Applied econometric work takes a superficial approach to causality. Understanding economic affairs, making good policy decisions, and progress in the economic discipline depend on our ability to infer causal relations from data. We review the dominant approaches to causality in econometrics, and...

The ever present possibility of confounding factors creates difficulties in identifying causal effects on the basis of observational data. A large number of approaches to resolve this difficulty have been proposed; see Zaman (2010) for a recent survey. One involves using a "natural experiment"...

This paper presents simulation results for Canada's new large-value payments system: Lynx. We simulate the settlement process of Lynx using a large sample of payments observed in the current system (LVTS), taking the initial level of liquidity as given. We calculate the resulting liquidity...

We conduct a follow-up to Chen et al. (2020) and study demand for and use of cash after the containment measures imposed at the beginning of the COVID-19 pandemic were relaxed during the summer of 2020. We find that bank notes in circulation continued to rise in July due to ongoing cash...

Online shopping is often guided by search platforms. Consumers type keywords into query boxes, and search platforms deliver a list of products. Consumers' attention is limited, and exhaustive searches are often impractical. Thus, the order in which products appear in search results affects the...

Interconnectedness is an inherent feature of the modern financial system. While it contributes to efficiency of financial services, it also creates structural vulnerabilities: pernicious shock transmission and amplification impacting banks' capitalization. This has recently been seen during the...

Default risk models have been widely employed to assess the ability of households and sovereigns to insure themselves against shocks. Grid search has often been used to solve these models because the complexity of the problem prevents the use of faster but less general methods. In this paper, we...

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. Using the quantum Monte Carlo (QMC) algorithm, we are the first to study whether quantum computing can improve the run time of economic applications and challenges in doing so....

We provide an update on the impact the COVID-19 pandemic on the demand for cash and the use of methods of payment based on data from the Bank Note Distribution System and from consumer surveys conducted in April and August 2021. Our key findings are as follows: Cash in circulation remained high...

Assessing the state of the economy in real time is critical for policy-making, and understanding the risks to those assessments is equally important. Policy-makers are typically provided with point forecasts that contain insufficient information about risks. In contrast, predictive densities...