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User Guide for the Survey of Household Spending, 2013

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1. Medium population centre 30 000 to 99 999 Large urban population centre 100 000 and over 4 6 8 Rural area All areas outside population centres are considered rural Taken together population centres and rural areas cover all of Canada 4 6 9 Age of reference person Households are grouped according to the age of the reference person as the following Less than 30 years 30 to 39 years 40 to 54 years 55 to 64 years 65 years and over 5 Derivation of data tables This section explains how the SHS data tables have been derived It then explains the calculations used most frequently to manipulate the data Users are advised to refer to this section before doing their data analysis As stated above only a subsample of the households have to fill out a diary Therefore different weights are calculated for the interview questionnaire and the diary which makes using the data more complicated 22 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series 5 1 Estimates of number of households Estimates are generated using two sets of weights one for the interview and the other for the diary Adjustments made during weighting ensure that the estimate of the number of households at the provincial level using either set of weights is equivalent for the following domains household sizes of one two or three or more persons and household income groups defined accor
2. 572 588 Diaries Unusable 140 31 40 69 2 The definition of usable and unusable diaries is given in the Data processing and quality control Section 3 Usable diaries Interview respondents selected for the diary x 100 Usable 4 048 1 555 1 403 1 090 Response rate percentage 68 9 66 0 74 5 69 8 67 4 61 4 59 5 Response rate percentage 68 9 73 5 69 6 62 4 Statistics Canada Catalogue no 62F0026M no 1 33 Household Expenditures Research Paper Series Text table 3 Diary response rates among the respondents to the interview by age of the reference person Canada 2013 Interview Diaries respondents Refusal Unusable Usable Response rate number percentage Reference person of all ages 5 878 1 690 140 4 048 68 9 Less than 30 years 558 187 20 351 62 9 30 to 39 years 878 269 31 578 65 8 40 to 54 years 1 717 554 35 1 128 65 7 55 to 64 years 1 181 278 23 880 74 5 65 years and over 1 544 402 31 1 111 72 0 1 Interview respondents from households selected to fill out the diary 2 The definition of usable and unusable diaries is given in the Data processing and quality control Section 3 Usable diaries Interview respondents selected for the diary x 100 Text table 4 Diary response rates among the respondents to the interview by before tax income quintile Canada 2013 Interview Diaries respondents Refusal Unusable Usable Response rate number percentage Total of all income quintiles
3. See section 5 Derivation of data tables 4 6 4 Housing tenure Whether a household member owned or rented the dwelling in which the household lived at the time of the interview Owners refers to all households living in a dwelling owned with or without mortgage by a household member at the time of the interview Owners with mortgage owned the dwelling with a mortgage at the time of the interview Owners without mortgage owned the dwelling without a mortgage at the time of the interview Renters rented a dwelling at the time of the interview as a regular tenant rent free or with reduced rent 4 6 5 Household type Households are divided according to the following types One person households are the households where the dwelling is occupied by only one person at the time of the interview Couple households are households where the married or common law spouse of the reference person is a member of the household at the time of the interview This household type may be further broken down into couple households without children without additional persons with children without additional persons and with additional persons Children are never married sons daughters or foster children of the reference person and may be any age Additional persons include sons daughters and foster children whose marital status is other than single never married other relatives by birth or marriage and unr
4. survey year depending on the collection month The hypothesis that the estimates produced from the SHS cover a single period when the data from 12 collection cycles has been combined assumes that expenditures made during the survey year and during the previous year are similar for items collected using a 12 month reference period Thus the validity of this hypothesis affects the interpretation of comparisons between expenditures collected over short periods and expenditures collected over a 12 month period The limits of the collection model in producing expenditure estimates covering the same period or the same year are known since the majority of countries use this methodology Despite any limitations continuous collection with reference periods adapted to the ability of the respondent to provide the information is considered preferable in order to obtain data that reflects households true expenditures Statistics Canada Catalogue no 62F0026M no 1 9 Household Expenditures Research Paper Series 2 8 Historical revisions The 2013 SHS estimates were computed with weights adjusted to 2013 population estimates These population estimates were based on 2006 Census data and more recent information from administrative sources such as birth death and migration registers SHS estimates prior to 2010 2001 2009 are based on weights calibrated to population estimates produced using data from the 2001 Census There is no plan to revise th
5. 315 337 189 390 399 593 531 1 156 413 332 411 453 percentage 68 9 71 7 72 0 69 5 69 4 75 1 71 5 64 0 68 5 71 5 68 3 66 0 64 8 1 Interview respondents from households selected to fill out the diary 2 The definition of usable and unusable diaries is given in the Data processing and quality control Section 3 Usable diaries Interview respondents selected for the diary x 100 Statistics Canada Catalogue no 62F0026M no 1 29 Appendix Il Response rates by collection month Text table 1 Interview response rates by collection month Canada 2013 Eligible sampled households All months 17 389 January 1 460 February 1 508 March 1 469 April 1 418 May 1 435 June 1 446 July 1 412 August 1 423 September 1 516 October 1 416 November 1 434 December 1 452 No contacts 1 158 93 124 103 81 77 78 118 104 93 67 99 121 1 Respondent households Eligible sampled households x 100 Text table 2 Diary response rates by collection month Canada 2013 Eligible sampled households All months 8 782 January 741 February 755 March 745 April 722 May 727 June 728 July 717 August 716 September 763 October 720 November 716 December 732 1 The eligible sampled households are those selected to fill out the diary 2 3 4 Usable diaries Eligible sampled households x 100 Interview non respondents 2 904 30 Statistics Canada Catalogue no 62F0026M no
6. 809 3 37 Subtotals may not add up to the total due to rounding 40 Statistics Canada Catalogue no 62F0026M no 1
7. 999 1 377 75 373 77 Population centre 100 000 to 249 999 2 875 225 726 109 Population centre 30 000 to 99 999 1 968 110 453 84 Population centre 1 000 to 29 999 2 085 128 428 65 Rural area 2 753 164 526 92 1 Respondent households Eligible sampled households x 100 Text table 2 Diary response rates by size of area of residence Canada 2013 Eligible Interview Diaries 3 sampled non respondents Refusal Unusable households number All population centres and rural area 8 782 2 904 1 690 140 Population centre 1 000 000 and over 2 443 794 538 33 Population centre 500 000 to 999 999 762 271 126 7 Population centre 250 000 to 499 999 705 278 132 9 Population centre 100 000 to 249 999 1 495 547 264 21 Population centre 30 000 to 99 999 991 320 190 23 Population centre 1 000 to 29 999 1 042 317 181 25 Rural area 1 344 377 259 22 1 The eligible sampled households are those selected to fill out the diary 2 Includes interview No contacts Refusals and Residual non respondents from households selected to fill out the diary 3 The definition of usable and unusable diaries is given in the Data processing and quality control Section 4 Usable diaries Eligible sampled households x 100 Respondents 11 686 3 264 999 852 1 815 1 321 1 464 1 971 Usable 4 048 1 078 358 286 663 458 519 686 Response rate percentage 67 2 68 0 65 1 61 9 63 1 67 1 70 2 71 6 Response rate percentage 46 1 44 1 47 0 40 6
8. Gifts Any expenditure may include gifts given to persons outside the household Only the value of gifts of clothing is reported separately 4 1 8 Insurance settlements Where an insurance settlement was used to repair or replace property the survey includes only the deductible amount paid for an item 4 1 9 Trade ins Where a trade in is used to lower the price of an item most commonly a vehicle the expenditure amount is the total cost after the trade in Real estate transactions are excepted 4 2 Household characteristics 4 2 1 Number of households in sample Corresponds to the number of eligible sample households minus households that interviewers were unable to contact households that refused to participate and households whose interview questionnaire were rejected for lacking too much information 4 2 2 Estimated number of households Estimation of the average number of households during the reference year 4 2 3 Household size Number of persons in the household at the time of the interview 4 2 4 Age of reference person Corresponds to the age of the reference person at the time of the interview 16 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series 4 2 5 Household income before tax Corresponds to the total income before tax received by the household the year prior to the reference year of the survey It refers to income from all sources including government transfers
9. as they are considered as an increase in assets investment rather than an expense 4 3 9 Water fuel and electricity for principal accommodation Expenditures for services related to water and sewage electricity and natural gas and other fuel for the principal accommodation whether rented or owned 4 3 10 Property taxes and sewage charges for owned vacation homes and other secondary residences Refers to the amount billed excluding any rebates Special service charges e g garbage sewage local improvements and water charges are included if these are part of the property tax bill 4 3 11 Accommodation away from home Includes all expenses for accommodation while travelling Excludes expenditures for accommodation that were part of a package trip 4 3 12 Household appliances Refers to the net purchase price after deducting trade in allowance and any discount Excludes appliances included in the purchase of a home 4 3 13 Purchase of automobiles vans and trucks Refers to the net purchase price including extra equipment accessories and warranties bought when the vehicle was purchased after deducting any trade in allowance or separate sales Separate sales occur when a vehicle is sold independently by the owner e g not traded in when purchasing or leasing another vehicle 4 3 14 Health care Includes direct costs to household out of pocket net of the expenditures reimbursed and health insurance premiums 4 3 15 Packa
