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How do firms adjust prices in the marketplace? Do they tend to adjust prices infrequently in response to changes in market conditions? If so, why? These remain key questions in macroeconomics, particularly for central banks that work to keep inflation low and stable. The authors use the Bank of Canada's 200203 price-setting survey data to investigate Canadian firms' price-setting behaviour; they also analyze the micro foundations for the firms' pricing behaviour using count data and probit models. The authors find that, all else being equal, firms tend to adjust prices more frequently if they are state-dependent price-setters, operate in the trade sector, or have large variable costs or more direct competitors. There are various sticky-price theories; in the Bank's price-setting survey, the senior management of firms were read a simple statement in non-technical language that paraphrased each sticky-price theory, and were then asked whether the statement applied to their firm. The most frequently recognized sticky-price theories are customer relations, cost-based pricing, and coordination failure. The authors' analysis indicates that if firms recognize coordination failure on price increases, sticky information, menu costs, factor stability, or customer relations as being important, they tend to adjust prices less frequently. The authors also find that the patterns discernible within firms' recognition of stickyprice theories are strongly associated with firms' micro foundations.

AbstractUnderstanding the factors that determine the migration of labour between regions is crucial for assessing the response of the economy to macroeconomic shocks and identifying policies that will encourage an efficient reallocation of labour. Using a gravity model, Poisson pseudo‐maximum likelihood specifications and Census data for 69 economic regions, this article examines the determinants of aggregate migration within Canada from 1991 to 2006. Our results suggest that migration tends to increase with differences in labour market performance. We also find that provincial borders have the strongest impact on migration involving low‐populated regions and that distance is most important across provincial borders.

A number of central banks publish their own business conditions survey based on non-random sampling methods. The results of these surveys influence monetary policy decisions and thus affect expectations in financial markets. To date, however, no one has computed the statistical accuracy of these surveys because their respective non-random sampling method renders this assessment non-trivial. This paper describes a methodology for modeling complex non-random sampling behaviour, and computing relevant measures of statistical confidence, based on a given survey's historical sample selection practice. We apply this framework to the Bank of Canada's Business Outlook Survey by describing the sampling method in terms of historical practices and Bayesian probabilities. This allows us to replicate the firm selection process using Monte Carlo simulations on a comprehensive micro-dataset of Canadian firms. We find, under certain assumptions, no evidence that the Bank's firm selection process results in biased estimates and/or wider confidence intervals.