Proportions for RTRA

Basic Proportions for RTRA

1. The RTRA proportion procedure calculates the population distribution of a discrete variable. For example, this procedure can be used to calculate the proportion of the population living with asthma. To generate a proportion, call the following RTRA procedure:

%RTRAProportion(
InputDataset=,
OutputName=,
ClassVarList=,
ByVar=,
UserWeight=);

2. %RTRAProportion parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files you want returned (maximum of 20 characters and the first character must be a letter).

ClassVarList = identify a maximum of four variables for the dimensions of the proportion procedure. These variables need to be delimited by spaces or asterisks. Each variable must contain more than one but no more than 500 unique values. This parameter may be left empty if you wish to calculate a proportion for the entire population.

ByVar = identify exactly one variable for the proportion procedure. This variable must contain more than one but no more than 500 unique values. Your population distribution will be calculated on this discrete variable.

UserWeight= refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged to the InputDataset using the ID variable.

3. Example: This procedure can be used to calculate the proportion of population living with asthma. Suppose you ran the following RTRA procedure to calculate a proportion of a variable called "Asthma" to generate a table named "Table1". You would like to calculate this proportion for each gender using variable called "Sex".

%RTRAProportion(
InputDataset=work.CCHS,
OutputName=Table1,
ClassVarList=Sex,
ByVar=Asthma,
UserWeight=Finalwt);

The following table displays results from the example procedure above.

Table 1
Results from example procedure
Sex	Asthma	_Proportion_	_Count_
			200
	Yes	0.10	20
	No	0.90	180
Female			110
Female	Yes	0.09	10
Female	No	0.91	100
Male			90
Male	Yes	0.11	10
Male	No	0.89	80

L5 Proportions for RTRA

1. This is the RTRA procedure macro for producing Proportion tabulations which include a selected Level 5 statistic. The RTRA proportion procedure calculates the population distribution of a discrete variable. For example, this procedure can be used to calculate the proportion of the population living with asthma. To generate a proportion, call the following RTRA procedure:

%RTRAProportionL5(
InputDataset=,
OutputName=,
ClassVarList=,
ByVar=,
L5Stat=,
L5Type=,
L5ByVar=,
L5BaseVal=,
UserWeight=);

2. %RTRAProportionL5 parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name that is given to the final output files corresponding to this call to RTRAProportionL5. The tabulated results output data set is assigned an internally generates name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names.

ClassVarList = identify a maximum of four variables for the dimensions of the proportion procedure. For RTRAProportionL5, it is valid to omit this parameter or specify blank. Variables in the list can be separated by any number of spaces, asterisks or combination of spaces and asterisks.

ByVar = identifies the name of the BY variable and is used as the share variable. It is also appended to the class variable list in CreateEngineXML.

L5Stat = identifies the name of the Level 5 statistic. Valid values are LC and ST (case insensitive).

L5Type = identifies the Level 5 statistic type. Valid values are SEQUENTIAL, BASE and GLOBAL (case insensitive).

L5ByVar = identifies the Level 5 BY variable. The specified variable must either exist in <classVarList> or be the same as <byVar>.

L5BaseVal = identifies the Level 5 base value. This parameter is only applicable if <L5Type> is BASE and must be blank if <L5Type> is SEQUENTIAL or GLOBAL. If applicable, the specified value must exist in the variable <L5ByVar> in the input data set.

UserWeight = the survey weight variable (and bootstrap weight variables if they exist) is located in a weights data set in the RTRA data library. The name of the weights data set is the same as the name of the survey weight variable that it contains.

3. Example: This procedure can be used to calculate the proportion of the population that has had a particular medical procedure completed.

Your RTRA procedure call will look like this:

%RTRAProportionL5(
InputDataset=work.ccs_asy,
OutputName=Table2,
ClassVarList=DHH_SEX,
byVar=either_sc,
L5Stat=LC,
L5Type=sequential,
L5ByVar=either_sc,
UserWeight=wts_m);

The following table displays results from the example L5 Proportions procedure above. For this example, either_sc refers to a "yes" or "no" answer as to whether or not an individual has had the particular medical procedure. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs.

Table 2
Results from example procedure
DHH_SEX	EITHER_SC	PROPORTION	PROPORTION_LCS	COUNT
Male	Yes	0.52	0.044	10500
Male	Yes	0.4	-0.194	50500
Male	No	0.63	0	43000
Male	No	0.48	0	9750
Female	Yes	0.27	-0.46	21250
Female	Yes	0.48	-0.041	9750
Female	No	0.73	0	57250
Female	No	0.52	0	10750

L5SOT Proportions for RTRA

This is the RTRA procedure macro for producing Proportion tabulations which include a selected Level 5 Sequential Over Time (L5SOT) statistic. The RTRA proportion procedure calculates the population distribution of a discrete variable. For example, this procedure can be used to calculate the proportion of the population living with asthma. To generate a proportion, call the following RTRA procedure:

%RTRAProportionL5SOT(
InputDataset=,
OutputName=,
ClassVarList=,
ByVar=,
L5Stat=,
L5YrVar=,
L5MonVar=,
L5QtrVar=,
L5TimeInt=,
UserWeight=);

2. %RTRAProportionL5SOT parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name that is given to the final output files corresponding to this call to RTRAProportionL5SOT. The tabulated results output data set is assigned an internally generates name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names.

ClassVarList = identify a maximum of four variables for the dimensions of the proportion procedure. These variables need to be delimited by spaces or asterisks. Each variable must contain more than one but no more than 500 unique values. It is valid to omit this parameter or specify blank.

ByVar = identifies the name of the BY variable and is used as the share variable. It is also appended to the class variable list in CreateEngineXML.

L5Stat = identifies the name of the Level 5 statistic. Valid values are LC, PC and ST (case insensitive).

L5YrVar= identifies the Level 5 year variable.

L5MonVar = (optional) identifies the Level 5 month variable. Valid to omit this parameter or specify blank. If L5MonVar is specified then L5 QtrVar must be blank or omitted.

L5QtrVar = (optional) identifies the Level 5 quarter variable. Valid to omit this parameter or specify blank. If L5 QtrVar is specified then L5MonVar must be blank or omitted.

L5TimeInt= (optional) identifies the Level 5 time interval. Value specified must be an integer greater than 0. Valid to omit this parameter but default integer must be 1.

UserWeight = Refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged to the InputDataset using the ID variable.

3. Example: This procedure can be used to calculate the proportion of the population that has had a particular medical procedure completed.

Your RTRA procedure call will look like this:

%RTRAProportionL5SOT(
InputDataset=work.ccs_asy,
OutputName=Table3,
ClassVarList=DHH_SEX,
L5Stat=LC,
L5YrVar=ADM_YOI,
L5MonVar=ADM_MOI,
L5TimeInt=3,
UserWeight=wts_m);

The following table displays results from the example procedure above. In particular we are able to determine the "Sequential Over Time" proportion change between months based on various Genders. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs.

Table 3
Results from example procedure
ADM_YOI	ADM_MOI	SEX	_COUNT_	PROPORTION_LCS
2012	March	Male	178250
	April	Male	319000	0.151
	May	Male	235000	0.021
	June	Male	164750	0.058
	March	Female	220000
	April	Female	251250	0.061
	May	Female	276500	-0.041
	June	Female	144500	0.02

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Date modified:: 2021-06-15

Percentiles for RTRA

percentiles-rtra.pdf (PDF, 221.41 KB)

Basic Percentiles for RTRA

1. A percentile is the value of a variable below which a certain percent of observations fall. For example, the RTRA percentile procedure can be used to find the median income for males and females. To calculate percentiles, call the following RTRA procedure:

%RTRAPercentile(
InputDataset=,
OutputName=,
ClassVarList=,
AnalysisVar=,
Percentiles=,
UserWeight=);

2. %RTRAPercentile parameter definition:

InputDataset= identify the input data set from the WORK area to be used by the procedure.

OutputName= identify the name of the output files you want returned (maximum of 20 characters and the first character must be a letter).

ClassVarList= identify a maximum of five variables for the dimensions of the percentile procedure. These variables need to be delimited by spaces or asterisks. Each variable must contain more than one but no more than 500 unique values.

AnalysisVar= identify exactly one variable for the percentile procedure. This variable must be of type numeric.

Percentiles= identify up to three percentiles from the following list: 1, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 99. The percentile values need to be delimited by spaces.

UserWeight= refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Example: This procedure can be used to calculate income percentiles. Suppose you ran the following RTRA procedure to calculate the first quartile, the median, and the third quartile of a variable called "Income" to generate a table named "Table1". You would like to calculate these percentiles for each gender using a variable called "Sex".

Your RTRA procedure call will look like this:

%RTRAPercentile(
InputDataset=work.LFS,
OutputName=Table1,
ClassVarList=Education Sex,
AnalysisVar=Income,
Percentiles=25 50 75,
UserWeight=Finalwt);

The following table displays results from the example procedure above.

