RDP 2015-03: The Value of Payment Instruments: Estimating Willingness to Pay and Consumer Surplus 2. Literature

Our paper measures the consumers' benefit derived from the use of payment cards and examines how the mix of payments may change under direct pricing. To date, these two themes have been approached in two quite different ways.

There have been a number of attempts at quantifying consumer benefits from the use of different payment methods. These papers include a seminal paper by Garcia Swartz, Hahn and Layne-Farrar (2004) for the United States and a similar paper for Australia by Simes, Lancy and Harper (2006). The two papers hypothesise a range of features for card payments methods, which include, where appropriate, record-keeping, privacy, float (deferred payment), access to a line of credit, rewards and cash-out features. They then build up the aggregate consumer benefit from separate component estimates of the benefits of each feature. These components are valued using a variety of methods including: opportunity cost, explicit prices and inferred benefits.[1] However, since some of the benefits were quantified at cost or indirectly, it may not necessarily be the case that consumers would actually attach the estimated values to those benefits. Our methodology differs in that valuations are elicited directly from consumers and heterogeneity in valuations is permitted.

More recently, a number of papers have used cross-sectional databases to quantify the consumer response to transaction-based pricing.[2] Borzekowski, Kiser and Ahmed (2008) used survey data on debit card adoption and use to evaluate how US consumers reacted to per-transaction prices on card payments. They found that the likelihood of a consumer using a debit card was 12 percentage points lower if the consumer was charged a 1.8 per cent transaction fee by their issuing bank. Bolt, Jonker and van Renselaar (2010) is the closest to our own paper in that it evaluated consumers' responses to a surcharge at the point of sale. Using data from a survey of merchants on the share of sales made using a debit card and the merchant's surcharge on debit cards, they found that removing the average 2.3 per cent surcharge on small-value payments would increase the use of debit cards by around 8 percentage points. In contrast, Ching and Hayashi (2010) and Simon, Smith and West (2010) evaluated how the implicit price incentive provided by reward programs stimulates use of the payment method to which the rewards are attached. The same conclusions apply; consumers are prompted to increase their use of payment methods which have greater rewards and lower prices.

Our approach builds on these two streams of work, but is distinct in its methodology and use of stated preference data. First, we directly measure the value that consumers place on cards, and specific features of credit cards, by eliciting how willing individuals are to pay to use those cards through a DCE. The approach then enables us to evaluate how Australian consumers' payment choices might respond to different surcharge levels, using a different approach to that of Bolt et al (2010) for the Netherlands. Our data also allows us to calculate the changes in consumer surplus that occur as a result of consumers' payment choices.

To the best of our knowledge, this paper presents the first use of DCE and contingent valuation techniques in valuing card payments. DCEs involve a hypothetical question posed to respondents where they must choose between two or more outcomes that differ in their characteristics (e.g. price and features). They are an important and flexible tool in valuing goods or services where the prices are not observable or markets do not exist, including in environmental, health and transport economics. Hausman (1993), Carson, Flores and Meade (2001) and Kling, Phaneuf and Zhao (2012) provide reviews and critiques of this extensive area of literature. We are motivated to use a modified form of DCE to gather data because it allows us to observe the willingness to pay for all respondents. In contrast, the revealed preference data that we use only contain information about when a respondent both faces a surcharge (which is relatively rare) and chooses to pay it.


For example, privacy was valued at the discount forgone on not belonging to a store loyalty program, reward points were valued at the cost of purchasing rewards points and the float (deferred payment) was valued as the interest gained on the free funds. [1]

An early paper was Humprey, Kim and Vale (2001), which used aggregate time series data to evaluate how pricing affected the use of payment products. [2]