10. imputation taxes are added to those diary items that should be reported with taxes excluded In order to reduce the response burden instructions are provided to the respondents indicating when to include or exclude taxes from reported expenses Thus the Goods and Services Tax GST and the Provincial Sales Tax PST orthe Harmonized Sales Tax HST are added to the diary items according to the appropriate federal and provincial taxation rates 2 6 Estimation The estimation of population characteristics from a sample survey is based on the premise that each sampled household represents a certain number of other households in addition to itself This number is referred to as the survey weight and the weighting process involves computing the weight assigned to each household There are a number of steps in that process Statistics Canada Catalogue no 62F0026M no 1 7 Household Expenditures Research Paper Series First each household is given an initial weight equal to the inverse of its selection probability Since only 5096 of the households need to complete a diary different weights are computed for the interview questionnaire and the diary A few adjustments are later applied to the interview weights and the diary weights The interview weights are first adjusted to take into account the households that did not answer the questionnaire They are then adjusted so that selected survey estimates agree with aggregates or estimates from ind
11. 1 230 253 260 233 253 217 229 230 248 220 262 269 Refusals number 3 911 304 337 322 330 341 322 302 320 335 320 326 352 Refusal number 1 690 130 128 124 133 144 144 163 127 141 145 149 162 Residual non respondents 634 54 44 62 51 55 55 53 56 48 57 47 Diaries 3 Unusable 140 17 15 10 18 11 10 21 11 Includes interview No contacts Refusals and Residual non respondents from households selected to fill out the diary The definition of usable and unusable diaries is given in the Data processing and quality control Section Respondents 11 686 1 009 1 003 982 956 962 991 940 946 1 032 981 952 932 Usable 4 048 364 366 352 341 320 349 314 349 353 344 301 295 Response rate percentage 67 2 69 1 66 5 66 8 67 4 67 0 68 5 66 6 66 5 68 1 69 3 66 4 64 2 Response rate percentage 46 1 49 1 48 5 47 2 47 2 44 0 47 9 43 8 48 7 46 3 47 8 42 0 40 3 Appendix Ill Response rates by size of area of residence and by dwelling type Text table 1 Interview response rates by size of area of residence Canada 2013 Eligible No Refusals Residual sampled contacts non respondents households number All population centres and rural area 17 389 1 158 3 911 634 Population centre 1 000 000 and over 4 797 333 1 049 151 Population centre 500 000 to 999 999 1 534 123 356 56 Population centre 250 000 to 499
12. 11 Estimated number of households and average household size based on interview weights by household tenure All Owner Owner Renter households with without mortgage mortgage number Estimated number of households 13 514 009 4 812 813 4 219 949 4 481 247 Average household size 2 48 3 03 2 30 2 05 Text table 12 Average household expenditures obtained from interview and diary data by household tenure All Owner Owner Renter households with without mortgage mortgage dollars Total expenditure 39 621 54 439 36 000 27 163 Food expenditures 7 795 9 234 8 465 5 642 Food purchased from stores 5 588 6 583 6 053 4 098 Food purchased from restaurant 2 207 2 652 2 412 1 544 Shelter 15 210 23 712 9 643 11 320 Household furnishing and equipment 2 027 2 699 2 235 1 115 Clothing and accessories 3 360 4 289 3 268 2 448 Transportation 11 229 14 505 12 389 6 638 1 Total of expenditure for the categories used in this example Tables 7 to 10 above are not available to users however the following section provides examples on how to produce other estimates using tables such as 11 and 12 above 5 4 Calculating various estimates using the tables The following section explains the calculation method for some of the common SHS expenditure data manipulations 5 4 1 How to calculate average expenditures per person To calculate average expenditure per person for a given category divide the average expenditure per household for that category Table 12
13. 13 819 964 981 842 3 449 194 5 158 934 2 372 646 1 857 347 215 726 58 499 394 321 313 296 3 449 194 5 158 934 478 186 420 850 1 473 611 1 857 347 2 763 242 2 754 906 2 772 809 2 762 931 2 766 077 3 847 055 3 776 079 3 663 392 659 042 885 851 988 545 9 348 723 5 256 036 4 092 687 4 471 241 6 217 828 984 894 1 222 756 1 300 359 1 285 777 1 229 336 1 579 015 1 516 159 2 289 736 4 358 853 2 553 411 3 101 804 Average household size 2 48 2 34 2 30 2 60 2 57 2 43 2 34 2 45 2 32 2 33 2 30 2 60 2 49 2 42 2 64 2 43 1 49 2 11 2 49 2 95 3 34 1 00 2 00 3 94 4 92 2 50 2 98 2 70 3 05 2 25 2 01 2 61 2 36 2 37 2 47 2 20 2 33 2 48 2 30 2 98 2 93 2 28 1 71 Statistics Canada Catalogue no 62F0026M no 1 39 Household Expenditures Research Paper Series Text table 2 Estimated number of households and average household size by domain defined at the provincial level Canada 2013 Domain Estimated Average number of household households size Newfoundland and Labrador All quintiles 215 726 2 34 Lowest quintile 43 053 1 53 Second quintile 43 071 1 95 Third quintile 42 756 2 38 Fourth quintile 43 551 2 70 Highest quintile 43 294 3 11 Prince Edward Island All quintiles 58 499 2 45 Lowest quintile 11 696 1 30 Second quintile 11 594 2 20 Third quintile 11 794 2 56 Fourth quintile 11 480 3 05 Highest quintile 11 935 3 15 Nova Scotia All quin
14. 44 3 46 2 49 8 51 0 Statistics Canada Catalogue no 62F0026M no 1 31 Household Expenditures Research Paper Series Text table 3 Interview response rates by dwelling type Canada 2013 Eligible No Refusals Residual sampled contacts non respondents households number All dwelling types 17 389 1 158 3 911 634 Single detached 11 133 651 2 643 377 Double or row terrace 1 601 104 343 64 Duplex low rise or high rise apartment 4 244 361 824 178 Other 376 33 77 13 Not available 35 9 24 2 1 Respondent households Eligible sampled households x 100 Text table 4 Diary response rates by dwelling type Canada 2013 Eligible Interview Diaries 3 sampled non respondents Refusal Unusable households number All dwelling types 8 782 2 904 1 690 140 Single detached 5 590 1 877 1 026 74 Double or row terrace 804 253 149 14 Duplex low rise or high rise apartment 2 165 688 477 46 Other 204 67 38 6 Not available 19 19 0 0 The eligible sampled households are those selected to fill out the diary Includes interview No contacts Refusals and Residual non respondents from households selected to fill out the diary The definition of usable and unusable diaries is given in the Data processing and quality control Section Usable diaries Eligible sampled households x 100 Pon gt 32 Statistics Canada Catalogue no 62F0026M no 1 Respondents 11 686 7 462 1 090 2 881 253 Usable 4 048 2 613 388 954 93
15. 5 878 1 690 140 4 048 68 9 Lowest quintile 1 227 401 41 785 64 0 Second quintile 1 169 333 35 801 68 5 Third quintile 1 195 318 28 849 71 0 Fourth quintile 1 173 310 21 842 71 8 Highest quintile 1 114 328 15 771 69 2 1 Interview respondents from households selected to fill out the diary 2 The definition of usable and unusable diaries is given in the Data processing and quality control Section 3 Usable diaries Interview respondents selected for the diary x 100 34 Statistics Canada Catalogue no 62F0026M no 1 Appendix V Impact of expenditure imputation on communication services cablevision satellite distribution and security services Text table 1 Impact of expenditure imputation on communication services cablevision satellite distribution and security services Canada 2013 Impact of imputation percentage Landline telephone services 46 4 Cell phone pager and handheld text messaging services 11 6 Rental of cablevision services 58 5 Rental of satellite TV or radio services 23 8 Internet access services 55 0 Home security services 8 3 1 The impact of imputation represents the proportion of the total value of the estimate that is obtained from imputed data Statistics Canada Catalogue no 62F0026M no 1 35 Appendix VI Text table 1 Imputation of dwelling characteristics and household equipment Percentage of households requiring imputation of dwelling characteristics or househo
16. 8 0 01 0 01 0 18 0 02 0 09 0 62 0 11 0 20 1 91 2 22 0 30 0 91 0 07 0 04 1 52 0 10 0 65 0 20 0 50 0 12 0 75 Statistics Canada Catalogue no 62F0026M no 1 37 Appendix VIII Imputation rates by method for recording the expenses in the diary Text table 1 Imputation rates by type of imputation and method for recording the expenses in the section of the diary on Goods and services including food from stores Canada 2013 Type Transcribed Items All of items from a items imputation receipt percentage Imputation of a missing cost for a reported expense Food from stores 2 Other goods and services 3 All expenditures 3 Imputation of expenditure items and their individual cost from a total expense Food from stores Other goods and services All expenditures Imputation of detailed expenditure code Food from stores Other goods and services All expenditures a200 ooo Moo AOR N QNO 2o uii ga Oh QUII EMT ann NNO OND MOwW NON m Ne Text table 2 Imputation rates by type of imputation and method for recording the expenses in the section of the diary on Snacks beverages and meals purchased from restaurants or fast food outlets Canada 2013 Type Transcribed Items All of items from a items imputation receipt percentage Imputation of total cost 1 06 1 00 1 05 Imputation of costs for alcoholic beverages 3 50 6 25 3 89 Imputation of meal type breakfast lunch dinner or sna
17. 8 46 1 Atlantic provinces 2 742 909 467 51 1 315 48 0 Newfoundland and Labrador 718 250 121 10 337 46 9 Prince Edward Island 398 126 73 10 189 47 5 Nova Scotia 849 287 154 18 390 45 9 New Brunswick 777 246 119 13 399 51 4 Quebec 1 205 376 218 18 593 49 2 Ontario 1 300 470 284 15 531 40 8 Prairie provinces 2 513 826 495 36 1 156 46 0 Manitoba 862 284 155 10 413 47 9 Saskatchewan 723 237 141 13 332 45 9 Alberta 928 305 199 13 411 44 3 British Columbia 1 022 323 226 20 453 44 3 The eligible sampled households are those selected to fill out the diary Includes interview No contacts Refusals and Residual non respondents from households selected to fill out the diary The definition of usable and unusable diaries is given in the Data processing and quality control Section Usable diaries Eligible sampled households x 100 EOD The response rate varies from month to month Monthly response rates for the interview and diary can be found in Appendix Il Interview and diary response rates by size of area of residence and dwelling type can be found in Appendix Ill 12 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series The diary response rate of interview respondents can be found in Appendix IV broken down by various households characteristics including household type household tenure age of the reference person and before tax income quintile Cases in which the respondent fails
18. Catalogue no 62F0026M no 1 ISSN 1708 8879 ISBN 978 1 100 25563 7 Household Expenditures Research Paper Series User Guide for the Survey of Household Spending 2013 Income Statistics Division Telephone 613 951 7355 ivi pea mum exu Canada How to obtain more information For more information about survey results and related products and services contact Client Services 613 951 7355 1 888 297 7355 fax 613 951 3012 income statcan gc ca Income Statistics Division For information about this product or the wide range of services and data available from Statistics Canada visit our website www statcan gc ca You can also contact us by e mail at infostats statcan gc ca telephone from Monday to Friday 8 30 a m to 4 30 p m at the following toll free numbers Statistical Information Service 1 800 263 1136 National telecommunications device for the hearing impaired 1 800 363 7629 Faxline 1 877 287 4369 Depository Services Program Inquiries line 1 800 635 7943 Faxline 1 800 565 7757 To access this product This product Catalogue no 62F0026M is available free in electronic format To obtain a single issue visit our website www statcan gc ca and browse by Key resource gt Publications Standards of service to the public Statistics Canada is committed to serving its clients in a prompt reliable and courteous manner To this end this agency has developed standards of service that its employ