Table 1
Results from example procedure
Sex	Income_P25	Income_P50	Income_P75	Income_Count
	20000	45000	110000	27268000
Female	28000	50000	100000	13448000
Male	16000	38000	620000	13820000
Note: Output for surveys with bootstrap weights will have additional information on precision measures i.e. quality indicators, standard errors, confidence intervals, etc.

L5 Percentile for RTRA

1. A percentile is the value of a variable below which a certain percent of observations fall. Using the L5 function on Percentiles allows the user to calculate the difference between other statistics being run. For example, the RTRA L5 percentile procedure can be used to find the median income for males and females, while identifying a Percent Change. To calculate L5 percentiles, call the following RTRA procedure:

%RTRAPercentileL5(
InputDataset=,
OutputName=,
ClassVarList=,
AnalysisVar=,
Percentiles=,
L5STAT=,
L5TYPE=,
L5BYVAR=,
USERWEIGHT=);

2. %RTRAPercentileL5 parameter definition:

InputDataset= identify the input data set from the WORK area to be used by the procedure.

OutputName= identify the name of the output files you want returned (maximum of 20 characters and the first character must not be an underscore)

AnalysisVar= identify exactly one variable for the percentile procedure. This variable must be of type numeric.

Percentiles= identify up to three percentiles from the following list: 1, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 99. The percentile values need to be delimited by spaces.

L5Stat =identify which higher-order statistic you would like to use. The selection must be one of the following: LC (for Level Change), PC (for Percent Change), or ST (for Significance Test).

L5ByVar =identify the BY variable. The specified variable must also exist in the ClassVarList.

L5BaseVal =identify how the values in the table cells will compare to one another. The selection must be one of the following: Sequential, Base, or Global.

UserWeight= refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Example: This procedure can be used to calculate income percentiles by sex with a percentage change. Suppose you ran the following RTRA procedure to calculate the first quartile, the median, and the third quartile of a variable called "Income" to generate a table named "Table2". You would like to calculate these percentiles for each gender using a variable called "Sex".

Your RTRA procedure call will look like this:

%RTRAPercentileL5(
InputDataset=work.LFS,
OutputName=Table2,
ClassVarList=Sex,
AnalysisVar=Income,
Percentiles=25 50 75,
L5STAT=PC,
L5TYPE=global,
L5BYVAR=Sex,
USERWEIGHT=Finalwt);

The following table displays results from the example procedure above.

Table 2
Results from example procedure
Sex	Income_P25	Income_P50	Income_P75	Income_P25_PCG	Income_P50_PCG	Income_P75_PCG	Income_Count
	1640	2200	2600	0	0	0	231750
Female	1510	2200	2550	-0.08	0	-0.0192	94250
Male	1800	2250	2600	0.101	0.023	0	137500
Note:Output for surveys with bootstrap weights will have additional information on precision measures i.e. quality indicators, standard errors, confidence intervals, etc.

L5SOT Percentile for RTRA

1. This is the RTRA procedure macro for producing Percentile tabulations which include a selected Level 5 Sequential Over Time (L5SOT) statistic. A percentiles is the value of a variable below which a certain percent of observations fall. For example, the RTRA percentile procedure can be used to find the median income for males and females. To calculate percentiles, call the following RTRA procedure:

%RTRAPercentileL5SOT(
InputDataset=,
OutputName=,
ClassVarList=,
AnalysisVar=,
Percentiles=,
L5Stat=,
L5YrVar=,
L5MonVar=,
L5QtrVar=,
UserWeight=);

2. %RTRAPercentileL5SOT parameter definition:

InputDataset= identify the input data set from the WORK area to be used by the procedure.

OutputName= identify the name that is to be given to the final output files corresponding to this call to RTRAPercentileL5SOT. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names.

ClassVarList= identify a maximum of five variables for the dimensions of the percentile procedure. These variables need to be delimited by spaces or asterisks.

AnalysisVar= identify exactly one variable for the percentile procedure. This variable must be of type numeric.

Percentiles= identify up to three percentiles from the following list: 1, 5, 10, 20, 25, 30, 40, 50, 60, 70, 75, 80, 90, 95, 99. The percentile values need to be delimited by spaces.

L5Stat= Valid values are LC, PC and ST (case insensitive).

L5YrVar= identifies the name of the variable used as the Level 5 year variable.

L5MonVar= (optional) identifies the Level 5 month variable. Valid to omit this parameter or specify blank. If L5MonVar is specified then L5 QtrVar must be blank or omitted

L5QtrVar= (optional) identifies the Level 5 quarter variable. Valid to omit this parameter or specify blank. If L5 QtrVar is specified then L5MonVar must be blank or omitted.

L5TimeInt= (optional) identifies the Level 5 time interval. Value specified must be an integer greater than 0. Valid to omit this parameter but default integer must be 1.

UserWeight= Refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Example: This procedure can be used to analyze the Percent Change in weekly earnings based on different genders throughout the year.

%RTRAPercentileL5SOT(
InputDataset=work.LFS,
OutputName=Table3,
ClassVarList=Sex,
AnalysisVar=NUM_WKLYEARN,
Percentiles = 25 50 75,
L5Stat=PC,
L5YrVar=NUM_SYEAR,
L5MonVar=NUM_MONTH,
L5TimeInt=1,
UserWeight=FINALWT);

The following table displays results from the example procedure above. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs. For this example we will only use results for the first third of the year 2016 with a 25% change.

Table 3
Results from example procedure
NUM_MONTH	SEX	NUM_WKLYEARN_P25	NUM_WKLYEARN_P25_PCS	NUM_WKLYEARN_COUNT
January	Male	1500	0	6750
January	Female	1730	0	12250
February	Male	2100	0.4	9750
February	Female	1900	0.101	15500
March	Male	2000	-0.048	11750
March	Female	1550	-0.184	14000
April	Male	2000	0	8500
April	Female	1200	-0.23	14750
Note: Output for surveys with bootstrap weights will have additional information on precision measures i.e. quality indicators, standard errors, confidence intervals, etc.

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Date modified:: 2022-10-25

Percent Distribution for RTRA

percent-distribution-rtra.pdf (PDF, 302.19 KB)

Basic Percent Distribution for RTRA

1. Percentage Distribution is a frequency distribution in which the individual class frequencies are expressed as a percentage of the total frequency equated to 100. Also known as relative frequency distribution; relative frequency table.

The %RTRAPercentDist macro can be used for producing percentage distribution tabulations.

To generate a Percent Distribution, call the following RTRA procedure:

%RTRAPercentDist(
InputDataset=,
OutputName=,
ClassVarList=,
UserWeight=);

2. %RTRAPercentDist parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files you want returned (maximum of 20 characters and the first character must be a letter).

ClassVarList = identify a maximum of five variables for the dimensions of the Percent procedure. These variables need to be delimited by spaces or asterisks. Each variable must contain more than one but no more than 500 unique values.

UserWeight = refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Applying %RTRAPercentDist varies depending if the data has bootstrap weights.

When data has bootstrap weights applied, the output will contain quality indicators specific to the selected variables. For more information about quality indicators, please visit the RTRA Outputs page.

An example of %RTRAPercentDist using data with bootstrap weights:

Suppose you ran the following RTRA procedure to generate a percent distribution table named "Table1" with the variable called "Gender" using the Aboriginal Peoples Survey (APS) 2012.

Your RTRA procedure call will look like this:

%RTRAPercentDist(
InputDataset=work.APS,
OutputName=Table1,
ClassVarList= Gender,
UserWeight=WGHT);

Table 1
Results from example procedure
GENDER	_PERCENTDIST_	PERCENTDIST_SE	PERCENTDIST_CILB	PERCENTDIST_CIUB	PERCENTDIST_BSWCNT	_COUNT_
	1	0	0.999865	1	1000	963100
Female	0.53	0.00523	0.52	0.54	1000	513640
Male	0.47	0.00523	0.46	0.48	1000	449460

L5 Percent Distribution for RTRA

1. This is the RTRA procedure macro for producing Percent Distribution tabulations which include a selected Level 5 statistic. RTRAPercentDistL5 is a wrapper macro. It calls the macro ProcessRequest which is the processing routine common to all RTRA procedure macros and can be used for producing percentage distribution tabulations.

To generate an L5 Percent Distribution, call the following RTRA procedure:

%RTRAPercentDistL5(
InputDataset=,
OutputName=,
ClassVarList=,
L5Stat=,
L5Type=,
L5ByVar=,
L5BaseVal=,
UserWeight=);

2. %RTRAPercentDistL5 parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files corresponding to this call to %RTRAPercentDistL5. Tabulated results are assigned an internally generated name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names. Post-processing is then responsible for creating the final output files name.

