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Microdata User Guide

1. 2 53 f Since f 2 53 is less than 2 it must be concluded that there is a significant difference between the two estimates at the 0 05 level of significance 10 4 Coefficients of Variation for Quantitative Estimates For quantitative estimates special tables would have to be produced to determine their sampling error Since most of the variables for the CFCS are primarily categorical in nature this has not been done As a general rule however the coefficient of variation of a quantitative total will be larger than the coefficient of variation of the corresponding category estimate i e the estimate of the number of persons contributing to the quantitative estimate If the corresponding category estimate is not releasable the quantitative estimate will not be either For example the coefficient of variation of the total number of personal bank accounts held by women would be greater than the coefficient of variation of the corresponding proportion of women with a personal bank account Hence if the coefficient of variation of the proportion is unacceptable making the proportion not releasable then the coefficient of variation of the corresponding quantitative estimate will also be unacceptable making the quantitative estimate not releasable Coefficients of variation of such estimates can be derived as required for a specific estimate using a technique known as pseudo replication This involves dividing the records on the m
2. 50 persons in the population The weighting phase is a step which calculates for each record what this number is This weight appears on the microdata file and must be used to derive meaningful estimates from the survey For example if the number of people in Canada who do not have a personal bank account is to be estimated it is done by selecting the records referring to those individuals in the sample with that characteristic DE_Q02A 0 and summing the weights entered on those records Details of the method used to calculate these weights are presented in Chapter 11 0 7 7 Suppression of Confidential Information It should be noted that the Public Use Microdata Files PUMF may differ from the survey master files held by Statistics Canada These differences usually are the result of actions taken to protect the anonymity of individual survey respondents The most common actions are the suppression of file variables grouping values into wider categories and coding specific values into the Not stated category Users requiring access to information excluded from the microdata files may purchase custom tabulations Estimates generated will be released to the user subject to meeting the guidelines for analysis and release outlined in Chapter 9 0 of this document Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 8 0 Data Quality 8 1 Response Rates The following table summarizes the
3. and are the coefficients of variation of x and XG respectively The coefficient of variation of d is given by o d This formula is accurate for the difference between separate and uncorrelated characteristics but is only approximate otherwise Rule 4 Estimates of Ratios In the case where the numerator is a subset of the denominator the ratio should be converted to a percentage and Rule 2 applied This would apply for example to the case where the denominator is the number of women with a household budget and the numerator is the number of women with a household budget who report that they always stay within their budget In the case where the numerator is not a subset of the denominator as for example the ratio of the number of men with a household budget as compared to the number of women with a household budget the standard error of the ratio of the estimates is approximately equal to the square root of the sum of squares of each coefficient of variation considered separately multiplied by R That is the standard error of a ratio L Xx X is Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 5 2 2 o Rya a where and are the coefficients of variation of x and Ke respectively The coefficient of variation of R is given by ol R The formula will tend to overstate the error if and are positively correlated and understate the error if X and x are negatively cor
4. exceeds the funds on deposits Part Time Employment Part time employment consists of persons who usually work less then 30 hours per week at their main or only job Person Most Knowledgeable PMK The PMK is the person in the household that is most knowledgeable concerning financial issues Respondents were asked to self identify with respect to the PMK in two sections of the questionnaire Ongoing Expenses and Financial Management Registered Disability Savings Plan RDSP A plan that allows funds to be invested tax free until withdrawal It is intended to help parents and others to save for the long term financial security of a child with a disability 12 Special Surveys Division Canadian Financial Capability Survey 2009 User Guide Registered Education Savings Plans RESP A savings vehicle designed for individuals to accumulate income for post secondary education Typically the plans are entered into by parents seeking to save for their children s post secondary education Investing in RESPs can be advantageous since the federal government makes a contribution and income generated is tax sheltered until it is withdrawn for the child s post secondary education Registered Income Fund RIF A fund into which RRSP monies may be transferred Payments from a RIF may be varied but a minimum amount must be withdrawn annually Registered Retirement Savings Plan RRSP or RSP A capital accumulation program desig
5. from a complete count taken under similar conditions is called the sampling error of the estimate Errors which are not related to sampling may occur at almost every phase of a survey operation Interviewers may misunderstand instructions respondents may make errors in answering questions the answers may be incorrectly entered on the questionnaire and errors may be introduced in the processing and tabulation of the data These are all examples of non sampling errors Over a large number of observations randomly occurring errors will have little effect on estimates derived from the survey However errors occurring systematically will contribute to biases in the survey estimates Considerable time and effort was made to reduce non sampling errors in the survey Quality assurance measures were implemented at each step of the data collection and Special Surveys Division 23 24 Canadian Financial Capability Survey 2009 User Guide processing cycle to monitor the quality ofthe data These measures include cognitive testing to ensure concepts were clear extensive training of interviewers with respect to the survey procedures and computer assisted telephone interviewing CATI application observation of interviewers to detect problems of questionnaire design or misunderstanding of instructions and testing of the CATI application to ensure that range checks edits and question flow were all programmed correctly 8 2 1 Data Collection Inte
6. monitoring their interviewers and reviewing their completed documents The senior interviewers are in turn under the supervision of the program managers located in each of the Statistics Canada regional offices Special Surveys Division 19 Canadian Financial Capability Survey 2009 User Guide 7 0 Data Processing The main output of the Canadian Financial Capability Survey CFCS is a clean microdata file This chapter presents a brief summary of the processing steps involved in producing this file 7 1 Data Capture Responses to survey questions are captured directly by the interviewer at the time of the interview computer assisted telephone interviewing using a computerized questionnaire The computerized questionnaire reduces processing time and costs associated with data entry transcription errors and data transmission The response data are encrypted to ensure confidentiality and sent via modem to the appropriate Statistics Canada Regional Office From there they are transmitted over a secure line to Ottawa for further processing Some editing is done directly at the time of the interview Where the information entered is out of range too large or small of expected values or inconsistent with the previous entries the interviewer is prompted through message screens on the computer to modify the information However for some questions interviewers have the option of bypassing the edits soft edit and of skipping quest
7. occurred when the respondent did not understand or misinterpreted a question refused to answer a question or could not recall the requested information In order to provide complete data concerning the distribution of personal and household income among sampled units values were imputed when these were missing All imputations involved donors that were selected using a score function For each item non response or partial non response records also called recipient records certain characteristics were compared to characteristics from all the donors When the characteristics were the same between a donor and the recipient a value was added to the score of that donor The donor with the highest score was deemed the closest donor and was chosen to fill in missing pieces of information of the non respondents If there was more than one donor with the highest score a random selection occurred The pool of donors was made up in such a way that the imputed value assigned to the recipient in conjunction with other non imputed items from the recipient would still pass the edits Imputation of personal and household incomes was performed together whenever necessary and then always from the same donor The following table shows the imputation rate for each of the variables where applicable Special Surveys Division Canadian Financial Capability Survey 2009 User Guide In total almost 10 000 respondents 63 were eligible donors hav
8. t ON e arera eaaa re ev 24 8 22 Data ProCOSSING vicereasiniceceatucersaccedcecaetiteredscedeccee2 cedeecnelotenedecedecanectteseadcndcecueloeerecias 24 8 2 3 Non response uuununnenuunannnnnnnunnnnnnnannnnnnnannnnnnnnannnnnnnannnnnnn ia aar iaai an nnnnen anne nn 24 8 2 4 Measurement of Sampling Error ccoo 25 Guidelines for Tabulation Analysis and Release unsunssasnnnnnansnnnnnnnannnnnnnnnnnnnnnnannnnnnnnnnnannn 27 9 1 Rounding Guidelines E 27 9 2 Sample Weighting Guidelines for Tabulation uunsussnennnnnnnnnnnnnnnnnnnnnnnnnnnnnnunnnnnnnannnnnannnnnnn 27 9 3 Definitions of Types of Estimates Categorical and Quantitative unnesnnnennnnnnnnnnnnnnnnnnnennnnnn 28 o Ae D We Telela ee E 28 9 3 2 Quantitative Estimates uuunnnnnnannnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnannnnnannnnnnnnnnnnnnnannnnnnnnnnnn 28 9 3 3 Tabulation of Categorical Estimates nuunnnnnnnannnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnannnnnannnnnn 29 9 3 4 Tabulation of Quantitative Estimates nuunnnnnnnannnnnnnnnnnnnnnnnnnnnnnnnnnannnnnnnnnnannnnnannnnnn 29 9 4 Guidelines for Statistical Analysis unnsunannnnnannnnnnnnnnnnnnnannnnnnnnnnnnnnnnnnnnnnannnnnannnnnnnnnannnnnannnnnn 29 9 5 Coefficient of Variation Release Guidelines conocieran 30 9 6 Release C t Hfl s 2 ea een is 32 Special Surveys Division 3 10 0 11 0 12 0 13 0 Canadian Financial Capability Survey 2009 User Guide Approximate Sampling Variability Tables unuun
