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188 Results

Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19

Staff working paper 2021-2 James Chapman, Ajit Desai
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

Allocative Efficiency and the Productivity Slowdown

Staff working paper 2021-1 Lin Shao, Rongsheng Tang
In our analysis of the US productivity slowdown in the 1970s and 2000s, we find that a significant portion of this deceleration can be attributed to a lack of improvement in allocative efficiency across sectors. Our analysis further identifies increased sector-level volatility as a major contributor to this lack of improvement in allocative efficiency.

Losing Contact: The Impact of Contactless Payments on Cash Usage

Staff working paper 2020-56 Marie-Hélène Felt
Contactless payment cards are a competitive alternative to cash. Using Canadian panel data from 2010 to 2017, this study investigates whether contactless credit cards are an important contributor to the decline in the transactional use of cash. 

Earnings Dynamics and Intergenerational Transmission of Skill

Staff working paper 2020-46 Lance Lochner, Youngmin Park
How are your past, current and future earnings related to those of your parents? We explore this by using 37 years of Canadian tax data on two generations.

On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity

Staff working paper 2020-42 Ruben Hipp
Banks’ business interactions create a network of relationships that are hidden in the correlations of bank stock returns. But for policy interventions, we need causality to understand how the network changes. Thus, this paper looks for the causal network anticipated by investors.

The New Benchmark for Forecasts of the Real Price of Crude Oil

How can we assess the quality of a forecast? We propose a new benchmark to evaluate forecasts of temporally aggregated series and show that the real price of oil is more difficult to predict than we thought.

Survival Analysis of Bank Note Circulation: Fitness, Network Structure and Machine Learning

Staff working paper 2020-33 Diego Rojas, Juan Estrada, Kim Huynh, David T. Jacho-Chávez
Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

Sample Calibration of the Online CFM Survey

Technical report No. 118 Marie-Hélène Felt, David Laferrière
The Canadian Financial Monitor (CFM) survey uses non-probability sampling for data collection, so selection bias is likely. We outline methods for obtaining survey weights and discuss the conditions necessary for these weights to eliminate selection bias. We obtain calibration weights for the 2018 and 2019 online CFM samples.

Classical Decomposition of Markowitz Portfolio Selection

Staff working paper 2020-21 Christopher Demone, Olivia Di Matteo, Barbara Collignon
In this study, we enhance Markowitz portfolio selection with graph theory for the analysis of two portfolios composed of either EU or US assets. Using a threshold-based decomposition of their respective covariance matrices, we perturb the level of risk in each portfolio and build the corresponding sets of graphs.
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