19. Response rate percentage 67 2 67 0 68 1 67 9 67 3 0 0 Response rate percentage 46 1 46 7 48 3 44 1 45 6 0 0 Appendix IV Diary response rates among the respondents to the interview by various household characteristics Text table 1 Diary response rates among the respondents to the interview by household type Canada 2013 All household types One person household Couple without children Couple with children Couple with other related or unrelated persons Lone parent household with no additional persons Other household with related or unrelated persons 1 Interview respondents from households selected to fill out the diary Interview respondents 5 878 1 596 1 783 1 495 233 428 343 Refusal number 1 690 501 423 425 72 147 122 Diaries 2 Unusable Usable 140 4 048 42 1 053 32 1 328 27 1 043 4 157 18 263 17 204 2 The definition of usable and unusable diaries is given in the Data processing and quality control Section 3 Usable diaries Interview respondents selected for the diary x 100 Text table 2 Diary response rates among the respondents to the interview by household tenure Canada 2013 All household tenures Owner without mortgage Owner with mortgage Renter with or without rent paid 1 Interview respondents from households selected to fill out the diary Interview respondents 1 5 878 2 116 2 015 1 747 Refusal number 1 690 530
20. able 1 Interview response rates Canada and provinces 2013 Eligible No Refusals Residual Respondents Response sampled contacts non respondents rate households number percentage Canada 17 389 1 158 3 911 634 11 686 67 2 Atlantic provinces 5 420 295 1 239 236 3 650 67 3 Newfoundland and Labrador 1 417 94 352 43 928 65 5 Prince Edward Island 790 28 173 36 553 70 0 Nova Scotia 1 679 73 405 88 1 113 66 3 New Brunswick 1 534 100 309 69 1 056 68 8 Quebec 2 374 102 550 73 1 649 69 5 Ontario 2 567 195 612 124 1 636 63 7 Prairie provinces 5 013 413 1 049 141 3 410 68 0 Manitoba 1 725 135 354 56 1 180 68 4 Saskatchewan 1 447 131 300 46 970 67 0 Alberta 1 841 147 395 39 1 260 68 4 British Columbia 2 015 153 461 60 1 341 66 6 1 Respondent households Eligible sampled households x 100 Some of the households selected to fill out a diary did not complete it or provided a diary that was considered unusable under the criteria set out in section 2 5 For the 2013 SHS the diary response rate among the households selected to fill out a diary having completed the interview is 68 9 and provincial rates are given in Appendix The final diary response rate is 46 1 nationally and provincial rates are shown in Table 2 Text table 2 Diary response rates Canada and provinces 2013 Eligible Interview Diaries 3 Response sampled _non respondents Refusal Unusabe Usable Unusable Usable rate households number percentage Canada 8 782 2 904 1 690 140 4 04
21. ation A number of edits are also carried out on the diary data when the diaries are received at Head Office and throughout the capture and coding steps For example checks are carried out to ensure that the start and end dates of the reference period of the diary are indicated that the reported expenditures were made during the specified reference period and that there are no items that appear in both the data recorded in the diary and the receipts provided by the respondent After validation capture and coding quality control procedures are applied A sample of diaries is selected and completely rechecked to ensure that the diaries were captured and coded as specified in the procedures 6 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series Then a series of detailed edits are performed on all diaries Invalid responses are corrected or flagged for imputation The final step is to assess whether the information reported in the diaries is of sufficient quality using parameters which differ according to the household characteristics The reported expenditures and number of items are compared with minimum thresholds estimated for each geographic area Atlantic Provinces Quebec Ontario Prairie Provinces and British Columbia each household income class and each household size Diaries that satisfy the conditions are deemed usable The other diaries are examined They will be deemed usable if there is a
22. by the average household size found on the second line of Table 11 For example the average food expenditure per person for renter households is calculated as follows Figure 2 Average food expenditure per person for renter households Average food expenditure per person for renter households Average food expenditure per renter household Average size of renter households Example 5 642 2 05 2 752 When comparing estimates of average expenditure per person note that household composition number of children and adults is a significant factor in many expenditure patterns Statistics Canada Catalogue no 62F0026M no 1 25 Household Expenditures Research Paper Series 5 4 2 How to calculate percentages of total average household expenditure budget shares To calculate the budget share of an individual expenditure category as a percentage of total average household expenditure divide the average expenditure per household for that expenditure category by the total average expenditure per household and then multiply by 100 For example using the Table 12 the percentage of total average expenditure per household represented by the average expenditures on food per household for renter households is calculated as follows Figure 3 Percentage of total average expenditure per household Percentage of total average expenditure per household represented by the average expenditures on food per household for renter h
23. calculate the average expenditure for multiple columns calculate the aggregate expenditure for each of the columns for an expenditure category from the average expenditure Table 12 add them and then divide the total by the sum of the estimated number of households in those columns in Table 11 For example the average expenditure on food per owner household with or without a mortgage is calculated as follows Figure 4 Average expenditure on food per owner household Average expenditure on food per owner household with or without a mortgage Average expenditure on food per owner household with a mortgage x Estimated number of owner households with mortgage Average expenditure on food per mortgage free owner household x Estimated number of mortgage free owner households Estimated number of owner households with a mortgage Estimated number of mortgage free owner households Example 9 234 x 4 812 813 8 465 x 4 219 949 4 812 813 4 219 949 8 875 5 4 7 Calculating the expenditure share of a subgroup among all households An expenditure share is the percentage of the aggregate expenditure for an expenditure category that can be attributed to a particular subgroup of households e g the percentage of all food expenditures made by renter households It is calculated by deriving the household subgroup s aggregate expenditure for an expenditure category and dividing it by the aggregate expenditure for the ex
24. ck and beverages 8 58 7 18 8 38 38 Statistics Canada Catalogue no 62F0026M no 1 Appendix IX Estimated number of households and average household size by domain Text table 1 Estimated number of households and average household size by domain defined at the national level Canada 2013 Domain Canada All classes Region Atlantic Region Quebec Ontario Prairie Region British Columbia Province Newfoundland and Labrador Prince Edward Island Nova Scotia New Brunswick Quebec Ontario Manitoba Saskatchewan Alberta British Columbia Before tax household income quintile national Lowest quintile Second quintile Third quintile Fourth quintile Highest quintile Household type One person households Couples without children Couples with children Couples with other related or unrelated persons Lone parent households with no additional persons Other households with related or unrelated persons Household tenure Owner Owner with mortgage Owner without mortgage Renter Size of area of residence Population centre 1 000 000 and over Population centre 500 000 to 999 999 Population centre 250 000 to 499 999 Population centre 100 000 to 249 999 Population centre 30 000 to 99 999 Population centre 1 000 to 29 999 Rural Age of reference person Less than 30 years 30 to 39 years 40 to 54 years 55 to 64 years 65 years and over Subtotals may not add up to the total due to rounding Estimated number of households
25. cks unspecified Parts and supplies for automobiles mini vans and trucks unspecified Transportation unspecified Health care supplies and equipment unspecified Medicine unspecified Eye care goods and services unspecified Medical services unspecified Personal care supplies and equipment unspecified Massage Unspecified Personal care services unspecified Video game systems and parts unspecified Camera and accessories unspecified Operation of recreational vehicle unspecified Digital download unpsecified Electronics unspecified Entertainment unspecified Movies unspecified Recreational goods and services unspecified Magazines unspecified Newspapers unspecified Printed matter unspecified Tuition fees unspecified Tobacco products unspecified Alcoholic Beverages purchased from store unspecified Games of chance unspecified Services unspecified Goods unspecified Gift unspecified Baby goods unspecified Repairs renovations and maintenance of home unspecified Utilities unspecified Taxes unspecified Gifts of money unspecified Gifts of money and other support payments to persons unspecified Donations unspecified Insurance unspecified Other goods and services unspecified Tips unspecified Don t know percentage 43 65 10 52 10 53 2 40 3 72 0 58 0 33 0 01 0 35 0 33 0 45 0 38 0 68 0 01 0 26 0 98 1 20 1 00 0 28 0 12 0 10 1 27 0 05 0 12 2 18 0 08 0 12 0 12 0 02 0 01 0 29 0 21 0 51 0 57 0 0
26. d monthly the sample is divided into 12 subsamples of similar size During that process the SHS sample is coordinated with the samples of the LFS and to a lesser extent the Canadian Community Health Survey CCHS which use the same sampling frame and conduct personal interviews for part of their sample Coordination means that wherever possible if a cluster is selected for more than one survey collection for the surveys will take place in the same month This will enable the interviewerto become familiar with the neighbourhood collect the data and carry out the necessary follow up for more than one survey at a time Statistics Canada Catalogue no 62F0026M no 1 5 Household Expenditures Research Paper Series 2 4 Data collection The SHS is a voluntary survey For the most part the data are obtained directly from the respondent by combining two collection modes a personal interview conducted by an interviewer using a questionnaire on a laptop and a diary in which the household is required to report its daily expenditures over a two week period The data were collected on a continuous basis from January to December 2013 from a sample of households spread over 12 monthly collection cycles First households in the sample are asked to complete a questionnaire that for the most part collects regular expenditures such as rent and electricity and less frequent expenditures such as furniture and dwelling repairs for a reference period t
