At its core, portfolio and risk management is about gathering and processing market-related data in order to make effective investment decisions. To this end, risk and return statistics are estimated from relevant financial data and used as inputs within the investment process. It is this...

When impulse responses in dynamic multivariate models such as identified VARs are given economic interpretations, it is important that reliable statistical inferences be provided. Before probability assessments are provided, however, the model must be normalized. Contrary to the conventional...

We construct new estimates of potential output and the output gap using a multivariate approach that allows for an explicit role for measurement errors in the decomposition of real output. Because we include data on hours, output, employment, and the labor force, we are able to decompose our...

Economists often seek to estimate unobserved variables, representing “equilibrium” or “expected” values of economic variables, as benchmarks against which observed, realised values of these variables may be evaluated. Such comparisons are often used as economic policy indicators, for...

In this paper we extend the standard Blanchard-Quah decomposition to enable fluctuations in aggregate demand to have a long-run impact on the productive capacity of the economy through hysteresis effects. These demand shocks are found to be quantitatively important in the US, in particular if...

In this paper, we identify demand shocks that can have a permanent effect on output through hysteresis effects. We call these shocks permanent demand shocks. They are found to be quantitatively important in the United States, in particular when the sample includes the Great Recession. Recessions...

This paper advances the application of Bayesian graphical structural vector autoregressive (BGSVAR) models to address the problem of impulse response estimation in VAR-based systems. The BGSVAR is designed as a robust empirical framework for impulse response estimation using information from the...