ClassVarList = identify a maximum of five variables to be included on the percent distribution table. Variables in the list can be separated by any number of spaces, asterisks or combination of spaces and asterisks.

L5Stat= identifies the name of the Level 5 statistic. Valid values are LC and ST (case insensitive)

L5Type = identifies the Level 5 statistic type. Valid values are SEQUENTIAL, BASE and GLOBAL (case insensitive).

L5ByVar = identifies the Level 5 BY variable. The specified variable must exist in <classVarList>.

3. Example: Suppose you ran the following RTRA procedure to generate a percent distribution table named "Table2" with the variables called "Education" and "Province" using the Labour Force Survey.

Your RTRA procedure call will look like this:

%RTRAPercentDistL5(
InputDataset=work.LFS,
OutputName=Table2,
ClassVarList= Education Province,
L5Stat=LC,
L5Type=sequential,
L5ByVar=education,
L5BaseVal=,
UserWeight=FINALWT);

The following table displays results from the Level 5 Percent Distribution example procedure above. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs.

Table 2
Results from example procedure
EDUCATION	PROVINCE	PERCENTDIST	PERCENTDIST_LCS	COUNT
College	Manitoba	0.0079	0	3321500
High School	Manitoba	0.0088	0.00091	3702250
University	Manitoba	0.003	-0.0057	2531750
College	Ontario	0.096	0	40167000
High School	Ontario	0.093	-0.0031	38880000
University	Ontario	0.086	-0.028	36012500

L5SOT Percent Distribution for RTRA

1. This is the RTRA procedure macro for producing Percent Distribution tabulations which include a selected Level 5 Sequential Over Time (L5SOT) statistic. RTRAPercentDistL5SOT is a wrapper macro. It calls the macro ProcessRequest which is the processing routine common to all RTRA procedure macros.

The %RTRAPercentDistL5SOT macro can be used for producing percentage distribution tabulations.

To generate an L5 Percent Distribution, call the following RTRA procedure:

%RTRAPercentDistL5SOT(
InputDataset=,
OutputName=,
ClassVarList=,
L5Stat=,
L5YrVar=,
L5MonVar=,
L5QtrVar=,
L5TimeInt=,
UserWeight=);

2. %RTRAPercentDistL5SOT parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files corresponding to this call to RTRAPercentDistL5SOT. Tabulated results are assigned an internally generated name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names. Post-processing is then responsible for creating the final output files name.

L5Stat= identifies the name of the Level 5 statistic. Valid values are LC and ST (case insensitive).

L5YrVar= identifies the Level 5 year variable.

L5MonVar = (optional) identifies the Level 5 month variable. Valid to omit this parameter or specify blank. If L5MonVar is specified then L5 QtrVar must be blank or omitted.

L5QtrVar = (optional) identifies the Level 5 quarter variable. Valid to omit this parameter or specify blank. If L5 QtrVar is specified then L5MonVar must be blank or omitted.

L5TimeInt= (optional) identifies the Level 5 time interval. Value specified must be an integer greater than 0. Valid to omit this parameter but default integer must be 1.

UserWeight = refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Applying %RTRAPercentDistL5SOT varies depending on if the data has bootstrap weights.When data has bootstrap weights applied, the output will contain quality indicators specific to the selected variables. For more information about quality indicators, please visit the RTRA Outputs page.

An example of %RTRAPercentDistL5SOT using data with bootstrap weights:

Suppose you ran the following RTRA procedure to generate a percent distribution table named "Table3" with the variable called "Education" using the Labour Force Survey.

Your RTRA procedure call will look like this:

%RTRAPercentDistL5SOT(
InputDataset=work.LFS,
OutputName=Table3,
ClassVarList= Education,
L5Stat=LC,
L5YrVar=NUM_SYEAR,
L5MonVar=NUM_SMTH,
L5TimeInt=4,
UserWeight=FINALWT);

The following table displays results from the example procedure above. In particular we are able to determine the "Sequential Over Time" Percent Distribution between months based on various Education levels. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs. For this example we will only pull results for University responses.

Table 3
Results from example procedure
NUM_SYEAR	NUM_SMTH	EDUCATION	PERCENTDIST	PERCENTDIST_LCS	COUNT
2015	April	University	0.194		6773500
	May	University	0.195	0.00173	6799250
	June	University	0.198	0.0045	6908500
	July	University	0.2	0.0076	7024250
	August	University	0.2	0.009	7113250

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Date modified:: 2021-06-15

Mean for RTRA

mean-rtra.pdf (PDF, 222.52 KB)

Basic Mean for RTRA

1. The RTRA mean procedure produces the average for a continuous variable. For example, this procedure can be used to calculate the average income of those with different education levels and gender. To generate a mean, call the following RTRA procedure:

%RTRAMean(
InputDataset=,
OutputName=,
ClassVarList=,
AnalysisVarList=,
UserWeight=);

2. %RTRAMean parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files you want returned (maximum of 20 characters and the first character must be a letter).

ClassVarList = identify a maximum of five variables for the dimensions of the mean procedure. These variables need to be delimited by spaces or asterisks. Each variable must contain more than one but no more than 500 unique values.

AnalysisVarList = identify a maximum of three variables for the mean procedure. These variables must be of type numeric. Each of these variables must contain at least four unique values. These variables need to be delimited by spaces or asterisks.

UserWeight = refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Example: This procedure can be used to calculate average income. Suppose you ran the following RTRA procedure to calculate the mean of a variable called "Income" for a table named "Table1". You would like to calculate this average for different education levels and gender using variables called "Education" and "Sex".

Your RTRA procedure call will look like this:

%RTRAMean(
InputDataset=work.LFS,
OutputName=Table1,
ClassVarList=Education Sex,
AnalysisVarList=Income,
UserWeight=Finalwt);

The following table displays results from the example procedure above.

Table 1
Results from example procedure
Education	Sex	Income_mean	Income_Count
	Female	30000	100
	Male	40000	100
Above high school	Female	35000	60
Above high school	Male	50000	55
Below high school	Female	25000	40
Below high school	Male	30000	45
Note: Output for surveys with bootstrap weights will have additional information on precision measures i.e. quality indicators, standard errors, confidence intervals, etc.

L5 Mean for RTRA

1. This is the RTRA procedure macro for producing Mean tabulations which include a selected Level 5 statistic. RTRAMeanL5 is a wrapper macro. It calls the macro ProcessRequest which is the processing routine common to all RTRA procedure macros. To generate a mean, call the following RTRA procedure:

%RTRAMeanL5(
InputDataset=,
OutputName=,
ClassVarList=,
AnalysisVarList=,
L5Stat=,
L5Type=,
L5ByVar=,
L5BaseVal=,
UserWeight=);

2. %RTRAMeanL5 parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files corresponding to this call to RTRAMeanL5. Tabulated results are assigned an internally generated name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names. Post-processing is then responsible for creating the final output files name.

ClassVarList = identify a maximum of five variables for the dimensions of the mean procedure. Variables in the list can be separated by any number of spaces, asterisks or combination of spaces and asterisks.

AnalysisVarList = identify a maximum of three variables for the mean procedure. These variables must be separated by spaces.

L5Stat = identifies the name of the Level 5 statistic. Valid values are LC, PC and ST (case insensitive).

L5Type = identifies the Level 5 statistic type. Valid values are SEQUENTIAL, BASE and GLOBAL (case insensitive).

L5ByVar = identifies the Level 5 BY variable. The specified variable must exist in <classVarList>.

L5BaseVal =identifies the Level 5 base value. This parameter is only applicable if <L5Type> is BASE and must be blank if <L5Type> is SEQUENTIAL or GLOBAL. If applicable, the specified value must exist in the variable <L5ByVar> in the input data set.

3. Example: This procedure can be used to calculate average dwelling types. Suppose you ran the following RTRA procedure to calculate the mean of a variable called "NUM_DWELCODE" for a table named "Table2". You would like to calculate this average for different education levels and by province using variables called "Education" and "Province".

%RTRAMeanL5(
InputDataset=work.LFS,
OutputName=Table2,
ClassVarList=Education Province,
AnalysisVarList=NUM_DWELCODE,
L5Stat=LC,
L5Type=global,
L5ByVar=education,
L5BaseVal=,
UserWeight=FINALWT);

The following table displays results from the Level 5 Mean example procedure above. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs.

