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395 Results

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

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.

Bitcoin Awareness and Usage in Canada: An Update

Staff Analytical Note 2018-23 Christopher Henry, Kim Huynh, Gradon Nicholls
The results of our 2017 Bitcoin Omnibus Survey (December 12 to 15, 2017) when compared with those from 2016 show that Bitcoin “awareness” increased from 64 to 85 per cent, while ownership increased from 2.9 to 5.0 per cent. Most Bitcoin purchasers are using the cryptocurrency as an investment and not as a means of payment for goods or services.

Bootstrapping Mean Squared Errors of Robust Small-Area Estimators: Application to the Method-of-Payments Data

Staff Working Paper 2018-28 Valéry Dongmo Jiongo, Pierre Nguimkeu
This paper proposes a new bootstrap procedure for mean squared errors of robust small-area estimators. We formally prove the asymptotic validity of the proposed bootstrap method and examine its finite sample performance through Monte Carlo simulations.

On the Evolution of the United Kingdom Price Distributions

We propose a functional principal components method that accounts for stratified random sample weighting and time dependence in the observations to understand the evolution of distributions of monthly micro-level consumer prices for the United Kingdom (UK).

Noisy Monetary Policy

Staff Working Paper 2018-23 Tatjana Dahlhaus, Luca Gambetti
We introduce limited information in monetary policy. Agents receive signals from the central bank revealing new information (“news") about the future evolution of the policy rate before changes in the rate actually take place. However, the signal is disturbed by noise.

Applying the Wage-Common to Canadian Provinces

Staff Analytical Note 2018-16 Jonathan Lachaine
As at the national level, available sources of hourly wage data for Canadian provinces sometimes send conflicting signals about wage growth. This note has two objectives. First, we develop a common measure of provincial wages (the provincial wage-common) to better capture the underlying wage pressures, reflecting the overall trend across all data sources.

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.

The (Un)Demand for Money in Canada

Staff Working Paper 2018-20 Casey Jones, Geoffrey R. Dunbar
A novel dataset from the Bank of Canada is used to estimate the deposit functions for banknotes in Canada for three denominations: $1,000, $100 and $50. The broad flavour of the empirical findings is that denominations are different monies, and the structural estimates identify the underlying sources of the non-neutrality.

State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models

Staff Working Paper 2018-14 Luis Uzeda
Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood.
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