9. target population for the CFCS was all persons 18 years of age and over living in Canada with the following two exceptions 1 residents of the Yukon Northwest Territories and Nunavut and 2 full time residents of institutions Because the survey was conducted using a sample of telephone numbers households and thus persons living in households that do not have telephone land lines were excluded from the sample population This means that people without telephones and people with cell phones only were excluded People without land lines account for about 8 of the target population However the survey estimates have been weighted to include persons without land lines 5 2 Stratification In order to ensure that people from all parts of Canada were represented in the sample each of the 10 provinces were divided into strata or geographic areas Census Metropolitan Areas CMA are areas defined by the Census of Population and correspond roughly to the cities with populations of 100 000 or more Many CMAs were each considered as a separate stratum This was the case for St John s Halifax Saint John Montreal Quebec City Toronto Ottawa Hamilton Winnipeg Regina Saskatoon Calgary Edmonton and Vancouver The remaining CMAs in Ontario Quebec and British Columbia were combined into two separate strata Generally within each province a non CMA stratum was created though in Prince Edward Island there was only one stratum for the entire
10. with the letter F or some similar identifier and the following warning should accompany the estimates Please be warned that these estimates flagged with the letter F do not meet Statistics Canada s quality standards Conclusions based on these data will be unreliable and most likely invalid Special Surveys Division 31 32 Canadian Financial Capability Survey 2009 User Guide 9 6 Release Cut off s The following table provides an indication of the precision of population estimates as it shows the release cut offs associated with each of the three quality levels presented in the previous section These cut offs are derived from the coefficient of variation CV tables discussed in Chapter 10 0 For example the table shows that the quality of a weighted estimate of 15 000 people possessing a given characteristic in Newfoundland and Labrador is marginal Note that these cut offs apply to estimates of population totals only To estimate ratios users should not use the numerator value nor the denominator in order to find the corresponding quality level Rule 4 in Section 10 1 and Example 4 in Section 10 1 1 explain the correct procedure to be used for ratios Province Acceptable CV Marginal CV Unacceptable CV 0 0 to 16 5 16 6 to 33 3 gt 33 3 Newfoundland and Labrador 27 500 over 7 000 to lt 27 500 under 7 000 Prince Edward Island 13 000 8 over 3 5
11. 0 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000 10 000 12 500 15 000 20 000 NOTE ERER FEE Hette HEERE PERRE HEERE HEERE HEERE 2 2 2 2 Sue EFFE ERHE 90 52 EEEF HEEE a PERRE PERRE HEERE ARRE 97 2 EE 90 0 82 2 63 36 94 82 73 ETa 62 8 94 4 r 92 5 90 0 87 5 84 9 82 2 TO ice 73 67 52 30 81 80 78 9 13s 71 68 So 63 58 45 26 GEN els 69 67 65 63 61 SO 56 32 40 23 66 3 65 63 61 60 58 56 54 52 47 36 2 Lo 61 S 60 58 SZ 39 53x 52a S10 48 43 34 19 o ro oa o h H H PB OO Oo Ww o o oa oa aa h H NNWA UD o o to o 1 0 TEELE 2 0 14 6 1 4 153 1 2 1 1 10 0 9 0 9 0 8 0 7 KKK KKK KK KK oO OO OO oO oO OO OO H for correct usage of these tables please refer to microdata documentation Example 3 Estimates of Differences Between Aggregates or Percentages Suppose that a user estimates that that 2 478 643 7 055 176 35 1 of women with a household budget report that they always stay within their budget while 2 402 986 6 178 565 38 9 of men with a household budget report that they always stay within their budget How does the user determine the coefficient of variation of the difference between these two estimates 1 Using the CANADA coefficient of variation table in the same manner as described in Example 2 gives the CV of the estimate for women as 3 0 and the CV of the estimate f
12. 0 4 78 1 75 8 73 4 70 9 68 3 65 7 59 9 46 4 26 8 KEE 73 0 71 5 69 6 67 7 65 7 63 6 61 4 59 2 56 9 51 9 40 2 23 2 SE 65 3 64 0 62 3 60 5 58 7 56 9 54 9 52 9 50 9 46 4 36 0 20 8 GE 59 6 58 4 56 9 55 3 53 6 51 9 50 1 48 3 46 4 42 4 32 8 19 0 BES 54 9 54 1 52 6 51 2 49 6 48 1 46 4 44 7 43 0 39 2 30 4 100 14 3 13 9 13 5 13 1 12 7 12 3 11 8 11 4 10 4 8 0 125 12 8 12 5 12 1 11 7 11 4 11 0 10 6 10 2 9 3 7 2 150 ee 11 4 11 1 10 7 10 4 10 0 9 7 9 3 8 5 6 6 200 er 9 8 9 6 9 3 9 0 8 7 8 4 8 0 7 3 5 7 250 ae 8 8 8 6 8 3 8 0 7 8 75 7 2 6 6 5 1 300 Ke 7 8 7 6 7 3 7 1 6 8 6 6 6 0 4 6 350 RER 7 2 7 0 6 8 6 6 6 3 6 1 5 5 4 3 400 Fan 6 8 6 6 6 4 6 1 5 9 5 7 5 2 4 0 450 Re 6 2 6 0 5 8 5 6 5 4 4 9 3 8 500 Keen SH 5 9 5 7 5 5 5 3 5 1 4 6 3 6 750 KEN ee 4 5 4 3 4 2 3 8 2 9 1 000 Anen DE Kerr RRE 3 6 33 25 1 500 DEET ETH DTD STE DTD DTD 21 2 000 RK DTD DTD AAR DT DTD DST NOTE for correct usage of these tables please refer to microdata documentation 10 2 How to Use the Coefficient of Variation Tables to Obtain Confidence Limits Although coefficients of variation are widely used a more intuitively meaningful measure of sampling error is the confidence interval of an estimate A confidence interval constitutes a statement on the level of confidence that the true value for the population lies within a specified range of values For example a 95 confidence interval can be described as follows If sampling of the population is repeated indefinitely each
13. 00 to lt 13 000 under 3 500 Nova Scotia 43 000 amp over 11 000 to lt 43 000 under 11 000 New Brunswick 46 000 amp over 12 000 to lt 46 000 under 12 000 Quebec 93 000 amp over 23 000 to lt 93 000 under 23 000 Ontario 113 500 over 28 000 to lt 113 500 under 28 000 Manitoba 52 500 A over 13 500 to lt 52 500 under 13 500 Saskatchewan 33 000 amp over 8500 to lt 33 000 under 8 500 Alberta 77 000 amp over 19 500 to lt 77 000 under 19 500 British Columbia 129 500 amp over 32 500 to lt 129 500 under 32 500 Canada 99 000 amp over 24 500 to lt 99 000 under 24 500 Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 10 0 Approximate Sampling Variability Tables In order to supply coefficients of variation CV which would be applicable to a wide variety of categorical estimates produced from this microdata file and which could be readily accessed by the user a set of Approximate Sampling Variability Tables has been produced These CV tables allow the user to obtain an approximate coefficient of variation based on the size of the estimate calculated from the survey data The coefficients of variation are derived using the variance formula for simple random sampling and incorporating a factor which reflects the multi stage clustered nature of the sample design This factor known as the design effect was determined by first calculating design effects for a wide range of characteristics and
14. 1 First of all this estimate is a ratio estimate where the numerator of the estimate X is the number of women with a household budget who report that they always stay within their budget The denominator of the estimate X is the number of men with a household budget who report that they always stay within their budget 2 Refer to the coefficient of variation table for CANADA 3 The numerator of this ratio estimate is 2 478 643 The figure closest to it is 2 000 000 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row namely 3 5 4 The denominator of this ratio estimate is 2 402 986 The figure closest to it is 2 000 000 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row namely 3 5 5 So the approximate coefficient of variation of the ratio estimate is given by Rule 4 which is 2 2 Qg la a where a and are the coefficients of variation of X and x respectively That is Special Surveys Division 37 Canadian Financial Capability Survey 2009 User Guide a 0 035 0 035 0 001225 0 001225 0 049 6 The obtained ratio of women versus men with a household budget who report that they always stay within their budget is 2 478 643 2 402 986 which is 1 03 to be rounded according to the rounding guidelines in Section 9 1 The coefficient of variation of this estimat
15. 13 233 741 36 9 of Canadian adults with a household budget report that they always stay within this budget How does the user determine the coefficient of variation of this estimate 1 Refer to the coefficient of variation table for CANADA 2 Because the estimate is a percentage which is based on a subset of the total population i e adults with a household budget it is necessary to use both the percentage 36 9 and the numerator portion of the percentage 4 881 629 in determining the coefficient of variation Special Surveys Division 35 36 3 Canadian Financial Capability Survey 2009 User Guide The numerator 4 881 629 does not appear in the left hand column the Numerator of Percentage column so it is necessary to use the figure closest to it namely 5 000 000 Similarly the percentage estimate does not appear as any of the column headings so it is necessary to use the percentage closest to it 35 0 The figure at the intersection of the row and column used namely 1 9 is the coefficient of variation to be used So the approximate coefficient of variation of the estimate is 1 9 The finding that 36 9 of adults with a household budget report that they always stay within their budget can be published with no qualifications Canadian Financial Capability Survey 2009 Approximate Sampling Variability Tables Canada All Ages NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 0 1 1 0 5 0 10 0 15 0 2
16. 18 years and older in Census Metropolitan Areas The method called generalized regression GREG estimation was used to modify the weights to ensure that the survey estimates agreed with the external totals simultaneously along the two dimensions The person weights obtained after this step were considered final and appear on the microdata file Special Surveys Division 47 Canadian Financial Capability Survey 2009 User Guide 12 0 Questionnaires The Canadian Financial Capability Survey CFCS questionnaire was used in 2009 to collect information for the survey The file CFCS2009_QuestE pdf contains the English questionnaire Special Surveys Division 49 Canadian Financial Capability Survey 2009 User Guide 13 0 Record Layout with Univariate Frequencies See CFCS2009_CdBk pdf for the record layout with univariate frequencies Special Surveys Division 51
17. Microdata User Guide Canadian Financial Capability Survey 2009 Bai og Soe Canada Canadian Financial Capability Survey 2009 User Guide Table of Contents 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 INTO UCTION NEEN SEENEN EES R RETAS NESA iii 5 Background WEE 7 Objectives ue EE 9 Concepts and DeTINIIONS geg ates ecueestedesutueeacadeedserecedexcducerstnesecnatie 11 SUrvey E Oe Le e E 15 5 1 Population Coverage E 15 5 2 Stratification e 5 Ar E SEENEN ne ren Een 15 5 3 Sample Design and Allocation uuunsnnsunannnnnnnnnnnnnnnnnnnnnannunnannnnnnnnnnannnnnannnnnnnnnnnnnnnannnnnannnnnn 15 5 4 ue e E 15 5 5 ell SIE 16 5 6 Questionnaire Structure EE 16 Data Collection aa 19 6 1 Questionnaire Design cocoa 19 6 2 la e DE 19 6 3 Supervision and Quality Control uunensnnannnnnnnnnnnnnnnnnnnnnannnnnannnnnnnnnnannnnnannnnnannnnnnnnnannnnnannnnnn 19 Data Processing dd 21 7 1 Data a Ee ES GEESS EN 7 2 dng ege EA 7 3 Coding of Open ended Questions unnnunannnnnnnnnnnnnnnnnnnnnnnnnnnannnnnnnnnnannnnnannnnnannnnnnnnnannnnnannnnnn 21 7 4 A sdsGuectsacosuectusecqcessisauecssdeuuces A 22 7 5 Creation of Derived Variables unnuunnnnsnnannnnnnnnnnnnnnnnnnnnnannnnnannnnnnnnnnannnnnnnnnnnnnnnnnnnnnannnnnannnnnn 22 7 6 Een EE 22 7 7 Suppression of Confidential Information uuesuunneansnnnnnnnannnnnannnnnnnnnnnnnnnnnnunnnnnnnnnnnnnannnnnannnnnn 22 Data o TUTE 23 8 1 O 2 2 nl 23 8 2 A AO 23 82 1 Data Colle
