Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects Staff Working Paper 2019-16 Kerem Tuzcuoglu Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals. Content Type(s): Staff research, Staff working papers Topic(s): Credit risk management, Econometric and statistical methods, Economic models JEL Code(s): C, C2, C23, C25, C5, C58, G, G2, G24
The Trend Unemployment Rate in Canada: Searching for the Unobservable Staff Working Paper 2019-13 Dany Brouillette, Marie-Noëlle Robitaille, Laurence Savoie-Chabot, Pierre St-Amant, Bassirou Gueye, Elise Nelson In this paper, we assess several methods that have been used to measure the Canadian trend unemployment rate (TUR). We also consider improvements and extensions to some existing methods. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Economic models, Inflation and prices, Labour markets JEL Code(s): C, C5, C52, C53, E, E2, E24, E27
Inference in Games Without Nash Equilibrium: An Application to Restaurants’ Competition in Opening Hours Staff Working Paper 2018-60 Erhao Xie This paper relaxes the Bayesian Nash equilibrium (BNE) assumption commonly imposed in empirical discrete choice games with incomplete information. Instead of assuming that players have unbiased/correct expectations, my model treats a player’s belief about the behavior of other players as an unrestricted unknown function. I study the joint identification of belief and payoff functions. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Market structure and pricing JEL Code(s): C, C5, C57, L, L1, L13, L8, L85
GDP by Industry in Real Time: Are Revisions Well Behaved? Staff Analytical Note 2018-40 Patrick Rizzetto The monthly data for real gross domestic product (GDP) by industry are used extensively in real time both to ground the Bank of Canada’s monitoring of economic activity and in the Bank’s nowcasting tools, making these data one of the most important high-frequency time series for Canadian nowcasting. Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Central bank research, Econometric and statistical methods JEL Code(s): C, C5, C53, C8, C82, E, E0, E01
An Alternative Estimate of Canadian Potential Output: The Multivariate State-Space Framework Staff Discussion Paper 2018-14 Lise Pichette, Maria Bernier, Marie-Noëlle Robitaille In this paper, we extend the state-space methodology proposed by Blagrave et al. (2015) and decompose Canadian potential output into trend labour productivity and trend labour input. As in Blagrave et al. (2015), we include output growth and inflation expectations from consensus forecasts to help refine our estimates. Content Type(s): Staff research, Staff discussion papers Topic(s): Economic models, Potential output JEL Code(s): C, C5, E, E0, E5
The Framework for Risk Identification and Assessment Technical Report No. 113 Cameron MacDonald, Virginie Traclet Risk assessment models are an important component of the Bank’s analytical tool kit for assessing the resilience of the financial system. We describe the Framework for Risk Identification and Assessment (FRIDA), a suite of models developed at the Bank of Canada to quantify the impact of financial stability risks to the broader economy and a range of financial system participants (households, businesses and banks). Content Type(s): Staff research, Technical reports Topic(s): Economic models, Financial institutions, Financial stability, Housing JEL Code(s): C, C3, C5, C6, C7, D, D1, E, E0, E00, E2, E27, E3, E37, E4, E47, G, G0, G2, G21
Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches Staff Analytical Note 2018-34 Andrew Lee-Poy In this note, I use two multivariate frequency filtering approaches to characterize the Canadian financial cycle by capturing fluctuations in the underlying variables with respect to a long-term trend. The first approach is a dynamically weighted composite, and the second is a stochastic cycle model. Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial stability, Monetary and financial indicators, Recent economic and financial developments JEL Code(s): C, C0, C01, C1, C13, C14, C18, C3, C32, C5, C51, C52, E, E3, E32, E6, E66, G, G0, G01, G1, G18
Challenges in Implementing Worst-Case Analysis Staff Working Paper 2018-47 Jon Danielsson, Lerby Ergun, Casper G. de Vries Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach. Content Type(s): Staff research, Staff working papers Topic(s): Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58
Nowcasting Canadian Economic Activity in an Uncertain Environment Staff Discussion Paper 2018-9 Tony Chernis, Rodrigo Sekkel This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components. Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C53, E, E3, E37, E5, E52
Analysis of Asymmetric GARCH Volatility Models with Applications to Margin Measurement Staff Working Paper 2018-21 Elena Goldman, Xiangjin Shen 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. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C58, G, G1, G19, G2, G23, G28