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Freedman and Engert focus on the changing pattern of lending and borrowing in Canada in the past thirty to forty years, including the types of financial instruments used and the relative roles of financial institutions and financial markets. They examine how borrowing mechanisms have changed over time and consider the challenges facing the Canadian financial sector, including whether our financial markets are in danger of disappearing because of the size and pre-eminence of U.S. financial markets. Some of the trends examined here include syndicated lending, securitization, and credit derivatives, a form of financial engineering that has become increasingly important in the last few years. They also study bond and equity markets to determine whether Canadian capital markets have been hollowed out or abandoned by Canadian firms and conclude that the data do not provide much support for that view.

We identify the drivers of unsecured and collateralized loan volumes, rates and haircuts in Canada using the Bayesian model averaging approach to deal with model uncertainty. Our results suggest that the key friction driving behaviour in this market is the collateral reallocation cost faced by borrowers.

I examine the impact of non-regulated lenders in the mortgage market using a dynamic stochastic general equilibrium (DSGE) model. My model features two types of financial intermediaries that differ in three ways: (i) only regulated intermediaries face a capital requirement, (ii) non-regulated intermediaries finance themselves by selling securities and cannot accept deposits, and (iii) non-regulated intermediaries face a more elastic demand.

This paper evaluates the effectiveness of macroprudential policies when regulations are uneven across mortgage lender types. We look at credit tightening that results from macroprudential regulations and examine how much of it is counteracted by credit shifting to unregulated lenders. We also study the impact of monetary policy tightening when some lenders are unregulated.

Severe disruptions in the financial markets, as observed during the 2008 global financial crisis or the COVID-19 pandemic, can impair the stability of the entire financial system and worsen macroeconomic downturns.

Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.

We document a strong asymmetry in the evolution of federal funds rate expectations and map this observed asymmetry into measures of monetary policy uncertainty. We show that periods of monetary policy tightening and easing are distinctly related to downside (policy rate is higher than expected) and upside (policy rate is lower than expected) uncertainty.

This paper examines the cross-border spillovers from major economies’ quantitative easing (QE) policies to their trading partners. We concentrate on spillovers from the US to Canada during the zero lower bound period when QE policies were actively used.

The U.S. recovery from the Great Recession has been slow relative to other postwar-era recoveries in the United States. Encouraged by loose lending standards in the pre-crisis period, U.S. households took on unsustainable amounts of debt, making them vulnerable to adverse shocks. Subsequently, a considerable drop in asset prices forced households to repair their balance sheets. While there has been progress in household deleveraging, the government sector now needs to delever, which will restrain growth over the next few years.

The existence of downward nominal wage rigidity (DNWR) has often been used to justify a positive inflation target. It is traditionally assumed that positive inflation could “grease the wheels” of the labour market by putting downward pressure on real wages, easing labour market adjustments during a recession.