Staff working papers
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State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models
Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood. -
Did U.S. Consumers Respond to the 2014–2015 Oil Price Shock? Evidence from the Consumer Expenditure Survey
The impact of oil price shocks on the U.S. economy is a topic of considerable debate. In this paper, we examine the response of U.S. consumers to the 2014–2015 negative oil price shock using representative survey data from the Consumer Expenditure Survey. -
Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?
The official Chinese labour market indicators have been seen as problematic, given their small cyclical movement and their only-partial capture of the labour force. In our paper, we build a monthly Chinese labour market conditions index (LMCI) using text analytics applied to mainland Chinese-language newspapers over the period from 2003 to 2017. -
The Macroeconomic Effects of Quantitative Easing in the Euro Area: Evidence from an Estimated DSGE Model
This paper estimates an open-economy dynamic stochastic general equilibrium model with Bayesian techniques to analyse the macroeconomic effects of the European Central Bank’s (ECB’s) quantitative easing (QE) programme. Using data on government debt stocks and yields across maturities, we identify the parameter governing portfolio adjustment in the private sector. -
Dismiss the Gap? A Real-Time Assessment of the Usefulness of Canadian Output Gaps in Forecasting Inflation
We use a new real-time database for Canada to study various output gap measures. This includes recently developed measures based on models incorporating many variables as inputs (and therefore requiring real-time data for many variables).