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2010 SCPC Data User’s Guide Introduction There are 2102 observations in the 2010 Survey of Consumer Payment Choice (SCPC). The Consumer Payments Research Center (CPRC) designed a more rigorous data cleaning procedure for processing the 2010 data, and retrospectively applied the procedure to the 2008 and 2009 SCPC datasets to make the data across years comparable. As a result, the values of some variables pertaining to payment use and cash management might be changed from those released in previous years. The 2010 SCPC was administered online to a sample of 2102 U.S. consumers by the RAND Corporation as a module of the American Life Panel (ALP). Survey responses were weighted to match the national population estimates from the U.S. Census Bureau’s Current Population Survey. Variable types There are two broad categories of variables: created and survey variables. The created variables were created by the staff of the CPRC to aid in data analysis. Most of these variables have descriptive names based on a combination of mnemonics. The next section of this document, titled “Mnemonic-based variables” explains the mnemonics and the structure of the variable names that use them. Every effort has been made to maintain a consistent mnemonic structure across all years of the SCPC. However, changes in the survey questionnaire have led to the creation of some new mnemonics, with some of the older ones falling out of use. In addition, this section describes flags, which have names that are based on both mnemonic and survey variables. A brief explanation of these variables and their purpose is provided in the Flags subsection. Because these variables were created for preliminary data analysis, only some of the questions and concepts in the survey have corresponding mnemonic-based variables. The third section of this document, “Non-mnemonic variables,” describes created variables that do not follow the mnemonic-based naming conventions. These variables include unique respondent identifiers, weights, and certain demographic categories. The section also includes “intermediate” created variables that were created as part of the frequency conversion of some responses, or in unwinding of randomized response options. The survey variables are the actual results from the survey questions. Prior to answering the questions in the SCPC, the respondent is asked to complete the ALP’s My Household Questionnaire (MHQ). The 1 MHQ is used to gather demographic data about each respondent. The names and definitions of survey variables are embedded in the questionnaires, which are available for download on the Boston Fed SCPC website. Conversions of survey variables Two processes have been applied to some variables in the dataset to make them useful for researchers. First, questions with randomized response options have been processed to unrandomize the responses. Second, survey variables that allow respondents to choose between multiple response frequencies have been converted to one frequency for analysis. More detail on each process follows. Unwinding randomization: To avoid potential biases arising from the order of response options presented to respondents, the survey instrument randomizes response options for some questions. The questionnaire clearly indicates if response options were randomized. The raw data from the unrandomized variables and the SAS macros that unrandomize the responses will be made available upon request. Frequency conversion: Respondents are given the option of enumerating payment use and cash management in terms of a typical week, month, or year. This dataset includes variables where responses have been standardized to a monthly frequency. The difference between the “intermediate” and the “mnemonic-based” is that the mnemonic-based variables are coded as 0 for respondents who have not adopted the respective payment instrument. The SAS macros for these frequency conversions can be made available upon request. Further information: Please see Federal Reserve Bank of Boston Research Data Report No. 13-2, The 2010 Survey of Consumer Payment Choice, by Foster, Schuh, and Zhang (RDR 13-2), for further information, including: • An overview of the survey • Tables of survey results • Definitions of the terminology used • Additional contact information. Stable URL: http://www.bostonfed.org/economic/rdr/2013/rdr1302.htm Stable URL for the data: http://www.bostonfed.org/economic/cprc/scpc/index.htm Questions regarding the data can be directed