C5 - Econometric Modeling
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Analysis of Asymmetric GARCH Volatility Models with Applications to Margin Measurement
We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH (GTARCH) family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an asymmetric response to past negative news in both autoregressive conditional heteroscedasticity (ARCH) and GARCH terms. -
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. -
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. -
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). -
What Drives Interbank Loans? Evidence from Canada
We identify the drivers of unsecured and collateralized loan volumes, rates and haircuts in Canada using the Bayesian model averaging approach to deal with model uncertainty. Our results suggest that the key friction driving behaviour in this market is the collateral reallocation cost faced by borrowers. -
A Calibrated Model of Intraday Settlement
This paper estimates potential exposures, netting benefits and settlement gains by merging retail and wholesale payments into batches and conducting multiple intraday settlements in this hypothetical model of a single "calibrated payments system." The results demonstrate that credit risk exposures faced by participants in the system are largely dependent on their relative activity in the retail and wholesale payments systems. -
Tail Risk in a Retail Payment System: An Extreme-Value Approach
The increasing importance of risk management in payment systems has led to the development of an array of sophisticated tools designed to mitigate tail risk in these systems. In this paper, we use extreme value theory methods to quantify the level of tail risk in the Canadian retail payment system (ACSS) for the period from 2002 to 2015. -
Is the Discretionary Income Effect of Oil Price Shocks a Hoax?
The transmission of oil price shocks has been a question of central interest in macroeconomics since the 1970s. There has been renewed interest in this question after the large and persistent fall in the real price of oil in 2014–16. In the context of this debate, Ramey (2017) makes the striking claim that the existing literature on the transmission of oil price shocks is fundamentally confused about the question of how to quantify the effect of oil price shocks. -
Evaluating Real GDP Growth Forecasts in the Bank of Canada Monetary Policy Report
This paper examines the quality of projections of real GDP growth taken from the Bank of Canada Monetary Policy Report (MPR) since they were first published in 1997. Over the last decade, it has become common practice among the central banking community to discuss forecast performance publicly. -
On the Tail Risk Premium in the Oil Market
This paper shows that changes in market participants’ fear of rare events implied by crude oil options contribute to oil price volatility and oil return predictability. Using 25 years of historical data, we document economically large tail risk premia that vary substantially over time and significantly forecast crude oil futures and spot returns.