27. d using a hierarchical system of more than 200 expenditure codes For some reported expenditure items the food product may have been known e g dairy products or even milk but the level of detail required e g skim milk 1 milk or 2 milk had to be imputed This type of imputation gives rise to a risk of bias only in expenditure estimates at a very detailed level In other cases however almost no information on the type of expenditure was available before imputation e g it was known only that the expenditure was for a good When so little information is available the risks of bias in the estimates of the expenditure categories are more significant Additional results regarding the imputation of expenditure codes that are more detailed can be found in Appendix VII which contains a breakdown of the imputed expenditure codes by the initial level of the information from the respondent Restaurant expenditures are reported using a slightly different format in the second section of the diary Imputation is used primarily to assign a value when the total amount of the restaurant expenditure or the cost of alcoholic beverages is missing or when the type of meal breakfast lunch dinner or snack and beverage has not been specified The imputation rate for each of these three types of imputation is shown in Table 5 14 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series Text table 5 Imputation rate
28. ding to provincial quintiles By default the estimate of the number of households for any aggregation of these domains also results in equivalent estimates For any other domain an estimate of the number of households may differ somewhat depending on the reliability of these estimates The estimate of the number of households in the SHS tables has been produced using interview weights as opposed to diary weights The average household size is also produced from the interview weights The estimated number of households and the average household size of the various domains for which estimates are produced in CANSIM tables are available in Appendix IX 5 2 Estimates of average expenditure per household Estimates using both interview and diary expenditure data are produced in two steps estimates are produced separately from the interview and the diary and then they are added together For average expenditure per household the interview average expenditure per household is calculated using the weighted sum of expenditure data obtained from the interview divided by the sum of the interview weights Similarly the diary average expenditure per household is estimated using the weighted sum of expenditure data obtained from the diary divided by the sum of the diary weights The two components are then added to obtain the average expenditure per household With this approach the combined interview and diary average expenditure per household does not e
29. ee highest personal income classes based on the 95 5th 97th and 98 5th percentiles for each province except Prince Edward Island where one income class is used This adjustment aims to compensate for the under representation of these groups among the survey respondents The diary weights are also subject to a series of adjustments A factor adjusts for the nonresponse to the questionnaire Another factor compensates for households that respond to the questionnaire but refuse to complete the diary The weights are also adjusted to demographic estimates in a manner similar to that used for the interview weights Indeed the demographic estimates of the number of persons at the provincial level are the same However at the census metropolitan area level the distinction between the two age groups 0 to 17 and 18 and over is retained only for Montreal Toronto and Vancouver and for SHS 2013 no adjustment was done for Calgary As for the number of households the weights are adjusted to annual provincial estimates for the three household size categories as done for the interview but no quarterly adjustments are made The diary weights are also adjusted in function of the income However instead of adjusting on wages and salaries T4 the weights are adjusted to the estimated number of households per income group by province calculated from the interview data Specifically the estimated number of households for each provincial quintile of total househ
30. ees observe To obtain a copy of these service standards please contact Statistics Canada toll free at 1 800 263 1136 The service standards are also published at www statcan gc ca under About us gt The agency gt Providing services to Canadians Statistics Canada Income Statistics Division User Guide for the Survey of Household Spending 2013 Published by authority of the Minister responsible for Statistics Canada O Minister of Industry 2015 All rights reserved Use of this publication is governed by the Statistics Canada Open License Agreement http www statcan gc ca reference licence eng html January 2015 Catalogue no 62F0026M no 1 ISSN 1708 8879 ISBN 978 1 100 25563 7 Frequency Occasional Ottawa Cette publication est galement disponible en frangais Note of appreciation Canada owes the success of its statistical system to a long standing partnership between Statistics Canada the citizens of Canada its businesses governments and other institutions Accurate and timely statistical information could not be produced without their continued cooperation and goodwill User information Symbols The following standard symbols are used in Statistics Canada publications Os not available for any reference period not available for a specific reference period not applicable true zero or a value rounded to zero value rounded to 0 zero where there is a meaningful distinc
31. elated persons Lone parent households are households where the reference person has no spouse at the time of the interview and there is at least one child never married son daughter or foster child of the reference person The lone parent households for which data are presented do not include any additional persons Other households are households composed of relatives only or households having at least one household member who is unrelated to the reference person e g lodger roommate employee Relatives may include son daughter or foster child of the reference person whose marital status is other than single never married relatives of the reference person by birth or marriage not spouse son daughter or foster child Statistics Canada Catalogue no 62F0026M no 1 21 Household Expenditures Research Paper Series 4 6 6 Size of area of residence Sampled dwellings are assigned to the following groups depending on the area in which they are located according to the 2006 Census boundaries and population size Population centres 1 000 000 and over 500 000 to 999 999 250 000 to 499 999 100 000 to 249 999 30 000 to 99 999 1 000 to 29 999 Rural 4 6 7 Population centre Area with a population of at least 1 000 or more and a density of 400 or more people per square kilometre Population centres are classified as either small medium or large as defined below Small population centre 1 000 to 29 999
32. ember 31st 2013 4 1 2 Household A person or group of persons occupying one dwelling unit is defined as a household The number of households therefore equals the number of occupied dwellings 4 1 3 Household member A person usually residing in the dwelling unit at the time of the interview Statistics Canada Catalogue no 62F0026M no 1 15 Household Expenditures Research Paper Series 4 1 4 Reference person The household member being interviewed chooses which household member should be listed as the reference person after hearing the following definition The household reference person is the member of the household mainly responsible for its financial maintenance e g pays the rent mortgage property taxes and electricity When members of the household share the responsibility equally choose one of these members to be shown as the reference person This person must be a member of the household at the time of the interview 4 1 5 Expenditures The net cost of all goods and services received for private use within a given period for example 1 3 or 12 months whether or not the goods or services were paid for during that period and regardless of whether these expenditures were made in Canada or abroad Business expenditures are excluded 4 1 6 Taxes included All expenditures include the Goods and Services Tax provincial retail sales taxes tips customs duties and any other additional charges or taxes 4 1 7
33. ependent auxiliary sources The first source is the number of persons by age group and the number of households by household size from population estimates produced by the Demography Division using data from the 2006 Census Annual estimates of the number of persons in eight age groups 0 6 7 17 18 24 25 34 35 44 45 54 55 64 and 65 are used at the provincial level and two age groups 0 17 and 18 at the census metropolitan area level For the number of households the weights are calibrated to the annual provincial estimates for three household size categories one two and three or more persons An adjustment is also done to ensure that each quarter is adequately represented in terms of the total number of households The second source is the Statement of Remuneration Paid T4 data from the Canada Revenue Agency CRA which ensure that the survey s weighted distribution of income on the basis of wages and salaries agree with the income distribution of the Canadian population Interview weights are therefore calibrated to the T4 accounts of the number of persons per province in six categories of wages and salaries on the basis of provincial percentiles Oth 25th 25th 50th 50th 65th 65th 75th 75th 95th and 95th 1 00th Starting with SHS 2012 a third source for totals is provided by the personal income tax data T1 from the CRA The interview weights are adjusted to reflect the number of persons in each of the thr
34. es Households have the option of providing receipts to reduce the amount of information recorded in the diary However they are asked to write out additional information on the receipt if the description is incomplete Telephone follow up is carried out a few days after the interview to find out if the respondent has any questions about the diary and to reiterate important information about how to complete it At the end of the two week period the interviewer returns to the respondent s residence to pick up the diary and ask a few additional questions to help the respondent report expenditures that he or she might have forgotten The diaries and all receipts supplied by respondents are scanned and captured at Statistics Canada s Head Office An expenditure classification code is assigned to each item from a list of more than 650 different codes 2 5 Data processing and quality control The computerized questionnaire contains many features designed to maximize the quality of the data collected Many edits are built into the questionnaire to compare the reported data with unusual values and detect logical inconsistencies When an edit fails the interviewer is prompted to correct the information with the respondent s help if necessary Once the data are transmitted to Head Office a comprehensive series of processing steps is undertaken for the purpose of detailed verification of each questionnaire Invalid responses are corrected or flagged for imput
35. eses estimates based on the 2006 Census data due to the break in the data series starting with the 2010 SHS see section 2 9 2 9 Comparability over time The SHS has been conducted each year since 1997 This survey includes most of the content of its predecessors the periodic Family Expenditure Survey and the Household Facilities and Equipment Survey Some changes to the methodology and definitions were made between 1997 and 2009 but the SHS was primarily based on an interview during the first quarter of the year in which households reported expenditures incurred in the preceding calendar year A new methodology which combines a questionnaire and a diary to collect the household expenditures was introduced for the 2010 survey The reference periods have been reduced for many expenditure items and collection is continuous throughout the year Although the expenditure data collected since 2010 are similar to those of previous years the changes to data collection processing and estimation methods have created a break in the data series As a result caution should be used in comparing SHS data since 2010 with previous years unless otherwise noted Since 2010 the SHS incorporates a significant amount of content from the Food Expenditure Survey FES last conducted in 2001 Although there are some differences between the SHS and FES methodologies food expenditure data in both surveys have been collected using a daily expenditure diary that househ
