The Determinants of Consumers’ Inflation Expectations: Evidence from the US and Canada Staff Working Paper 2020-52 Charles Bellemare, Rolande Kpekou Tossou, Kevin Moran We compare the determinants of consumer inflation expectations in the US and Canada by analyzing two current surveys. We find that Canadian consumers rely more on professional forecasts and the history of actual inflation when forming their expectations, while US consumers rely more on their own lagged expectations. Content Type(s): Staff research, Staff working papers Research Topic(s): Central bank research, Econometric and statistical methods, Inflation and prices, Inflation targets JEL Code(s): C, C3, C33, D, D8, D83, D84, E, E3, E31
May 21, 2003 Conference Summary: Price Adjustment and Monetary Policy Bank of Canada Review - Spring 2003 Robert Amano, Donald Coletti The 2002 Bank of Canada Conference focused on price adjustment, a critically important issue for monetary policy. Given the acceptance throughout the 1990s and 2000s of the existence of price stickiness in goods or labour markets, or both, and of the important role that monetary policy can play in an economy, the time was right for a conference that would focus on current developments in this area of research, particularly within a Canadian context. Conference papers covering both theoretical and empirical studies explored such themes as sources of the persistence of inflation, forward-looking models of inflation, models of inflation in open economies, the macroeconomic effects of technology shocks, and models of the interaction between wages, prices, and real economic outcomes. Content Type(s): Publications, Bank of Canada Review articles
The impact of a central bank digital currency on payments at the point of sale Staff Analytical Note 2024-27 Walter Engert, Oleksandr Shcherbakov, André Stenzel We simulate the impact of a central bank digital currency (CBDC) on consumer adoption, merchant acceptance and use of different payment methods. Modest frictions that deter consumer adoption of a CBDC inhibit its market penetration. Minor pricing responses by financial institutions and payment service providers further reduce the impact of a CBDC. Content Type(s): Staff research, Staff analytical notes Research Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods, Financial services JEL Code(s): C, C5, C51, D, D1, D12, E, E4, E42, L, L1, L14, L5, L52
The Sale of Durable Goods by a Monopolist in a Stochastic Environment Staff Working Paper 1998-18 Gabriel Srour This paper examines the sale of durable goods by a monopolist in a stochastic partil equilibrium setting. It analyzes the responses of prices and output to various types of shocks and notes the differences with non-durable goods and competitive markets. It shows that behavior in this model with constant marginal costs of production is in […] Content Type(s): Staff research, Staff working papers Research Topic(s): Market structure and pricing JEL Code(s): D, D4
Occasionally Binding Constraints in Large Models: A Review of Solution Methods Staff Discussion Paper 2021-5 Jonathan Swarbrick Solving macroeconomic models is difficult. One challenge is the occasionally binding constraint of the zero lower bound on nominal interest rates. This paper reviews various ways to solve models that include this feature. Content Type(s): Staff research, Staff discussion papers Research Topic(s): Business fluctuations and cycles, Economic models JEL Code(s): C, C6
May 13, 2004 Business Outlook Survey - Spring 2004 Businesses’ expectations for the pace of economic activity over the next 12 months remain positive, although somewhat less so than in the winter survey.Supplemental questions on the appreciation of the Canadian dollar - April 2004Supplemental questions on the appreciation of the Canadian dollar - February 2004 Content Type(s): Publications, Business Outlook Survey
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 Research Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C13, C14, C2, C21
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 Research Topic(s): Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58
Bank Screening Heterogeneity Staff Working Paper 2016-56 Thibaut Duprey Production efficiency and financial stability do not necessarily go hand in hand. With heterogeneity in banks’ abilities to screen borrowers, the market for loans becomes segmented and a self-competition mechanism arises. When heterogeneity increases, the intensive and extensive margins have opposite effects. Content Type(s): Staff research, Staff working papers Research Topic(s): Financial institutions, Financial stability, Financial system regulation and policies JEL Code(s): G, G1, G14, G2, G21, L, L1, L13
Privacy in CBDC technology Staff Analytical Note 2020-9 Sriram Darbha, Rakesh Arora Privacy is a key aspect of a potential central bank digital currency system. We outline different technical choices to enact various privacy models while complying with the appropriate regulations. We develop a framework to evaluate privacy models and list key risks and trade-offs in privacy design. Content Type(s): Staff research, Staff analytical notes Research Topic(s): Central bank research, Digital currencies and fintech JEL Code(s): E, E4, E42, E5, E51, O, O3