Table 2
Results from example procedure
Education	Province	NUM_DWELCODE Mean	NUM_DWELCODE _MEAN_LCG	NUM_DWELCODE Count
College	Manitoba	1.82	-0.084	3319000
High School	Manitoba	1.94	0.042	3699000
University	Manitoba	1.93	0.035	2531500
College	Ontario	2.1	-0.099	40139250
High School	Ontario	2.2	0.044	38821750
University	Ontario	2.3	0.164	35991000

L5SOT Mean for RTRA

1. This is the RTRA procedure macro for producing Mean tabulations which include a selected Level 5 Sequential Over Time (L5SOT) statistic. RTRAMeanL5SOT is a wrapper macro. It calls the macro ProcessRequest which is the processing routine common to all RTRA procedure macros. To generate a mean, call the following RTRA procedure:

%RTRAMeanL5SOT(
InputDataset=,
OutputName=,
ClassVarList=,
AnalysisVarList=,
L5Stat=,
L5YrVar=,
L5MonVar=,
L5QtrVar=,
UserWeight=);

2. %RTRAMeanL5SOT parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files corresponding to this call to RTRAMeanL5SOT. Tabulated results are assigned an internally generated name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names. Post-processing is then responsible for creating the final output files name.

AnalysisVarList = identify a maximum of three variables for the mean procedure. These variables must be of type numeric. A maximum of three variables can be specified and must be separated by spaces.

L5Stat = identifies the name of the Level 5 statistic. Valid values are LC, PC and ST (case insensitive).

L5YrVar= identifies the Level 5 year variable. If the L5MonVar or L5QtrVar are not used, this field should reference a variable that contains multiple years to demonstrate the "Sequential Over Time" factor.

L5MonVar = (optional) identifies the Level 5 month variable. Valid to omit this parameter or specify blank. If L5MonVar is specified then L5 QtrVar must be blank or omitted.

L5QtrVar = (optional) identifies the Level 5 quarter variable. Valid to omit this parameter or specify blank. If L5 QtrVar is specified then L5MonVar must be blank or omitted.

L5TimeInt= (optional) identifies the Level 5 time interval. Value specified must be an integer greater than 0. Valid to omit this parameter but default integer must be 1.

UserWeight = Refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Example: This procedure can be used to calculate average dwelling types. Suppose you ran the following RTRA procedure to calculate the mean of a variable called "NUM_DWELCODE" for a table named "Table3". You would like to calculate this average for different education levels and by province using variables called "Education" and "Province".

%RTRAMeanL5SOT(
InputDataset=work.LFS,
OutputName=Table3,
ClassVarList=Education Province,
AnalysisVarList=NUM_DWELCODE,
L5Stat=LC,
L5YrVar=NUM_SYEAR,
L5MonVar=NUM_SMTH,
L5TimeInt=2,
UserWeight=FINALWT);

The following table displays results from the example procedure above. In particular we are able to determine the "Sequential Over Time" Mean change between months based on various Education levels. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs. For this example we will only pull results for University responses.

Table 3
Results from example procedure
NUM_SYEAR	NUM_SMTH	Education	NUM_DWELCODE Mean	NUM_DWELCODE _MEAN_LCS	NUM_DWELCODE Count
2015	January	University	2.4		6717000
	February	University	2.4		6725500
	March	University	2.4	0.032	6731750
	April	University	2.4	0.0132	6770750
	May	University	2.4	-0.021	6796750
	June	University	2.4	-0.027	6905750

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Date modified:: 2021-06-15

Frequency for RTRA

frequency-rtra.pdf (PDF, 221.42 KB)

Basic Frequency for RTRA

1. The RTRA frequency procedure provides counts of a discrete variable. For example, this procedure can be used to calculate the number of people in the population by different education levels and gender. To generate frequency tabulations, call the following RTRA procedure:

%RTRAFreq(
InputDataset=,
OutputName=,
ClassVarList=,
UserWeight=);

2. %RTRAFreq parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name of the output files you want returned (maximum of 20 characters and the first character must be a letter).

ClassVarList = identify a maximum of five variables to be included on the frequency table. These variables need to be delimited by spaces or asterisks. Each variable must contain more than one but no more than 500 unique values.

UserWeight = refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Example: Suppose you ran the following RTRA procedure to generate a frequency table named "Table1" with variables called "Education" and "Sex".

Your RTRA procedure call will look like this:

%RTRAFreq(
InputDataset=work.LFS,
OutputName=Table1,
ClassVarList=Education Sex,
UserWeight=Finalwt);
The following table displays results from the example procedure above.

Table 1
Results from example procedure
Education	Sex	Count
	Female	100
	Male	100
Above high school	Female	60
Above high school	Male	55
Below high school	Female	40
Below high school	Male	45
Note: Output for surveys with bootstrap weights will have additional information on precision measures i.e. quality indicators, standard errors, confidence intervals, etc.

L5 Frequency for RTRA

1. This is the RTRA procedure macro for producing Frequency (sum of weight) tabulations which include a selected Level 5 statistic. RTRAFreqL5 is a wrapper macro. It calls the macro ProcessRequest which is the processing routine common to all RTRA procedure macros. For example, this procedure can be used to calculate the specific L5 (Level Change) between various Educations for individuals in each Province. To generate the year frequency tabulations, call the following RTRA procedure:

%RTRAFreqL5(
InputDataset=,
OutputName=,
ClassVarList=,
L5Stat=,
L5Type=,
L5ByVar=,
L5BaseVal=,
UserWeight=);

2. %RTRAFreqL5 parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName = identify the name given to the final output files corresponding to this call to RTRAFreqL5. Tabulated results are assigned an internally generated name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names. Post-processing is then responsible for creating the final output files name.

ClassVarList = identify a maximum of five variables to be included on the frequency table. Variables in the list can be separated by any number of spaces, asterisks or combination of spaces and asterisks.

L5Stat = identifies the name of the Level 5 statistic. Valid values are LC, PC and ST (case insensitive).

L5Type = identifies the Level 5 statistic type. Valid values are SEQUENTIAL, BASE and GLOBAL (case insensitive).

L5ByVar = identifies the Level 5 BY variable. The specified variable must exist in <classVarList>.

3. Example: Suppose you ran the following RTRA procedure to generate an L5 frequency table named "Table2" with variables called "Education" and "Province" using the L5YrVar.

Your RTRA procedure call will look like this:

%RTRAFreqL5(
InputDataset=work.LFS,
OutputName=Table2,
ClassVarList=province education,
L5Stat=LC,
L5Type=global,
L5ByVar=province,
L5BaseVal=,
UserWeight=FINALWT);

The following table displays results from the Level 5 Frequency example procedure above. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs.

Table 2
Results from example procedure
EDUCATION	PROVINCE	_COUNT_	COUNT_LCG
College	Manitoba	3321500	-108137000
College	Ontario	40167000	-71291500
College	Other	67970000	-43488500
High School	Manitoba	3702250	-92634500
High School	Ontario	38880000	-57456750
High School	Other	53754500	-42582250
University	Manitoba	2531750	-81162500
University	Ontario	36012500	-47681750
University	Other	45150000	-38544250
Note: Output for surveys with bootstrap weights will have additional information on precision measures i.e. quality indicators, standard errors, confidence intervals, etc.

L5SOT Frequency for RTRA

1. This is the RTRA procedure macro for producing Frequency (sum of weight) tabulations which include a selected Level 5 Sequential Over Time (L5SOT) statistic. RTRAFreqL5SOT is a wrapper macro. It calls the macro ProcessRequest which is the processing routine common to all RTRA procedure macros. For example, this procedure can be used to calculate the specific L5 (Level Change) between various Educations for individuals in each Province. To generate the year frequency tabulations, call the following RTRA procedure:

%RTRAFreqL5SOT(
InputDataset=,
OutputName=,
ClassVarList=,
L5Stat=,
L5YrVar=,
L5MonVar=,
L5QtrVar=,
L5TimeInt=,
UserWeight=);

2. %RTRAFreqL5SOT parameter definition:

InputDataset = identify the input data set from the WORK area to be used by the procedure.

OutputName= identify the name of the output files corresponding to this call to RTRAFreqL5SOT. Tabulated results are assigned an internally generated name rather than the name in this parameter. The post-processing parameters data set defines the correspondence between the internally generated name and the final output file names. Post-processing is then responsible for creating the final output files name.

ClassVarList= identify a maximum of five variables to be included on the frequency table. Variables in the list can be separated by any number of spaces, asterisks or combination of spaces and asterisks.

L5Stat = identifies the name of the Level 5 statistic. Valid values are LC, PC and ST (case insensitive).

L5MonVar = (optional) identifies the Level 5 month variable. Valid to omit this parameter or specify blank. If L5MonVar is specified then L5QtrVar must be blank or omitted.

L5QtrVar = (optional) identifies the Level 5 quarter variable. Valid to omit this parameter or specify blank. If L5 QtrVar is specified then L5MonVar must be blank or omitted.

L5TimeInt= (optional) identifies the Level 5 time interval. Value specified must be an integer greater than 0. Valid to omit this parameter but default integer must be 1.

UserWeight= Refer to the RTRA parameters document to identify a survey weight. The weight variable identified will be merged onto the input data set using the ID variable.

3. Example: Suppose you ran the following RTRA procedure to generate an L5 frequency table named "Table3" with variables called "Education" and "Province" using the L5YrVar.