36. espondent may have reported a particular expenditure item without its cost or given the total amount spent on groceries for example without listing the individual items Imputation is also used to enhance the level of detail in coding the items reported For example the information provided by the respondent may simply indicate that a bakery product was purchased but a more detailed code is required to meet the survey s needs In this case donor imputation is used to impute the type of bakery product bread crackers cookies cakes and other pastries etc Diary imputation is carried out at the reported item level and the characteristics most often used to identify the donor are cost available partial code household income and household size Imputation is done by province and quarter to control for provincial differences and seasonality of expenditures Starting in 2012 the imputation method was refined to use supplementary information on the type of store where the purchases were made to produce detailed expenditures when a respondent has only provided a total amount in their diary This method takes into account the increasing amount of grocery products sold in large chain stores that do not specialize in groceries For personal income tax data missing or invalid data are generally donor imputed Income and expenditure imputation is performed primarily with Statistics Canada s Canadian Census Edit and Imputation System CANCEIS After
37. ethodology data quality and other relevant research related to household expenditures from the Survey of Household Spending 62F0026MIE Household Expenditures Research Paper Series 6 3 Custom tabulations For clients with more specialized data needs custom tabulations can be produced on a cost recovery basis Custom tabulations can be produced to your specifications on a contract basis subject to confidentiality restrictions Aggregate data at the detailed expenditure level are also available on a custom basis 7 References 1 Charlebois J and Dubreuil G 2011 Variance Estimation for the Redesigned Survey of Household Spending Proceedings of the Survey Methods Section Statistical Society of Canada Annual Meeting June 2011 28 Statistics Canada Catalogue no 62F0026M no 1 Appendix Diary response rates among the respondents to the interview Text table 1 Diary response rates among the respondents to the interview Canada and provinces 2013 Diaries Interview respondents 1 Refusal Unusable Usable Response rate Canada 5 878 Atlantic provinces 1 833 Newfoundland and Labrador 468 Prince Edward Island 272 Nova Scotia 562 New Brunswick 531 Quebec 829 Ontario 830 Prairie provinces 1 687 Manitoba 578 Saskatchewan 486 Alberta 623 British Columbia 699 number 1 690 467 121 73 154 119 218 284 495 155 141 199 226 140 51 10 18 13 18 15 36 10 13 20 4 048 1
38. f households based on the diary weights from Table 9 we could derive the weighted sum of expenditures We then get Average expenditure on food per renter household x Estimated number of renter households Example 5 642 x 4 513 374 25 464 456 108 The estimates of aggregate expenditure are exact for all domains for which the sum of interview and diary weights are the same see section 5 1 as well as for all variables coming from the interview questionnaire All other estimates for which we have to derive aggregate expenditure are approximated by default if the aggregate expenditure is approximated 26 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series 5 4 5 Calculating aggregate expenditures by combining data columns To calculate aggregate expenditures for multiple columns calculate the aggregate expenditure for each of the columns for an expenditure category and add them after For example aggregate expenditure on food by owner households with or without a mortgage is calculated as follows Average expenditure on food per owner household with a mortgage x Estimated number of owner households with mortgage Average expenditure on food per mortgage free owner household x Estimated number of mortgage free owner households Example 9 234 x 4 812 813 8 465 x 4 219 949 80 163 383 527 5 4 6 How to calculate average expenditures per household by combining data columns To
39. ge trips Includes at least two components such as transportation and accommodation or accommodation with food and beverages 4 3 16 Tobacco products and smokers supplies Includes cigarettes tobacco cigars matches pipes lighters ashtrays cigarette papers and tubes and other smokers supplies 18 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series 4 3 17 Alcoholic beverages Includes alcoholic beverages purchased from stores and restaurants Expenditures on supplies and fees for self made beer wine or liquor are also included 4 3 18 Games of chance Expenditures on all types of games of chance The expenditures are not net of the winnings from these games 4 3 19 Discounts and refunds Presented in the data tables as negative expenditures since they represent a flow of money into the household instead of out of it 4 3 20 Income taxes The sum of federal and provincial income taxes payable for the taxation year prior to the reference year of the survey Income taxes include taxes on income capital gains and RRSP withdrawals after taking into account exemptions deductions non refundable tax credits and the refundable Quebec abatement 4 4 Dwelling characteristics 4 4 1 Type of dwelling Type of dwelling in which the household resided at the time of interview A dwelling is a structurally separate set of living premises with a private entrance from outside the building
40. hat varies in length depending on the type of expenditure For regular expenditures the last payment method is usually used It involves collecting the amount of the last payment and the period it covered For the other types of expenditures collected in the interview reference periods of one month three months or twelve months are generally used The periods are defined in terms of months preceding the month of the interview For example for a household in the June sample the past three months means the period from March 1 to May 31 2013 The demographic characteristics dwelling characteristics and household equipment which are also collected in the interview relate to the household s situation at the time of the interview Starting in 2013 respondents are informed that the survey data will be combined with tax data to obtain some variables related to personal income Personal income tax data from household members aged 16 and over correspond to the calendar year prior to the Survey year Fifty percent of sampled households are selected to also complete an expenditure diary Following the interview respondents of this subsample are asked to record the expenditures of all household members in a daily expenditure diary for a period of two weeks starting the day after the interview Households are required to include all their spending except a few types of expenditures such as rent regular utilities payments and real estate and vehicle purchas
41. ht fixtures and switches cracked or broken panes leaking sinks missing shingles or siding and peeling paint Statistics Canada Catalogue no 62F0026M no 1 19 Household Expenditures Research Paper Series 4 4 3 Tenure Housing status of the household at the time of the interview Owned with mortgage indicates that the dwelling was owned by a household member and that there was a mortgage at the time of the interview Owned without mortgage indicates that the dwelling was owned by a household member and that there was no mortgage at the time of the interview Rented indicates that the dwelling was rented by the household or occupied rent free at the time of the interview 4 4 4 Number of bathrooms for dwelling occupied at the time of the interview Number of rooms in the dwelling with an installed bathtub and or shower 4 5 Household equipment 4 5 1 Telephone includes business use Includes telephones used for business if the business is conducted in the dwelling Cordless phones are also included 4 5 2 Cellular telephone Includes cellular telephones and handheld text messaging devices with cell phone capability 4 5 3 Compact disc player A compact disc player may be a separate unit part of a component or built in as in a receiver cassette recorder compact disc combination unit 4 5 4 Home computer Excludes computers used exclusively for business purposes 4 5 5 Internet use from home Indicates whe
42. iability for an expenditure item is the difference between members of the population in spending on that item In general the greater the differences between households the larger the sampling error will be 10 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series A common measure of sampling error is the standard error SE The SE is the degree of variation in the estimates as a result of selecting one particular sample over another The SE expressed as a percentage of the estimate is called the coefficient of variation CV The CV is used to indicate the degree of uncertainty associated with an estimate For example if the estimated number of households having a given dwelling characteristic is 10 000 with a CV of 5 then the actual number is between 9 500 and 10 500 households 68 of the time and between 9 000 and 11 000 households 95 of the time The standard errors for the SHS are estimated using the bootstrap method see reference 1 in section 7 CVs are available for the national and provincial estimates as well as for the estimates by household type age of reference person household income quintile household tenure and size of area of residence 3 2 Data suppression To ensure accuracy the estimates for which the CVs have been estimated at more than 3396 have been suppressed However from an operational standpoint when tables are created the suppression rule is based on the number
43. ices for cablevision satellite distribution and security systems 2 Including expenditures related to communication services and services for cablevision satellite distribution and security systems Statistics Canada Catalogue no 62F0026M no 1 13 Household Expenditures Research Paper Series Users of expenditure estimates relating to communication services and cablevision satellite television and security System services should therefore take into account the high level of imputation of the expenditure data if they are examining individual services rather than the combined totals A measure of the impact of imputation on each individual service has been produced and is discussed in Appendix V This measure represents the proportion of the total value of the estimate obtained from imputed data The percentages of households that responded to the interview and for which dwelling characteristics or household equipment had to be imputed can be found in Appendix VI The imputation rates for all expenditures reported in the expenditure diary are shown in tables 4 and 5 Table 4 deals with expenditures reported in the first section of the diary on goods and services including food from stores Table 5 shows the imputation rates for the second section of the diary on expenses from restaurants For expenditure data from the diaries imputation is used primarily to assign a value when the amount of a reported expenditure is missing to assign a