18. X Y 9 3 4 Tabulation of Quantitative Estimates Estimates of quantities can be obtained from the microdata file by multiplying the value of the variable of interest by the final weight for each record then summing this quantity over all records of interest For example to obtain an estimate of the total number of personal bank accounts held by adult women in Canada multiply the value reported in question OE_Q02A number of personal chequing or savings accounts by the final weight for the record then sum this value over all records with SEX 2 female To obtain a weighted average of the form X Y the numerator x is calculated as for A a quantitative estimate and the denominator Y is calculated as for a categorical estimate For example to estimate the average number of personal bank accounts held by women A a estimate the total number of personal bank accounts X as described above A b estimate the women in Canada Y in this category by summing the final weights of all records with SEX 2 then c divide estimate a by estimate b X Y 9 4 Guidelines for Statistical Analysis The CFCS is based upon a complex sample design with stratification multiple stages of selection and unequal probabilities of selection of respondents Using data from such complex surveys presents problems to analysts because the survey design and the selection probabilities affect the estimation and variance calculation proce
19. ach telephone number had a flag indicating whether it was expected to be a residential business or unknown type of telephone number and a flag indicating whether or not it was screened out before collection as a non working or business number The adjustment for the unresolved telephone numbers was done within province the expected line type and whether or not the number was sent to the field For each province expected line type sent EE gt W for resolved telephone numbers SW forunresolved telephone numbers KEN SW for resolved telephone numbers 3 Remove out of scope telephone numbers Telephone numbers corresponding to businesses out of service numbers or out of scope numbers such as cottage telephone numbers were dropped after the non resolved adjustment had been applied Note that if household or person data existed then the telephone number was assumed to be a household There were 38 040 out of scope telephone numbers and 25 231 telephone numbers belonging to a household Special Surveys Division 45 46 Canadian Financial Capability Survey 2009 User Guide 4 Adjust for non response of number of telephone lines in the household The number of telephone lines in the household was calculated If the number of different telephone lines within the household could not be calculated but household or person data existed then it was imputed as one in order to retain good data After imputation there were 7 384 telephone
20. an gc ca rdc cdr bootvar_sas eng htm SPSS http www statcan gc ca rdc cdr bootvar_spss eng htm Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 11 0 Weighting For the microdata file statistical weights were placed on each record to represent the number of sampled persons that the record represents One weight was calculated for each responding person The weighting for the Canadian Financial Capability Survey CFCS consisted of several steps calculation of a basic weight adjustments for non response dropping out of scope records an adjustment for selecting one individual in the household and finally an adjustment to make the populations estimates consistent with known province age sex totals from the Census projected population counts for persons 18 years and over 11 1 Weighting Procedures 1 Calculate telephone weight Each telephone number in the sample was assigned a basic weight W equal to the inverse of its probability of selection W Total number of possible sampled telephone numbers in province i Number of sampled telephone numbers in province There were 68 462 telephone numbers in the sample with assigned weights 2 Adjust for non resolved telephone numbers There were 5 191 telephone numbers that were not resolved leaving 63 271 resolved telephone numbers The unresolved telephone numbers were not determined to belong to a household business or out of scope E
21. based on Don t know or Refusal all skipped questions are set to Not stated 9 99 999 etc The remaining empty items are filled with a numeric value 9 99 999 etc depending on variable length These codes are reserved for processing purposes and mean that the item was Not stated 7 3 Coding of Open ended Questions A few data items on the questionnaire were recorded by interviewers in an open ended format This typically occurs when a respondent selects the Other Specify response to a question In these instances the responses are reviewed to determine if they should be allocated to one of the pre existing categories be joined with other similar responses to create a new category or whether they remain as just Other Special Surveys Division 21 Canadian Financial Capability Survey 2009 User Guide 22 7 4 Imputation Imputation is the process that supplies valid values for those variables that have been identified for a change either because of invalid information or because of missing information The new values are supplied in such a way as to preserve the underlying structure of the data and to ensure that the resulting records will pass all required edits In other words the objective is not to reproduce the true microdata values but rather to establish internally consistent data records that yield good aggregate estimates We can distinguish between three types of non response Comp
22. be determined If this number is less than 30 the weighted estimate should be considered to be of unacceptable quality For weighted estimates based on sample sizes of 30 or more users should determine the coefficient of variation of the estimate and follow the guidelines below These quality level guidelines should be applied to rounded weighted estimates All estimates can be considered releasable However those of marginal or unacceptable quality level must be accompanied by a warning to caution subsequent users Special Surveys Division Quality Level Guidelines Canadian Financial Capability Survey 2009 User Guide Quality Level of Estimate Guidelines 1 Acceptable Estimates have a sample size of 30 or more and low coefficients of variation in the range of 0 0 to 16 5 No warning is required 2 Marginal Estimates have a sample size of 30 or more and high coefficients of variation in the range of 16 6 to 33 3 Estimates should be flagged with the letter E or some similar identifier They should be accompanied by a warning to caution subsequent users about the high levels of error associated with the estimates 3 Unacceptable Estimates have a sample size of less than 30 or very high coefficients of variation in excess of 33 3 Statistics Canada recommends not to release estimates of unacceptable quality However if the user chooses to do so then estimates should be flagged
23. bility Survey that was conducted by Statistics Canada in 2009 The survey was conducted with the cooperation and support of Human Resources and Skills Development Canada Finance Canada and the Financial Consumer Agency of Canada This manual provides information on the objectives methodology and estimation procedures as well as the guidelines for releasing estimates based on the survey Contained within this package are the questionnaire and approximate variance tables with examples of their use Any question about the data set or its use should be directed to Statistics Canada Client Services Special Surveys Division Telephone 613 951 3321 or call toll free 1 800 461 9050 Fax 613 951 4527 E mail ssd statcan gc ca Special Surveys Division 5 Canadian Financial Capability Survey 2009 User Guide 2 0 Background This is the first Canadian Financial Capability Survey CFCS The need for this survey has been brought about by changing economic conditions the variety and complexity of financial products available and the need to establish baseline data The CFCS was conducted between February and May 2009 with the objective to develop a statistical database providing estimates surrounding the issues of financial capability The intention of the survey is to collect information that will illuminate the degree of knowledge that Canadians have concerning financial decision making Specifically the survey will shed light on Canad
24. d SEX men 3 for each ofthese respondents calculate a RESCALED weight equal to the original person weight divided by the AVERAGE weight 4 perform the analysis for these respondents using the RESCALED weight However because the stratification and clustering of the sample s design are still not taken into account the variance estimates calculated in this way are likely to be under estimates The calculation of more precise variance estimates requires detailed knowledge of the design of the survey Such detail cannot be given in this microdata file because of confidentiality Variances that take the complete sample design into account can be calculated for many statistics by Statistics Canada on a cost recovery basis 9 5 Coefficient of Variation Release Guidelines Before releasing and or publishing any estimates from the CFCS users should first determine the quality level of the estimate The quality levels are acceptable marginal and unacceptable Data quality is affected by both sampling and non sampling errors as discussed in Chapter 8 0 However for this purpose the quality level of an estimate will be determined only on the basis of sampling error as reflected by the coefficient of variation as shown in the table below Nonetheless users should be sure to read Chapter 8 0 to be more fully aware of the quality characteristics of these data First the number of respondents who contribute to the calculation of the estimate should
25. dit account LOC A formal agreement between a borrower and a lender usually a financial institution which allows the borrower to borrow as much or as little as they wish up to a pre specified maximum or credit limit For purposes of the survey the amount to be reported is the amount currently owing on the line of credit Mortgage Any loan that uses a home or other real estate as collateral Mutual Funds A collection of numerous financial securities that are bought by an investment company and sold as a particular group or fund Investors purchase units of these funds Net Value Value that results from deducting operating costs from price Not in the Labour Force Persons not in the labour force are those who during the reference week were unwilling or unable to offer or supply labour services under conditions existing in their labour markets that is they were neither employed nor unemployed Occupation The Canadian Financial Capability Survey provides information about the occupation attachment of employed and unemployed persons and of persons not in the labour force who have held a job in the past 12 months These codes sets are based on the National Occupational Classification Statistics NOC S 2006 Old Age Security Pension OAS A monthly benefit available to most Canadians 65 years of age or older who have lived in Canada for at least 10 years Overdraft The amount by which a cheque or other payments