Your RTRA procedure call will look like this:

%RTRAFreqL5SOT(
InputDataset=work.LFS,
OutputName=Table3,
ClassVarList=Province Education,
L5Stat=LC,
L5YrVar=NUM_SYEAR,
L5MonVar=NUM_SMTH,
L5TimeInt=1,
UserWeight=FINALWT);

The following table displays results from the example procedure above. In particular we are able to determine the "Sequential Over Time" frequency change between months based on various Provinces and Education levels. Please note that this is a section of the data in the documentation and a select few entries of the actual output have been pulled for the purpose of having smaller outputs.

Table 3
Results from example procedure
NUM_SYEAR	NUM_SMTH	EDUCATION	PROVINCE	_COUNT_	COUNT_LCS
2015	January	College	Manitoba	275000
	February	College	Manitoba	270500	-4500
	March	High School	Ontario	3339750
	April	High School	Ontario	3316500	-23250
	May	University	Other	3680500
	June	University	Other	3714750	34250
Note: Output for surveys with bootstrap weights will have additional information on precision measures i.e. quality indicators, standard errors, confidence intervals, etc.

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Date modified:: 2021-06-15

Variables and definitions

data steps: A sequence of procedures in SAS
keep: SAS procedure specifies the variables to process
libname: Associates or disassociates a SAS data library with a libref
proc freq: A SAS procedure that produces one-way to n-way frequency
proc sort: SAS procedure that orders SAS data set observations by the values of one or more character or numeric variables
SAS libref: SAS procedure that Verifies that a libref has been assigned
Tag Name: Unique name given to each survey

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Date modified:: 2021-06-15

Why are we conducting this survey?

This survey is conducted by Statistics Canada in order to collect the necessary information to support the Integrated Business Statistics Program (IBSP). This program combines various survey and administrative data to develop comprehensive measures of the Canadian economy.

The purpose of this survey is to obtain information on the volume of refined petroleum products distributed by secondary distributors in Canada. It supplements energy consumption data collected from the refineries in the Annual Survey of End Use of Refined Petroleum Products.

Your information may also be used by Statistics Canada for other statistical and research purposes.

Your participation in this survey is required under the authority of the Statistics Act.

Other important information

Authorization to collect this information

Data are collected under the authority of the Statistics Act, Revised Statutes of Canada, 1985, Chapter S-19.

Confidentiality

By law, Statistics Canada is prohibited from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent, or as permitted by the Statistics Act. Statistics Canada will use the information from this survey for statistical purposes only.

Record linkages

To enhance the data from this survey and to reduce the reporting burden, Statistics Canada may combine the acquired data with information from other surveys or from administrative sources.

Data-sharing agreements

To reduce respondent burden, Statistics Canada has entered into data-sharing agreements with provincial and territorial statistical agencies and other government organizations, which have agreed to keep the data confidential and use them only for statistical purposes. Statistics Canada will only share data from this survey with those organizations that have demonstrated a requirement to use the data.

Section 11 of the Statistics Act provides for the sharing of information with provincial and territorial statistical agencies that meet certain conditions. These agencies must have the legislative authority to collect the same information, on a mandatory basis, and the legislation must provide substantially the same provisions for confidentiality and penalties for disclosure of confidential information as the Statistics Act. Because these agencies have the legal authority to compel businesses to provide the same information, consent is not requested and businesses may not object to the sharing of the data.

For this survey, there are Section 11 agreements with the provincial and territorial statistical agencies of Newfoundland and Labrador, Nova Scotia, New Brunswick, Québec, Ontario, Manitoba, Saskatchewan, Alberta, British Columbia and the Yukon. The shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province or territory. Section 12 of the Statistics Act provides for the sharing of information with federal, provincial or territorial government organizations.

Under Section 12, you may refuse to share your information with any of these organizations by writing a letter of objection to the Chief Statistician, specifying the organizations with which you do not want Statistics Canada to share your data and mailing it to the following address:

Chief Statistician of Canada
Statistics Canada
Attention of Director, Enterprise Statistics Division
150 Tunney's Pasture Driveway
Ottawa, Ontario
K1A 0T6

You may also contact us by email at Statistics Canada Help Desk or by fax at 613-951-6583.

For this survey, there are Section 12 agreements with the statistical agencies of Prince Edward Island, the Northwest Territories and Nunavut as well as with the Newfoundland and Labrador Department of Natural Resources, New Brunswick Department of Environment and Local Government, the ministère des Finances du Québec, the ministère de l'Environnement et de la Lutte contre les changements climatiques du Québec, the ministère de l'Énergie et des Ressources naturelles du Québec, Transition énergétique Québec, the Manitoba Department of Mineral Resources, the British Columbia Ministry of Energy and Mines, the British Columbia Ministry of Natural Gas Development, Canada Energy Regulator, Natural Resources Canada and Environment and Climate Change Canada.

For agreements with provincial and territorial government organizations, the shared data will be limited to information pertaining to business establishments located within the jurisdiction of the respective province or territory.

Business or organization and contact information

1. Verify or provide the business or organization's legal and operating name and correct where needed.

Note: Legal name modifications should only be done to correct a spelling error or typo.

Note: Press the help button (?) for additional information.

Legal Name
The legal name is one recognized by law, thus it is the name liable for pursuit or for debts incurred by the business or organization. In the case of a corporation, it is the legal name as fixed by its charter or the statute by which the corporation was created.

Modifications to the legal name should only be done to correct a spelling error or typo.

To indicate a legal name of another legal entity you should instead indicate it in question 3 by selecting 'Not currently operational' and then choosing the applicable reason and providing the legal name of this other entity along with any other requested information.

Operating Name
The operating name is a name the business or organization is commonly known as if different from its legal name. The operating name is synonymous with trade name.

Legal name

Operating name (if applicable)

2. Verify or provide the contact information of the designated business or organization contact person for this questionnaire and correct where needed.

Note: The designated contact person is the person who should receive this questionnaire. The designated contact person may not always be the one who actually completes the questionnaire.

First name
Last name
Title
Preferred language of communication
- English
- French
Mailing address (number and street)
City
Province, territory or state
Postal code or ZIP code
Country
- Canada
- United States
Email address
Telephone number (including area code)
Extension number (if applicable)
The maximum number of characters is 10.
Fax number (including area code)

3. Verify or provide the current operational status of the business or organization identified by the legal and operating name above.

Operational
Not currently operational

Why is this business or organization not currently operational?

Seasonal operations
Ceased operations
Sold operations
Amalgamated with other businesses or organizations
Temporarily inactive but will re-open
No longer operating due to other reasons

When did this business or organization close for the season?
Date

When does this business or organization expect to resume operations?
Date

When did this business or organization cease operations?
Date

Why did this business or organization cease operations?

Bankruptcy
Liquidation
Dissolution
Other

Specify the other reasons why the operations ceased

When was this business or organization sold?
Date

What is the legal name of the buyer?

When did this business or organization amalgamate?
Date

What is the legal name of the resulting or continuing business or organization?

What are the legal names of the other amalgamated businesses or organizations?

When did this business or organization become temporarily inactive?
Date

When does this business or organization expect to resume operations?
Date

Why is this business or organization temporarily inactive?

When did this business or organization cease operations?
Date

Why did this business or organization cease operations?

4. Verify or provide the current main activity of the business or organization identified by the legal and operating name above.

Note: The described activity was assigned using the North American Industry Classification System (NAICS).

Note: Press the help button (?) for additional information, including a detailed description of this activity complete with example activities and any applicable exclusions.

This question verifies the business or organization's current main activity as classified by the North American Industry Classification System (NAICS). The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply-side or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance.

The target entity for which NAICS is designed are businesses and other organizations engaged in the production of goods and services. They include farms, incorporated and unincorporated businesses and government business enterprises. They also include government institutions and agencies engaged in the production of marketed and non-marketed services, as well as organizations such as professional associations and unions and charitable or non-profit organizations and the employees of households.

The associated NAICS should reflect those activities conducted by the business or organizational units targeted by this questionnaire only, as identified in the 'Answering this questionnaire' section and which can be identified by the specified legal and operating name. The main activity is the activity which most defines the targeted business or organization's main purpose or reason for existence. For a business or organization that is for-profit, it is normally the activity that generates the majority of the revenue for the entity.

The NAICS classification contains a limited number of activity classifications; the associated classification might be applicable for this business or organization even if it is not exactly how you would describe this business or organization's main activity.

Please note that any modifications to the main activity through your response to this question might not necessarily be reflected prior to the transmitting of subsequent questionnaires and as a result they may not contain this updated information.

The following is the detailed description including any applicable examples or exclusions for the classification currently associated with this business or organization.

Description and examples

This is the current main activity
This is not the current main activity

Provide a brief but precise description of this business or organization's main activity

e.g., breakfast cereal manufacturing, shoe store, software development

Main activity

5. You indicated that is not the current main activity.

Was this business or organization's main activity ever classified as: ?

