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For several decades, the prices of services have been rising more rapidly than the prices of goods in Canada and the other major industrialized countries. In 2002, this gap between the growth rates of these two components of the consumer price index (CPI) widened considerably, leading researchers to ask if this was the beginning of a trend. Analysis reveals, however, that the gap is based on short-term dynamics and that it appears to be independent of the trend in the development of the overall price level. Evidence also shows that the gap is eventually reabsorbed. The authors examine a number of potential causes for the prices of services to rise faster than those of goods. These include the more rapid pace of productivity growth in the goods sector, the greater openness of goods to foreign trade, and stronger growth in the demand for services.

In this paper, we argue that differences in the cost structures across sectors play an important role in firms’ decisions to adjust their prices. We develop a menu-cost model of pricing in which retail firms intermediate trade between producers and consumers.

Many central banks are considering issuing a central bank digital currency (CBDC). This would introduce a new policy tool—interest on CBDC. We investigate how this new tool would interact with traditional monetary policy tools, such as the interest on central bank reserves.

Merchants who accept credit cards face payment processing fees. In most countries, the no-surcharge rule prohibits them from using surcharges to pass these fees on to customers.

This article focuses on a quantitative method to identify financial system vulnerabilities, specifically, an imbalance indicator model (IIM) and its application to Canada. An IIM identifies potential vulnerabilities in a financial system by comparing current economic and financial data with data from periods leading up to past episodes of financial stress. It complements other sources of information - including market intelligence and regular monitoring of the economy - that policy-makers use to assess vulnerabilities.

We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data.

During and after the Great Recession of 2008–09, conventional monetary policy in the United States and many other advanced economies was constrained by the effective lower bound (ELB) on nominal interest rates. Several central banks implemented large-scale asset purchase (LSAP) programs, more commonly known as quantitative easing or QE, to provide additional monetary stimulus.