to: 2 Kevin Foster Survey Methodologist Consumer Payment Research Center Federal Reserve Bank of Boston (617) 973-3955 kevin.foster@bos.frb.org Mnemonic-based variables Most created variable names are a combination of two or more mnemonics, combined using underscores. Typically, the first mnemonic refers to the payment instrument and the second or last mnemonic indicates the concept being communicated, such as its characteristic, adoption, or typical use. This is not always the case: a number of variables describe concepts that are independent of any payment instrument. This section covers mnemonics in roughly the order their corresponding questions appear in the SCPC questionnaire. The major subsections describe mnemonics for payment instruments, the assessment of payment characteristics, payment adoption, and payment use. The last subsection, Flags, includes a brief explanation of the data cleaning and imputations. For definitions of concepts in this section please see Section XI, Definitions and concepts, in the 2010 SCPC results paper. Payment instruments csh Cash chk Check dc Debit card cc Credit card svc Stored-value card/prepaid card banp Bank account number payment obbp Online banking bill payment mon Money order tc Traveler’s check Payment instruments are grouped as follows: 3 paper Cash, check, money order, traveler’s checks card Credit cards, debit cards, prepaid cards elect Bank account number payments, online banking bill payments pi Used in variables describing the set of all payment instruments Note: Respondents are asked about their use of direct deductions from income to make automatic bill payments; thus income is included as a payment instrument for payment use variables (discussed below). However, it is not considered a payment instrument and is not included as an electronic payment instrument. Assessment of payment characteristics security Security setup Getting and setting up acceptance Acceptance for payment cost Cost records Payment records convenience Convenience For example: The variable csh_security contains respondents’ rankings (1 to 5) of the security of cash. Other ‘assessment of characteristics’ mnemonics Questions AS012_a to AS012_h presented respondents with a randomized list of payment characteristics and asked them to rank the importance of each payment characteristic. In 2010 respondents were asked to rank six payment characteristics. After unwinding the randomization of the order in which payment characteristics were presented, the ranking variables are grouped as follows: as012_an[1-6] Acceptance for payment as012_bn[1-6] Getting and Set up as012_dn[1-6] Cost as012_en[1-6] Convenience as012_fn[1-6] Payment records as012_hn[1-6] Security 4 Questions as004_a to as004_e asks respondents to assess the security features of five different payment locations. Question as005 asks respondents to rate the security of different methods of authorizing a debit card payment. Both sets of variables as004 and as005 have a 5-point scale for the response options. All these variables are named as a combination of mnemonics and “_security”. inperson In person payment online Online payment bymail Payment made by mail byphone Payment made by phone mobile Mobile payment pindc PIN debit card payment sigdc Signature debit card payment nopinsigdc No PIN and no signature debit card payment onlinedc Debit card payment online For example: The variable sigdc_security contains respondents’ rankings (1 to 5) of the security of transactions made by signature debit card. Payment adoption adopt Respondent is currently an adopter (Y/N) ever Respondent was an adopter (Y/N) discard Respondent was an adopter, not anymore (Y/N) num Number of payment instruments (equals 0 for non-adopters) Payment history stolen_lost Incidence of payment instrument stolen or lost (Y/N) stolen_lost_amnt_incidence Dollar amount of financial losses or fraudulent charges due to payment instrument 5 being lost or stolen For more detail about the variables listed above, please refer to questions ph022 and ph023 in 2010 SCPC questionnaire. Examples: csh_stolen_lost equals 1 if the respondent reported cash being lost or stolen in the past 12 months; csh_stolen_lost_amnt_incidence indicates the amount of cash being lost or stolen in the past 12 months. Payment accounts In addition to the payment instruments above, respondents are also asked about their bank account adoption, and adoption of other payment technologies. chk_acnt Checking account sav_acnt Savings account bnk_acnt Bank account (checking