equilibrium Term Structure of Equity

Output, wages, and dividends feature term structures of variance ratios that are respectively flat, increasing, and decreasing. Income insurance from shareholders to workers explains these term structures. Risk‐sharing smooths wages but only concerns transitory risk and hence enhances short‐run dividend risk. As a result, actual labor‐share variation largely forecasts the risk, premium, and slope of dividend strips. A simple general equilibrium model in which labor rigidity affects dividend dynamics and the price of short‐run risk reconciles standard asset pricing facts with the term structures of the equity premium, volatility, and macroeconomic variables, which are at odds in leading models.     

Expectations, learning and macroeconomic persistence

Monetary DGSE models under rational expectations typically require large degrees of features as habit formation in consumption and inflation indexation to match the inertia of macroeconomic variables.This paper presents an estimated model that departs from rational expectations and nests learning by economic agents, habits, and indexation. Bayesian methods facilitate the joint estimation of the learning gain coefficient together with the ‘deep’ parameters of the economy.The empirical results show that when learning replaces rational expectations, the estimated degrees of habits and indexation drop closer to zero, suggesting that persistence arises in the model economy mainly from expectations and learning.     

Expectation-driven cycles in the housing market: Evidence from survey data

Using a vector-autoregression (VAR) model and data from the University of Michigan Survey of Consumers, we provide evidence on the importance of news and consumers’ beliefs for housing-market dynamics and aggregate fluctuations. We document that innovations to News on Business Conditions generate hump-shaped responses in house prices and other macroeconomic variables. We also show that innovations to Expectations of Rising House Prices are particularly important in explaining the path of macroeconomic variables during housing booms. To disentangle the effects of News on Business Conditions from other sources of expectation-driven cycles, we estimate a VAR where the News variable is ordered first. Innovations to News on Business Conditions generate Expectations of Rising House Prices. However, during housing booms, innovations to Expectations of Rising House Prices unrelated to News on Business Conditions account for a large part of macroeconomic fluctuations. Shocks to News and Expectations account together for more than half of the forecast error variance of house prices, and other macroeconomic variables, during periods of booms in house prices.     

A Conceptual Framework for Learning Management Accounting

This paper demonstrates how Schoenfeld's ( 1985 ) conceptual framework for mathematics can provide an alternate framework for learning and thereby teaching management accounting. The four‐part framework—heuristics, resources, beliefs, and controls—is a refinement to problem‐based learning with three attributes in regard to management accounting. First, all aspects for teaching management accounting are integrated into a single framework or theory. Consistency among all parts of management accounting clarifies student and instructor roles in the learning process. Second, the framework's problem‐solving focus with linkages to explanatory materials or resources allows students to be rigorously informed about the functionality of management accounting heuristics. Third, transition or extension of relatively simple, standard problems to more complex nonstandard problems or cases is facilitated by introducing appropriate beliefs and controls. In effect, this approach enables management accounting, and particularly case analysis, to be taught with more structure.     

Macroeconomic fundamentals and the exchange rate dynamics: A no-arbitrage macro-finance approach

In this paper, we propose an arbitrage-free international macro-finance model that links the exchange rate dynamics to macroeconomic fundamentals. Jointly using data on exchange rates, yields of zero-coupon bonds, and macroeconomic variables of the US and the Euro area, we find a close link between macroeconomic fundamentals and the exchange rate dynamics. The model-implied monthly exchange rate changes can explain about 57% variation of the observed data. The macroeconomic innovations can help capture large variation of exchange rate changes. Robustness checks show that the results also hold for other major exchange rates.     

Have We Underestimated the Likelihood and Severity of Zero Lower Bound Events?

Prior to the financial crisis, most economists probably did not view the zero lower bound (ZLB) as a major problem for central banks. Using a range of structural and statistical models, we find that previous research understated the ZLB threat by ignoring uncertainty about model parameters and latent variables, focusing too much on the Great Moderation experience, and relying on structural models whose dynamics cannot generate sustained ZLB episodes. Our analysis also suggests that the Federal Reserve's asset purchases, while materially improving macroeconomic conditions, did not prevent the ZLB constraint from having first‐order adverse effects on real activity and inflation.     

MACROECONOMIC NEWS,STOCK TURNOVER,AND VOLATILITY CLUSTERING IN DAILY STOCK RETURNS

We study volatility clustering in daily stock returns at both the index and firm levels from 1985 to 2000. We find that the relation between today's index return shock and the next period's volatility decreases when important macroeconomic news is released today and increases with the shock in today's stock market turnover. Collectively, our results suggest that volatility clustering tends to be stronger when there is more uncertainty and disperse beliefs about the market's information signal. Our findings also contribute to a better understanding of the joint dynamics of stock returns and trading volume.     

A macroeconomic hedge portfolio and the cross section of stock returns

We use a stock's returns on days when important macroeconomic news is released to form a hedge portfolio, which is long (short) in stocks which have a sensitive (insensitive) reaction to the surprise component of the macroeconomic news. This macroeconomic hedge portfolio (MHP) earns a risk premium of about 5% p.a. over time and a similar premium when used as a risk factor in an asset pricing model. This premium can be interpreted as a cost of an insurance against unexpected changes in an investor's marginal utility. We show that risk premiums associated with the MHP are estimated with a higher precision than traditional macroeconomic tracking portfolios. Furthermore, when the MHP is present in a common factor model, risk factors like high minus low lose much of their ability to explain the cross section of stock returns.     

The heterogeneous impact of macroeconomic information on firms' earnings forecasts

This paper re-examines the role of macroeconomic information in forecasting firm earnings. We adopt a Fama–MacBeth regression model with the important extension of including information from over 140 macroeconomic variables that enter into the model in a reduced dimension form as a consequence of common factor analysis. The resulting factor-augmented model is then used to evaluate the importance of macroeconomic information on earnings forecasts for U.S. firms from 1962 to 2009. The same model is also examined for each individual time window and industry subsample. The results reveal a clear and heterogeneous impact of macroeconomic information on firm-specific earnings forecasts, and that these effects differ markedly during certain periods and across industries. In addition, when compared to analyst forecasts, we show that our model is generally more accurate over longer forecast horizons. The results of the identified heterogeneous impacts are used to define the conditions under which macroeconomic information becomes important for the firm.     

Sovereign credit spreads

The paper develops a structural credit risk model to study sovereign credit risk and the dynamics of sovereign credit spreads. The model features endogenous default and recovery rates that both depend on the interaction between domestic output fluctuations and global macroeconomic conditions. We show that sovereigns choose to default at higher levels of economic output once global macroeconomic conditions are bad. This yields to default rates and credit spreads that are substantially higher compared to normal times. We derive closed-form expressions for sovereign debt values and default times and focus on the dynamics of sovereign credit spreads. As opposed to standard theories of sovereign debt, this paper’s structural model generates much richer default patterns and non-linearities through regime-shifts in the global macroeconomic environment. Moreover, changes in the global environment reveal the interconnectedness of the financial system.     

Information Consumption and Asset Pricing

We study whether firm and macroeconomic announcements that convey systematic information generate a return premium for firms that experience information spillovers. We use information consumption to proxy for investor learning during these announcements and construct ex ante measures of expected information consumption (EIC) to calibrate whether learning is priced. On days when there are information spillovers, affected stocks earn a significant return premium (5% annualized) and the capital asset pricing model performs better. The positive effect of the Federal Reserve Open Market Committee announcements on the risk premia of individual stocks appears to be modulated by EIC. Our findings are most consistent with a risk‐based explanation.