26. dures that should be used In order for survey estimates and analyses to be free from bias the survey weights must be used While many analysis procedures found in statistical packages allow weights to be used the meaning or definition of the weight in these procedures may differ from that which is appropriate in a sample survey framework with the result that while in many cases the estimates produced by the packages are correct the variances that are calculated are poor Approximate variances for simple estimates such as totals proportions and ratios for qualitative variables can be derived using the accompanying Approximate Sampling Variability Tables For other analysis techniques for example linear regression logistic regression and analysis of variance a method exists which can make the variances calculated by the standard packages more meaningful by incorporating the unequal probabilities of selection The method rescales the weights so that there is an average weight of 1 Special Surveys Division 29 Canadian Financial Capability Survey 2009 User Guide For example suppose that analysis of all male respondents is required The steps to rescale the weights are as follows 1 select all respondents from the file who reported SEX men 2 calculate the AVERAGE weight for these records by summing the original person weights from the microdata file for these records and then dividing by the number of respondents who reporte
27. e is 4 9 which makes the estimate releasable with no qualifications Canadian Financial Capability Survey 2009 Approximate Sampling Variability Tables Canada All Ages NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 FEER PERE HEERE HEERE HERRE HERPE EREE AAA 52 MAA 2 2 2 2 HEERE HEERE HERRE HERPE PERHE 2 2 2 2 97 2 GELAT 90 0 82 2 63 36 94 8 94 4 93 9 92 5 90 0 87 5 84 9 82 2 TB Ho Tess 67 32 30 82 81 81 80 78 19 73 Plz 68 66 63 58 45 26 13 Ti 72 sl 69 67 65 63 61 SA SG 52 40 23 67 66 66 65 63 61 60 58 56 54 925 47 36 21 62 61 61 60 y TN D5 53 32 0 48 43 34 19 750 xx 1 000 1 500 2 000 3 000 x x 4 000 5 000 6 000 7 000 x 8 000 e e AKKKR a N N HMD Lu e u e u Abo o o o h HM We q D H h H M Lu PB u o ou b i N mb o o vw N UEP DAW CO m 9 000 x e AKKKR a o o too to b H d s A t PU o A vw o BF ORNO D o o ta oa ta oa ta bb WU 10 000 S e ok KKK FRPP o oo to h NND WR 8 WW PB OD OO WO WO DD CO Ab Ab OD o o o AOI N D 125 500 Fee S e kK KKK m 15 000 x x e e AKKKR KK KKK KKK KK SS E D OD OD o o AJ DON WH WL 3 3 2 8 23 2 0 1 6 1 4 1 3 Le ES 1 0 0 9 0 9 0 8 0 7 KKK oO OO OO OO oO oO oO OFF BB 20 000 e e
28. ed unacceptable and Statistics Canada recommends this estimate not be released However should the user choose to do so the estimate should be flagged with the letter F or some similar identifier and be accompanied by a warning to caution subsequent users about the high levels of error associated with the estimate Canadian Financial Capability Survey 2009 Approximate Sampling Variability Tables Nova Scotia All Ages NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 1109 110 3 1086 1057 1027 997 965 932 898 863 788 610 352 0784780 768 747 726 705 682 659 635 on 557 432 249 606387 627 610 593 575 557 588 519 498 455 35 2 20 83 54 552 543 529 514 498 482 466 449 432 394 305 14 9 14 1 14 3 13 4 13 6 2 12 9 13 1 12 4 12 6 S 11 9 12 2 11 5 11 1 10 8 10 5 10 2 10 0 8 9 8 1 TTT TTT TTT for correct usage of these tables please refer to microdata documentation Special Surveys Division 39 Canadian Financial Capability Survey 2009 User Guide Canadian Financial Capability Survey 2009 Approximate Sampling Variability Tables Alberta All Ages NUMERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 146 7 146 1 143 1 1393 135 3 1313 1271 1228 1184 113 7 103 8 80 4 46 4 103 8 103 3 101 2 98 5 95 7 92 8 89 9 86 8 83 7 80 4 73 4 56 9 32 8 pee 84 3 82 6 8
29. eholds in the CFCS sample Province Sample Size Newfoundland and Labrador 1 224 Prince Edward Island 572 Nova Scotia 1 326 New Brunswick 1 213 Quebec 5 824 Ontario 8 185 Manitoba 1 427 Saskatchewan 1 976 Alberta 2 748 British Columbia 3 061 Canada 27 555 5 6 Questionnaire Structure The survey collected a large amount of data for each selected respondent as well as some information about the household Of particular interest was to identify whether the selected respondent deemed themselves the most knowledgeable person for the household s ongoing expenses and financial management This self identification occurred in both of these sections of the survey Users are referred to Chapter 12 0 of this document for a copy of the actual survey questionnaire s used Identified below are the sections of the questionnaire Introduction Control form and development of household roster The control form guides the interviewer through the opening phase of the interview and provides a shell table to build the household roster Based on the household roster an eligible household member is randomly selected to complete the survey Special Surveys Division Canadian Financial Capability Survey 2009 User Guide Demography DM This section provides some basic demographic information Labour force LF The labour force section identifies current employment status whether the responde
30. ers using sample estimates The sample estimates can be numbers Special Surveys Division 41 42 Canadian Financial Capability Survey 2009 User Guide averages percentages ratios etc Tests may be performed at various levels of significance where a level of significance is the probability of concluding that the characteristics are different when in fact they are identical Let X and X be sample estimates for two characteristics of interest Let the standard error on the difference X X be O A A X If t is between 2 and 2 then no conclusion about the difference between the O d characteristics is justified at the 5 level of significance If however this ratio is smaller than 2 or larger than 2 the observed difference is significant at the 0 05 level That is to say that the difference between the estimates is significant 10 3 1 Example of Using the Coefficient of Variation Tables to Do a T test Let us suppose that the user wishes to test at 5 level of significance the hypothesis that there is no difference between the proportion of women with a household budget reporting that they always stay within their budget and the proportion of men with a household budget reporting that they always stay within their budget From Example 3 Section 10 1 1 the standard error of the difference between these two estimates was found to be 0 015 Hence X X 0 351 0 389 0 038 0 0 015 0 015 d
31. ese estimates may be obtained using domain estimation techniques through the Bootstrap variance program e Second should a user require more sophisticated analyses such as estimates of coefficients from linear regressions or logistic regressions the Approximate Sampling Variability Tables will not provide correct associated coefficients of variation Although some standard statistical packages allow sampling weights to be incorporated in the analyses the variances that are produced often do not properly take into account the design and or calibration of the weights whereas the Bootstrap variance program does e Third for estimates of quantitative variables separate tables are required to determine their sampling error 10 7 Statistical Packages for Variance Estimation Special Surveys Division 43 44 Canadian Financial Capability Survey 2009 User Guide Statistics Canada has developed a program that can perform bootstrap variance estimation the Bootvar program The Bootvar program is available in SAS or SPSS format It is made up of macros that compute variances for totals ratios differences between ratios and for linear and logistic regression Bootvar may be downloaded from Statistics Canada s Research Data Centre RDC website Users must accept the Bootvar Click Wrap Licence before they can read the files There is a document on the site explaining how to adapt the system to meet users needs SAS http www statc
32. fined as unpaid work contributing directly to the operation of a farm business or professional practice owned and operated by a related member of the same household Such activities may include keeping books selling products waiting on tables and so on Tasks such as housework or maintenance of the home are not considered unpaid family work Special Surveys Division 11 Canadian Financial Capability Survey 2009 User Guide Full time Employment Full time employment consists of persons who usually work 30 hours or more per week at their main or only job Guaranteed Investment Certificate GIC A savings vehicle having terms generally ranging from one to five years during which time the interest rate is guaranteed and the money is usually locked in until maturity Home Buyers Plan HBP This is a government sponsored plan that allows people to withdraw up to 20 000 tax free from their Registered Retirement Savings Plan RRSP to apply towards the purchase of a home Household A household consists of any person or group of persons related or not occupying a dwelling who has no usual place of residence elsewhere Interest Payment made at a specified rate for the use of borrowed money Labour Force Status Designates the status of the respondent vis vis the labour market a member of the non institutional population 15 years of age and over is either employed unemployed or not in the labour force Line of cre
33. ians knowledge abilities and behaviour concerning financial decision making In other words how Canadians understand their financial situation the financial services available to them and their plans for the future The survey is designed to collect information surrounding respondents approaches to day to day money management and budgeting longer term money management and general financial planning Information for the survey was collected from Canadians 18 years of age and older in the ten provinces Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 3 0 Objectives The fundamental objective of the Canadian Financial Capability Survey CFCS is to gain a greater understanding of the financial knowledge preferences and financial needs of Canadians In particular the survey will collect information on Canadians financial knowledge and understanding their financial skills ability to apply knowledge and make financial decisions and their financial responsibility behaviour in financial matters The information obtained from the CFCS will help governments and industry better understand the knowledge and behaviours of Canadians with respect to participation in financial service markets and in various government programs designed to facilitate financial planning for education and retirement For example the Registered Education Savings Program RESP Registered Retirement Savings Plan RRSP and program
