We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...

We propose a methodology to gauge the uncertainty in output gap nowcasts across a large number of commonly-deployed vector autoregressions in US inflation and various measures of the output gap. Our approach constructs ensemble nowcast densities using a linear opinion pool. This yields...

We examine the effectiveness of recursive-weight and equal-weight combination strategies for forecasting using many time-varying models of the relationship be- tween inflation and the output gap. The forecast densities for inflation reflect the uncertainty across models using many statistical...

To match the NBER business cycle features it is necessary to employ Gen- eralised dynamic categorical (GDC) models that impose certain phase re- strictions and permit multiple indexes. Theory suggests additional shape re- strictions in the form of monotonicity and boundedness of certain...

Macroeconometric and fi?nancial researchers often use secondary or constructed binary random variables that differ in terms of their sta- tistical properties from the primary random variables used in micro- econometric studies. One important difference between primary and secondary binary...

Simulations from a standard two-region model where producers respond to changes in interest rates are better able to match observed data than an identical model without supply-side responses. This indicates that incorporating the supply-side behaviour of oil producers is quantitatively important...

The model simulated in this paper shows that falling interest rates contribute to rising oil prices. This occurs because oil producers treat oil in the ground as an asset and attempt to arbitrage differences between its rate of return and the interest rate. When calibrated to match observed data...

It is commonly understood that macroeconomic shocks influence commodity prices and that one channel for this is the link between interest rates, expected future asset returns and stockholding. In this paper the link is extended to the petroleum market with the recognition that recorded stocks of...

We show the importance of endogenous oil prices and production in the real business cycle framework. Endogenising these variables improves the model’s predictions of business cycle statistics, oil related and non-oil related, relative to a situation where either is exogenous. This result is...

Extracting a trend component from nonstationary data is one of the first challenges in estimating a DSGE model. The misspecification of the component can distort structural parameter estimates and translate into a bias in policy-relevant statistic estimates. This paper investigates how important...