Heng Chen is a Research Advisor in the Currency Department at the Bank of Canada. His primary research interests center on understanding cash demand and usage through surveys and casual inference. Heng Chen received his PhD in economics from Vanderbilt University.
This paper develops a travel-based metric to measure Canadians’ access to cash from automated banking machines (ABMs) and financial institution branches. We find that, overall, access to cash remained stable between 2019 and 2022. The total number of ABMs in Canada increased by 3.7% and the total number of branches decreased by 5.2% during that period.
This paper studies Canadians’ access to cash using the geographical distribution of automated banking machines (ABMs). During the pandemic, there have been no sustained adverse effects on cash accessibility.
Chen et al. (2021) show that almost one-third of First Nations band offices in Canada are within 1 kilometre (km) of an automated banking machine (ABM) or financial institution (FI) branch and more than half are within 5 km.
Using data from the Bank Note Distribution System and consumer surveys, we find that bank notes in circulation remained high through 2021. Canadians continued to rely on electronic methods of payment, but a significant share also continued using cash for payments.
The COVID-19 pandemic significantly increased the demand for cash. Cash in circulation increased sharply from March through December 2020, particularly in the early months of this period. Although use of electronic methods of payment also increased significantly, cash use for payments remains high for low-value transactions and among certain demographic groups.
Adequate cash distribution is one the Bank of Canada’s core interests. Canadians’ ability to access cash influences the Bank’s thinking on issuing a central bank digital currency. We provide a perspective on these issues by exploring access of First Nations reserves to cash.
Using Bank Note Distribution System data on the demand for cash up to September 2020, we find that demand was strong. This is true even though cash use for payments declined early in the pandemic. When mobility restrictions and lockdown measures were eased, cash use for payments increased sharply but remained less popular than electronic methods of payment.
Consumer spending declined significantly during the recent COVID-19 pandemic. This negative shock likely reduced spending across all methods of payment (cash, debit, credit, etc.). The mix of payment methods consumers use could also be affected. We study how the pandemic has influenced the demand for and use of cash. We also offer insights into the use of other payment methods, such as debit and credit cards.
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.
The physical network of bank branches is important in how consumers manage their cash holdings. This paper estimates how consumer withdrawal behaviour responds to the distance they must travel to their branch.
Using data on bank branch locations across Canada from 2008 to 2018, we explore an interesting aspect of bank branch competition—geographic concentration. We find that bank branch density does not correlate with geographic and market concentration; however, we do find strong correlation with postal-code demographics.
Cash is the preferred method of payment for small value transactions generally less than $25. We provide insight to this finding with a new theoretical model that characterizes and compares consumers’ costs of paying with cash to paying with cards for each transaction.
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.
Estimation of the quantile model, especially with a large data set, can be computationally burdensome. This paper proposes using the Gaussian approximation, also known as quantile coupling, to estimate a quantile model.
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.
Calibrated weights are created to (a) reduce the nonresponse bias; (b) reduce the coverage error; and (c) make the weighted estimates from the sample consistent with the target population in terms of certain key variables.
Sampling units for the 2013 Methods-of-Payment Survey were selected through an approximate stratified random sampling design. To compensate for non-response and non-coverage, the observations are weighted through a raking procedure.
Multi-dimensional Latent Group Structure with Heterogeneous Distributions (with Wendun Wang and Xuan Leng), Accepted, Journal of Econometrics.
Quantile Treatment Effects in the Regression Kink Design (with Harold D. Chiang and Yuya Sasaki), Econometric Theory, 2020.
A Spatial Panel Model of Bank Branches in Canada (with Matthew Strathearn), Advances in Econometrics (Volume 42): The Econometrics of Networks. Editors: Áureo De Paula (UCL), Elie Tamer (Harvard), and Marcel Voia (Carleton), 2019.
Identification and Wavelet Estimation of Weighted ATE in a Class of Switching Regime Models (with Yanqin Fan), Journal of Econometrics, 2019.
The Mode is the Message: Using Paradata to Identify Survey Design Effects (with Geoff Dunbar and Rallye Shen), Advances in Econometrics (Volume 41): Essays in Honor of Cheng Hsiao. Editors: M. Hashem Pesaran (USC), Tong Li (Vanderbilt), and Dek Terrell (LSU), 2019.
Cash versus Card: Payment Discontinuities and the Burden of Holding Coins (with Kim Huynh and Oz Shy), Journal of Banking and Finance, 2019.
Variance Estimation for Survey-Weighted Data Using Bootstrap Resampling Methods: 2013 Methods-of-Payment Survey Questionnaire (with Rallye Shen), Advances in Econometrics (Volume 39): The Econometrics of Complex Survey Data: Theory and Applications. Editors: Gautam Tripathi (U Luxembourg), David Jacho-Chavez (Emory U), Kim P. Huynh (Bank of Canada), 2018.
Measuring Consumer Cash Holdings: Lessons from the 2013 Bank of Canada Methods-of-Payment Survey (with Chris Henry, Kim Huynh, Rallye Shen, Kyle Vincent), Survey Practice, 2016.
Retail Payment Innovations and Cash Usage: Accounting for Attrition Using Refreshment Samples (with Marie-Helene Felt and Kim Huynh), Journal of Royal Statistical Society: Series A, 2016.
Inference for the Correlation Coefficient between Potential Outcomes in the Gaussian Switching Regime Model (with Yanqin Fan and Ruixuan Liu), Journal of Econometrics, 2016.
Sheep in Wolf's Clothing: Using the Least Squares Criterion for Quantile Regression, Economics Letters, 2015.
A Flexible Parametric Approach for Estimating Switching Regime Models and Treatment Effect Parameters (with Yanqin Fan and Jisong Wu), Journal of Econometrics, 2014.