44. ld equipment Canada and provinces 2013 Canada Newfoundland and Labrador Prince Edward Island Nova Scotia New Brunswick Quebec Ontario Manitoba Saskatchewan Alberta British Columbia 36 Statistics Canada Catalogue no 62F0026M no 1 Number of variables imputed out of 25 E CD c ED D CAEN OY cl SELON O0 OC 0 0d B2ON 320N2N 325 AROONBDWWADA BOS SOO FON COE OMNDAN ONDO Total 8 8 9 7 12 5 8 7 8 9 7 9 9 2 10 2 5 0 9 9 Appendix VII Breakdown of the imputed expenditure codes by the initial level of the information from the respondent Text table 1 Distribution of imputation of detailed expenditure codes by the initial level of information collected from the section of the diary on Goods and services including food from stores Canada 2013 Initial collected information initial expenditure category Specific food group Food unspecified Grocery item unspecified Non food grocery item unspecified Walmart item unspecified Costco item unspecified Communication equipment and services unspecified Child care unspecified Pet expenses unspecified Garden supplies unspecified Household supplies unspecified Furnishings and decor unspecified Housewares unspecified Home and garden services unspecified Home and garden tools and equipment unspecified Household equipment parts and accessories unspecified Apparel unspecified General repairs for automobiles mini vans and tru
45. list of expenditure items with individual costs when only the total cost was provided e g to assign grocery items and their individual cost when the respondent has provided only the total amount of the bill or to assign an expenditure code that is more detailed than the one that could be assigned using the information from the respondent e g the type of bakery product The imputation rate for each of these three types of imputation is shown in Table 4 Each rate represents the proportion of imputed items out of all the expenditure items from the diaries Text table 4 Imputation rates by type of imputation for the section of the diary on Goods and services including food from stores Canada 2013 Type of Imputation imputation rate percentage Imputation of a missing cost for a reported expense Food from stores Other goods and services All expenditures Imputation of expenditure items and their individual cost from a total expense Food from stores Other goods and services All expenditures Imputation of detailed expenditure code Food from stores Other goods and services All expenditures Aaa Kon NANO NS 2o OND NoN The risks of bias associated with the imputed data depend largely on the level of detail at which the SHS data are used For example food expenditure data in the SHS are produced at a high level of detail to meet the needs of the Food Expenditure Survey users last conducted in 2001 Food expenditures are categorize
46. note explaining their low expenditures or their small number of reported items for example a person living alone who had few expenses to report because he she was on a business trip during the diary recording period Diaries that do not meet the usability criteria are treated the same as non response diaries they are excluded from the estimates It should be noted that some of the usable diaries are incomplete and could have non responded days To solve problems of missing or invalid information in interview questions donor imputation by the nearest neighbour method is generally used Data from another respondent with similar characteristics the donor are used to impute The imputation is done on one group of variables at a time with the groups formed on the basis of the relationships among the variables The characteristics used to identify the donor are selected such that they are correlated with the variables to be imputed Household income dwelling type and number of adults and children are commonly used characteristics For operational reasons the income information from personal income tax data is not available in time for imputation of the survey data Consequently the household income used for imputation is taken from an additional question on total household income that is asked during the interview exclusively for the purpose of data imputation Donor imputation is also used when information is missing from the daily expenditure diary A r
47. of households that declare an expense for an item Indeed there is a relationship between the CV and the number of reporting households and analyses carried out on a very large number of SHS estimates show that a threshold of 30 reporting households generally allows for a CV of at most 3396 for the expenditure estimates However data for suppressed items do contribute to summary level variables For example the expenditure estimate for a particular item of clothing might be suppressed but this amount is included in the total estimate for clothing expenditure 3 3 Non sampling errors Non sampling errors occur because certain factors make it difficult to obtain accurate responses or responses that retain their accuracy throughout processing Unlike sampling errors non sampling errors are not readily quantified Four sources of non sampling error can be identified coverage error response error non response error and processing error 3 3 1 Coverage error Coverage error arises when sampling frame units do not adequately represent the target population This error may occur during sample design or selection or during data collection or processing 3 3 2 Response error Response error occurs when respondents provide inaccurate information This error may be due to many factors including faulty design of the questionnaire misinterpretation of questions by interviewers or respondents or faulty reporting by respondents In general the acc
48. of households 13 514 009 4 812 813 4 219 949 4 481 247 Text table 8 Average household expenditures obtained from interview data by household tenure All Owner Owner Renter households with without mortgage mortgage dollars Shelter 15 210 23 712 9 643 11 320 Household furnishing and equipment 2 027 2 699 2 235 1 115 Clothing and accessories 3 360 4 289 3 268 2 448 Transportation 11 229 14 505 12 389 6 638 5 3 2 Examples of expenditure estimates obtained from diary data Text table 9 Estimated number of households based on diary weights by household tenure All Owner Owner Renter households with without mortgage mortgage number Estimated number of households 13 514 009 4 785 857 4 214 778 4 513 374 Text table 10 Average household expenditures obtained from diary data by household tenure All Owner Owner Renter households with without mortgage mortgage dollars Food expenditures 7 795 9 234 8 465 5 642 Food purchased from stores 5 588 6 583 6 053 4 098 Food purchased from restaurant 2 207 2 652 2 412 1 544 5 3 3 Examples of estimates obtained from both interview and diary expenditure data In Table 11 we present the estimated number of households and the average household size as provided in Appendix IX while Table 12 represents a typical example of an average household expenditures table available to users 24 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series Text table
49. old income is used The adjustment to the interview estimates ensures that the weighted income distribution of diary respondent households is consistent with the weighted income distribution of interview respondent households The diary weights are also adjusted for the number of high income individuals according to personal income tax data similarly to the interview but a single income class based on the 95 5th percentile is used This personal income diary adjustment is not applied to Prince Edward Island however All expenditure variables in the interview and diary are annualized by multiplying them by a factor appropriate for the reference period Some expenditure data are also corrected by an adjustment factor when influential values are identified For the diary another adjustment factor is produced to compensate for the non responded days The estimates for a given expenditure category collected from the interview are therefore the weighted sums using interview weights of the annualized and adjusted amounts The estimates of an expenditure category derived from diary data are calculated in a similar manner using diary weights and the appropriate annualisation and adjustment factors Lastly summary expenditure category estimates that include components from both collection methods are produced by taking the sum of the estimates of the diary and the interview components 8 Statistics Canada Catalogue no 62F0026M no 1 Household Expendit
50. olds are asked to fill in for a period of two weeks The content of the SHS diary is slightly less detailed than that of the FES diary e g the weight and quantity of foods are not collected to limit the SHS respondent s burden The content of the SHS has also been reviewed in 2010 to reduce the time required for the interview A number of components regarding household equipment and dwelling characteristics and most of the questions regarding changes in household assets and liabilities have been dropped Some definitions have also been changed As well starting with the 2010 survey the data related to household income and income tax come mainly from personal income tax data Finally the estimates from 2010 to 2013 are based on weights calibrated to population estimates produced using data from the 2006 Census Estimates in previous years 2001 2009 are based on weights calibrated to population estimates produced using data from the 2001 Census 3 Data quality Like all surveys the SHS is subject to error despite all the precautions taken in each step of the survey to prevent them or reduce their impact There are two types of error sampling and non sampling 3 1 Sampling errors Sampling errors occur because inferences about the entire population are based on information obtained from only a sample of the population The sample design estimation method sample size and data variability determine the size of the sampling error The data var
51. om personal income tax data is also combined with the survey data For expenditure information collected with the questionnaire the length of the reference period depends on the question e g the past month the past three months or the past 12 months The period covered also varies with the collection month e g for households in the January 2013 sample the past 12 months means the period from January 2012 to December 2012 while for households in the December 2013 sample it refers to the months between December 2012 and November 2013 Expenditures collected in the daily expenditure diary are reported for a period of two weeks In general longer reference periods are used for goods and services that are more expensive or purchased infrequently or irregularly On the contrary shorter reference periods are used for goods and services that are of less value or purchased frequently or at regular intervals For demographic characteristics dwelling characteristics and household equipment the reference period is the interview date For income the reference period is the calendar year preceding the survey year i e 2012 for SHS 2013 2 3 The sample design The sample of the 2013 Survey of Household Spending consists of 17 389 households spread over the 10 provinces A stratified multi stage sampling plan was used to select the sample It is generally a two stage plan the first stage being a sample of geographic areas referred to as cl