34. icrodata files into subgroups or replicates and determining the variation in the estimate from replicate to replicate Users wishing to derive coefficients of variation for quantitative estimates may contact Statistics Canada for advice on the allocation of records to appropriate replicates and the formulae to be used in these calculations Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 10 5 Coefficient of Variation Tables Refer to CFCS2009_CVTabsE pdf for the coefficient of variation tables 10 6 Mean Bootstrap Method for Variance Estimation In order to determine the quality of the estimate and to calculate the CV the standard deviation must be calculated Confidence intervals also require the standard deviation of the estimate The CFCS uses a multi stage survey design and calibration which means that there is no simple formula that can be used to calculate variance estimates Therefore an approximate method was needed The mean bootstrap method is used because the sample design and calibration needs to be taken into account when calculating variance estimates The mean bootstrap method does this and with the use of the Bootvar program discussed in the next section is a method that is fairly easy for users The CFCS uses the mean bootstrap method described by W Yung Yung W 1997b Variance estimation for public use microdata files Proceedings of Symposium 1997 New Directions in Surveys and Cens
35. in only a few selected cities in the spring of 2008 The computer assisted telephone interviewing CAT application was developed and tested during the summer and fall months in 2008 6 2 Interviewing Statistics Canada interviewers are employees hired and trained to carry out the household surveys The interviewers conducting the CFCS were given specific training in preparation for the survey Data were collected using computer assisted telephone interviewing A front end module contains a set of standard response codes for dealing with all possible call outcomes as well as the associated scripts to be read by the interviewers A standard approach set up for introducing the agency the name and purpose of the survey the survey sponsors how the survey results will be used and the duration of the interview was used The CATI application ensured that only valid question responses were entered and that all the correct flows were followed Edits were built into the application to check the consistency of responses identify and correct outliers and to control who gets asked specific questions This meant that the data was already quite clean at the end of the collection process 6 3 Supervision and Quality Control All Statistics Canada interviewers are under the supervision of a staff of senior interviewers who are responsible for ensuring that interviewers are familiar with the concepts and procedures of the survey and also tor periodically
36. inancial Capability Survey 2009 User Guide Users should also note that some software packages may not allow the generation of estimates that exactly match those available from Statistics Canada because of their treatment of the weight field 9 3 Definitions of Types of Estimates Categorical and Quantitative Before discussing how the CFCS data can be tabulated and analyzed it is useful to describe the two main types of point estimates of population characteristics which can be generated from the microdata file for the CFCS 9 3 1 Categorical Estimates Categorical estimates are estimates of the number or percentage of the surveyed population possessing certain characteristics or falling into some defined category The number of Canadian adults who have a household budget or the proportion who are behind in their payments are examples of such estimates An estimate of the number of persons possessing a certain characteristic may also be referred to as an estimate of an aggregate Examples of Categorical Questions Q Do you have a household budget Yes No future home R Q As of today what percent of the total price have you managed to save for your R Less than 5 5 to 10 11 to 20 21 to 50 51 to 75 76 to 100 9 3 2 Quantitative Estimates Quantitative estimates are estimates of totals or of means medians and other measures of central tendency of quantities based upon some or all of the members of the su
37. ing reported both household and personal incomes Respondents who did not provide a dollar estimate of their incomes were asked questions in order to derive an income range Almost 2 000 respondents 13 did not provide any information on their incomes The reported income ranges and the missing income information were imputed by the donor values in a series of steps depending on the information available for other variables involved in forming the imputation groups In a final step the income values whether reported or imputed were converted into quartiles quintiles and deciles to assist in the analysis of survey results Personal Household Income Income Imputed 4 775 5 223 Total 15 519 15 519 Rate 30 8 33 7 The CFCS imputation process worked well and helped to fill incomplete responses with the experience of other respondents with similar or identical characteristics This will add to the number of units used in any analysis performed by researchers 8 2 4 Measurement of Sampling Error Since it is an unavoidable fact that estimates from a sample survey are subject to sampling error sound statistical practice calls for researchers to provide users with some indication of the magnitude of this sampling error This section of the documentation outlines the measures of sampling error which Statistics Canada commonly uses and which it urges users producing estimates from this microdata file to use also The ba
38. ions if the respondent does not know the answer or refuses to answer Therefore the response data are subjected to further edit and imputation processes once they arrive in head office 7 2 Editing Electronic text files containing the daily transmissions of completed cases are combined to create the raw survey file At the end of collection this file should contain one record for each sampled individual Before further processing verification is performed to identify and eliminate potential duplicate records and to drop non response and out of scope records As a result editing takes place by modifying the data at the individual variable level The first step in editing is to determine which items from the survey output need to be kept on the survey master file Subsequently invalid characters are deleted and the data items are formatted appropriately Text fields are stripped off the main files and written to a separate file for coding The first type of error treated was errors in questionnaire flow where questions that did not apply to the respondent and should therefore not have been answered were found to sometimes contain answers In this case a computer edit automatically eliminated superfluous data by following the flow of the questionnaire implied by answers to previous and in some cases subsequent questions For skips based on answered questions all skipped questions are set to Valid skip 6 96 996 etc For skips
39. lete non response is when the respondent does not provide the minimum set of answers These records are dropped and accounted for in the weighting process see Chapter 11 0 Item non response is when the respondent does not provide an answer to one question but goes on to the next question These are usually handled using the Not stated code or are imputed Finally partial non response is when the respondent provides the minimum set of answers but does not finish the interview These records can be handled like either complete non response or multiple item non response In the case of the CFCS donor imputation was used to fill in missing data for item and partial non response for personal and household income Further information on the imputation process is given in Chapter 8 0 Data Quality 7 5 Creation of Derived Variables A total of 36 data items on the microdata file have been derived by combining items on the questionnaire in order to facilitate data analysis Most are continuous variables related to age and the number of years of service These variables and were grouped in pre determined intervals to aid the analytical process 7 6 Weighting The principle behind estimation in a probability sample such as the CFCS is that each person in the sample represents besides himself or herself several other persons not in the sample For example in a simple random 2 sample of the population each person in the sample represents
40. more reliable than the corresponding estimates of the numerator of the proportion or percentage when the proportion or percentage is based upon a sub group of the population For example the proportion of Canadian women who have a household budget is more reliable than the estimated number of Canadian women who have a household budget Note that in the tables the coefficients of variation decline in value reading from left to right When the proportion or percentage is based upon the total population of the geographic area covered by the table the CV of the proportion or percentage is the same as the CV of the numerator of the proportion or percentage In this case Rule 1 can be used When the proportion or percentage is based upon a subset of the total population e g those in a particular sex or age group reference should be made to the proportion or percentage across the top of the table and to the numerator of the proportion or percentage down the left side of the table The intersection of the appropriate row and column gives the coefficient of variation Rule 3 Estimates of Differences Between Aggregates or Percentages The standard error of a difference between two estimates is approximately equal to the square root of the sum of squares of each standard error considered separately That is the standard error of a difference i X Jis Ka Raa O X a OKT EI where x is estimate 1 x is estimate 2 and o
41. ned as a bank Special Surveys Division 15 Canadian Financial Capability Survey 2009 User Guide which contains at least one working residential telephone number Thus all banks with only unassigned non working or business telephone numbers are excluded from the survey frame Next a systematic sample of banks with replacement was selected within each stratum For each selected bank a two digit number 00 to 99 was generated at random This random number was added to the bank to form a complete telephone number This method allowed listed and unlisted residential numbers as well as business and non working numbers i e not currently or never in service to have a chance of being in the sample A screening activity aimed at removing not in service and known business numbers was performed prior to sending the sample to the computer assisted telephone interviewing CATI unit Each telephone number in the CATI sample was dialled to determine whether or not it reached a household If the telephone number is found to reach a household the person answering the telephone was asked to provide information on the individual household members The ages of the household members were used to determine who in the household would be selected for the interview Respondents were interviewed in the official language of their choice and interviews by proxy respondents were not permitted 5 5 Sample Size The following table shows the number of hous
