(StatCan Product) Participation and unemployment rates and student population counts for Canada and provinces by selected age groups (annual averages in %). Customization details: This information product has been customized to present information onparticipation rates, unemployment rates and student population counts for Canada and provinces by selected age groups (annual averages in percentage). Participation and unemployment rates age groups presented are: - 18 to 24 years - 18 to 34 years - 15 years and over The variables presented for the student population are (18 to 34 years – 8 month averages): - Student and non-student - Number attending college - Number attending university - Others - Total attending PS - % Total attending PS Labour Force Survey The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. Target population The LFS covers the civilian, non-institutionalized population 15 years of age and over. It is conducted nationwide, in both the provinces and the territories. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; full-time members of the Canadian Armed Forces and the institutionalized population. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over. National Labour Force Survey estimates are derived using the results of the LFS in the provinces. Territorial LFS results are not included in the national estimates, but are published separately. Instrument design The current LFS questionnaire was introduced in 1997. At that time, significant changes were made to the questionnaire in order to address existing data gaps, improve data quality and make more use of the power of Computer Assisted Interviewing (CAI). The changes incorporated included the addition of many new questions. For example, questions were added to collect information about wage rates, union status, job permanency and workplace size for the main job of currently employed employees. Other additions included new questions to collect information about hirings and separations, and expanded response category lists that split existing codes into more detailed categories. Sampling This is a sample survey with a cross-sectional design. Data sources Responding to this survey is mandatory. Data are collected directly from survey respondents. Data collection for the LFS is carried out each month during the week following the LFS reference week. The reference week is normally the week containing the 15th day of the month. LFS interviews are conducted by telephone by interviewers working out of a regional office CATI (Computer Assisted Telephone Interviews) site or by personal visit from a field interviewer. Since 2004, dwellings new to the sample in urban areas are contacted by telephone if the telephone number is available from administrative files, otherwise the dwelling is contacted by a field interviewer. The interviewer first obtains socio-demographic information for each household member and then obtains labour force information for all members aged 15 and over who are not members of the regular armed forces. The majority of subsequent interviews are conducted by telephone. In subsequent monthly interviews the interviewer confirms the socio-demographic information collected in the first month and collects the labour force information for the current month. Persons aged 70 and over are not asked the labour force questions in subsequent interviews, but rather their labour force information is carried over from their first interview. In each dwelling, information about all household members is usually obtained from one knowledgeable household member. Such 'proxy' reporting, which accounts for approximately 65% of the information collected, is used to avoid the high cost and extended time requirements that would be involved in repeat visits or calls necessary to obtain information directly from each respondent. Error detection The LFS CAI questionnaire incorporates many features that serve to maximize the quality of the data collected. There are many edits built into the CAI questionnaire to compare the entered data against unusual values, as well as to check for logical inconsistencies. Whenever an edit fails, the interviewer is prompted to correct the information (with the help of the respondent when necessary). For most edit failures the interviewer has the ability to override the edit failure if they cannot resolve the apparent discrepancy. As well, for most questions the interviewer has the ability to enter a response of Don't Know or Refused if the respondent does not answer the question. Once the data is received back at head office an extensive series of processing steps is undertaken to thoroughly verify each record received. This includes the coding of industry and occupation information and the review of interviewer entered notes. The editing and imputation phases of processing involve the identification of logically inconsistent or missing information items, and the correction of such conditions. Since the true value of each entry on the questionnaire is not known, the identification of errors can be done only through recognition of obvious inconsistencies (for example, a 15 year-old respondent who is recorded as having last worked in 1940). Estimation The final step in the processing of LFS data is the assignment of a weight to each individual record. This process involves several steps. Each record has an initial weight that corresponds to the inverse of the probability of selection. Adjustments are made to this weight to account for non-response that cannot be handled through imputation. In the final weighting step all of the record weights are adjusted so that the aggregate totals will match with independently derived population estimates for various age-sex groups by province and major sub-provincial areas. One feature of the LFS weighting process is that all individuals within a dwelling are assigned the same weight. In January 2000, the LFS introduced a new estimation method called Regression Composite Estimation. This new method was used to re-base all historical LFS data. It is described in the research paper ""Improvements to the Labour Force Survey (LFS)"", Catalogue no. 71F0031X. Additional improvements are introduced over time; they are described in different issues of the same publication. Data accuracy Since the LFS is a sample survey, all LFS estimates are subject to both sampling error and non-sampling errors. Non-sampling errors can arise at any stage of the collection and processing of the survey data. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors and other types of processing errors. Non-response to the LFS tends to average about 10% of eligible households. Interviews are instructed to make all reasonable attempts to obtain LFS interviews with members of eligible households. Each month, after all attempts to obtain interviews have been made, a small number of non-responding households remain. For households non-responding to the LFS, a weight adjustment is applied to account for non-responding households. Sampling errors associated with survey estimates are measured using coefficients of variation for LFS estimates as a function of the size of the estimate and the geographic area.

You work hard, your colleagues work hard, and Canadians work hard. Need help proving it? Marie-Josee Major, subject matter analyst from Statistics Canada, introduces the Labour Force Survey. Topics covered include: LFS basics: Respondent classification LFS methodology, modes of access to LFS microdata, and annualizing monthly LFS data.