or savings account) mm_acnt Money market or brokerage account pp_acnt (or pp) Non-bank online payment account (e.g. Paypal, Google Checkout, Amazon Payments) mm_acnt_chk Money market account with check writing privileges atm ATM-only cards chk_blnk Blank checks tb Telephone banking ob Online banking (need not include bill pay) mb Mobile banking mp Mobile payments smartphone Smart phone text_plan Cell phone with text plan feature web_browsing Cell phone with web browsing capability 6 contactless Contactless payment technology (used with cc, dc, svc, mp) txtpay Payment made via text message (used with mp) keyfob Key fob etp Electronic toll payment rewards Rewards (used with cc, dc) norewards No rewards (used with cc, dc) onlyrewards All cards bear rewards, i.e.: no non-reward cards (used with cc, dc) reloadable Feature of prepaid cards whose value can be increased reload Action taken to increase value of a prepaid card Example: • svc_reloadable_adopt equals 1 if the respondent has a reloadable prepaid card; svc_reload equals 1 if the respondent reloaded his/her prepaid card in the preceding 12 months. Note: Please refer to Section XI, Definitions and concepts, Table 3 in the 2010 SCPC results paper for definitions of adoption for payment instruments, bank accounts, and payment technologies. Table 1 contains more detailed definitions of banking concepts listed above. Payment cards In the 2010 SCPC, respondents were asked about three types of credit cards and four types of prepaid cards. Variables containing disaggregated information for each type of card have names with the following mnemonics (indicating card type) following the respective mnemonic for the card. Pages 21–23 of the questionnaire define these card types in greater detail. gp General purpose (used with cc, svc) charge Charge cards (used with cc) – balance has to be paid in full at the end of each billing period branded Branded cards (used with cc) – having a merchant’s logo on it, e.g.: Sears card, Amazon.com card specific Specific purpose (used with svc) – to be used with a specific merchant, or public transportation cards 7 payroll Cards containing wages or salary (used with svc) ebt Electronic benefits transfer – cards containing government benefits (used with svc) Examples: • cc_gp_rewards_num: the number of general purpose credit cards bearing rewards • cc_gp_num: the number of general purpose credit cards • cc_rewards_num: the number of rewards cards. Payment use For each payment instrument and seven transaction types, respondents are asked to report their payment use behavior—how frequently they use a payment instrument for a specific transaction type. Therefore, at the most disaggregated level, a payment use variable name consists of three mnemonic components: the payment instrument, followed by the transaction type, ending with a suffix that indicates the type of payment use information (incidence of use, frequency of use, and share of all transactions made). The two tables below list the mnemonics for the transaction types and the information type. Transaction types abp Automatic bill payment obp Online bill payment ipbp In-person bill payment (or via mail) bp Bill payment i.e. sum of abp, obp, ipbp op Online (non-bill) payments rp Retail payments (made in-person) serv Services and other payments (in-person) p2p Person-to-person payment pos Point-of-sale payment (sum of rp and serv) servp2p Sum of service and p2p payments posp2p All in-person (non-bill) payments, i.e. sum of rp, serv and p2p 8 Note: For definitions of these transaction types, please see Section XI, Table 5 in the 2010 SCPC results paper and the question text on pages 28-35 of the 2010 SCPC questionnaire. Types of payment use information: typ Number of transactions in a typical month t_m Respondent makes the corresponding type of payment at least once in a typical month (Y/N) t_y Respondent makes the corresponding type of payment at least once in a typical year (Y/N) sh Number of transactions in a typical month, as proportion of all payments Note: For definitions of these categories of payment use, please see Section XI, Table 4 in the 2010 SCPC results paper. Examples: • csh_serv_typ: number of payments made for a service or other non-retail transaction using cash in a typical month • obbp_obp_typ: number of online bill payments made using online banking bill payment in a typical month • dc_op_t_y: dummy variable indicating whether respondent uses a debit card to make an online (non-bill) payment in a typical year These variables