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We revisit an old question: how do financial constraints affect the transmission of monetary policy to the real economy? To answer this question, we propose a simple empirical strategy that combines firm-level employment and balance sheet data, identified monetary policy shocks and survey data on financing activities.

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.

The year that just passed posed many challenges for all Canadians. The slowdown in the global economy became more pronounced as the year went on, and this affected households, businesses, and governments alike. The tragedy of 11 September compounded the economic difficulties and issues facing us all. Through this period of rapidly changing circumstances, the Bank met its responsibilities by responding quickly and vigorously to events in order to underpin confidence and support the economy.

Since the early 1980s, long-term government bond yields in the euro zone have declined, in line with those in other industrialized countries.

An effective technique governments use to evaluate the desirability of different financing strategies involves stochastic simulation. This approach requires the postulation of the future dynamics of key macroeconomic variables and the use of those variables in the construction of a debt charge distribution for each individual financing strategy.

The Canadian overnight repo market persistently shows signs of latent funding pressure around month-end periods. Both the overnight repo rate and Bank of Canada liquidity provision tend to rise in these windows. This paper proposes three non-mutually exclusive hypotheses to explain this phenomenon.

We show how participants in Canada’s new high-value payment system save liquidity by exploiting the new gridlock resolution arrangement. The findings have important implications for the design of these systems and shed light on financial institutions’ liquidity preference.

We use four decades of Canadian matched employer-employee data to explore how inequality and the dynamics of individual earnings have evolved over time in Canada. We also examine how the earnings growth of individuals is related to the growth of their employers.

We examine how intermediary capitalization affects asset prices in a framework that allows for intermediary market power. We introduce a model in which capital-constrained intermediaries buy or trade an asset in an imperfectly competitive market, and we show that weaker capital constraints lead to both higher prices and intermediary markups.

Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.