(StatCan Product) Labour force, Number of employed and Number of unemployed by selected National Occupational Classification (NOC) (2006 Occupations - Energy Sector) for Canada and Alberta from 1987 to 2012 (annual averages). Customization details: This information product has been customized to present information on the labour force, including the employed and unemployed by occupation specifically within the energy sector for Canada and Alberta. Labour Force Survey The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. Target population The LFS covers the civilian, non-institutionalized population 15 years of age and over. It is conducted nationwide, in both the provinces and the territories. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; full-time members of the Canadian Armed Forces and the institutionalized population. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over. National Labour Force Survey estimates are derived using the results of the LFS in the provinces. Territorial LFS results are not included in the national estimates, but are published separately. Instrument design The current LFS questionnaire was introduced in 1997. At that time, significant changes were made to the questionnaire in order to address existing data gaps, improve data quality and make more use of the power of Computer Assisted Interviewing (CAI). The changes incorporated included the addition of many new questions. For example, questions were added to collect information about wage rates, union status, job permanency and workplace size for the main job of currently employed employees. Other additions included new questions to collect information about hirings and separations, and expanded response category lists that split existing codes into more detailed categories. Sampling This is a sample survey with a cross-sectional design. Data sources Responding to this survey is mandatory. Data are collected directly from survey respondents. Data collection for the LFS is carried out each month during the week following the LFS reference week. The reference week is normally the week containing the 15th day of the month. LFS interviews are conducted by telephone by interviewers working out of a regional office CATI (Computer Assisted Telephone Interviews) site or by personal visit from a field interviewer. Since 2004, dwellings new to the sample in urban areas are contacted by telephone if the telephone number is available from administrative files, otherwise the dwelling is contacted by a field interviewer. The interviewer first obtains socio-demographic information for each household member and then obtains labour force information for all members aged 15 and over who are not members of the regular armed forces. The majority of subsequent interviews are conducted by telephone. In subsequent monthly interviews the interviewer confirms the socio-demographic information collected in the first month and collects the labour force information for the current month. Persons aged 70 and over are not asked the labour force questions in subsequent interviews, but rather their labour force information is carried over from their first interview. In each dwelling, information about all household members is usually obtained from one knowledgeable household member. Such 'proxy' reporting, which accounts for approximately 65% of the information collected, is used to avoid the high cost and extended time requirements that would be involved in repeat visits or calls necessary to obtain information directly from each respondent. Error detection The LFS CAI questionnaire incorporates many features that serve to maximize the quality of the data collected. There are many edits built into the CAI questionnaire to compare the entered data against unusual values, as well as to check for logical inconsistencies. Whenever an edit fails, the interviewer is prompted to correct the information (with the help of the respondent when necessary). For most edit failures the interviewer has the ability to override the edit failure if they cannot resolve the apparent discrepancy. As well, for most questions the interviewer has the ability to enter a response of Don't Know or Refused if the respondent does not answer the question. Once the data is received back at head office an extensive series of processing steps is undertaken to thoroughly verify each record received. This includes the coding of industry and occupation information and the review of interviewer entered notes. The editing and imputation phases of processing involve the identification of logically inconsistent or missing information items, and the correction of such conditions. Since the true value of each entry on the questionnaire is not known, the identification of errors can be done only through recognition of obvious inconsistencies (for example, a 15 year-old respondent who is recorded as having last worked in 1940). Estimation The final step in the processing of LFS data is the assignment of a weight to each individual record. This process involves several steps. Each record has an initial weight that corresponds to the inverse of the probability of selection. Adjustments are made to this weight to account for non-response that cannot be handled through imputation. In the final weighting step all of the record weights are adjusted so that the aggregate totals will match with independently derived population estimates for various age-sex groups by province and major sub-provincial areas. One feature of the LFS weighting process is that all individuals within a dwelling are assigned the same weight. In January 2000, the LFS introduced a new estimation method called Regression Composite Estimation. This new method was used to re-base all historical LFS data. It is described in the research paper ""Improvements to the Labour Force Survey (LFS)"", Catalogue no. 71F0031X. Additional improvements are introduced over time; they are described in different issues of the same publication. Data accuracy Since the LFS is a sample survey, all LFS estimates are subject to both sampling error and non-sampling errors. Non-sampling errors can arise at any stage of the collection and processing of the survey data. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors and other types of processing errors. Non-response to the LFS tends to average about 10% of eligible households. Interviews are instructed to make all reasonable attempts to obtain LFS interviews with members of eligible households. Each month, after all attempts to obtain interviews have been made, a small number of non-responding households remain. For households non-responding to the LFS, a weight adjustment is applied to account for non-responding households. Sampling errors associated with survey estimates are measured using coefficients of variation for LFS estimates as a function of the size of the estimate and the geographic area.

The statistic shows the average inflation rate in Canada from 1987 to 2024, with projections up until 2030. The inflation rate is calculated using the price increase of a defined product basket. This product basket contains products and services, on which the average consumer spends money throughout the year. They include expenses for groceries, clothes, rent, power, telecommunications, recreational activities and raw materials (e.g. gas, oil), as well as federal fees and taxes. In 2022, the average inflation rate in Canada was approximately 6.8 percent compared to the previous year. For comparison, inflation in India amounted to 5.56 percent that same year. Inflation in Canada In general, the inflation rate in Canada follows a global trend of decreasing inflation rates since 2011, with the lowest slump expected to occur during 2015, but forecasts show an increase over the following few years. Additionally, Canada's inflation rate is in quite good shape compared to the rest of the world. While oil and gas prices have dropped in Canada much like they have around the world, food and housing prices in Canada have been increasing. This has helped to offset some of the impact of dropping oil and gas prices and the effect this has had on Canada´s inflation rate. The annual consumer price index of food and non-alcoholic beverages in Canada has been steadily increasing over the last decade. The same is true for housing and other price indexes for the country. In general there is some confidence that the inflation rate will not stay this low for long, it is expected to return to a comfortable 2 percent by 2017 if estimates are correct.