which represent payment instrument and transaction type level of payments can be aggregated by payment instrument, by transaction type, or by groups of payment instruments or transaction types. For example: • abp_typ: number of automatic bill payments in a typical month • posp2p_typ: number of in-person transactions made in a typical month • chk_typ: number of payments made using checks in a typical month • elect_typ: number of payments made using any of the electronic payment instruments in a typical month 9 Although these examples all use _typ, corresponding dummy variables exist with _t_m or _t_y suffixes. Please note that not all combinations of payment instruments and transaction types exist. This is because they were assumed not to be possible at the time of the survey. The following table illustrates combinations that do exist in the data and the corresponding combinations of mnemonic prefixes: bp op posp2p rp servp2p pos† abp obp ipbp op rp serv p2p csh_rp csh_serv csh_p2p csh csh_ipbp chk chk_ipbp chk_op chk_rp chk_serv chk_p2p mon mon_ipbp mon_op mon_rp mon_serv mon_p2p tc tc_ (not asked by transaction type) dc dc_abp dc_obp dc_ipbp dc_op dc_rp dc_serv dc_p2p cc cc_abp cc_obp cc_ipbp cc_op cc_rp cc_serv cc_p2p svc_ipbp svc_op svc_rp svc_serv svc obbp obbp_abp obbp_obp banp banp_abp banp_obp income income_abp obbp_p2p banp_op banp_p2p † For comparison with 2008 SCPC data, pos = rp + serv * Although respondents may have automatic bill payments directly deducted from their paycheck, “income” is not treated as a payment instrument and is excluded from the assessments of payment characteristics. The variable tot_pay_typ is defined for each respondent as the sum of all payments made in a typical month. The share variables “_sh” express the original “typ” variable as a proportion of tot_pay_typ for that respondent. The tables in the 2010 SCPC results paper describing payment shares are not computed using these individually defined variables. Instead, each share denotes the total number of transactions falling under that category as a proportion of all reported transactions, aggregated over all respondents. This differs slightly from taking means of the _sh variables defined in this document: it weights respondents who have a large number of transactions more heavily than respondents who have a smaller number of transactions. 10 Number of payment instruments In addition to being used as a suffix, the mnemonic “num” is also used as a prefix, to indicate the number of payment instruments, or groups of payment instruments. Examples: • num_pi_adopt: number of payment instruments adopted by respondent • num_pi_t_m: number of payment instruments used in a typical month • num_paper_bp_t_y: number of paper instruments used for bill payments in a typical year (Note that from the table above, this variable can only take the values 0, 1, 2, or 3.) • num_op_t_m: number of payment instruments used for online payments in a typical month • num_card_t_m: number of payment instruments of the card group (cc, dc, svc) used in a typical month Cash use The SCPC includes a number of questions specifically on where respondents get cash, how often they get cash, and what amounts of cash they obtain most often. The following mnemonics are all used exclusively with the prefix “csh”: get Respondent gets cash in a typical month or year from the source indicated in the suffix that follows (see cash sources below) amnt Dollar amount of cash per withdrawal freq Frequency of cash withdrawals month Total dollar amount of cash got in a typical month wallet Amount of cash kept on person (in a purse, wallet or pocket) house Amount of cash kept in respondent’s home or on their property. Cash sources: atm ATM bankteller Bank teller checkstore Check cashing store 11 retail Cash back at the retail point of sale employer Directly from an employer family A friend or family member other Some other source of cash Examples: • csh_get_checkstore equals 1 if respondent reports that a check cashing store is their most common source of cash • csh_freq_retail: The number of times in a typical month that respondent gets cash from cash back at the retail point of sale • csh_wallet: The amount of cash respondent keeps on her/his person The following variables are related to cash use, but do not use the mnemonics above. • csh_amnt_1st: Amount of cash withdrawn from primary source of cash • csh_freq_1st: Frequency of cash withdrawals from primary source of cash • csh_month_1st: Total amount of cash withdrawn from primary source