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The formulation of monetary policy at the Bank of Canada relies on the analysis of a broad set of economic information. Greater availability of immediate and detailed information would improve real-time economic decision making. Technological advances have provided an opportunity to exploit “big data” - the vast amount of digital data from business transactions, social media and networked computers. Big data can be a complement to traditional information sources, offering fresh insight for the monitoring of economic activity and inflation.

We study the impact of the Bank of Canada’s choice of settlement mechanism in Lynx on participant behaviors, liquidity usage, payment delays and the overall operational efficiency of the new system.

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.

A model of over-the-counter markets is proposed. Some asset buyers are informed in that they can identify high quality assets. Heterogeneous sellers with private information choose what type of buyers they want to trade with.

In the year and a half leading up to mid-2003, both employment and labour force participation increased at an unusually rapid pace compared to domestic economic activity. Gains in employment were unusually large, relative to output growth, compared to gains in total hours worked. This is explained by a faster rate of increase in the participation rate of the 55 and older age group, many of whom opted for part-time employment. This shift in the composition of employment contributed to a reduction in the length of the average workweek in 2002. As a result, labour input progressed at a rate that was markedly slower than for employment and more in line with its historical relationship to output growth. The authors anticipate that the 55 and older age group will continue to participate strongly in the labour force, but that as the economy rebounds and uncertainty diminishes, the cyclical component in the growth of part-time work should diminish and that of full-time employment increase. Employment growth should moderate in relation to output growth and there may be a cyclical rebound in labour productivity as total hours worked increases during the initial recovery in output growth.

Crowdfunding may enable unique products to reach the consumer market. I model a crowdfunding technology that publicly screens consumer demand early in the production process. In this model, entrepreneurs like crowdfunding for risky projects where demand is uncertain, but not for large, safe projects or for projects where production costs are uncertain.

Market power and pass-through of cost and demand shocks are studied in a market with free entry of heterogeneous firms and consumer mixed search. Equilibrium prices and markups are driven by variation in the elasticity of demand across firms. Improved conditions for buyers can either raise or lower market power.

In this paper, the author calculates new measures of the trend inflation rate using changes in the components of total CPI; the hypothesis is that extreme fluctuations in certain prices reflect temporary supply shocks rather than any basic price trend.

We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information.