E37 Prices, Business Fluctuations, and Cycles: Forecasting and Simulation

December 18, 2012

This paper investigates the relationship between the main features of business cycles and the institutional and structural characteristics of countries of up to 62 industrial, emerging and formerly centrally planned economies from all continents. We derive the business cycle characteristics using the nonparametric Harding-Pagan approach. Our analysis reveals that institutional factors have significant associations with the duration and amplitude of business cycles. Examining the determinants of business cycle synchronization for the countries in our sample, we also demonstrate that the bilateral proximity of institutional and policy environments matters in addition to the gravity arguments, trade intensity and bilateral financial linkages used in earlier studies.

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August 1, 2010

This paper characterizes business cycle phenomena in a sample of 27 developed and developing economies using a univariate Markov regime switching approach. It examines the efficacy of this approach for detecting business cycle turning points and for identifying distinct economic regimes for each country in question. The paper also provides a comparison of the business cycle turning points implied by this study and those derived in other studies. Our findings document the importance of heterogeneity of individual countries’ experiences. We also argue that consideration of a large and diverse group of countries provides an alternative perspective on the comovement of aggregate economic activity worldwide.

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March 3, 2010

We propose a methodology for producing density forecasts for the output gap in real time using a large number of vector autoregessions in inflation and output gap measures. Density combination utilizes a linear mixture of experts framework to produce potentially non-Gaussian ensemble densities for the unobserved output gap. In our application, we show that data revisions alter substantially our probabilistic assessments of the output gap using a variety of output gap measures derived from univariate detrending filters. The resulting ensemble produces well-calibrated forecast densities for US inflation in real time, in contrast to those from simple univariate autoregressions which ignore the contribution of the output gap. Combining evidence from both linear trends and more flexible univariate detrending filters induces strong multi-modality in the predictive densities for the unobserved output gap. The peaks associated with these two detrending methodologies indicate output gaps of opposite sign for some observations, reflecting the pervasive nature of model uncertainty in our US data.

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February 1, 2011

We use TVP models and real-time data to describe the evolution of the leading properties of the yield spread for output growth in five European economies and in the US over the last decades and until the third quarter of 2010. We evaluate the predictive performance of benchmark term-structure models and identify structural breaks in the marginal processes of term spreads and government bond yields to shed light on the dynamic characteristics of the yield curve. Econometric analysis shows that: (i) the predictive content of the term spread is not always significant over time and across countries; (ii) the spread significantly contributes to the forecast performance of simple growth regressions in Europe, but not in the US in recent years; (iii) the variance of the random shocks to the term spreads tends to fall in all countries. This decline is accompanied by vanishing leading properties from the mid-1990s. Such properties reappear after 2008.

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October 1, 2005

We study 30 vintages of FRB/US, the principal macro model used by the Federal Reserve Board staff for forecasting and policy analysis. To do this, we exploit archives of the model code, coefficients, baseline databases and stochastic shock sets stored after each FOMC meeting from the model’s inception in July 1996 until November 2003. The period of study was one of important changes in the US economy with a productivity boom, a stock market boom and bust, a recession, the Asia crisis, the Russian debt default, and an abrupt change in fiscal policy. We document the surprisingly large and consequential changes in model properties that occurred during this period and compute optimal Taylor-type rules for each vintage. We compare these optimal rules against plausible alternatives. Model uncertainty is shown to be a substantial problem; the efficacy of purportedly optimal policy rules should not be taken on faith. We also find that previous findings that simple rules are robust to model uncertainty may be an overly sanguine conclusion.

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October 1, 2005

This paper describes a method for calculating daily real-time estimates of the current state of the US economy. The estimates are computed from data on scheduled US macroeconomic announcements using an econometric model that allows for variable reporting lags, temporal aggregation, and other complications in the data. The model can be applied to find real-time estimates of GDP, inflation, unemployment or any other macroeconomic variable of interest. In this paper I focus on the problem of estimating the current level of and growth rate in GDP. I construct daily real-time estimates of GDP that incorporate public information known on the day in question. The real-time estimates produced by the model are uniquely suited to studying how perceived developments the macro economy are linked to asset prices over a wide range of frequencies. The estimates also provide, for the first time, daily time series that can be used in practical policy decisions.

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