42. ned to encourage savings for retirement Contributions are tax deductible within prescribed limits Investment income earned in the RRSP is tax exempt but benefits are taxable Amounts in these plans include amounts originally invested plus accrued interest earnings Stocks Common and preferred shares of corporations could also be referred to as equities Related terms publicly traded stock common shares preferred stock shares Tax Free Savings Account or Tax Free Savings Plan TFSA Canadian residents age 18 and older can contribute up to 5 000 per year without being taxed on investment income or capital gains Term Deposits A deposit instrument most commonly available from trust companies and chartered banks requiring a minimum investment at a predetermined rate of interest for a stated term The interest rate varies according to the amount invested and the term to maturity Trust A trust is an arrangement whereby the right to property is held by one party the trustee or manager for the benefit of another the beneficiary Trust Company A financial institution that provides financial and trust services to individuals and corporations A large part of the business of trust companies is acting as trustees for other corporations in handling pension funds bond issues and the like They are active financial intermediaries taking in deposits and making loans of various kinds Unemployment Unemployed pers
43. nt and their spouse partner if appropriate has worked in the past 12 months and the type of work Ongoing expenses OE This section of the survey deals with day to day expenses and ongoing bill payments The information collected in this section pertains to how individuals keep track of their finances and how they manage money Financial management FM This section of the questionnaire deals with longer term financial planning It involves questions surrounding major expenditures over ten thousand dollars retirement planning and planning for children s post secondary education Major expenses ME This section of the questionnaire asks questions about how respondents are planning for future purchases or major expenditures such as a home a new car a cottage or a child s upcoming wedding Postsecondary education funding EF This section of the questionnaire asks questions about financial plans for any child or children in the event that they pursue postsecondary education such as college college d enseignement g n ral et professionnel CEGEP in Quebec university or a trade apprenticeship or vocational school Retirement planning RP This section contains questions about plans for retirement Assets and debts AD This section of the questionnaire asks questions concerning the assets and debts attributable to the individual or household as appropriate This information helps to profile the financial situation of the ho
44. numbers that were still missing the number of lines Thus there were 17 847 households with the number of lines calculated or imputed The adjustment was done within province W W w for households with number of lines w for households mis sin g number of re 3 2 Sw for households with number of lines 5 Calculate household weight with multiple telephone lines adjustment Weights for households with more than one telephone line with different telephone numbers were adjusted downwards to account for the fact that such households have a higher probability of being selected The weight for each household was divided by the number of distinct residential telephone lines up to a maximum of 4 that serviced the household The adjustment was done within province W W 3 E of in scope telephone lines in the household l 6 Adjust for non responding households Household respondents responded to the questions used to create the household roster If these questions were not sufficiently answered perhaps refused or only partially answered then the household was considered a non respondent There were 71 non respondents Thus 17 776 in scope household weights were used and adjusted within province E SW for household respondents K W for household non gel 5 Wa SW for household respondents 7 Assign household weights to selected persons All selected persons from the in scope responding households with com
45. ok KK KK ee ee RR NOTE for correct usage of these tables please refer to microdata documentation Example 5 Estimates of Differences of Ratios Suppose that the user estimates that the ratio of women with a household budget who report that they always stay within their budget to men with a household budget who report that they always stay within their budget is 0 83 for Nova Scotia while it is 1 18 for Alberta The user is interested in comparing the two ratios to see if there is a statistical difference between them How does the user determine the coefficient of variation of the difference 1 First calculate the approximate coefficient of variation for the Nova Scotia ratio R A and the Alberta ratio R as in Example 4 The approximate CV for the Nova Scotia ratio is 19 4 and 15 0 for Alberta Special Surveys Division Canadian Financial Capability Survey 2009 User Guide A 2 Using Rule 3 the standard error of a difference d R R is e Ra Ra where a and are the coefficients of variation of D and R respectively That is the standard error of the difference d 0 83 1 18 0 35 is o y 0 83X0 194 P 1 18 0 150 P 0 0259 0 0313 0 239 A 3 The coefficient of variation of d is given by O d 0 239 0 35 0 683 4 Sothe approximate coefficient of variation of the difference between the estimates is 68 3 The difference between the estimates is consider
46. ons are those who during the reference week a were on temporary layoff during the reference week with the expectation of recall and were available for work or b were without work had actively looked for work in the past four weeks and were available for work or c had anew job to start within four weeks from the reference week and were available for work 2 Persons are regarded as available for work if they i reported that they could have worked in the reference week if a suitable job had been offered or if the reason they could not take a job was of a temporary nature such as because of own illness or disability personal or family responsibilities because they already have a job to start in the near future or because of vacation prior to 1997 those on vacation were not considered available ii were full time students seeking part time work who also met condition i above Full time students currently attending school and looking for full time work are not considered to be available for work during the reference week Special Surveys Division 13 Canadian Financial Capability Survey 2009 User Guide 5 0 Survey Methodology The Canadian Financial Capability Survey CFCS was administered between February 11th and May 9th 2009 as a Random Digit Dialling RDD survey a technique whereby telephone numbers are generated randomly by computer Interviewing was conducted over the telephone 5 1 Population Coverage The
47. or men as 2 8 An A Using Rule 3 the standard error of a difference i X x is Special Surveys Division Ss 45 OO D o o JJ o wo 4 Canadian Financial Capability Survey 2009 User Guide where x is estimate 1 women x is estimate 2 men and and are the coefficients of variation of X and e respectively That is the standard error of the difference d 0 351 0 389 0 038 is Cae l0 351 0 030 0 389 X0 028 P 0 000111 0 000119 0 015 3 The coefficient of variation of d is given by o d 0 015 0 038 0 395 4 So the approximate coefficient of variation of the difference between the estimates is 39 5 The difference between the estimates is considered unacceptable and Statistics Canada recommends this estimate not be released However should the user choose to do so the estimate should be flagged with the letter F or some similar identifier and be accompanied by a warning to caution subsequent users about the high levels of error associated with the estimate Example 4 Estimates of Ratios Suppose that the user estimates that 2 478 643 women with a household budget report that they always stay within their budget while 2 402 986 men have and stay within their household budget The user is interested in comparing the estimate of women versus that of men in the form of a ratio How does the user determine the coefficient of variation of this estimate A
48. pleted rosters i e no missing ages were assigned their household weights W W 8 Calculate selected person sub weight The weight for each selected person is then inflated using the roster information to represent the number of people within the household who were eligible to be selected aged 18 years or older W W Number of eligible household members 9 Adjust for non responding individuals The data file includes records of individual respondents who completed a sufficient amount of the questions asked There were 2 257 non respondents Special Surveys Division Canadian Financial Capability Survey 2009 User Guide Thus 15 519 in scope individual weights were used and adjusted within province age groups derived from the roster 18 to 24 25 to 44 45 to 64 65 and over and sex Meios gt for person respondents Sw for person non 8 7 to ooasSsS gt Sw for person respondents 10 Adjust to external totals An adjustment was made to the person weights in order to make population estimates consistent with external population counts for persons 18 years and older This is known as post stratification The following external control totals as projected for February 2009 were used 1 Population totals by province sex and the following age groups 18 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 and 70 and over 2 Population totals of persons aged
49. province This resulted in a design with 27 strata in all 5 3 Sample Design and Allocation The sample design is a two phase stratified random sample of telephone numbers In the first phase households are selected using RDD In the second phase one individual from the contacted household is selected Because the survey is mainly intended to produce reliable estimates at the national level but also strives for provincial and CMA level estimates of reasonable quality a Kish allocation was used As a result of this compromise there are more respondents in the sample from the larger provinces but the number is not strictly proportional to the population in each The initial sample size of telephone numbers depended upon the expected response rate and the expected RDD hit rate proportion of sampled telephone numbers which are screened in as households It was estimated that a total of more than 53 000 telephone numbers was needed to obtain 20 000 respondents This assumed a 66 response rate and hit rate that varied substantially by province with an expected overall average of about 40 5 4 Sample Selection The sample for the CFCS was generated using a refinement of RDD sampling called the Elimination of Non Working Banks ENWB Within each province stratum combination a list of working banks area code next five digits was compiled from telephone company administrative files A working bank for the purposes of social surveys is defi
