RDP 2020-06: Consumer Payment Behaviour in Australia: Evidence from the 2019 Consumer Payments Survey Appendix A: Survey Methodology
September 2020
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The fieldwork for the 2019 CPS was conducted by the research firm Roy Morgan Research on behalf of the Reserve Bank in October and November 2019. The survey consisted of three parts: a pre-diary questionnaire about the demographic characteristics of respondents; a seven-day payments diary; and a post-survey questionnaire about respondents' automatic payment arrangements and their preferences and attitudes about different payment methods. To encourage participation and engagement with the survey, respondents received a gift card on completion of the three components.
The survey was delivered online for most respondents but to ensure the sample was broadly representative of the Australian population, participants without internet access were recruited by telephone to complete a paper-based survey. The overall response rate was good, resulting in a final sample of 1,115 respondents (Table A1). Respondents recorded a total of around 16,000 transactions in the survey, comprising day-to-day payments, transfers to family or friends, automatic payments and cash top-ups (Table A2).
Number recruited | Number of completed responses | Response rate (%) | |
---|---|---|---|
Online respondents | 1,661 | 950 | 57 |
Offline respondents | 249 | 165 | 66 |
Total | 1,910 | 1,115 | 58 |
Source: RBA calculations, based on data from Roy Morgan Research |
Number | Value ($) | ||
---|---|---|---|
Day-to-day payments | 13,083 | 1,386,804 | |
Transfers and cash deposits | 552 | 399,523 | |
Automatic payments | 1,474 | 266,247 | |
Cash top-ups | 822 | 182,402 | |
Total | 15,931 | 2,234,976 | |
Source: RBA calculations, based on data from Roy Morgan Research |
A.1 Survey Instruments
Pre-diary questionnaire
The demographic information collected in the pre-diary questionnaire was mostly the same as that collected in 2016. Demographic variables included age, sex, personal and household income, family composition, household size, location (capital city or regional area), employment status, occupation, and education level. In 2019, the survey also asked whether respondents experienced any disabilities. A full list of debit and credit cards held by the respondent was collected, with the respondent also identifying their primary debit and credit card. Respondents also provided information about how they usually paid off their credit card debt (i.e. whether they paid off their debt every month or whether they let part of the balance roll over from month to month).
Payments diary
In the payments diary, respondents recorded details about every transaction they made for a week, excluding automatic payments (which were recorded in the post-survey questionnaire). These details included the value, payment method, payment channel and type of merchant. The payment methods and channels that respondents chose from were modified from 2016 to better match the ways that people pay – for example, BNPL services were added as a payment method. For card transactions, online respondents selected the specific card they used (from the list of cards they provided in the pre-diary questionnaire); offline participants only recorded the type of card they used (e.g. debit card, Visa/Mastercard credit card). Respondents also recorded the dollar value or percentage amount of any payment surcharges that they paid. Along with their payments, respondents were asked to include details of cash top-ups, including the value of any ATM fee paid. The full list of fields used in the 2019 diary is set out in in Table A3.
Post-survey questionnaire
In the post-survey questionnaire, respondents were asked to record details of any automatic payments that occurred during the diary week, referring to their latest bank statements.
In 2019, qualitative questions in the post-survey questionnaire focused on consumers' preferences and attitudes towards different payment methods. Key topics included use of and reliance on cash, payment preferences in different environments, awareness and use of new payment methods (such as BNPL services) and perceptions around privacy in payments.
Payments | |
---|---|
Date Day-of-week Payment amount Payment surcharge paid (dollar/per cent amount) Payment method:
Payment channel: In person
Not in person
|
Payment purpose:
|
Cash top-ups | |
Date Day-of-week Cash top-up amount ATM fee paid (dollar amount) Total value of banknotes in wallet after top-up |
Source of cash:
|
Note: (a) Online respondents selected the specific card they used (from the list of cards they provided in the pre-diary questionnaire); offline respondents selected from: debit card, MasterCard/Visa credit card, American Express/Diners Club, or another credit card |
A.2 Survey Sample and Weighting
The overall sampling process for the 2019 CPS was similar to that used for the 2016 survey. To ensure the survey sample was broadly representative of the Australian population, there were minimum recruitment targets covering key demographic variables: age, sex, household income, location (i.e. capital city or regional area), credit card ownership, and household internet access. Recruitment targets for most demographic variables were based on data from the Australian Bureau of Statistics (ABS); data on credit card ownership were obtained from HILDA Survey Release 17.0. Minimum targets were based on a sample size of 1,000 respondents.
Recruitment for the survey commenced on Friday, 4 October 2019 using Computer Assisted Telephone Interviewing. Most recruits were obtained by Thursday, 10 October 2019; subsequent recruitment ensured each minimum recruitment target was met. Roy Morgan Research used a combination of automated email/SMS reminders and ad hoc contacts to support completions of the survey.
Due to different response rates across the demographic categories for which recruitment targets were set, we constructed survey weights so that the final (weighted) dataset aligns with population benchmarks. Essentially, weighting ensures that the survey data can be used to make inferences about the Australian population. We used the iterative proportional fitting procedure, or raking, to calibrate the survey weights; the same procedure was used for the 2016 CPS. We implemented the raking algorithm using the ‘ipfweight’ program in Stata 16.0. Table A4 presents the unweighted sample distribution for selected demographic variables, alongside the population distribution and the mean weight for respondents in each group.
Unweighted sample proportion (%) |
Population proportion (%) |
Mean weight | |
---|---|---|---|
Age(a) | |||
18–24 | 12 | 12 | 0.98 |
25–34 | 19 | 20 | 1.02 |
35–44 | 14 | 18 | 1.19 |
45–54 | 14 | 16 | 1.15 |
55–64 | 17 | 15 | 0.87 |
65+ | 23 | 20 | 0.87 |
Gender(a) | |||
Female | 53 | 51 | 0.96 |
Male | 47 | 49 | 1.04 |
Location(a) | |||
Regional | 40 | 33 | 0.81 |
Capital city | 60 | 67 | 1.13 |
Household income quartile(a),(b) | |||
1st | 25 | 24 | 0.95 |
2nd | 21 | 25 | 1.18 |
3rd | 26 | 26 | 0.87 |
4th | 26 | 24 | 1.04 |
Credit card ownership(c) | |||
Yes | 61 | 56 | 0.92 |
No | 39 | 44 | 1.12 |
Notes: (a) Population proportion is based on ABS data Source: RBA calculations, based on data from ABS, HILDA and Roy Morgan Research |