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We hope to be able to provide answers to the following questions: 1) Has there been a structural break in postwar U.S. real GDP growth toward more stabilization? 2) If so, when would it have been? 3) What's the nature of the structural break? For this purpose, we employ a Bayesian approach to dealing with structural break at an unknown changepoint in a Markov-switching model of business cycle. Empirical results suggest that there has been a structural break in U.S. real GDP growth toward more stabilization, with the posterior mode of the break date around 1984:1. Furthermore, we #nd a narrowing gap between growth rates during recessions and booms is at least as important as a decline in the volatility of shocks. Key Words: Bayes Factor, Gibbs sampling, Marginal Likelihood, Markov-Switching, Stabilization, Structural Break. JEL Classi#cations: C11, C12, C22, E32. 1. Introduction In the literature, the issue of postwar stabilization of the U.S. economy relative to the prewar period has...

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Exchange rate regime optimality, as well as monetary policy effectiveness, depends on the tightness of the link between exchange rate movements and import prices. Recent debates hinge on whether producer-currency-pricing (PCP) or local currency pricing (LCP) of imports is more prevalent, and on whether exchange rate passthrough rates are endogenous to a country’s macroeconomic conditions. We provide cross-country and time series evidence on both of these issues for the imports of twenty-five OECD countries. Across the OECD and especially within manufacturing industries, there is compelling evidence of partial pass-through in the short-run– rejecting both PCP and LCP. Over the long run, PCP is more prevalent for many types of imported goods. Higher inflation and exchange rate volatility are weakly associated with higher pass-through of exchange rates into import prices. However, for OECD countries, the most important determinants of changes in pass-through over time are microeconomic and relate to the industry composition of a country’s import bundle.

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In this paper, we develop the theoretical and empirical properties of a new class of multivariate GARCH models capable of estimating large time-varying covariance matrices, Dynamic Conditional Correlation Multivariate GARCH. We show that the problem of multivariate conditional variance estimation can be simplified by estimating univariate GARCH models for each asset, and then, using transformed residuals resulting from the first stage, estimating a conditional correlation estimator. The standard errors for the first stage parameters remain consistent, and only the standard errors for the correlation parameters need be modified. We use the model to estimate the conditional covariance of up to 100 assets using S&P 500 Sector Indices and Dow Jones Industrial Average stocks, and conduct specification tests of the estimator using an industry standard benchmark for volatility models. This new estimator demonstrates very strong performance especially considering ease of implementation of the estimator.

This paper examines the link between information technology (IT) and the post-1995 U.S. productivity revival. Industry-level data show a broad productivity growth resurgence that reflects both the production and the use of IT. The most IT-intensive industries experienced significantly larger productivity gains than other industries and there is a strong link between IT capital shares and the relative acceleration of labor productivity. A novel decomposition shows that all of the direct contribution to the post-1995 productivity acceleration can be traced to the industries that either produce IT or use IT most intensively, with no net contribution from other industries that are relatively isolated from the IT revolution.

An experiment is performed to assess the prevalence of instability in univariate and bivariate macroeconomic time series relations and to ascertain whether various adaptive forecasting techniques successfully handle any such instability. Formal tests for instability and out-of-sample forecasts from 16 different models are computed using a sample of 76 representative U.S. monthly postwar macroeconomic time series, constituting 5,700 bivariate forecasting relations. The tests for instability and the forecast comparisonsuggest that there is substantial instability in a significant fraction of the univariate and bivariate autoregressive models.

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Estimating the effects of government debt and deficits on Treasury yields is complicated from the effects of the business cycle, and associated monetary policy actions, on debt, deficits, and interest rates, this paper studies the relationship between long-horizon expected government debt and deficits, measured by CBO and OMB projections, and expected future long-term interest rates. The estimated effects of government debt and deficits on interest rates are statistically and economically significant: a one percentage point increase in the projected deficit-to-GDP ratio is estimated to raise long-term interest rates by roughly 25 basis points. Under plausible assumptions these estimates are shown to be consistent with predictions of the neoclassical growth model. JEL classification: E6, H6.