in a typical month These variables can also be found with the suffix “2nd” instead of “1st”. The suffix 2nd means cash from all other sources besides primary source. Variables defined conditional on adoption Some tables in the 2010 SCPC results paper include statistics that are calculated conditional on the adoption of a bank account, a certain payment instrument, or other payment technology. Separate variables were created to facilitate this calculation for the tables; these variables all end with the suffixes “_adopt_only”, indicating the conditional coding of the underlying variable. Such variables contain missing values (rather than zeros) for non-adopters of the respective account/instrument/technology. Flags Some variables are cleaned based on outlier analysis done by the staff of the CPRC at the Boston Fed. All variables of the form “f_” followed by a variable name are flags for the corresponding variables, with a value of 1 indicating that the particular observation was identified as an outlier and cleaned by the CPRC. 12 Non-mnemonic variables Identifiers prim_key Unique respondent identifier The variable prim_key is of the form xyyzzzz:n or xxyyzzzz:n (for 2010 onward), where x or xx is year (9 for 2009, 10 for 2010, e.g.), yy is month (08 for august, e.g.), and zzzz is a household identifier within that year/month. xyyzzzz and xxyyzzzz are the unique household identifier. The number to the right of the colon is the member id (1, 2, ..., n) for a panel member inside a household. It is assigned in the order that the respondent entered the survey; only respondents with memberid equal to 1 were originally recruited from the University of Michigan’s Survey of Consumers or the Face to Face Internet Survey Platform. Those with member id numbers of 2 or greater are household members of the original recruits. Weights r_weight Post-stratification weights - from a raking procedure Demographic variables age Age cellphone Have cell phone (Y/N) edu_lhs Education: less than high school (Y/N) edu_hs Education: high school (Y/N) edu_sc Education: some college (Y/N) edu_c Education: college (Y/N) edu_pgs Education: post-graduate studies (Y/N) white Race: white (Y/N) black Race: black/African American (Y/N) asian Race: Asian (Y/N) other Race: Other (Y/N) latino Ethnicity: Latino or Hispanic (Y/N) male Male (Y/N) inc_lt25 Household income: under $25,000 per year (Y/N) inc_2549 Household income: $25,000-49,999 per year (Y/N) inc_5074 Household income: $50,000-74,999 per year (Y/N) 13 inc_7599 Household income: $75,000-99,999 per year (Y/N) inc_100124 Household income: $100,000-124,999 per year (Y/N) inc_125199 Household income: $125,000-199,999 per year (Y/N) inc_gt200 Household income: Greater than $200,000 per year (Y/N) married Marital status: married (Y/N) separated Marital status: separated (Y/N) widowed Marital status: widowed (Y/N) single Marital status: single (Y/N) working_now Currently working (Y/N) unemployed Unemployed and looking for employment (Y/N) temp_laid_off Temporarily laid off, on sick leave, or other leave (Y/N) disabled Disabled (Y/N) retired Retired (Y/N) homemaker Homemaker (Y/N) job_other Current job status: Other (Y/N) house_market_value Market value of primary home (in 1000’s of USD) non_house_assets Value of assets besides primary home (in 1000’s of USD) non_house_debts All debt excluding amount owed on mortgage (in 1000’s of USD) loans_house Outstanding balance on all loans for your primary home Bank account adoption chk_acnt_inst Type of financial institution for primary checking account (See pa006 in questionnaire) chk_acnt_interest Primary checking account pays interest (Y/N) sav_acnt_inst Type of financial institution for primary savings account (See pa007 in questionnaire) chk_overdraft_adopt Does checking account have overdraft protection? (See 14 pa005 in questionnaire) no_chk_acnt_reason_1 - _7 Y/N variables corresponding to each reason for not having a checking account (see item pa002 in the 2010 SCPC questionnaire) Other variables cc_debt_revolver Does the respondent revolve their credit card balance? cc_debt_amnt The unpaid balance on all of last month’s credit card bills. See pu010. cc_debt_adopter_amnt The unpaid balance on all of last month’s credit card bills for adopters of credit cards only. cc_debt_revolver_amnt The unpaid balance on all of last month’s credit card bills for balance revolvers only. cc_balance_much_lower Unpaid balance last month compared to unpaid balance 12 months ago: much lower cc_balance_lower Unpaid balance last