When did the main activity change?
Date

6. Search and select the industry classification code that best corresponds to this business or organization's main activity.

How to search:

if desired, you can filter the search results by first selecting this business or organization's activity sector
enter keywords or a brief description that best describes this business or organization main activity
press the Search button to search the database for an activity that best matches the keywords or description you provided
then select an activity from the list.

Select this business or organization's activity sector (optional)

Farming or logging operation
Construction company or general contractor
Manufacturer
Wholesaler
Retailer
Provider of passenger or freight transportation
Provider of investment, savings or insurance products
Real estate agency, real estate brokerage or leasing company
Provider of professional, scientific or technical services
Provider of health care or social services
Restaurant, bar, hotel, motel or other lodging establishment
Other sector

Enter keywords or a brief description, then press the Search button

7. You have indicated that the current main activity of this business or organization is:

Main activity

Are there any other activities that contribute significantly (at least 10%) to this business or organization's revenue?

Yes, there are other activities
No, that is the only significant activity

Provide a brief but precise description of this business or organization's secondary activity

e.g., breakfast cereal manufacturing, shoe store, software development

8. Approximately what percentage of this business or organization's revenue is generated by each of the following activities?

When precise figures are not available, provide your best estimates.

	Percentage of revenue
Main activity
Secondary activity
All other activities
Total percentage

Products sold

1. In 2020 , which of the following refined petroleum products were sold or distributed by this business?

Select all that apply.

Propane

i.e., all propane types including those extracted from natural gas or refinery gas steams

Motor gasoline

i.e., all gasoline-type fuels for internal combustion engines other than aircraft; this includes any ethanol/methanol and other similar additives blended

Diesel fuel oil

i.e., all grades of distillate fuel used for diesel engines (dyed/marked or clear); this includes any biodiesel blended with fuel

Light fuel oil

i.e., all distillate type fuels used for power burners

Include fuel oil number 1, fuel oil number 2, fuel oil number 3, stove oil, furnace fuel oil, gas oils and light industrial fuel; this includes any biofuel blended.

Residual and heavy fuel oil

i.e., all grades of residual type fuels including low sulphur used for steam and electric power generation and steam and diesel motors installed on large marine vessels

Include fuel oil numbers 4, 5 and 6. Sometimes referred to as bunker fuel B or C.

Business's own use

2. How many litres of refined petroleum products did this business consume for its own use?

Report all amounts of refined petroleum products purchased that were used in company operations (that is used for your vehicles or heating).

Total number of litres used for own consumption

Litres

Sales by type of customer

3. To which types of customers did this business sell?

Select all that apply.

Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Transportation
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Manufacturing
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Mining and oil and gas extraction
Iron mines
Oil and gas extraction
Other mining
Other customer types
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional

Sales by location

4. In which of the following provinces and territories did this business sell?

Select all that apply.

Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
Yukon
Northwest Territories
Nunavut

Sales in Newfoundland and Labrador

5. How many litres of refined petroleum products were sold to the following types of customers in Newfoundland and Labrador?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Newfoundland and Labrador

Sales in Prince Edward Island

6. How many litres of refined petroleum products were sold to the following types of customers in Prince Edward Island?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Prince Edward Island

Sales in Nova Scotia

7. How many litres of refined petroleum products were sold to the following types of customers in Nova Scotia?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Nova Scotia

Sales in New Brunswick

8. How many litres of refined petroleum products were sold to the following types of customers in New Brunswick?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in New Brunswick

Sales in Quebec

9. How many litres of refined petroleum products were sold to the following types of customers in Quebec?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Quebec

Sales in Ontario

10. How many litres of refined petroleum products were sold to the following types of customers in Ontario?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Ontario

Sales in Manitoba

11. How many litres of refined petroleum products were sold to the following types of customers in Manitoba?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Manitoba

Sales in Saskatchewan

12. How many litres of refined petroleum products were sold to the following types of customers in Saskatchewan?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Saskatchewan

Sales in Alberta

13. How many litres of refined petroleum products were sold to the following types of customers in Alberta?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Alberta

Sales in British Columbia

14. How many litres of refined petroleum products were sold to the following types of customers in British Columbia?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in British Columbia

Sales in Yukon

15. How many litres of refined petroleum products were sold to the following types of customers in Yukon?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Yukon

Sales in Northwest Territories

16. How many litres of refined petroleum products were sold to the following types of customers in Northwest Territories?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Northwest Territories

Sales in Nunavut

17. How many litres of refined petroleum products were sold to the following types of customers in Nunavut?

	Litres
Residential
Wholesalers and dealers of refined petroleum products
Retail pump sales
Railways
Road transport and urban transit
Canadian marine
Foreign marine
Food, beverage, tobacco manufacturing
Pulp and paper manufacturing
Iron and steel manufacturing
Aluminum and non-ferrous metals manufacturing
Cement manufacturing
Refined petroleum products manufacturing
Chemical manufacturing
All other manufacturing
Iron mines
Oil and gas extraction
Other mining
Forestry, logging, and support activities
Agriculture, fishing, hunting and trapping
Construction
Public administration
Electric power generation and distribution
Commercial and other institutional
Total litres of sold in Nunavut

Summary of sold by province and territory

18. This is a summary of refined petroleum products sold by province and territory.

Note: You cannot make changes to this page.
Please review the values and, if needed press the Previous button at the bottom of the page to navigate to the previous pages to make any modifications.

	Total Number of Litres
Summary by Province
Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
Yukon
Northwest Territories
Nunavut
Total litres of sold

Changes or events

1. Indicate any changes or events that affected the reported values for this business or organization, compared with the last reporting period.

Select all that apply.

Strike or lock-out
Exchange rate impact
Price changes in goods or services sold
Contracting out
Organizational change
Price changes in labour or raw materials
Natural disaster
Recession
Change in product line
Sold business or business units
Expansion
New or lost contract
Plant closures
Acquisition of business or business units
Other
Specify the other changes or events:
No changes or events

Contact person

1. Statistics Canada may need to contact the person who completed this questionnaire for further information.

Is the provided given names and the provided family name the best person to contact?

Who is the best person to contact about this questionnaire?

First name:
Last name:
Title:
Email address:
Telephone number (including area code):
Extension number (if applicable):
The maximum number of characters is 5.
Fax number (including area code):

Feedback

1. How long did it take to complete this questionnaire?

Include the time spent gathering the necessary information.

Hours:

Minutes:

2. Do you have any comments about this questionnaire?

Business or organization information

1. Which of the following categories best describes this business or organization?

Government agency
Private sector business
Non-profit organization
- Who does this organization primarily serve?
  - Households or individuals
    e.g., child and youth services, community food services, food bank, women's shelter, community housing services, emergency relief services, religious organization, grant and giving services, social advocacy group, arts and recreation group
  - Businesses
    e.g., business association, chamber of commerce, condominium association, environment support or protection services, group benefit carriers (pensions, health, medical)
Don't know

2. In what year was this business or organization first established?

Year business or organization was first established:
OR
1: Don't know

3. In the last 12 months, did this business or organization conduct any of the following international activities?

Select all that apply.

Export goods or services outside of Canada
Make investments outside of Canada
Sell goods to businesses or organizations in Canada who then resold them outside of Canada
Import goods or services from outside of Canada
Include both intermediate and final goods.
Relocate any business or organizational activities or employees from another country into Canada
Exclude temporary foreign workers.
Engage in other international business or organizational activities
OR
None of the above

4. Over the next three months, how are each of the following expected to change for this business or organization?

Exclude seasonal factors or conditions.

Number of employees
- Increase
- Stay about the same
- Decrease
- Not applicable
Vacant positions
- Increase
- Stay about the same
- Decrease
- Not applicable
Sales
- Increase
- Stay about the same
- Decrease
- Not applicable
Selling price of goods and services offered by this business or organization
- Increase
- Stay about the same
- Decrease
- Not applicable
Demand for products and services offered by this business or organization
- Increase
- Stay about the same
- Decrease
- Not applicable
Imports
- Increase
- Stay about the same
- Decrease
- Not applicable
Exports
- Increase
- Stay about the same
- Decrease
- Not applicable
Operating income
- Increase
- Stay about the same
- Decrease
- Not applicable
Operating expenses
- Increase
- Stay about the same
- Decrease
- Not applicable
Profitability
- Increase
- Stay about the same
- Decrease
- Not applicable
Capital expenditures
e.g., machinery, equipment
- Increase
- Stay about the same
- Decrease
- Not applicable
Training expenditures
- Increase
- Stay about the same
- Decrease
- Not applicable

Business or organization obstacles

5. Over the next three months, which of the following are expected to be obstacles for this business or organization?

Select all that apply.