50. re and gas station cards Credit Union A co operative financial institution that is owned by its members and that operates for the benefit of its members by accepting savings deposits and making loans including mortgage loans and providing other services such as chequing and credit card services Co operatives Co ops see Credit Union above Debit Card see Bankcard above Debt An amount owed by one party to another for money goods or services Dividend Monetary amount paid to shareholders of a company from profits made by that company Employment Employed persons are those who during the reference week a did any work at all ata job or business or b had a job but were not at work due to factors such as own illness or disability personal or family responsibilities vacation labour dispute or other reasons excluding persons on layoff between casual jobs and those with a job to start at a future date Equity The residual interest in assets after deducting related liabilities For example the equity in a home equals the value of the home minus the amount owed on the mortgage Family a group of two or more persons who live in the same dwelling and are related to each other by blood marriage adoption or common law 1 Work includes any work for pay or profit that is paid work in the context of an employer employee relationship or self employment It also includes unpaid family work which is de
51. related Rule 5 Estimates of Differences of Ratios In this case Rules 3 and 4 are combined The CVs for the two ratios are first determined using Rule 4 and then the CV of their difference is found using Rule 3 10 1 1 Examples of Using the Coefficient of Variation Tables for Categorical Estimates The following examples based on the CFCS are included to assist users in applying the foregoing rules Example 1 Estimates of Numbers of Persons Possessing a Characteristic Aggregates Suppose that a user estimates that 13 233 741 adult Canadians report having a household budget How does the user determine the coefficient of variation of this estimate 1 Refer to the coefficient of variation table for CANADA 2 The estimated aggregate 13 233 741 does not appear in the left hand column the Numerator of Percentage column so it is necessary to use the figure closest to it namely 12 500 000 3 The coefficient of variation for an estimated aggregate is found by referring to the first non asterisk entry on that row namely 1 0 4 So the approximate coefficient of variation of the estimate is 1 0 The finding that there were 13 233 741 to be rounded according to the rounding guidelines in Section 9 1 adult Canadians with a household budget is publishable with no qualifications Example 2 Estimates of Proportions or Percentages of Persons Possessing a Characteristic Suppose that the user estimates that 4 881 629
52. rently unpublished figures in a manner consistent with these established guidelines 9 1 Rounding Guidelines In order that estimates for publication or other release derived from these microdata files correspond to those produced by Statistics Canada users are urged to adhere to the following guidelines regarding the rounding of such estimates a Estimates in the main body of a statistical table are to be rounded to the nearest hundred units using the normal rounding technique In normal rounding if the first or only digit to be dropped is 0 to 4 the last digit to be retained is not changed If the first or only digit to be dropped is 5 to 9 the last digit to be retained is raised by one For example in normal rounding to the nearest 100 if the last two digits are between 00 and 49 they are changed to 00 and the preceding digit the hundreds digit is left unchanged If the last digits are between 50 and 99 they are changed to 00 and the preceding digit is incremented by 1 b Marginal sub totals and totals in statistical tables are to be derived from their corresponding unrounded components and then are to be rounded themselves to the nearest 100 units using normal rounding c Averages proportions rates and percentages are to be computed from unrounded components i e numerators and or denominators and then are to be rounded themselves to one decimal using normal rounding In normal rounding to a single digit if the final or onl
53. response rates by province for the Canadian Financial Capability Survey CFCS Total Total Overall Province number of persons response households responding rate Newfoundland and Labrador 1 224 670 54 7 Prince Edward Island 572 324 56 7 Nova Scotia 1 326 779 58 8 New Brunswick 1 213 684 56 4 Quebec 5 824 3 336 57 3 Ontario 8 185 4 519 55 2 Manitoba 1 427 795 55 7 Saskatchewan 1 976 1 213 61 4 Alberta 2 748 1 690 61 5 British Columbia 3 061 1 509 49 3 Canada 27 555 15 519 56 3 A respondent has the following characteristics e The household roster was completed with no individual age refusals e The selected person was 18 years of age or older at the time of the interview confirmed with the selected person e The selected person answered at least two thirds of the key items in three out of the first five modules of the survey questionnaire Demography Labour force Ongoing expenses Financial management and Major expenses and at least one key item from the Financial management module 8 2 Survey Errors The estimates derived from this survey are based on a sample of households Somewhat different estimates might have been obtained if a complete census had been taken using the same questionnaire interviewers supervisors processing methods etc as those actually used in the survey The difference between the estimates obtained from the sample and those resulting
54. rval CI Cl X iXa 1Xa where is the determined coefficient of variation of x and t 1 if a68 confidence interval is desired t 1 6 if a 90 confidence interval is desired t 2 if a 95 confidence interval is desired t 2 6 if a 99 confidence interval is desired Note Release guidelines which apply to the estimate also apply to the confidence interval For example if the estimate is not releasable then the confidence interval is not releasable either 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence Limits A 95 confidence interval for the estimated proportion of Canadian adults with a household budget who reported that they always stay within their budget from Example 2 Section 10 1 1 would be calculated as follows A X 36 9 or expressed as a proportion 0 369 t 2 a 1 9 0 019 expressed as a proportion is the coefficient of variation of this estimate as determined from the tables CI 0 369 2 0 369 0 019 0 369 2 0 369 0 019 CT 0 369 0 014 0 369 0 014 CI 0 355 0 383 With 95 confidence it can be said that between 35 5 and 38 3 of Canadian adults with a household budget report that they always stay within their budget 10 3 How to Use the Coefficient of Variation Tables to Do a T test Standard errors may also be used to perform hypothesis testing a procedure for distinguishing between population paramet
55. rveyed population They also specifically involve estimates of the form X where X isan estimate of surveyed population quantity total and Y is an estimate of the number of persons in the surveyed population contributing to that total quantity An example of a quantitative estimate is the average number of personal bank accounts held by adult women in Canada The numerator is an estimate of the total number of personal bank accounts and its denominator is the number of adult women 18 years of age and older in Canada Examples of Quantitative Questions Q How many personal chequing or savings accounts do you currently have with a bank credit union or trust company _ _ accounts principal residence R Q For how many more years do you expect to make mortgage payments on your R _ _ _ years Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 9 3 3 Tabulation of Categorical Estimates Estimates of the number of people with a certain characteristic can be obtained from the microdata file by summing the final weights of all records possessing the characteristic s of interest Proportions and ratios of the form X Y are obtained by a summing the final weights of records having the characteristic of interest for the numerator X b summing the final weights of records having the characteristic of interest for the A denominator Y then c dividing estimate a by estimate b
56. rviewer training consisted of reading the CFCS Supervisor s Manual Procedures Manual and Interviewer s Manual practicing with the CFCS training cases on the computer and discussing any questions with senior interviewers before the start of the survey A description of the background and objectives of the survey was provided as well as a glossary of terms and a set of questions and answers The collection period ran from February 11 to May 9 2009 8 2 2 Data Processing Data processing of the CFCS was done in a number of steps including verification coding editing imputation estimation confidentiality etc At each step a picture of the output files is taken and an easy verification can be made comparing files at the current and previous step This greatly improved the data processing stage 8 2 3 Non response A major source of non sampling errors in surveys is the effect of non response on the survey results The extent of non response varies from partial non response failure to answer just one or some questions to total non response Total non response occurred because the interviewer was either unable to contact the respondent no member of the household was able to provide the information or the respondent refused to participate in the survey Total non response was handled by adjusting the weight of individuals who responded to the survey to compensate for those who did not respond In most cases partial non response to the survey
57. s such as the Guaranteed Income Supplement GIS and the Canada Pension Plan CPP Quebec Pension Plan QPP Special Surveys Division 9 Canadian Financial Capability Survey 2009 User Guide 4 0 Concepts and Definitions This chapter outlines concepts and definitions of interest to the users Users are referred to Chapter 12 0 of this document for a copy of the actual survey questionnaire s used Asset Anything having a monetary value that is owned by a person or business Real estate stocks bonds and money itself are all considered to be assets Bankcard A card issued by a bank that entitles the holder to make electronic payments with a point of sale terminal and to carry out banking transactions via an automatic teller Bonds A certificate of indebtedness issued by a government or corporation Interest rates are fixed for the term of the bond but the bond may be sold at more or less than its face value Canada Pension Plan CPP Quebec Pension Plan QPP Retirement pensions received at age 65 by people who have worked in Canada Also includes Survivors Benefits such as widows pensions widowers pensions orphans benefits and Disability Pensions for disabled pensioners Credit Card Method of paying for goods and services whereby the purchaser defers payment and repays the principal and interest in instalments over time These include bank type credit cards e VISA Mastercard as well as retail sto
