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Housing starts and building permits data are commonly used as leading indicators of economic activity. In British Columbia, all new homes must be registered with the Homeowner Protection Office, a branch of BC Housing, before the issuance of building permits and the start of construction.

We add agency costs as in Carlstrom and Fuerst (1997) into a two-country, two-good international business-cycle model. In our model, changes in the relative price of investment arise endogenously.

Average hourly real wage series from the Labor Productivity and Costs (LPC) program and the Current Employment Statistics (CES) program have evolved very differently over the past decades.

The Bank of Canada recently launched a quarterly survey to measure the expectations of Canadian households: the Canadian Survey of Consumer Expectations (CSCE). The data collected provide comprehensive information about consumer expectations for and uncertainty about inflation, the labour market and household finance. This article describes the CSCE and illustrates its potential to offer rich information about Canadian consumers for researchers and policy-makers.

While the CPI is the most commonly used measure to track inflation, it is not fully consistent with a true cost-of-living index (COLI). Although the official treatment of durable goods and housing in the CPI represents an acceptable compromise in the current environment of low and stable inflation, Sabourin and Duguay suggest that it would be worthwhile to consider treating housing and durables in the same way and bringing the actual CPI closer to a COLI. This could be accomplished by employing an enhanced user-cost approach to calculate the imputed cost of the services provided by the use of durable goods or housing.

Inflation rates in advanced economies experienced two consecutive puzzles during the period following the global financial crisis—unexpectedly high inflation from the end of 2009 to 2011 and unexpectedly low inflation from 2012 to the middle of 2014. We investigate these developments in two ways. First, we show that accounting for inflation expectations by households explains a significant share of the inflation puzzles at the international level. Second, we find that, for Canada, elevated competition in the retail sector is also important for understanding inflation dynamics in the post-crisis period.

This article describes experimental economics, in general, and new developments in experimental macroeconomics, in particular. The approach has a clear niche in providing evidence on economic phenomena that cannot be observed directly or that are difficult to measure. Experimental work conducted by Bank of Canada economists has shed light on a number of issues important to monetary policy, such as the relative efficacy between price-level and inflation targeting, and the nature of inflation expectations formation.

Forecasts of the price of crude oil play a significant role in the conduct of monetary policy, especially for commodity producers such as Canada. This article presents a range of recently developed forecasting models that, when pooled together, can generate, on average, more accurate forecasts of the price of oil than the oil futures curve. It also illustrates how policy-makers can evaluate the risks associated with the baseline oil price forecast and how they can determine the causes of past oil price fluctuations.

Canada’s Short-Term Indicator (CSI) is a new model that exploits the information content of 32 indicators to produce daily updates to forecasts of quarterly real GDP growth. The model is a data-intensive, judgment-free approach to short-term forecasting. While CSI’s forecasts at the start of the quarter are not very accurate, the model’s accuracy increases appreciably as more information becomes available. CSI is the latest addition to a wide range of models and information sources that the Bank of Canada uses, combined with expert judgment, to produce its short-term forecasts.

This article examines whether combining forecasts of real GDP from different models can improve forecast accuracy and considers which model-combination methods provide the best performance. In line with previous literature, the authors find that combining forecasts generally improves forecast accuracy relative to various benchmarks. Unlike several previous studies, however, they find that, rather than assigning equal weights to each model, unequal weighting based on the past forecast performance of models tends to improve accuracy when forecasts across models are substantially different.