Shortage of labour force
Recruiting skilled employees
Retaining skilled employees
Shortage of space or equipment
Rising cost of inputs
An input is an economic resource used in a firm's production process.
e.g., labour, capital, energy and raw materials
Difficulty acquiring inputs, products or supplies domestically
Difficulty acquiring inputs, products or supplies from abroad
Maintaining inventory levels
Insufficient demand for goods or services offered
Fluctuations in consumer demand
Attracting new or returning customers
Cost of insurance
Transportation costs
Obtaining financing
Government regulations
Travel restrictions and travel bans
Increasing competition
Challenges related to exporting goods and services
Maintaining sufficient cash flow or managing debt
Speed of internet connection
Intellectual property protection
Other
- Specify other:
OR
None of the above

Flow condition: If the business or organization is a private sector business, go to Q6. Otherwise, go to Q9.

Expectations for the next year

6. In the next 12 months, are there any plans to expand or restructure this business, or acquire or invest in other businesses?

Restructuring involves changing the financial, operational, legal or other structures of a business to make it more efficient or more profitable.

Yes
- Does this business plan to:
  Select all that apply.
  - Expand current location of this business
  - Expand this business to other locations
  - Restructure this business
  - Acquire other businesses or franchises
  - Invest in other businesses
No
Don't know

7. In the next 12 months, are there any plans to transfer, sell or close this business?

Yes
- Does this business plan to:
  - Transfer to family members without money changing hands
  - Sell to family members
  - Sell to employees
  - Sell to external parties
  - Close the business
  - Don't know
No
Don't know

Flow condition: If "Close the business" is selected in Q7, go to Q8. Otherwise, go to Q9.

8. Is this business or organization planning to permanently close in the next 12 months primarily due to either of the following?

The pandemic
Business performance prior to the pandemic
None of the above

Workforce changes

9. Over the next 12 months, does this business or organization plan to do any of the following?

Select all that apply.

Provide training to current employees in a different skill set
Lay off staff whose skills and knowledge no longer meet this business's or organization's needs
Lay off staff due to continued lack of demand
Hire employees living outside of this business's or organization's immediate vicinity to carry out work remotely
Hire staff with technical skills that current employees lack
Hire staff with management skills that current employees lack
Hire staff who have other skills or knowledge that current employees lack
Hire external contractors who have skills or knowledge that current employees lack
OR
None of the above

10. Over the next 12 months, does this business or organization plan to increase spending on employee training to do any of the following?

Include both current and new employees.

Select all that apply.

Prepare for when the economy recovers
Develop new skills to improve this business's or organization's competitiveness
Mitigate potential labour shortages when the economy recovers
Keep up with any future industry changes of this business or organization
Other
- Specify other:
OR
None of the above

Workforce challenges

11. Over the next three months, to what extent will each of the following be a challenge for this business or organization with regards to the workforce?

Finding qualified workers
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Recruiting qualified workers
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Retaining qualified workers
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Finding time and resources for training current staff
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Finding time and resources for training new staff
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Convincing staff that have been working remotely to return to working on-site
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Hiring temporary foreign workers
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Managing employees that are voluntarily working reduced hours or not working in order to take care of children
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Employees going on short-term medical leave
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know
Employees going on long-term medical leave
- Very challenging
- Somewhat challenging
- Not challenging
- Not applicable
- Don't know

Investments

12. Over the next 12 months, how likely is this business or organization to make investments in online sales or e-commerce capabilities?

Very unlikely
Somewhat unlikely
Neither likely nor unlikely
Somewhat likely
Very likely
Not applicable

Outreach to new customers

13. Over the last 12 months, did this business or organization use virtual connections to reach new customers, clients or partners in any of the following markets?

Include virtual meetings, virtual events, virtual trade shows, and initiating or expanding e-commerce presence.

Select all that apply.

New international markets
New domestic markets
Existing international markets
Existing domestic markets
OR
Did not use virtual connections to reach new customers, clients or partners

International markets

14. Over the next 12 months, what type of international activity does this business or organization primarily plan to focus on?

Exports
Imports
Investment into international markets
Attracting investments from international markets
None of the above

Flow condition: If "Exports", "Imports", "Investment into international markets", or "Attracting investments from international markets" is selected in Q14, go to Q15. Otherwise, go to Q16.

15. Over the next 12 months, which international market does this business or organization primarily plan to focus on?

United States
Mexico
South & Central America and the Caribbean
Exclude Mexico.
Europe
Asia
Other

Consultation and advice

16. Over the next 12 months, will this business or organization consult any of the following for advice related to opportunities or challenges?

Select all that apply.

Friends or family
Mentors
Employees or colleagues in this business or organization
External consultants
Contacts in other businesses or organizations
Professional or business associations
Federal government services or programs
Provincial or territorial government services or programs
Teachers in a training or education setting
Other
- Specify other:
OR
None of the above

Funding or credit

17. Due to COVID-19, was funding or credit for this business or organization approved or received from any of the following sources?

Select all that apply.

Canada Emergency Business Account (CEBA)
e.g., loan of up to $40,000 for eligible small businesses and non-profits
Temporary 10% Wage Subsidy
Canada Emergency Wage Subsidy (CEWS)
Canada Emergency Rent Subsidy (CERS)
Canada Emergency Commercial Rent Assistance (CECRA)
Export Development Canada (EDC) Small and Medium-sized Enterprise Loan and Guarantee program
Business Development Bank of Canada (BDC) Co-Lending Program for Small and Medium-sized Enterprises
Innovation Assistance Program
Regional Relief and Recovery Fund (RRRF)
Provincial, Territorial or Municipal government programs
Funding from philanthropic or mutual-aid sources
Financial institution
e.g., term loan or line of credit
Loan from family or friends
Other
- Specify other approved source of funding or credit :
OR
None of the above

Flow condition: If "None of the above" is selected in Q17, go to Q18. Otherwise, go to Q19.

18. For which of the following reasons has this business or organization not accessed any funding or credit due to COVID-19?

Select all that apply.

Funding or credit not needed
Waiting for approval or in process of applying
Eligibility requirements
Application requirements or complexity
Lack of awareness
Terms and conditions
e.g., interest rate, payment period
Public perception
Other
- Specify other:

19. Has this business's or organization's credit rating been negatively affected by the pandemic?

Yes
No
Don't know

Liquidity and debt

20. Does this business or organization have the cash or liquid assets required to operate for the next three months?

Yes
No
- Will this business or organization be able to acquire the cash or liquid assets required?
  - Yes
  - No
  - Don't know
Don't know

21. Does this business or organization have the ability to take on more debt?

Yes
No
- For which of the following reasons is this business or organization unable to take on more debt?
  Select all that apply.
  - Cash flow
  - Lack of confidence or uncertainty in future sales
  - Request would be turned down
  - Too difficult or time consuming to apply
  - Terms and conditions are unfavourable
    e.g., interest rate, payment period
  - Credit rating
  - Other
    - Specify other:
Don't know
This business or organization does not need to take on more debt

Measures permanently adopted

22. Using a scale from 1 to 5, where 1 means "very unlikely" and 5 means "very likely", how likely is this business or organization to permanently adopt each of the following measures once the COVID-19 pandemic is over?

An employee is someone who would be issued a T4 from this business or organization.

Online training
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Offer more employees the possibility of teleworking or working remotely
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Require more employees to telework or work remotely
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Require employees to come back to on-site work
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Increase IT infrastructure to support teleworking
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Make investments to increase the security of telework systems
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Adopt shiftwork to increase the distance between employees
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Modify the work space to increase the distance between employees
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Diversify supply chains within Canada
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Diversify supply chains outside Canada
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Reduce hiring of temporary foreign workers
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Increase online sales capacity
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Increase contactless delivery or pickup options
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Reduce the physical space used by this business or organization
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Increase the physical space used by this business or organization
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable
Increase investments in training
- 1 – Very unlikely
- 2
- 3
- 4
- 5 – Very likely
- Not applicable

Technology and automation

23. Over the next 12 months, does this business or organization plan to adopt or incorporate any of the following technologies?

Select all that apply.

Software or hardware using artificial intelligence
e.g., machine learning, predictive technology, virtual personal assistants, online customer support bots, image or speech recognition
Robotics
Automation of certain tasks
e.g., through the use of robots or computer algorithms
Cloud computing
Cloud computing: services that are used over the internet to access software, computing power, or storage capacity.
e.g., Microsoft 365®, Google Cloud™, Dropbox™
Collaboration tools
e.g., Zoom™, Microsoft Teams™, Slack™
Security software tools
e.g., anti-virus, anti-spyware, anti-malware, firewalls
Software or databases for purposes other than telework and online sales
Digital technology to move business operations or sales online (for purposes other than teleworking or remote working)
OR
None of the above

Flow condition: If at least one technology is selected in Q23, go to Q24. Otherwise, go to Q25.