month compared to unpaid balance 12 months ago: lower cc_balance_same Unpaid balance last month compared to unpaid balance 12 months ago: same cc_balance_higher Unpaid balance last month compared to unpaid balance 12 months ago: higher cc_balance_much_higher Unpaid balance last month compared to unpaid balance 12 months ago: much higher svc_reload_oadopt_amnt Typical dollar amount per prepaid card reloading svc_reload_oadopt_freq Number of prepaid card reloading in a typical month svc_reload_total_amnt Total dollar amount of prepaid card reloading in a typical month svc_reload_amnt Amount respondent adds most often to the prepaid card that is most often reloaded (see pa029) svc_reload_csh Prepaid card most commonly reloaded using: cash (see pa101) 15 svc_reload_cc Prepaid card most commonly reloaded using: credit card (see pa101) svc_reload_chk Prepaid card most commonly reloaded using: check (see pa101) svc_reload_income Prepaid card most commonly reloaded directly from income (see pa101) svc_reload_dc Prepaid card most commonly reloaded using: debit card (see pa101) svc_reload_other Prepaid card most commonly reloaded using something besides the options above (see pa101) email_bnk_acnt Ever disclosed online: bank account number email_cc Ever disclosed online: credit card number email_dc Ever disclosed online: debit card number email_maiden Ever disclosed online: mother’s maiden name email_ssn Ever disclosed online: social security number credit_sc_u600 Credit score: less than 600 credit_sc_600649 Credit score: 600-649 credit_sc_650700 Credit score: 650-699 credit_sc_700749 Credit score: 700-749 credit_sc_750799 Credit score: 750-800 credit_sc_o800 Credit score: greater than 800 credit_sc_dk Credit score: don’t know fin_diff_lostjob Financial difficulties in last 12 months: respondent or household member lost their job (see ph009) fin_diff_bankruptcy Financial difficulties in last 12 months: respondent declared bankruptcy (see ph009) fin_diff_foreclosure Financial difficulties in last 12 months: mortgage foreclosure on respondent’s primary home (see ph009) fin_diff_cc_closed Financial difficulties in last 12 months: credit card account closed or frozen (see ph009) fin_diff_7_bankruptcy Financial difficulties in last 7 years: respondent declared bankruptcy(see ph020) fin_diff_7_foreclosure Financial difficulties in last 7 years: mortgage foreclosure 16 on respondent’s primary home (see ph020) frugal_coupon During past 12 months: respondent used coupons frugal_rebate During past 12 months: respondent used a mail-in rebate frugal_wholesale During past 12 months: respondent shopped at a wholesale club frugal_paycash During past 12 months: respondent paid in cash in order to receive a discount taxes_computer Preparation of 2008 federal income tax return: respondent, using tax computer software (see ph014) taxes_paper Preparation of 2008 federal income tax return: respondent, by hand, on a paper tax return (see ph014) taxes_family Preparation of 2008 federal income tax return: a family member, household member, or friend (see ph014) taxes_company Preparation of 2008 federal income tax return: a tax service company (see ph014) taxes_accountant Preparation of 2008 federal income tax return: respondent’s accountant or financial planner (see ph014) taxes_none Preparation of 2008 federal income tax return: respondent has never submitted a federal tax return (see ph014) taxes_other Preparation of 2008 federal income tax return: other (see ph014) inflation_actual Respondent’s estimate of actual inflation during the previous 12 months inflation_expected Respondent’s estimate of expected inflation during the subsequent 12 months internet_access Does respondent have access to the internet for personal use at home, work or another location? internet_home Where respondent has access to internet: at home internet_work Where respondent has access to internet: at work internet_other Where respondent has access to internet: at another location 17 Frequency converted payment use variables pa018_1 How often respondent gets cash – 1st ranked location, aggregated to monthly frequency pa018_2 How often respondent gets cash – 2nd ranked location, aggregated to monthly frequency pa023 How often respondent reloads svc, aggregated to monthly frequency svc_reload_freq How often respondent reloads svc, aggregated to monthly frequency (see pa023, cleaned outliers) pu002_a Total number of abp made using dc, aggregated to monthly frequency pu002_b Total number of abp made using cc, aggregated to monthly