58. sample leading to a new confidence interval for an estimate then in 95 of the samples the interval will cover the true population value Using the standard error of an estimate confidence intervals for estimates may be obtained under the assumption that under repeated sampling of the population the various estimates obtained for a population characteristic are normally distributed about the true population value Under this assumption the chances are about 68 out of 100 that the difference between a sample estimate and the true population value would be less than one standard error about 95 out of 100 that the difference would be less than two standard errors and about 99 out of 100 that the difference would be less than three standard errors These different degrees of confidence are referred to as the confidence levels A Confidence intervals for an estimate X are generally expressed as two numbers one below the estimate and one above the estimate as X k X k where k is Special Surveys Division Canadian Financial Capability Survey 2009 User Guide determined depending upon the level of confidence desired and the sampling error of the estimate Confidence intervals for an estimate can be calculated directly from the Approximate Sampling Variability Tables by first determining from the appropriate table the coefficient of variation of the estimate X and then using the following formula to convert to a confidence inte
59. sis for measuring the potential size of sampling errors is the standard error of the estimates derived from survey results However because of the large variety of estimates that can be produced from a survey the standard error of an estimate is usually expressed relative to the estimate to which it pertains This resulting measure known as the coefficient of variation CV of an estimate is obtained by dividing the standard error of the estimate by the estimate itself and is expressed as a percentage of the estimate For example suppose that based upon the survey results one estimates that 13 5 of Canadians report that they check their personal or joint account balances daily and this estimate is found to have a standard error of 0 0034 Then the coefficient of variation of the estimate is calculated as 0 0034 X 100 2 5 0 135 There is more information on the calculation of coefficients of variation in Chapter 10 0 Special Surveys Division 25 Canadian Financial Capability Survey 2009 User Guide 9 0 Guidelines for Tabulation Analysis and Release This chapter of the documentation outlines the guidelines to be adhered to by users tabulating analyzing publishing or otherwise releasing any data derived from the survey microdata files With the aid of these guidelines users of microdata should be able to produce the same figures as those produced by Statistics Canada and at the same time will be able to develop cur
60. snssesnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnannnnnnnnnannnnnnnn 33 10 1 Howto Use the Coefficient of Variation Tables for Categorical EstimatesS mmmmmmmomom lt m 33 10 1 1 Examples of Using the Coefficient of Variation Tables for Categorical lu EE 35 10 2 Howto Use the Coefficient of Variation Tables to Obtain Confidence Limits 40 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence DS eege gees SEENEN EHNEN ES 41 10 3 Howto Use the Coefficient of Variation Tables to Do a T test unneenannnnnannnnnnnnnnnnnnnnnnnnnnnn 41 10 3 1 Example of Using the Coefficient of Variation Tables to Do a Tiet seen 42 10 4 Coefficients of Variation for Quantitative Estimates unnsunennnnnnnnnnnnnnnnnnnnnannnnnnnnnnnnnnnnannnnnn 42 10 5 Coefficient of Variation Tables cnc 43 10 6 Mean Bootstrap Method for Variance Estimation unnesnnssnnnnnnennnnnnnennnnnnnennnnannennnnn anne nenn 43 10 7 Statistical Packages for Variance Estimation euunnsnnsnnnnnnnunnnnnannnnnnnnnnnnnnnnnnnnnnnnnnannnnnannnnnnn 43 TO 45 11 1 Weighting ProceduUlEOS mmcccnnnnncnnnnnnnc nn 45 QuUEStONNA ES iaa 49 Record Layout with Univariate Frequencies ununnssnrnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn nennen nenn 51 Special Surveys Division Canadian Financial Capability Survey 2009 User Guide 1 0 Introduction This package is designed to enable interested users to access and manipulate the microdata file for the Canadian Financial Capa
61. then choosing from among these a conservative value usually the 75 percentile to be used in the CV tables which would then apply to the entire set of characteristics The table below shows the conservative value of the design effects as well as sample sizes and population counts by province which were used to produce the Approximate Sampling Variability Tables for the Canadian Financial Capability Survey CFCS Province Design Effect Sample Size Population Newfoundland and Labrador 1 32 670 410 773 Prince Edward Island 1 21 324 109 723 Nova Scotia 1 29 779 750 481 New Brunswick 1 53 684 602 590 Quebec 1 39 3 336 6 167 275 Ontario 1 39 4 519 10 161 677 Manitoba 1 32 795 911 804 Saskatchewan 1 47 1 213 771 190 Alberta 1 33 1 690 2 740 104 British Columbia 1 54 1 509 3 586 822 Canada 1 60 15 519 26 212 439 All coefficients of variation in the Approximate Sampling Variability Tables are approximate and therefore unofficial Estimates of actual variance for specific variables may be obtained from Statistics Canada on a cost recovery basis Since the approximate CV is conservative the use of actual variance estimates may cause the estimate to be switched from one quality level to another For instance a marginal estimate could become acceptable based on the exact CV calculation Remember If the number of observations on which an estimate is based is less than 30 the weighted es
62. timate is most likely unacceptable and Statistics Canada recommends not to release such an estimate regardless of the value of the coefficient of variation 10 1 How to Use the Coefficient of Variation Tables for Categorical Estimates The following rules should enable the user to determine the approximate coefficients of variation from the Approximate Sampling Variability Tables for estimates of the number proportion or percentage of the surveyed population possessing a certain characteristic and for ratios and difterences between such estimates Special Surveys Division 33 34 Canadian Financial Capability Survey 2009 User Guide Rule 1 Estimates of Numbers of Persons Possessing a Characteristic Aggregates The coefficient of variation depends only on the size of the estimate itself On the Approximate Sampling Variability Table for the appropriate geographic area locate the estimated number in the left most column of the table headed Numerator of Percentage and follow the asterisks if any across to the first figure encountered This figure is the approximate coefficient of variation Rule 2 Estimates of Proportions or Percentages of Persons Possessing a Characteristic The coefficient of variation of an estimated proportion or percentage depends on both the size of the proportion or percentage and the size of the total upon which the proportion or percentage is based Estimated proportions or percentages are relatively
63. usehold Income IN This information provides contextual information surrounding both the individual and where appropriate the household s income Financial choices FC This section of the survey addresses how we approach financial choices and is relevant for issues of planning and responsibility Subjective personal assessment SA In this section of the survey respondents provide a self assessment of their comfort with financial matters Objective personal assessment OA The final section of the questionnaire asks respondents to provide answers to a short money quiz Special Surveys Division 17 Canadian Financial Capability Survey 2009 User Guide 6 0 Data Collection Data collection for the Canadian Financial Capability Survey CFCS was carried out between February and early May 2009 6 1 Questionnaire Design In the case of the Canadian Financial Capability Survey it was proposed from conception that it be collected by telephone interview an approach that reflected previous successes in other countries with similar subject matter A first round of cognitive testing including one on one interviews and focus group discussions across Canada in spring 2007 confirmed that this was indeed the best way to proceed With the addition of Finance Canada and the Bank of Canada as active partners the content was modified to reflect each of the partners data needs This of course led to a second round of cognitive testing
64. uses Statistics Canada Independently in each stratum a simple random sample of n 1 of the n units in the sample is selected with replacement Note that since the selection is with replacement a unit may be chosen more than once This step is repeated R times to form R bootstrap samples An average initial bootstrap weight based on the R samples is calculated for each sample unit in the stratum The entire process selecting simple random samples recalculating weights for each stratum is repeated B times where B is large yielding B different initial bootstrap weights The CFCS uses R 20 and B 250 to produce 250 bootstrap weights These weights are then adjusted according to the same weighting process as the regular weights non response adjustment calibration and so on The end result is 250 final mean bootstrap weights for each unit in the sample The variation among the 250 possible estimates based on the 250 mean bootstrap weights are related to the variance of the estimator based on the regular weights and can be used to estimate it There are a number of reasons why a user may need to calculate the coefficient of variation of estimates with the mean bootstrap method A few are given below e First if a user wishes to have estimates at a geographic level smaller than the province for example at the urban or rural level then the Approximate Sampling Variability Tables provided are not adequate Coefficients of variation of th
65. y digit to be dropped is 0 to 4 the last digit to be retained is not changed If the first or only digit to be dropped is 5 to 9 the last digit to be retained is increased by 1 d Sums and differences of aggregates or ratios are to be derived from their corresponding unrounded components and then are to be rounded themselves to the nearest 100 units or the nearest one decimal using normal rounding e In instances where due to technical or other limitations a rounding technique other than normal rounding is used resulting in estimates to be published or otherwise released which differ from corresponding estimates published by Statistics Canada users are urged to note the reason for such differences in the publication or release document s f Under no circumstances are unrounded estimates to be published or otherwise released by users Unrounded estimates imply greater precision than actually exists 9 2 Sample Weighting Guidelines for Tabulation The sample design used for the Canadian Financial Capability Survey CFCS was not self weighting When producing simple estimates including the production of ordinary statistical tables users must apply the proper survey weights If proper weights are not used the estimates derived from the microdata files cannot be considered to be representative of the survey population and will not correspond to those produced by Statistics Canada Special Surveys Division 27 28 Canadian F

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