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310 Results

Partial Identification of Heteroskedastic Structural Vector Autoregressions: Theory and Bayesian Inference

Staff working paper 2025-14 Helmut Lütkepohl, Fei Shang, Luis Uzeda, Tomasz Woźniak
We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions.

The Shift in Canadian Immigration Composition and its Effect on Wages

Staff discussion paper 2025-8 Julien Champagne, Antoine Poulin-Moore, Mallory Long
We document recent changes in Canadian immigration, marked by an increasing prevalence of temporary residency. Using microdata from Statistics Canada's Labour Force Survey, we show that temporary workers' characteristics and nominal wages have diverged from those of Canadian-born workers.

Is anyone surprised? The high-frequency impact of US and domestic macroeconomic data announcements on Canadian asset prices

Staff analytical note 2025-10 Blake DeBruin Martos, Rodrigo Sekkel, Henry Stern, Xu Zhang
Using almost two decades of detailed high-frequency data, we show how Canadian interest rates, the CAD/USD spot exchange rate, and stock market returns react to both US and domestic macro announcements. We find that Canadian macroeconomic announcements invoke greater responses in short-term yields, whereas US macroeconomic announcements play an increasingly important role in the yield movements of longer-term assets.

Estimating the impacts on GDP of natural disasters in Canada

Staff analytical note 2025-5 Tatjana Dahlhaus, Thibaut Duprey, Craig Johnston
Extreme weather events contribute to increased volatility in both economic activity and prices, interfering with the assessment of the true underlying trends of the economy. With this in mind, we conduct a timely assessment of the impact of natural disasters on Canadian gross domestic product (GDP).

Breaking Down the US Employment Multiplier Using Micro­-Level Data

Using newly matched data on US defense contracts and restricted administrative employment data, we show that the employment effects of defense procurement are costly, concentrated and slow to diffuse.

Anchored Inflation Expectations: What Recent Data Reveal

Staff working paper 2025-5 Olena Kostyshyna, Isabelle Salle, Hung Truong
We analyze micro-level data from the Canadian Survey of Consumer Expectations through the lens of a heterogeneous-expectations model to study how inflation expectations form over the business cycle. We provide new insights into how households form expectations, documenting that forecasting behaviours, attention and noise in beliefs vary across socio-demographic groups and correlate with views about monetary policy.

Quantile VARs and Macroeconomic Risk Forecasting

Staff working paper 2025-4 Stéphane Surprenant
This paper provides an extensive evaluation of the performance of quantile vector autoregression (QVAR) to forecast macroeconomic risk. Generally, QVAR outperforms standard benchmark models. Moreover, QVAR and QVAR augmented with factors perform equally well. Both are adequate for modeling macroeconomic risks.

Bouncing Back: How Mothballing Curbs Prices

We investigate the macroeconomic impacts of mothballed businesses—those that closed temporarily—on sectoral equilibrium prices after a negative demand shock. Our results suggest that pandemic fiscal support for temporary closures may have eased inflationary pressures.

The Distributional Origins of the Canada-US GDP and Labour Productivity Gaps

Staff working paper 2024-49 James (Jim) C. MacGee, Joel Rodrigue
We find the top 10% of the income distribution accounts for three-quarters of the gap in GDP per adult between Canada and the United States. The large gaps in income for high-income earners help distinguish between alternative explanations of this persistent gap in GDP per adult.

Seasonal Adjustment of Weekly Data

Staff discussion paper 2024-17 Jeffrey Mollins, Rachit Lumb
The industry standard for seasonally adjusting data, X-13ARIMA-SEATS, is not suitable for high-frequency data. We summarize and assess several of the most popular seasonal adjustment methods for weekly data given the increased availability and promise of non-traditional data at higher frequencies.
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