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Year: 2013 Publisher: Cambridge, Mass. National Bureau of Economic Research
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This paper develops a vector autoregression (VAR) for time series which are observed at mixed frequencies - quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to implement a data-driven hyperparameter selection. Using a real-time data set, we evaluate forecasts from the mixed-frequency VAR and compare them to standard quarterly-frequency VAR and to forecasts from MIDAS regressions. We document the extent to which information that becomes available within the quarter improves the forecasts in real time.
Digital
Year: 2014 Publisher: Cambridge, Mass. National Bureau of Economic Research
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We develop a nonlinear state-space model that captures the joint dynamics of consumption, dividend growth, and asset returns. Our model consists of an economy containing a common predictable component for consumption and dividend growth and multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly consumption data after 1959, and monthly asset return data throughout. We maximize the span of the sample to recover the predictable component and use high-frequency data, whenever available, to efficiently identify the volatility processes. Our Bayesian estimation provides strong evidence for a small predictable component in consumption growth (even if asset return data are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our measurement error specification implies that consumption is measured much more precisely at an annual than monthly frequency; and the estimated model is able to capture key asset-pricing facts of the data.
Digital
Year: 2018 Publisher: Cambridge, Mass. National Bureau of Economic Research
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Sovereign CDS quanto spreads--the difference between CDS premiums denominated in U.S. dollars and a foreign currency--tell us how financial markets view the interaction between a country's likelihood of default and associated currency devaluations (the Twin Ds). A noarbitrage model applied to the term structure of quanto spreads can isolate the interaction between the Twin Ds and gauge the associated risk premiums. We study countries in the Eurozone because their quanto spreads pertain to the same exchange rate and monetary policy, allowing us to link cross-sectional variation in their term structures to cross-country differences in fiscal policies. The ratio of the risk-adjusted to the true default intensities is 2, on average. Conditional on the occurrence of default, the true and risk-adjusted 1-week probabilities of devaluation are 5% and 77%, respectively. The risk premium for the euro devaluation in case of default exceeds the regular currency premium by up to 0.3% per week.
Digital
Year: 2019 Publisher: Cambridge, Mass. National Bureau of Economic Research
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We use traded equity dividend strips from U.S., Europe, and Japan from 2004-2017 to study the slope of the term structure of equity dividend risk premia. In the data, a robust finding is that the term structure of dividend risk premia (growth rates) is positively (negatively) sloped in expansions and negatively (positively) sloped in recessions. We develop a consumption-based regime switching model which matches these robust data-features and the historical probabilities of recession and expansion regimes. The unconditional population term structure of dividend-risk premia in the regime-switching model, as in standard asset pricing models (habits and long-run risks), is increasing with maturity. The regime-switching model also features a declining average term structure of dividend risk-premia if recessions are over-represented in a short sample, as is the case in the data sample from Europe and Japan. In sum, our analysis shows that the empirical evidence in dividend strips is entirely consistent with a positively sloped term structure of dividend risk-premia as implied by standard asset pricing models.
Digital
Year: 2011 Publisher: Cambridge, Mass. National Bureau of Economic Research
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Two often-divergent U.S. GDP estimates are available, a widely-used expenditure side version, GDPE, and a much less widely-used income-side version GDPI . We propose and explore a "forecast combination" approach to combining them. We then put the theory to work, producing a superior combined estimate of GDP growth for the U.S., GDPC. We compare GDPC to GDPE and GDPI , with particular attention to behavior over the business cycle. We discuss several variations and extensions.
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