Demand for Payment Services and Consumer Welfare: The Introduction of a Central Bank Digital Currency Staff working paper 2020-7 Kim Huynh, Jozsef Molnar, Oleksandr Shcherbakov, Qinghui Yu Using a two-stage model, we study the determinants of Canadian consumers’ choices of payment method at the point of sale. We estimate consumer preferences and adoption costs for various combinations of payment methods. We analyze how introducing a central bank digital currency would affect the market equilibrium. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C51, E, E4, E42, L, L1, L14, L5, L52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Money and payments, Digital assets and fintech, Retail payments
Trading for Bailouts Staff working paper 2020-23 Toni Ahnert, Caio Machado, Ana Elisa Pereira In times of high uncertainty, governments often implement interventions such as bailouts to financial institutions. To use public resources efficiently and to avoid major spillovers to the rest of the economy, policy-makers try to identify which institutions should receive assistance. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D8, D83, G, G1, G12, G14, G18 Research Theme(s): Financial markets and funds management, Market functioning, Financial system, Financial institutions and intermediation, Financial stability and systemic risk, Financial system regulation and oversight
Estimating the Appropriate Quantity of Settlement Balances in a Floor System Staff discussion paper 2023-26 Narayan Bulusu, Matthew McNeely, Kaetlynd McRae, Jonathan Witmer This paper presents two complementary approaches to estimating the appropriate quantity of settlement balances needed to effectively operate monetary policy under a floor system in Canada. Content Type(s): Staff research, Staff discussion papers JEL Code(s): E, E4, E41, E42, E5, E52, E58, G, G2, G21, G28 Research Theme(s): Monetary policy, Monetary policy tools and implementation, Money and payments, Payment and financial market infrastructures
Should Bank Capital Regulation Be Risk Sensitive? Staff working paper 2018-48 Toni Ahnert, James Chapman, Carolyn A. Wilkins We present a simple model to study the risk sensitivity of capital regulation. A banker funds investment with uninsured deposits and costly capital, where capital resolves a moral hazard problem in the banker’s choice of risk. Content Type(s): Staff research, Staff working papers JEL Code(s): G, G2, G21, G28 Research Theme(s): Financial system, Financial stability and systemic risk, Financial system regulation and oversight
Redefining Financial Inclusion for a Digital Age: Implications for a Central Bank Digital Currency Staff discussion paper 2023-22 Alexandra Sutton-Lalani, Sebastian Hernandez, John Miedema, Jiamin Dai, Badr Omrane We explore quantitative and qualitative information about Canadians who face barriers to making digital payments. We also consider the implications of ongoing digitalization for modern financial inclusion and a potential central bank digital currency. Content Type(s): Staff research, Staff discussion papers JEL Code(s): A, A1, A14, E, E4, E42, E5, E50, I, I3, I31, O, O3, O33, O5, O51 Research Theme(s): Money and payments, Digital assets and fintech, Retail payments, Structural challenges, Demographics and labour supply, Digitalization and productivity
Trading on Long-term Information Staff working paper 2020-20 Corey Garriott, Ryan Riordan Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading. Content Type(s): Staff research, Staff working papers JEL Code(s): G, G1, G14, G2, G20, L, L1 Research Theme(s): Financial markets and funds management, Market functioning, Market structure, Financial system, Financial institutions and intermediation
The Effects of Government Licensing on E-commerce: Evidence from Alibaba Staff working paper 2021-32 Ginger Zhe Jin, Zhentong Lu, Xiaolu Zhou, Chunxiao Li How does government licensing affect selling on online platforms? We examine the impact of China’s 2015 Food Safety Law on sellers and buyers on Alibaba, the largest e-commerce platform in that country. Content Type(s): Staff research, Staff working papers JEL Code(s): D, D8, D82, K, K2, K23, L, L5, L8, L81 Research Theme(s): Financial markets and funds management, Market functioning, Market structure
Labour Supply and Firm Size Staff working paper 2023-47 Lin Shao, Faisal Sohail, Emircan Yurdagul This paper documents a systematic pattern of how wages, hours and their relationship vary across firms of different sizes. Using a model with heterogeneous firms and workers, we show how the interplay between wages, hours and firm size affect worker sorting and inequality. Content Type(s): Staff research, Staff working papers JEL Code(s): E, E2, E24, J, J2, J3, J31 Research Theme(s): Monetary policy, Real economy and forecasting, Structural challenges, Demographics and labour supply
Firm-level Investment Under Imperfect Capital Markets in Ukraine Staff working paper 2019-14 Oleksandr Shcherbakov This paper develops and estimates a model of firm-level fixed capital investment when firms face borrowing constraints. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C6, C61, C63, D, D2, D24, G, G3, G31 Research Theme(s): Financial system, Household and business credit, Models and tools, Econometric, statistical and computational methods, Economic models
Identifying Nascent High-Growth Firms Using Machine Learning Staff working paper 2023-53 Stéphanie Houle, Ryan Macdonald Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C55, C8, C81, L, L2, L25 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Structural challenges, Digitalization and productivity