This statistic shows the distribution of the gross domestic product (GDP) of Alberta in 2022, by industry. In that year, the construction industry accounted for 8.27 percent of the GDP of Alberta.

This product provides information on Alberta Average Hourly Wage Rates (by Gender, by Age-groups, and by Full-time, Part-time) for Agriculture and Other Major Industries for a five-year period. Annual Percent Change from previous year 2013 is included.

In 2023, the gross domestic product of all industries in Alberta increased by 4.8 billion dollars since 2022. With 336.3 billion dollars, the gross domestic product reached its highest value in the observed period. Find more key insights for the gross domestic product of all industries in countries and regions like na of all industries (British Columbia), na of all industries (Manitoba), and na of all industries (Newfoundland and Labrador).

Economic multipliers are used to assess the impacts on the economy of an exogenous change in final demand or output of a given industry. Based on the Input-Output (I/O) tables released by Statistics Canada, they provide a measure of the interdependence between an industry and the rest of the economy. Multipliers for the Alberta economy have been developed using the Alberta Treasury Board and Finance Input-Output (I/O) model. Impacts are estimated in terms of total output, gross domestic product, employment and labour income. There are two main types of economic multipliers provided in the dataset: 1) Open model (direct and indirect impacts), and 2) Closed model (direct, indirect and induced impacts). Starting with the 2008 publication, a supplemental set of multipliers was added to the dataset: under a Closed model with a “Safety Net”, these additional multipliers incorporate the assumption that new jobs were filled by people previously receiving employment insurance, effectively reducing the amount of additional income spent in the economy. The multipliers are accompanied by commodity supply ratios, which represent the aggregated proportion of the supply that comes from within and outside Alberta for each major commodity group.

Interprovincial employees or IPEs are individuals who found employment in Alberta but maintained their primary residence in another part of the country. This Demographic Spotlight shows a breakdown of IPEs working in Alberta by industry and by region.

Output by industry, in current dollars, evaluated at basic price for all provinces and territories. These estimates are derived from the provincial Supply and Use Tables.

This product provides information on Alberta Average Hourly Wage Rates (by Gender, by Age-groups, and by Full-time, Part-time) for Agriculture and Other Major Industries for a five-year period. Annual Percent Change from previous year 2013 is included.

Alberta’s manufacturing sector is currently in recession as a result of the dramatic drop in crude oil prices. Lower oil prices have translated into much lower selling prices of refinery products and are causing oil and gas companies to drastically lower their capital spending which translates into reduced demand for machinery and equipment produced by Alberta’s manufacturing and fabricated metals sectors.

The table break down the Alberta injury claims to major industry sectors. For each major industry sector, it shows number of 3 type injury claims, person-year worked, and injury rates in the most current 2 years. In addition, the percentage change comparing to the previous year.

This report was compiled to describe the overall sectoral characteristics and trends in economic activity in southern Alberta, to identify key drivers that may determine the future direction of the economy, and to give a general description of the types of environmental impacts that might be expected as a result of economic development in key sectors. Data included in this report were collected through a document and literature review and through interviews with social and environmental scientists, economists, industry representatives, and government officials.

The 2014 Small Business, Big Impact: Alberta Small Business Profile provides useful statistics about the contributions made by small businesses to the provincial economy and their roles in some of Alberta’s important and growing industries.

The labour productivity in all industries in Alberta decreased by 1.8 chained (2012) dollars per hour (-2.28 percent) in 2023 in comparison to the previous year. Nevertheless, the last two years recorded a significant higher labour productivity than the preceding years.Find more key insights for the labour productivity in all industries in countries and regions like labour productivity in all industries (British Columbia), labour productivity in all industries (New Brunswick), and labour productivity in all industries (Newfoundland and Labrador).

(StatCan Product) Detailed employed labour force by selected industries (Food and Beverage Manufacturing) for Canada, provinces and Alberta's Economic Regions (annual averages). Customization details: This information product has been customized to present information on employed labour force by selected industries (Food and Beverage Manufacturing) for Canada, provinces and Alberta's Economic Regions (ER). A comparison is also made between Food and Beverage Manufacturing industries that includes tobacco manufacturing to the one that does not. The file includes 5 tables: Table 1: Detailed Employed Labour Force by Selected Industries, Canada and Provinces Table 2a: Alberta Employed Labour Force in the Food Related Industries, Canada and Provinces (Food and Beverage Manufacturing Industries Exludes Tobacco Manufacturing) Table 2b: Alberta Employed Labour Force in Food Related Industries, Canada and Provinces (Food and Beverage Manufacturing Industries includes Tobacco Manufacturing. Table 3: Employed Labour Force, Agriculture and Food and Beverage Manufacturing Industries, Alberta and Alberta Economic Regions. Table 4: Detailed Employed Labour Force for All Industries (4-digit NAICS), 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.

