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3029 Results

Forecasting Short-Term Real GDP Growth in the Euro Area and Japan Using Unrestricted MIDAS Regressions

Staff Discussion Paper 2014-3 Maxime Leboeuf, Louis Morel
In this paper, the authors develop a new tool to improve the short-term forecasting of real GDP growth in the euro area and Japan. This new tool, which uses unrestricted mixed-data sampling (U-MIDAS) regressions, allows an evaluation of the usefulness of a wide range of indicators in predicting short-term real GDP growth.

PayTech and the D(ata) N(etwork) A(ctivities) of BigTech Platforms

Staff Working Paper 2022-35 Jonathan Chiu, Thorsten Koeppl
Why do BigTech platforms introduce payment services? We explore this using a model in which a monopoly platform faces a trade-off between the costs associated with privacy concerns and the revenue from data services. We then analyze the feedback effects between data and payments.

A Financial Conditions Index for the United States

Staff Discussion Paper 2009-11 Kimberly Beaton, René Lalonde, Corinne Luu
The financial crisis of 2007–09 has highlighted the importance of developments in financial conditions for real economic activity. The authors estimate the effect of current and past shocks to financial variables on U.S. GDP growth by constructing two growthbased financial conditions indexes (FCIs) that measure the contribution to quarterly (annualized) GDP growth from financial conditions.

The Propagation of Regional Shocks in Housing Markets: Evidence from Oil Price Shocks in Canada

Staff Working Paper 2018-56 Lutz Kilian, Xiaoqing Zhou
How do global oil price shocks spread through Canada’s economy? With Canada’s regionally diverse economy in mind, we explore the implications of oil price shocks for Canadian housing markets and regional economies. We show that the belief that oil price shocks only matter in oil-rich regions is false.

A Look Inside the Box: Combining Aggregate and Marginal Distributions to Identify Joint Distributions

Staff Working Paper 2018-29 Marie-Hélène Felt
This paper proposes a method for estimating the joint distribution of two or more variables when only their marginal distributions and the distribution of their aggregates are observed. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure.
October 3, 2006

A New Effective Exchange Rate Index for the Canadian Dollar

An effective exchange rate is a measure of the value of a country's currency vis-à-vis the currencies of its most important trading partners. The Bank of Canada has created a new Canadian-dollar effective exchange rate index (CERI) to replace the C-6 index that it currently uses. The CERI uses multilateral trade weights published by the International Monetary Fund and includes the six currencies of countries or economic zones with the largest share of Canada's international trade. As such, it better reflects the recent changes in Canada's trade profile, including the rise in the importance of China and Mexico and the relative decline in importance of Europe and Japan in Canada's international trade. The author describes the methodology and construction of the new index and reviews the advantages it offers over the C-6, particularly the use of multilateral trade weights, the inclusion of trade in services, and the use of more recent trade data.

Liquidity Effects and Market Frictions

Staff Working Paper 1998-11 Scott Hendry, Guang-Jia Zhang
The goal of this paper is to shed light on the nature of the monetary transmission mechanism. Specifically, we attempt to tackle two problems in standard limited-participation models: (1) the interest rate liquidity effect is not as persistent as in the data; and (2) some nominal variables are unrealistically volatile. To address these problems, we […]
Content Type(s): Staff research, Staff working papers Research Topic(s): Monetary policy transmission JEL Code(s): E, E5

Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data

Staff Working Paper 2015-24 Pierre Guérin, Danilo Leiva-Leon
This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes – Bayesian (static) model averaging and dynamic model averaging – so as to explicitly reflect the objective of forecasting a discrete outcome.
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