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Calibrated weights are created to (a) reduce the nonresponse bias; (b) reduce the coverage error; and (c) make the weighted estimates from the sample consistent with the target population in terms of certain key variables.

In 2015, the Bank of Canada undertook the large-scale Retailer Survey on the Cost of Payment Methods.

Nonresponse is a considerable challenge in the Retailer Survey on the Cost of Payment Methods conducted by the Bank of Canada in 2015. There are two types of nonresponse in this survey: unit nonresponse, in which a business does not reply to the entire survey, and item nonresponse, in which a business does not respond to particular questions within the survey.

The Bank of Canada’s 2013 Methods-of-Payment Survey indicates that the share of cash in the overall number of retail transactions has continued to decrease, mainly because of increased use of contactless credit cards. The share of cash in the total value of retail transactions was virtually unchanged from 2009 to 2013. In particular, the value share of cash transactions above $50 increased. Automated banking machines (ABMs), still the major source of cash for Canadians, were used less often in 2013 than in 2009. Cash use in Canada is broadly similar to that in Australia and the United States.

The formulation of monetary policy at the Bank of Canada relies on the analysis of a broad set of economic information. Greater availability of immediate and detailed information would improve real-time economic decision making. Technological advances have provided an opportunity to exploit “big data” - the vast amount of digital data from business transactions, social media and networked computers. Big data can be a complement to traditional information sources, offering fresh insight for the monitoring of economic activity and inflation.

Over the past 20 years, there has been a major shift away from the use of paper-based retail payment instruments, such as cash and cheques, toward electronic means of payment, such as debit cards and credit cards. Recent Bank of Canada research on consumers’ choice of payment instruments indicates that cash is frequently used for transactions with low values because of its speed, ease of use and wide acceptance, while debit and credit cards are more commonly used for transactions with higher values because of perceived attributes such as safety and record keeping. While innovations in retail payments currently being introduced into the Canadian marketplace could lead to a further reduction in the use of cash over the longer term, the implications for the use of cash of some of the structural and regulatory developments under way are less clear.

A number of central banks publish their own business conditions surveys based on complex 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 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 selection practice. We apply this framework to the Bank of Canada’s Business Outlook Survey by describing the sampling method in terms of rules-based criteria, 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.