Staff research

Rising housing costs are leading to an increasing share of first-time homebuyers seeking financial support from their parents. Specifically, Canada has experienced a noticeable rise in instances of parents co-signing mortgages with their adult children. This practice allows buyers to purchase more expensive homes—but it can also make both parties vulnerable to financial disruptions.

As the economy emerges from a crisis, macroeconomic policy confronts a dilemma: a protracted stimulus can foster a more inclusive labor market recovery, yet risks igniting inflation that ultimately undermines workers’ welfare through real income erosion. This tension amplifies in the presence of the ZLB and aggregate capacity constraints. We embed this insight into a quantitative model of the US economy.

This note finds evidence of a positive and nonlinear relationship between mortgage interest costs (MIC) and rental inflation: the impact of MIC on rents is small when population growth is near its historical norm, but significantly stronger during periods of rapid population growth.

Mortgage debt represents over 70% of all Canadian household financial liabilities, and the performance of these debts is critical to the health of the financial system. We explore the relationships between mortgage arrears and key macroeconomic fundamentals such as labour market variables, interest rates, house prices and inflation. We then develop a framework to assess future household mortgage stress.

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.

We develop an approach to quantify transaction costs in the repo market using OTC transaction data, where quoted bid-ask spreads are not observable. By estimating effective spreads at the level of individual trades, we construct a novel metric to evaluate intermediation costs across different segments of the market.

Statistical inference--both estimation and testing--for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student’s t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply “winsorization” to improve stability and finite-sample performance. Except for the degrees of-freedom parameter, closed-form expressions are available for all other parameters, extending Ahsan and Dufour (2019, 2021), thus eliminating the need for numerical optimization or initial values. We derive the estimators’ asymptotic distribution and show that, due to their analytical tractability, they support reliable, and even exact, simulation-based inference via Monte Carlo or bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models.

Previous research suggests that lower-income Canadians may have unique experiences with the use of payments, including the use of cash and digital payments. We conduct a case study using data from [the Canadian Financial Diaries project/Canadian financial diaries] to gain insight into how some lower-income Canadians pay.

This note examines how monetary policy responses to shelter inflation affect both the overall economy and different households. We find that the aggregate macroeconomic effects of responding to shelter inflation are modest, whereas the redistributive consequences across households are substantially larger.

In markets with costly buyer entry, information transparency about prices draws in buyers, increasing demand-side competition and putting upward pressure on prices. We show that this buyer entry effect may dominate seller competition as emphasized by conventional wisdom and prices and markups may rise with information transparency.