Cash Flow News and Stock Price Dynamics

We develop a new approach to modeling dynamics in cash flows extracted from daily firm-level dividend announcements. We decompose daily cash flow news into a persistent component, jumps, and temporary shocks. Empirically, we find that the persistent cash flow component is a highly significant predictor of future growth in dividends and consumption. Using a log-linearized present value model, we show that news about the persistent dividend growth component predicts stock returns consistent with asset pricing constraints implied by this model. News about the daily dividend growth process also helps explain concurrent return volatility and the probability of jumps in stock returns.     

Mandatory and Voluntary Disclosures: Dynamic Interactions

Firms sometimes obtain soft private information about growth prospects along with hard information about current or past performance. In this environment, we find that optimizing disclosures over multiple periods yields nonlinear stock price reactions following both voluntary and mandatory disclosures. Further, we derive several predictions about distinct short‐run and long‐run effects of disclosures and nondisclosures on security prices. Under specified conditions, when the volatility of the firm's earnings increases, the average contemporaneous and prospective post‐mandatory‐disclosure market premia (for voluntary disclosures over nondisclosures) rise, while farther‐in‐future market discounts (for such voluntary disclosures) also become larger. Our analysis moreover predicts that both the disclosure probability and the information content of nondisclosures can increase in the persistence of earnings.     

Monetary Regime Switches and Central Bank Preferences

Monetary policy objectives and targets are not necessarily constant over time. The regime‐switching literature has typically analyzed and interpreted changes in policymakers' behavior through simple interest rate rules. This paper analyzes policy regime switches by explicitly modeling policymakers' behavior and objectives. We show that changes in the parameters of simple rules do not necessarily correspond to changes in policymakers' preferences. In fact, capturing and interpreting regime changes in preferences through interest rate rules can lead to misleading results.     

Forecasting Time Series Subject to Multiple Structural Breaks

This paper provides a new approach to forecasting time series that are subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks occurring over the forecast horizon, taking account of the size and duration of past breaks (if any) by means of a hierarchical hidden Markov chain model. Predictions are formed by integrating over the parameters from the meta-distribution that characterizes the stochastic break-point process. In an application to U.S. Treasury bill rates, we find that the method leads to better out-of-sample forecasts than a range of alternative methods.     

The Aggregate and Distributional Effects of Financial Globalization: Evidence from Macro and Sectoral Data

We take a fresh look at the aggregate and distributional effects of policies to liberalize international capital flows—financial globalization. Both country‐ and industry‐level results suggest that such policies have led on average to limited output gains while contributing to significant increases in inequality. The country‐level results are based on 228 capital account liberalization episodes spanning 149 advanced and developing economies from 1970 to the present. Difference‐in‐difference estimation using industry‐level data for 23 advanced economies suggests that liberalization episodes reduce the share of labor income, particularly for industries with higher external financial dependence, higher natural propensity to use layoffs to adjust to idiosyncratic shocks, and higher elasticity of substitution between capital and labor.