52. ood suppliers outdoor farmers markets and stands and all other non service establishments The expenditures are net of cash premium vouchers or rebates at the cash register and include deposits paid for at the time of purchase These deposits are excluded from the expenditures when reimbursed and are shown as negative expenditures flow of money in in the Miscellaneous expenditures section 4 3 4 Food purchased from restaurants Restaurants includes full service restaurants fast food outlets cafeterias but also refreshments stands snack bars vending machines mobile canteens caterers and chip wagons Includes tips Does not include expenditures for alcoholic beverages 4 3 5 Shelter Principal accommodation either owned or rented and other accommodation such as vacation homes or accommodation while travelling 4 3 6 Rent Net rent excluding rent paid for business or rooms rented out Includes additional amounts paid to landlord Statistics Canada Catalogue no 62F0026M no 1 17 Household Expenditures Research Paper Series 4 3 7 Tenants Homeowners insurance premiums Premiums paid for fire and comprehensive policies 4 3 8 Repairs and maintenance owned living quarters Covers expenditures for labor and materials for all types of repairs and maintenance including expenditures to repair and maintain built in equipment appliances and fixtures Expenditures related to alterations and improvements are excluded
53. or from a common hall or stairway A single detached dwelling contains only one dwelling unit and is completely separated by open space on all sides from any other structure except its own garage or shed A single attached dwelling is a double or semi detached unit side by side or a row or terrace unit Apartment includes duplexes two dwellings situated one above the other triplexes quadruplexes and apartment buildings Other dwellings include mobile homes motor homes tents railroad cars or houseboats which are used as permanent residences and are capable of being moved on short notice 4 4 2 Repairs needed Indicates the respondent s perception of the repairs the dwelling needed at the time of the interview to restore it to its original condition Remodelling additions conversions or energy improvements that would upgrade the dwelling over and above its original condition are not included Major repairs include serious deficiencies in the structural condition of the dwelling as well as the plumbing electrical and heating systems Examples include corroded pipes damaged electrical wiring sagging floors bulging walls damp walls and ceilings and crumbling foundation Minor repairs include deficiencies in the surface or covering materials ofthe dwelling and less serious deficiencies in the plumbing electrical and heating systems Examples include small cracks in interior walls and ceilings broken lig
54. ouseholds Average expenditure on food per renter household Total average expenditure per renter household amp 109 Example 5 642 x 100 27 163 20 77 5 4 3 Combining expenditure categories into your own groupings The average expenditure per household for different expenditure categories can be added together to make new subtotals For example the average expenditure on shelter and transportation per renter household is calculated as follows Average expenditure on shelter per renter household Average expenditure on transportation per renter household Example 11 320 6 638 17 958 5 4 4 Calculating aggregate expenditures To calculate aggregate expenditures multiply the average expenditure per household from one column for an expenditure category Table 12 by the estimated number of households from the same column in Table 11 For example the aggregate expenditure on food for renter households is calculated as follows Average expenditure on food per renter household x Estimated number of renter households Example 5 642 x 4 481 247 25 283 195 574 Note Since the estimated variable comes from diary data and the estimated number of households in the domains used differs slightly depending on whether it is calculated using interview weights or diary weights the estimate only approximates the estimate that would have been obtained using the weighted sum of expenditures Indeed if we use the estimated number o
55. penditure category for all households and multiplying by 100 Statistics Canada Catalogue no 62F0026M no 1 27 Household Expenditures Research Paper Series For example the percentage of food expenditures made by renter households is calculated as follows Figure 5 Percentage of food expenditures made by renter households Percentage of food expenditures made by renter households Average expenditure on food per renter household x Estimated number of renter households Average expenditure on food per household for all households x Estimated total number of households x 100 Example 5 642 x 4 481 247 x 100 7 795 x 13 514 009 24 00 6 Related products and services 6 1 CANSIM CANSIM the Canadian Socio Economic Information Management System is a data base consisting of multi dimensional cross sectional tables Eight tables presenting annual information from the Survey of Household Spending are available Table 203 0021 presents household detailed level expenditure data while tables 203 0022 to 203 0026 present data according to household income quintile household type household tenure size of area of residence and age of reference person respectively Table 203 0027 presents data on dwelling characteristics and household equipment Finally table 203 0028 provides detailed food expenditure data 6 2 Household Expenditures Research Paper Series This series provides detailed documentation on issues concepts m
56. pulation The target population of the 2013 SHS is the population of Canada s 10 provinces excluding residents of institutions members of the Canadian Forces living in military camps and people living on Indian reserves In all these exclusions make up about 2 of the population of the 10 provinces For operational reasons people living in some remote areas where the rate of vacant dwellings is very high and where the collection cost would be exorbitant are excluded from collection Also excluded in addition to people living in institutions are people living in other types of collective dwellings people living in residences for dependent seniors and people living permanently in school residences work camps etc and members of religious and other communal colonies Collection exclusions make up less than 0 5 of the target population However these people are included in the population estimates to which the SHS estimates are adjusted see section 2 6 4 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series 2 2 The survey content and reference periods The SHS primarily collects detailed information on household expenditures It also collects information about demographic characteristics of the household certain dwelling characteristics e g type age and tenure and certain information on household equipment e g electronics and communications equipment Income information fr
57. s by type of imputation for the section of the diary on Snacks beverages and meals purchased from restaurants or fast food outlets Canada 2013 Type of Imputation imputation rate percentage Imputation of total cost 1 05 Imputation of costs for alcoholic beverages 3 89 Imputation of meal type breakfast lunch dinner or snack and beverages 8 38 Lastly households have the option of providing receipts or recording their expenditure information in the diary Table 6 shows the percentage of expenditures reported using each method for food expenditures restaurant expenditures and other goods and services Text table 6 Methods for recording expenses in the diary Canada 2013 Expenditure Transcriptions Receipts category percentage Food 24 0 76 0 Restaurant 85 8 14 2 Other goods and services 47 5 52 5 Imputation rates vary depending on the expenditure reporting method The rates in tables 4 and 5 are shown by the expenditure reporting method in Appendix VIII 3 4 The effect of large values For any sample estimates of totals averages and standard errors can be affected by the presence or absence of large values in the sample Large values are more likely to arise from positively skewed populations Such values are found in the SHS and are taken into account when the final estimates are generated 4 Definitions 4 1 General concepts 4 1 1 Reference year of the survey Corresponds to the data collection year from January 1st to Dec
58. scholarships bursaries and fellowships wages and salaries before deductions farm self employment net income non farm self employment net income universal child care tax benefit Old Age Security pension CPP and QPP benefits Employment Insurance benefits social assistance workers compensation benefits Federal GST HST Credit provincial tax credits other government transfers private retirement pensions support payments received other taxable income and income from a RDSP and investment income 4 2 6 Homeowner Household living in a dwelling owned with or without a mortgage by a member of the household at the time of the interview 4 3 Selected household expenditures 4 3 1 Total expenditure The sum of total current consumption income taxes personal insurance payments and pension contributions and gifts of money alimony and contributions to charity 4 3 2 Total current consumption Sum of the expenditures for food shelter household operations household furnishings and equipment clothing and accessories transportation health care personal care recreation education reading materials and other printed matter tobacco products and alcoholic beverages games of chance and miscellaneous expenditures 4 3 3 Food purchased from stores Stores includes all establishments where food can be bought such as grocery stores specialty food stores department stores warehouse type stores and convenience stores but also frozen f
59. ther the household has access to the Internet at home 4 5 6 Owned vehicles Number of vehicles automobiles vans and trucks owned by members of the household at the end of the month prior to the time of the interview 4 6 Classification categories 4 6 1 Canada Canada level data for 2013 include the 10 provinces only 4 6 2 Province territory No data for the territories for 2013 20 Statistics Canada Catalogue no 62F0026M no 1 Household Expenditures Research Paper Series 4 6 3 Before tax household income quintile national Income groupings are obtained by ranking the households responding to the interview in ascending order by the total income before tax of the households then partitioning the households into five groups of similar size The estimated number of households in each group should be the same in principle but differences may occur due to the weight of the household at the boundary of two quintiles since this household must lie in either one or the other of these quintiles Moreover the specific methodology of the survey with a series of weights for the interview and another series for the diary ensures that the same estimate of the number of households for the interview and the diary will occur only if the quintiles are defined at the provincial level For the national quintiles there may be a difference between the estimate of the number of households based on either the interview weights or the diary weights
60. tiles 394 321 2 32 Lowest quintile 78 561 1 41 Second quintile 79 064 2 14 Third quintile 78 774 2 22 Fourth quintile 78 589 2 71 Highest quintile 79 331 3 12 New Brunswick All quintiles 313 296 2 33 Lowest quintile 62 630 1 44 Second quintile 62 577 1 98 Third quintile 62 734 2 28 Fourth quintile 62 508 2 83 Highest quintile 62 847 3 12 Quebec All quintiles 3 449 194 2 30 Lowest quintile 688 715 1 33 Second quintile 690 874 1 80 Third quintile 689 698 2 39 Fourth quintile 689 908 2 89 Highest quintile 689 998 3 10 Ontario All quintiles 5 158 934 2 60 Lowest quintile 1 028 500 1 58 Second quintile 1 031 939 2 30 Third quintile 1 034 765 2 53 Fourth quintile 1 029 475 3 08 Highest quintile 1 034 254 3 50 Manitoba All quintiles 478 186 2 49 Lowest quintile 95 529 1 50 Second quintile 95 738 2 15 Third quintile 95 441 2 62 Fourth quintile 95 648 2 87 Highest quintile 95 830 3 31 Saskatchewan All quintiles 420 850 2 42 Lowest quintile 84 047 1 51 Second quintile 84 263 2 06 Third quintile 83 534 2 51 Fourth quintile 84 527 2 85 Highest quintile 84 479 3 15 Alberta All quintiles 1 473 611 2 64 Lowest quintile 294 607 1 58 Second quintile 294 465 2 35 Third quintile 294 231 2 86 Fourth quintile 295 504 3 03 Highest quintile 294 803 3 36 British Columbia All quintiles 1 857 347 2 43 Lowest quintile 368 839 1 46 Second quintile 373 787 2 13 Third quintile 371 329 2 29 Fourth quintile 371 582 2 93 Highest quintile 371