24. Using a scale from 1 to 5, where 1 means "not at all challenging" and 5 means "extremely challenging", how challenging are the following for this business or organization when adopting or incorporating technologies?

Reorienting business strategy and processes
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant
Retraining employees with skills to use new technologies and processes
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant
Hiring workers with skills in technologies
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant
Finding suitable hardware or software vendors
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant
Ensuring high-speed connectivity
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant
Integrating new digital technologies into this business's or organization's existing technology infrastructure
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant
Having access to financial resources to invest in new technologies
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant
Ensuring security and privacy of data
- 1 – Not at all challenging
- 2
- 3
- 4
- 5 – Extremely challenging
- Not relevant

25. Was this business or organization impacted by more, less or approximately the same number of cyber security incidents in 2020 compared to 2019?

A cyber security incident is any unauthorized attempt, whether successful or not, to gain access to, modify, destroy, delete or render unavailable any computer network or system resource.

More
Less
Approximately the same
This business or organization has not experienced any cyber security incidents in 2019 or 2020
Don't know

26. Over the next 12 months, how much will 5G availability impact the operations or services of this business or organization?

5G is the latest standard for high-speed cellular networks.

No impact
A small impact
A moderate impact
A major impact
Don't know

International trade

27. To what degree is this business or organization impacted by changes to international trade agreements or provisions?

e.g., Buy American, Brexit

Not at all
Low
Medium
High
Don't know

Future outlook

28. Over the next 12 months, what is the future outlook for this business or organization?

Very optimistic
Somewhat optimistic
Not optimistic
Don't know

29. How long can this business or organization continue to operate at its current level of revenue and expenditures before having to consider the following options?

Laying off staff:
- Less than 1 month
- 1 month to less than 3 months
- 3 months to less than 6 months
- 6 months to less than 12 months
- 12 months or more
- Not applicable
- Don't know
Closure or bankruptcy:
- Less than 1 month
- 1 month to less than 3 months
- 3 months to less than 6 months
- 6 months to less than 12 months
- 12 months or more
- Not applicable
- Don't know

Flow condition: If the business or organization is a private sector business, go to Q30. Otherwise, go to "Contact person".

Ownership

(i) The groups identified within the following questions are included in order to gain a better understanding of the impact of COVID-19 on businesses or organizations owned by members of various communities across Canada.

30. What percentage of this business or organization is owned by women?

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
1: Don't know

31. What percentage of this business or organization is owned by First Nations, Métis or Inuit peoples?

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
1: Don't know

32. What percentage of this business or organization is owned by immigrants to Canada?

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
1: Don't know

33. What percentage of this business or organization is owned by persons with a disability?

Include visible and non-visible disabilities.
Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
1: Don't know

34. What percentage of this business or organization is owned by LGBTQ2 individuals?

The term LGBTQ2 refers to persons who identify as lesbian, gay, bisexual, transgender, queer and/or two-spirited.

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
1: Don't know

35. What percentage of this business or organization is owned by members of visible minorities?

A member of a visible minority in Canada may be defined as someone (other than an Indigenous person) who is non-white in colour or race, regardless of place of birth.

Provide your best estimate rounded to the nearest percentage.

Percentage:
OR
1: Don't know

Flow condition: If more than 50% of this business or organization is owned by members of visible minorities, go to Q36. Otherwise, go to "Contact person".

36. It was indicated that a percentage of this business or organization is owned by members of visible minorities. Please select the categories that describe the owner or owners.

Select all that apply.

South Asian
e.g., East Indian, Pakistani, Sri Lankan
Chinese
Black
Filipino
Latin American
Arab
Southeast Asian
e.g., Vietnamese, Cambodian, Laotian, Thai
West Asian
e.g., Afghan, Iranian
Korean
Japanese
Other group
- Specify other group:
OR
Prefer not to say

Monthly Survey of Food Services and Drinking Places: CVs for Total Sales by Geography - January 2021

CVs for Total sales by Geography
Table summary
This table displays the results of CVs for Total sales by Geography. The information is grouped by Geography (appearing as row headers), Month and percentage (appearing as column headers).
Geography	Month
	202001	202002	202003	202004	202005	202006	202007	202008	202009	202010	202011	202012	202101
	percentage
Canada	0.17	0.21	5.52	1.21	0.75	0.34	0.36	0.21	0.22	0.23	0.21	0.32	0.49
Newfoundland and Labrador	1.03	0.96	3.79	2.03	1.30	1.05	1.01	0.47	0.77	1.84	0.34	0.96	2.08
Prince Edward Island	4.12	1.42	464.61	52.43	11.92	9.11	8.64	1.14	0.92	1.45	1.10	3.10	5.41
Nova Scotia	0.45	0.94	36.92	4.09	3.94	0.88	1.67	1.49	0.50	0.99	0.39	1.55	2.01
New Brunswick	1.80	1.46	22.28	2.39	2.08	0.82	0.83	2.29	0.63	0.62	0.42	1.00	2.27
Quebec	0.31	0.34	10.28	1.93	1.66	0.70	0.77	0.49	0.62	0.75	0.57	0.82	1.92
Ontario	0.34	0.38	9.15	2.24	1.33	0.63	0.70	0.29	0.34	0.29	0.29	0.59	0.82
Manitoba	0.70	0.81	17.55	5.60	2.47	0.81	0.64	0.49	0.47	1.11	1.25	1.45	1.87
Saskatchewan	1.08	1.24	20.06	5.72	3.08	0.58	1.57	0.73	1.05	1.11	1.11	1.32	1.36
Alberta	0.34	0.68	13.85	2.62	1.76	0.63	0.52	0.26	0.60	0.40	0.38	0.82	0.98
British Columbia	0.33	0.49	14.23	3.21	2.19	1.03	0.90	0.73	0.62	0.76	0.69	0.56	0.75
Yukon Territory	3.01	2.64	35.75	10.07	3.77	3.06	2.06	2.16	2.02	3.50	2.36	6.18	20.98
Northwest Territories	1.57	1.64	20.02	6.95	3.24	2.48	2.31	2.73	2.63	2.68	2.06	2.67	28.75
Nunavut	2.42	61.77	3.97	315.64	5.07	3.93	1.83	2.93	0.65	2.47	73.35	1.91	3.66

New Interactive Tool Helps Users Better Understand Impacts of COVID-19 School Closures on Young Canadians

Ottawa, March 23, 2021

Statistics Canada, in partnership with Children First Canada, a national organization that is mobilizing an alliance of children's charities, hospitals and researchers, has launched a new online tool aimed at providing data-driven insights into the impacts of pandemic-related school closures on children and youth.

As the COVID-19 pandemic continues to affect communities and families across the country, policy-makers have employed remote learning approaches and temporarily closed schools in order to curb the spread of the virus. While these measures are intended to reduce the number of COVID-19 cases and deaths, school closures and other pandemic-related restrictions may have unintended effects on the 5.7 million children and youth attending primary or secondary school in Canada. Potential impacts include social isolation, poor mental health, learning loss, food insecurity and vulnerability to abuse.

The School Closures and COVID-19: Interactive tool brings together existing information about children and youth who were already known to be vulnerable before the pandemic, as well as available data on the impacts of temporary school closures on young Canadians. The tool, which includes interactive maps that identify the location of vulnerable communities, provides policy makers, industry leaders, teachers and parents with a single point of access to Statistics Canada data about this topic.

This tool is the result of a partnership between Statistics Canada and Children First Canada, which teamed up to identify effective ways to use existing data to better understand the potential impacts of school closures on children and youth. A virtual event was held in February to gather feedback and consult stakeholders on ways in which to make the tool relevant to their needs.

Quotes

"I want to thank our partner, Children First Canada, for their engagement and collaboration in the development of this tool. Together, we organized a hackathon on the subject of children and COVID-19 in order to provide policy makers information to assist them in meeting the challenges they face today. From this collaborative engagement, we have built a tool that brings together the relevant information into a single place that's accessible to everyone. We value and thank all those who have contributed to each phase of this project. We also acknowledge everyone's continued vested interest in improving the education, health and well-being of our children and youth."

Lynn Barr-Telford, Assistant Chief Statistician, Statistics Canada

"Children First Canada was honoured to be invited by Statistics Canada to partner on this project. The development of this new tool was a collaborative effort to harness data on the health and well-being of children in Canada, to inform policy making and programs to mitigate the impact of school closures on kids. Throughout the pandemic, children and youth have been disproportionately impacted by the COVID-19 restrictions, threatening their academic success, mental health, protection from violence, and food security. Our hope is that this new tool will help lift the burden of the pandemic off children."

Sara Austin, founder and CEO, Children First Canada

Contacts

For more information, contact Media Relations at 613-951-4636, statcan.mediahotline-ligneinfomedias.statcan@statcan.gc.ca or Children First Canada.

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Date modified:: 2024-11-28