Marie-Hélène is a Senior Economist. Her primary area of research is applied microeconometrics. In the field of retail payments, she conducts research evaluating the impact of payment innovations on cash usage.
Staff discussion papers
Using data from our 2014 cost-of-payments survey, we calculate resource costs for cash, debit cards and credit cards. For each payment method, we examine the total cost incurred by consumers, retailers, financial institutions and infrastructures, the Royal Canadian Mint and the Bank of Canada.
Staff working papers
Distributional Effects of Payment Card Pricing and Merchant Cost Pass-through in Canada and the United StatesAlthough credit cards are more expensive for merchants to accept than cash or debit cards, merchants typically pass through their costs evenly to all customers. Along with consumer card rewards and banking fees, this creates cross-subsidies between payment methods. Because higher-income individuals tend to use credit cards more than those with lower incomes, our results indicate that these cross-subsidies might lead to regressive distributional effects.
Because they mimic desirable features of cash and are typically used for smaller-value transactions, contactless payment cards are a competitive alternative to cash. This study investigates whether contactless credit cards are an important contributor to the decline in the transactional usage of cash, using Canadian panel data between 2010 and 2017.
A Look Inside the Box: Combining Aggregate and Marginal Distributions to Identify Joint DistributionsThis 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.
We exploit the panel dimension of the Canadian Financial Monitor (CFM) data to estimate the impact of retail payment innovations on cash usage. We estimate a semiparametric panel data model that accounts for unobserved heterogeneity and allows for general forms of non-random attrition.
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.
This technical report describes sampling, weighting and variance estimation for the Bank of Canada’s 2017 Methods-of-Payment Survey. Under quota sampling, a raking ratio method is implemented to generate weights with both post-stratification and nonparametric nonresponse weight adjustments.