C5 - Econometric Modeling - Bank of Canada
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Bank of Canada RSS Feedsen2024-03-29T09:40:13+00:00Is the Discretionary Income Effect of Oil Price Shocks a Hoax?
https://www.bankofcanada.ca/2017/11/staff-working-paper-2017-50/
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.2017-11-23T11:32:45+00:00enIs the Discretionary Income Effect of Oil Price Shocks a Hoax?2017-11-23Econometric and statistical methodsInternational topicsStaff Working Paper 2017-50https://www.bankofcanada.ca/wp-content/uploads/2017/11/swp2017-50.pdfIs the Discretionary Income Effect of Oil Price Shocks a Hoax?Christiane BaumeisterLutz KilianXiaoqing ZhouNovember 2017CC5C51QQ4Q43Evaluating Real GDP Growth Forecasts in the Bank of Canada Monetary Policy Report
https://www.bankofcanada.ca/2017/11/staff-analytical-note-2017-21/
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.2017-11-22T11:04:54+00:00enEvaluating Real GDP Growth Forecasts in the Bank of Canada Monetary Policy Report2017-11-22On the Tail Risk Premium in the Oil Market
https://www.bankofcanada.ca/2017/11/staff-working-paper-2017-46/
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.2017-11-20T07:47:32+00:00enOn the Tail Risk Premium in the Oil Market2017-11-20Asset pricingEconometric and statistical methodsFinancial marketsStaff Working Paper 2017-46https://www.bankofcanada.ca/wp-content/uploads/2017/11/swp2017-46.pdfOn the Tail Risk Premium in the Oil MarketReinhard EllwangerNovember 2017CC5C53C58DD8D84EE4E44GG1G12G13QQ4Q43Global Trade Flows: Revisiting the Exchange Rate Elasticities
https://www.bankofcanada.ca/2017/09/staff-working-paper-2017-41/
This paper contributes to the debate on the magnitude of exchange rate elasticities by providing a set of price and quantity elasticities for 51 advanced and emerging-market economies. Specifically, for each of these countries we report the elasticity of trade prices and trade quantities on both the export and on the import sides, as well as the reaction of the trade balance.2017-09-29T13:16:42+00:00enGlobal Trade Flows: Revisiting the Exchange Rate Elasticities2017-09-29Exchange ratesInflation and pricesInternational topicsStaff Working Paper 2017-41https://www.bankofcanada.ca/wp-content/uploads/2017/09/swp2017-41.pdfGlobal Trade Flows: Revisiting the Exchange Rate ElasticitiesMatthieu BussièreGuillaume GaulierWalter SteingressSeptember 2017CC5C51FF1F14F3F31F33F4F41A Dynamic Factor Model for Commodity Prices
https://www.bankofcanada.ca/2017/09/staff-analytical-note-2017-12/
In this note, we present the Commodities Factor Model (CFM), a dynamic factor model for a large cross-section of energy and non-energy commodity prices. The model decomposes price changes in commodities into a common “global” component, a “block” component confined to subgroups of economically related commodities and an idiosyncratic price shock component.2017-09-25T17:44:19+00:00enA Dynamic Factor Model for Commodity Prices2017-09-25How to Predict Financial Stress? An Assessment of Markov Switching Models
https://www.bankofcanada.ca/2017/08/staff-working-paper-2017-32/
This paper predicts phases of the financial cycle by using a continuous financial stress measure in a Markov switching framework. The debt service ratio and property market variables signal a transition to a high financial stress regime, while economic sentiment indicators provide signals for a transition to a tranquil state.2017-08-04T12:08:21+00:00enHow to Predict Financial Stress? An Assessment of Markov Switching Models2017-08-04Business fluctuations and cyclesCentral bank researchEconometric and statistical methodsFinancial marketsFinancial stabilityFinancial system regulation and policiesMonetary and financial indicatorsStaff Working Paper 2017-32https://www.bankofcanada.ca/wp-content/uploads/2017/08/swp2017-32.pdfHow to Predict Financial Stress? An Assessment of Markov Switching ModelsBenjamin KlausThibaut DupreyAugust 2017CC5C54GG0G01G1G15A Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth
https://www.bankofcanada.ca/2017/06/staff-discussion-paper-2017-8/
This paper estimates a three‐frequency dynamic factor model for nowcasting Canadian provincial gross domestic product (GDP). Canadian provincial GDP is released by Statistics Canada on an annual basis only, with a significant lag (11 months).2017-06-12T11:50:01+00:00enA Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth2017-06-12Business fluctuations and cyclesEconometric and statistical methodsRegional economic developmentsStaff Discussion Paper 2017-8https://www.bankofcanada.ca/wp-content/uploads/2017/06/sdp2017-8.pdfA Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP GrowthTony ChernisGabriella VelascoCalista CheungJune 2017CC5C53EE3E32E37RR1R11Assessing the Predictive Ability of Sovereign Default Risk on Exchange Rate Returns
https://www.bankofcanada.ca/2017/05/staff-working-paper-2017-19/
Increased sovereign credit risk is often associated with sharp currency movements. Therefore, expectations of the probability of a sovereign default event can convey important information regarding future movements of exchange rates.2017-05-17T08:24:48+00:00enAssessing the Predictive Ability of Sovereign Default Risk on Exchange Rate Returns2017-05-17Econometric and statistical methodsExchange ratesInternational financial marketsStaff Working Paper 2017-19https://www.bankofcanada.ca/wp-content/uploads/2017/05/swp2017-19.pdfAssessing the Predictive Ability of Sovereign Default Risk on Exchange Rate ReturnsClaudia ForoniFrancesco RavazzoloBarbara SadabaMay 2017CC2C22C5C52C53FF3F31Markov‐Switching Three‐Pass Regression Filter
https://www.bankofcanada.ca/2017/04/staff-working-paper-2017-13/
We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes.2017-04-20T13:08:27+00:00enMarkov‐Switching Three‐Pass Regression Filter2017-04-20Econometric and statistical methodsStaff Working Paper 2017-13https://www.bankofcanada.ca/wp-content/uploads/2017/04/swp2017-13.pdfMarkov‐Switching Three‐Pass Regression FilterPierre GuérinDanilo Leiva-LeonMassimiliano MarcellinoApril 2017CC2C22C23C5C53Assessing the Business Outlook Survey Indicator Using Real-Time Data
https://www.bankofcanada.ca/2017/04/staff-discussion-paper-2017-5/
Every quarter, the Bank of Canada conducts quarterly consultations with businesses across Canada, referred to as the Business Outlook Survey (BOS). A principal-component analysis conducted by Pichette and Rennison (2011) led to the development of the BOS indicator, which summarizes survey results and is used by the Bank as a gauge of overall business sentiment.2017-04-03T10:30:19+00:00enAssessing the Business Outlook Survey Indicator Using Real-Time Data2017-04-03Business fluctuations and cyclesRegional economic developmentsStaff Discussion Paper 2017‐5https://www.bankofcanada.ca/wp-content/uploads/2017/04/sdp2017-5.pdfAssessing the Business Outlook Survey Indicator Using Real-Time DataLise PichetteMarie-Noëlle RobitailleApril 2017CC5C53C8C82EE3E37