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395 Results

Retrieving Implied Financial Networks from Bank Balance-Sheet and Market Data

Staff working paper 2017-30 Jose Fique
In complex and interconnected banking systems, counterparty risk does not depend only on the risk of the immediate counterparty but also on the risk of others in the network of exposures.

CBDC: Banking and Anonymity

Staff working paper 2024-9 Yuteng Cheng, Ryuichiro Izumi
We examine the optimal amount of user anonymity in a central bank digital currency in the context of bank lending. Anonymity, defined as the lender’s inability to discern an entrepreneur’s actions that enable fund diversion, influences the choice of payment instrument due to its impact on a bank’s lending decisions.

Simulating Intraday Transactions in the Canadian Retail Batch System

Staff working paper 2023-1 Nellie Zhang
This paper proposes a unique approach to simulate intraday transactions in the Canadian retail payments batch system when such transactions are unobtainable. The simulation procedure has potential for helping with data-deficient problems where only high-level aggregate information is available.

Child Skill Production: Accounting for Parental and Market-Based Time and Goods Investments

Can daycare replace parents’ time spent with children? We explore this by using data on how parents spend time and money on children and how this spending is related to their child’s development.

Explaining the Interplay Between Merchant Acceptance and Consumer Adoption in Two-Sided Markets for Payment Methods

Staff working paper 2019-32 Kim Huynh, Gradon Nicholls, Oleksandr Shcherbakov
Recent consumer and merchant surveys show a decrease in the use of cash at the point of sale. Increasingly, consumers and merchants have access to a growing array of payment innovations as substitutes for cash.

Predictive Density Combination Using a Tree-Based Synthesis Function

This paper studies non-parametric combinations of density forecasts. We introduce a regression tree-based approach that allows combination weights to vary on the features of the densities, time-trends or economic indicators. In two empirical applications, we show the benefits of this approach in terms of improved forecast accuracy and interpretability.

Beating the “pros” with a semi-structural model of their own inflation forecasts

How can Surveys of Professional Forecasters (SPF) be used to improve inflation forecasts? By using US historical quarterly data on SPF forecasts, we provide better understanding of how we can use forecast disagreement to improve our own forecasts.

Macroeconomic Predictions Using Payments Data and Machine Learning

Staff working paper 2022-10 James Chapman, Ajit Desai
We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges.

The Welfare Cost of Inflation Revisited: The Role of Financial Innovation and Household Heterogeneity

We document that, across households, the money consumption ratio increases with age and decreases with consumption, and that there has been a large increase in the money consumption ratio during the recent era of very low interest rates. We construct an overlapping generations (OLG) model of money holdings for transaction purposes subject to age (older households use more money), cohort (younger generations are exposed to better transaction technology), and time effects (nominal interest rates affect money holdings).
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