(StatCan Product) Customization details: This information product has been customized to present information on manufacturing industries by Alberta's Census Divisions (CD) by 1, 3, 4, 5 and 6 digit NAICS codes for 2009. Other variables presented include: - Number of establishments - Total revenue - Revenue from goods manufactured - Total expenses - Total salaries and wages (direct and indirect labour) - Production workers wages (direct labour) - Non-manufacturing employees salaries (indirect labour) - Total cost of energy, water, utility and vehicle fuel - Cost of energy and water utility - Cost of vehicle fuel - Cost of materials and supplies - Total number of employees (direct and indirect labour) - Number of production workers (direct labour) - Number of non-manufacturing employees (indirect labour) - Total opening inventories - Opening inventories - Goods or work in process - Opening inventories - Finished goods manufactured - Total closing inventories - Closing inventories - Goods/work in process - Closing inventories - Finished good manufactured - Manufacturing value added Annual Survey of Manufactures and Logging The Annual Survey of Manufactures and Logging (ASML) is a survey of the manufacturing and logging industries in Canada. It is intended to cover all establishments primarily engaged in manufacturing and logging activities, as well as the sales offices and warehouses which support these establishments. The details collected include principal industrial statistics (such as revenue, employment, salaries and wages, cost of materials and supplies used, cost of energy and water utility, inventories, etc.), as well as information about the commodities produced and consumed. Data collected by the Annual Survey of Manufactures and Logging are important because they help measure the production of Canada's industrial and primary resource sectors, as well as provide an indication of the well-being of each industry covered by the survey and its contribution to the Canadian economy. Within Statistics Canada, the data are used by the Canadian System of National Accounts, the Monthly Survey of Manufacturing (record number 2101) and Prices programs. The data are also used by the business community, trade associations, federal and provincial departments, as well as international organizations and associations to profile the manufacturing and logging industries, undertake market studies, forecast demand and develop trade and tariff policies. Product Main Page

Number of employees by North American Industry Classification System (NAICS) and type of employee, last 5 years.

Annual Provincial and Territorial Gross Domestic Product (GDP) at basic prices, by North American Industry Classification aggregates, in chained and current dollars, growth rate.

This dataset is a customization of Statistics Canada data to present retirement median age by sex and major industry (NAICS 2 digit) for Canada and Provinces from 1987 to 2018.

(StatCan Product) Customization details: This information product has been customized to present information on concentration ratios in the manufacturing industries by 1, 3, 4, 5 and 6 digit NAICS codes for Alberta as a whole. Other variables presented include: Number of establishments, Revenue from goods manufactured and Leading Enterprises. Annual Survey of Manufactures and Logging The Annual Survey of Manufactures and Logging (ASML) is a survey of the manufacturing and logging industries in Canada. It is intended to cover all establishments primarily engaged in manufacturing and logging activities, as well as the sales offices and warehouses which support these establishments. The details collected include principal industrial statistics (such as revenue, employment, salaries and wages, cost of materials and supplies used, cost of energy and water utility, inventories, etc.), as well as information about the commodities produced and consumed. Data collected by the Annual Survey of Manufactures and Logging are important because they help measure the production of Canada's industrial and primary resource sectors, as well as provide an indication of the well-being of each industry covered by the survey and its contribution to the Canadian economy. Within Statistics Canada, the data are used by the Canadian System of National Accounts, the Monthly Survey of Manufacturing (record number 2101) and Prices programs. The data are also used by the business community, trade associations, federal and provincial departments, as well as international organizations and associations to profile the manufacturing and logging industries, undertake market studies, forecast demand and develop trade and tariff policies.

The Canada Power Industry size was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, exhibiting a CAGR of 8.50">> 8.50 % during the forecasts periods. The power market is a dynamic and evolving sector, driven by the growing energy demands and efforts to diversify its energy mix. The market is segmented into power generation, transmission, and distribution, with significant contributions from thermal, hydro, renewable, and nuclear sources. Thermal power, which includes oil, coal, natural gas, and nuclear energy, remains a dominant force in power generation landscape. Renewable energy, particularly wind and solar power, is gaining traction due to its environmental benefits and decreasing costs. The geographical advantages, such as its vast solar potential and favorable wind conditions, make it an ideal location for renewable energy projects. Hydropower also plays a significant role, leveraging the country's abundant water resources to generate clean energy. The power market is also characterized by its regulatory environment, which has seen significant changes in recent years. The government's efforts to reduce private investments and increase state control over the energy sector have created both opportunities and challenges for market participants. Recent developments include: Kineticor Resource is currently developing a combined cycle gas turbine (CCGT) power plant in Edson, Alberta, called as Cascade CCGT power plant. The 900MW power plant got its construction started in 2020, with an estimated investment plan of USD 1 billion. The project is to be completed in two phases by the end of 2022., In January 2022, Canada planned a new utility-scale solar power project, Fox Coulee Solar Project, in Alberta. The 85.6MW solar PV power project will be developed by Aura Power Developments and Subra GP in a single phase. Its construction is expected to commence in 2022, and it is expected to be in service by 2023.. Key drivers for this market are: 4., Favorable Government Policies4.; Declining Solar Panel Costs. Potential restraints include: 4., Development of Alternate Sources of Renewable Energy. Notable trends are: Renewables Expected to Witness Significant Growth.

Number of employees by North American Industry Classification System (NAICS) and data type (seasonally adjusted, trend-cycle and unadjusted), last 5 months. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.