We characterize and measure a long-term risk-return trade-off for the valuation of cash flows exposed to fluctuations in macroeconomic growth. This trade-off features risk prices of cash flows that are realized far into the future but continue to be reflected in asset values. We apply this analysis to claims on aggregate cash flows and to cash flows from value and growth portfolios by imputing values to the long-run dynamic responses of cash flows to macroeconomic shocks. We explore the sensitivity of our results to features of the economic valuation model and of the model cash flow dynamics. I.

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While much empirical work has addressed the role of monetary policy shocks in exchange rate behavior, conclusions have been clouded by the lack of plausible identifying assumptions. We apply a recently developed inference procedure allowing us to relax dubious identifying assumptions. This work overturns some earlier results and strengthens others: i) Contrary to earlier findings of "delayed overshooting," the peak exchange rate effect of policy shocks may come nearly immediately after the shock; ii) In every otherwise reasonable identification, monetary policy shocks lead to large uncovered interest rate parity (UIP) deviations; iii) Monetary policy shocks may account for a smaller portion of the variance of exchange rates than found in earlier estimates. While (i) is consistent with overshooting, (ii) implies that the overshooting cannot be driven by Dornbusch's mechanism, and (iii) gives reason to doubt whether monetary policy shocks are the main source of exchange rate volatility.

Non-technical summary 5 1

Non-technical summary 5 1

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In this paper we outline conditions under which the Diebold and Mariano (DM: 1995) test for predictive ability can be extended to the case of two forecasting models, each of which may include cointegrating relations, when allowing for parameter estimation error. We show that in the cases where either the loss function is quadratic or the length of the prediction period, P, grows at a slower rate than the length of the regression period, R, the standard DM test can be used. On the other hand, in the case of a generic loss function, if P R ! as T ! 1, 0 < < 1, then the asymptotic normality result of West (1996) no longer holds. We also extend the "data snooping" technique of White (2000) for comparing the predictive ability of multiple forecasting models to the case of cointegrated variables. In a series of Monte Carlo experiments, we examine the impact of both short run and cointegrating vector parameter estimation error on DM, data snooping, and related tests. Our results sugge...

Abstract not found

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Abstract not found