Sheep in Wolf’s Clothing: Using the Least Squares Criterion for Quantile Estimation Staff Working Paper 2014-24 Heng Chen Estimation of the quantile model, especially with a large data set, can be computationally burdensome. This paper proposes using the Gaussian approximation, also known as quantile coupling, to estimate a quantile model. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C13, C14, C2, C21
Monetary Policy Transmission during Financial Crises: An Empirical Analysis Staff Working Paper 2014-21 Tatjana Dahlhaus This paper studies the effects of a monetary policy expansion in the United States during times of high financial stress. The analysis is carried out by introducing a smooth transition factor model where the transition between states (“normal” and high financial stress) depends on a financial conditions index. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial markets, Monetary policy transmission JEL Code(s): C, C1, C11, C3, C32, E, E3, E32, E4, E44, G, G0, G01
Consumer Cash Usage: A Cross-Country Comparison with Payment Diary Survey Data Staff Working Paper 2014-20 John Bagnall, David Bounie, Kim Huynh, Anneke Kosse, Tobias Schmidt, Scott Schuh, Helmut Stix We measure consumers’ use of cash by harmonizing payment diary surveys from seven countries. The seven diary surveys were conducted in 2009 (Canada), 2010 (Australia), 2011 (Austria, France, Germany and the Netherlands), and 2012 (the United States). Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods, Financial services JEL Code(s): D, D1, D12, E, E4, E41, E5, E58
May 13, 2014 The Art and Science of Forecasting the Real Price of Oil Bank of Canada Review - Spring 2014 Christiane Baumeister Forecasts of the price of crude oil play a significant role in the conduct of monetary policy, especially for commodity producers such as Canada. This article presents a range of recently developed forecasting models that, when pooled together, can generate, on average, more accurate forecasts of the price of oil than the oil futures curve. It also illustrates how policy-makers can evaluate the risks associated with the baseline oil price forecast and how they can determine the causes of past oil price fluctuations. Content Type(s): Publications, Bank of Canada Review articles Topic(s): Econometric and statistical methods, International topics JEL Code(s): C, C5, C53, E, E3, E32, Q, Q4, Q43
Multiple Fixed Effects in Binary Response Panel Data Models Staff Working Paper 2014-17 Karyne B. Charbonneau This paper considers the adaptability of estimation methods for binary response panel data models to multiple fixed effects. It is motivated by the gravity equation used in international trade, where important papers such as Helpman, Melitz and Rubinstein (2008) use binary response models with fixed effects for both importing and exporting countries. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C2, C23, C25, F, F1, F14
Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work Staff Working Paper 2014-11 Christiane Baumeister, Pierre Guérin, Lutz Kilian The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, International topics JEL Code(s): C, C5, C53, G, G1, G14, Q, Q4, Q43
Regime Switches in the Risk-Return Trade-Off Staff Working Paper 2013-51 Eric Ghysels, Pierre Guérin, Massimiliano Marcellino This paper deals with the estimation of the risk-return trade-off. We use a MIDAS model for the conditional variance and allow for possible switches in the risk-return relation through a Markov-switching specification. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial markets JEL Code(s): G, G1, G10, G12
A Distributional Approach to Realized Volatility Staff Working Paper 2013-49 Selma Chaker, Nour Meddahi This paper proposes new measures of the integrated variance, measures which use high-frequency bid-ask spreads and quoted depths. The traditional approach assumes that the mid-quote is a good measure of frictionless price. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial markets JEL Code(s): C, C1, C14, C5, C51, C58
Volatility Forecasting when the Noise Variance Is Time-Varying Staff Working Paper 2013-48 Selma Chaker, Nour Meddahi This paper explores the volatility forecasting implications of a model in which the friction in high-frequency prices is related to the true underlying volatility. The contribution of this paper is to propose a framework under which the realized variance may improve volatility forecasting if the noise variance is related to the true return volatility. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial markets JEL Code(s): C, C1, C14, C5, C51, C58
CoMargin Staff Working Paper 2013-47 Jorge Cruz Lopez, Jeffrey H. Harris, Christophe Hurlin, Christophe Pérignon We present CoMargin, a new methodology to estimate collateral requirements for central counterparties (CCPs) in derivatives markets. CoMargin depends on both the tail risk of a given market participant and its interdependence with other participants. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial institutions, Financial markets, Financial stability JEL Code(s): G, G1, G13