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This note reviews the emerging evidence on AI’s labour-market and productivity effects, highlighting early task-level impacts, sizable micro level productivity gains, and the macroeconomic challenges these pose for monetary policy during the transition.

Growth has slowed in many emerging-market economies (EMEs) since the 2007–09 global financial crisis, reflecting both cyclical and structural factors. In this context, it will be in-creasingly important for EMEs to raise potential growth by maintaining steady progress on structural reforms. How do structural reforms generally support growth? What are the re-form priorities for EMEs over recent history and today? Finally, what will be the impact of planned structural reforms on potential output growth among the world’s larger EMEs? These are some of the questions considered by the authors.

Should monetary policy lean against housing market booms? We approach this question using a small-scale, regime-switching New Keynesian model, where housing market crashes arrive with a logit probability that depends on the level of household debt.

Model-based forecasts of important economic variables are part of the range of information considered for monetary policy decision making.

Governor Tiff Macklem talks about the COVID-19 pandemic and major economic forces are affecting the labour market, and the need for all groups to benefits from the recovery.

The MacroFinancial Risk Assessment Framework (MFRAF) models the interconnections between liquidity and solvency in a financial system, with multiple institutions linked through an interbank network. The MFRAF integrates funding liquidity risk as an endogenous outcome of the interactions between solvency risk and the liquidity profiles of banks, which is a complementary approach to the new […]

To what extent does a central bank digital currency (CBDC) compete with bank deposits? To answer this question, we develop and estimate a structural model where each household chooses which financial institution to deposit their digital money with.

In its role as fiscal agent to the government, the Bank of Canada provides analysis and advice on decisions about the government's domestic debt portfolio. Debt-management decisions depend on assumptions about future interest rates, macroeconomic outcomes, and fiscal policy, yet when a debt-strategy decision is taken, none of these factors can be known with certainty. Moreover, the government has various financing options (i.e., treasury bills, nominal bonds, and inflation-linked bonds) to meet its objectives of minimizing debt-service charges while simultaneously ensuring a prudent risk profile and well-functioning government securities markets. Bank of Canada staff have therefore developed a mathematical model to assist in the decision-making process. This article describes the key aspects of the debt manager's challenge and the principal assumptions incorporated in the debt-strategy model, illustrated with specific results.

This article by the Bank's visiting economist examines the role of money in the transmission of monetary policy. Professor Laidler argues against the view of money as a passive variable that reacts to changes in prices, output, and interest rates but has no direct causative effect on them. He maintains that the empirical evidence supports the view of money playing an active role in the transmission mechanism. While he agrees that individual monetary aggregates can be difficult to read because of instabilities in the demand-for-money function, he argues that monetary aggregates, particularly those relating to transactions money, should have a more significant place in the hierarchy of policy variables that the Bank considers when formulating monetary policy.