61. tion between true zero and the value that was rounded preliminary revised suppressed to meet the confidentiality requirements of the Statistics Act use with caution too unreliable to be published significantly different from reference category p lt 0 05 2 Statistics Canada Catalogue no 62F0026M no 1 Table of contents User Guide for the Survey of Household Spending 2013 1 Introduction 2 Survey methodology 3 Data quality 4 Definitions 5 Derivation of data tables 6 Related products and services 7 References Appendix Diary response rates among the respondents to the interview II Response rates by collection month Hl Response rates by size of area of residence and by dwelling type IV Diary response rates among the respondents to the interview by various household characteristics V Impact of expenditure imputation on communication services cablevision satellite distribution and security services VI Imputation of dwelling characteristics and household equipment VII Breakdown of the imputed expenditure codes by the initial level of the information from the respondent VIII Imputation rates by method for recording the expenses in the diary IX Estimated number of households and average household size by domain Statistics Canada Catalogue no 62F0026M no 1 10 15 22 28 28 29 30 31 33 35 36 37 38 39 3 User Guide for the Survey of Household Spending 2013 1 Introd
62. tion services telephone cell phone and Internet and cablevision satellite distribution and security system services This distinction has been made because those services are increasingly being purchased as a package Households are often billed for bundled services making it difficult or impossible to provide separate expenditure data for each service Therefore the total amount paid for the package is allocated to individual services through imputation which significantly increases the number of households for which expenditures must be imputed Text table 3 Percentage of households requiring imputation for consumer expenses collected during the interview Canada and provinces 2013 Number of variables imputed out of 179 Number of variables imputed out of 185 1 2109 10 or Total 1 2 to 9 10 or Total more more percentage Canada 19 4 36 9 2 6 58 8 9 8 64 7 4 8 79 3 Newfoundland and Labrador 19 5 32 1 13 52 9 7 3 69 6 3 6 80 5 Prince Edward Island 22 4 31 5 2 0 55 9 9 8 70 2 4 3 84 3 Nova Scotia 19 9 34 9 1 7 56 5 8 1 71 4 4 0 83 5 New Brunswick 20 4 25 1 1 4 46 9 9 4 61 2 3 1 73 7 Quebec 24 1 32 1 2 1 58 3 10 4 67 0 4 2 81 6 Ontario 21 9 34 2 1 4 57 5 14 1 57 0 3 2 74 3 Manitoba 15 5 42 1 6 0 63 6 10 8 58 9 8 6 78 3 Saskatchewan 17 8 36 6 3 0 57 4 8 0 62 9 5 1 76 0 Alberta 16 9 41 5 3 2 61 6 10 3 61 1 54 76 8 British Columbia 14 9 53 8 3 4 72 1 6 7 73 0 6 7 86 4 1 Excluding expenditures related to communication services and serv
63. to answer some of the questions are referred to as partial non response Imputing missing values compensates for this partial non response Imputation rates are described in section 3 3 5 There are also cases in which a household fails to complete the diary for all 14 days as required leaving days with no data Adjustment factors were thus calculated to take into consideration these days with no data 3 3 4 Processing error Processing errors may occur in any of the data processing stages including data entry coding editing imputation of partial non response weighting and tabulation Steps taken to reduce processing error are described in section 2 5 3 3 5 Imputation of partial non response The residual bias remaining after the imputation of partial non response is difficult to measure It depends on the imputation method s ability to produce unbiased estimates The imputation rates provide an indication of the magnitude of partial non response Partial interview non response may result from a lack of information or an invalid response to a question The national and provincial percentages of households for which certain categories of expenditures had to be imputed because of partial interview non response is shown in Table 3 by number of imputed expenditure variables per household out of all consumer expenditure data collected during the interview The table contains two series of results including and excluding expenditures on communica
64. uction This guide presents information of interest to users of data from the 2013 Survey of Household Spending SHS It includes descriptions of the survey methodology and data quality and definitions of survey terms and variables There is also a section describing various statistics that can be drawn from the survey data The SHS is conducted annually The SHS combines a questionnaire with recall periods based on the type of expenditure 1 3 or 12 months last payment four weeks and a daily expenditure diary that selected households complete for two weeks following the interview As well data collection is continuous throughout the year Starting in 2012 the sample size for the expenditure diary was 50 of the total sample The 2013 SHS was conducted from January 2013 to December 2013 using a sample of 17 389 households in the 10 provinces Detailed spending information was collected as well as limited information on dwelling characteristics and household equipment Household expenditure estimates are available for the national and provincial levels and by household tenure age of reference person size of area of residence type of household and household income quintile Detailed estimates on food expenditures are also available For custom tabulations or more information on the SHS please contact Client Services 613 951 7355 1 888 297 7355 or income statcan gc ca Income Statistics Division 2 Survey methodology 2 1 The target po
65. uracy of SHS data depends largely on respondents ability to remember recall household expenditures and their willingness to consult records Response error is the most difficult aspect of data quality to measure 3 3 3 Non response error Errors due to non response occur when potential respondents do not provide the required information or the information they provide is unusable The main impact of non response on data quality is that it can cause a bias in the estimates if the characteristics of respondents and non respondents differ and the difference has an impact on the expenditures studied While non response rates can be calculated they provide only an indication of data quality since they do not measure the bias associated with the estimates The magnitude of non response can be considered a simple indicator of the risks of bias in the estimates Statistics Canada Catalogue no 62F0026M no 1 11 Household Expenditures Research Paper Series For the 2013 SHS the interview response rate is 67 2 and provincial response rates are shown in Table 1 The table also shows the number of non responding households by reason for non response Reasons include the inability to contact the household the household s refusal to participate in the survey and the inability to hold an interview because of special circumstances e g the respondent speaks neither official language or has a physical condition that precludes an interview Text t
66. ures Research Paper Series 2 7 Reference period of the estimates With continuous monthly collection the reference period of the data differs from one month to the other as illustrated in Figure 1 For example for an expenditure item with a three month reference period the data from the July sample covers expenditures made between April 1 and June 30 whereas the data from the December sample covers expenditures made between September 1 and November 30 Figure 1 Monthly sample reference periods of three different lengths Year previous to the survey year JFMAMJJASOND EM reference period One month reference period Three month reference period SHS estimates are produced by combining the data from the 12 monthly collection cycles and by annualizing the expenditures collected over various reference periods in order to standardize them The period covered by the estimates is therefore a function of the length of reference period and of the collection months considered Collection period When combining the data of the 12 collection cycles to generate estimates for expenditure items with short reference periods e g one month the expenditures that are covered occur mostly in the survey year That is also true for all expenditure data collected with the diary As for expenditure items with a 12 month reference period the data collected include expenses occurring between January of the year before the survey year and November of the
67. usters Then a list of all the dwellings in the selected clusters is prepared and a sample of dwellings is selected The selected dwellings that are inhabited by members of the target population constitute the survey s sample of households The SHS uses a number of components of the Labour Force Survey s LFS sample design to minimize operating costs though the dwellings selected are different Fifty percent of sampled households are selected to receive an expenditure diary Thus in each selected cluster a subsample of the previously chosen dwellings is selected in order to identify the dwellings for which the households will be asked to fill out a diary The national sample is first divided among the provinces on the basis of the variability of total household expenditures and to a lesser extent the number of households in each province The goal is to obtain estimates of similar quality at the provincial level The sample sizes for the provinces are shown in Table 1 in Section 3 The sample is then divided among the strata defined by grouping clusters with similar characteristics based on a number of socio demographic variables Some strata were defined to target specific subpopulations such as the high income household strata To improve the quality of the estimates the high income household strata are allocated a larger share of the sample than the other strata where an allocation proportional to stratum size is used Since data are collecte
68. xactly match the combined interview and diary weighted sum of expenditure divided by the estimated number of households produced using the interview weights for domains in which the interview and diary estimates do not match Nevertheless the approach ensures that the sum of the average expenditure per household for all categories equals the total average expenditure per household 5 3 Examples of expenditure estimates The tables in this section contain examples of expenditure estimates produced separately from interview and from diary data as well as an example of expenditure estimates where interview and diary data have to be combined 5 3 1 Examples of expenditure estimates obtained from interview data The CANSIM tables include estimates of average expenditure per household For technical reasons the estimated number of households and the average household size are not included in these tables but are provided in Appendix IX In this document we present an example of the estimated number of households in Table 7 associated with estimates of average expenditure per household from Table 8 in order to help in the understanding of the subsequent examples Statistics Canada Catalogue no 62F0026M no 1 23 Household Expenditures Research Paper Series Text table 7 Estimated number of households based on interview weights by household tenure All Owner Owner Renter households with without mortgage mortgage number Estimated number

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