frequency pu002_c Total number of abp made using banp, aggregated to monthly frequency pu002_d Total number of abp made using income, aggregated to monthly frequency pu002_e Total number of abp made using obbp, aggregated to monthly frequency pu003_a Total number of obp made using dc, aggregated to monthly frequency pu003_b Total number of obp made using cc, aggregated to monthly frequency pu003_c Total number of obp made using banp, aggregated to monthly frequency pu003_d Total number of obp made using obbp, aggregated to monthly frequency pu004_a Total number of ipbp made using cash, aggregated 18 to monthly frequency pu004_b Total number of ipbp made using chk, aggregated to monthly frequency pu004_bmo Total number of ipbp made using mon, aggregated to monthly frequency pu004_c Total number of ipbp made using dc, aggregated to monthly frequency pu004_d Total number of ipbp made using cc, aggregated to monthly frequency pu004_e Total number of ipbp made using svc, aggregated to monthly frequency pu005_a Total number of op made using chk, aggregated to monthly frequency pu005_amo Total number of op made using mon, aggregated to monthly frequency pu005_b Total number of op made using dc, aggregated to monthly frequency pu005_c Total number of op made using banp, aggregated to monthly frequency pu005_d Total number of op made using cc, aggregated to monthly frequency pu005_e Total number of op made using svc, aggregated to monthly frequency pu006a_a Total number of rp made using cash, aggregated to monthly frequency pu006a_b Total number of rp made using chk, aggregated to monthly frequency pu006a_bmo Total number of rp made using mon, aggregated to monthly frequency pu006a_c Total number of erp made using dc, aggregated to 19 monthly frequency pu006a_d Total number of rp made using cc, aggregated to monthly frequency pu006a_e Total number of rp made using svc, aggregated to monthly frequency pu006c_a Total number of serv made using cash, aggregated to monthly frequency pu006c_b Total number of serv made using chk, aggregated to monthly frequency pu006_bmo Total number of serv made using mon, aggregated to monthly frequency pu006c_c Total number of serv made using dc, aggregated to monthly frequency pu006c_d Total number of serv made using cc, aggregated to monthly frequency pu006c_e Total number of serv made using svc, aggregated to monthly frequency pu021_a Total number of p2p made using csh, aggregated to monthly frequency pu021_b Total number of p2p made using chk, aggregated to monthly frequency pu021_bmo Total number of p2p made using mon, aggregated to monthly frequency pu021_c Total number of p2p made using dc, aggregated to monthly frequency pu021_d Total number of p2p made using cc, aggregated to monthly frequency pu021_e Total number of p2p made using banp, aggregated to monthly frequency pu021_f Total number of p2p made using obbp, aggregated 20 to monthly frequency pu008_c Total number of payments made using tc, aggregated to monthly frequency Unrandomized variables as003a1 Rating for security of cash, equivalent to csh_security as003a2 Rating for acceptance of cash, equivalent to csh_acceptance as003a3 Rating for cost of cash, equivalent to csh_cost as003a4 Rating for convenience of cash, equivalent to csh_convenience as003a5 Rating for getting and setting up of cash, equivalent to csh_setup as003a6 Rating for payment records of cash, equivalent to csh_records as003b1–as003b6 Same characteristics as above, except for check as003c1–as003c6 Same characteristics as above, except for debit card as003d1–as003d6 Same characteristics as above, except for credit card as003e1–as003e6 Same characteristics as above, except for prepaid card as003f1–as003f6 Same characteristics as above, except for bank account number payment as003g1–as003g6 Same characteristics as above, except for online banking bill pay ph005_a Ever entered online: Account number (Y/N) ph005_c Ever entered online: Credit card number (Y/N) ph005_d Ever entered online: Debit card number (Y/N) ph005_e Ever entered online: Mother maiden name (Y/N) ph005_g Ever entered online: Social security number (Y/N) 21 The difference between these “intermediate” frequency converted variables and the corresponding “mnemonic-based” variables is that the latter accounts for payment instrument adoption in the way missing values are coded. Payment use variables for non-adopters are adjusted to 0 instead of missing. We recommend that you use the mnemonic-based variables instead of the non-mnemonic variables wherever possible. 22