Get data on Ontario gross domestic product (GDP) by manufacturing industries. The GDP is a monetary measure of the value of all final goods and services produced in a period. This dataset shows Ontario’s GDP by manufacturing industries, including: * food, beverage and tobacco * chemical and petroleum products * primary metal products * fabricated metal products * machinery * electrical and electronic products * transportation equipment * paper products and printing * plastic and rubber products * other manufacturing

Personal Income Tax Statistics for California resident sole proprietorships by major industry.

Manufacturing industries, annual 21 principal statistics (revenues, expenses, salaries, employment, stocks, etc.), by North American Industry Classification System (NAICS), total and 3-digit level.

This dataset provides a comprehensive view of the job market in California, highlighting companies and cities with the highest number of job opportunities. Created by JoPilot, it contains valuable information for anyone interested in the employment landscape across different industries and regions. It includes key information such as:

• Company name • City • State • Number of active jobs

For job seekers, employers, and researchers, this resource can be particularly useful in several ways:

1. Identifying hot job markets: The data highlights cities with the highest number of job openings, helping job seekers focus their search on areas with more opportunities.
2. Company targeting: By showing which companies have the most active job listings, the dataset allows job seekers to target their applications to organizations that are actively hiring.
3. Industry trends: The information can reveal which industries or sectors are experiencing growth in California, guiding career decisions and educational pursuits.
4. Regional comparisons: Users can compare job markets across different California cities and regions, which is valuable for those considering relocation or analyzing economic trends.
5. Skill alignment: While the dataset doesn't directly provide skill requirements, it can be used alongside other resources to align job seekers' skills with in-demand positions.

For a more comprehensive job search strategy, consider complementing this dataset with additional resources such as the California Labor Market Information tools, which offer detailed insights into wages, employment projections, and industry-specific data.

This table contains data described by the following dimensions (Not all combinations are available): Geography (17 items: Canada; Atlantic Region; Newfoundland and Labrador; Prince Edward Island; ...) Principal statistics (22 items: Total revenue; Revenue from goods manufactured; Total expenses; Total salaries and wages, direct and indirect labour; ...) North American Industry Classification System (NAICS) (290 items: Manufacturing; Food manufacturing; Animal food manufacturing; Animal food manufacturing; ...).

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Industry. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Industry. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Industry, where there exist only two delineated age groups, the median household income is $111,042 for householders within the 65 years and over age group, compared to $56,250 for the 25 to 44 years age group.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Industry median household income by age. You can refer the same here

This table contains 5976 series, with data for years 1984 - 2011 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Newfoundland and Labrador; New Brunswick; Nova Scotia; Prince Edward Island ...), Value (4 items: Current dollars; 1997 constant dollars; Chained (2002) dollars; Chained (1997) dollars ...), North American Industry Classification System (NAICS) (115 items: All industries; Forestry and logging; Agriculture; forestry; fishing and hunting; Crop and animal production ...).

The Comparative Political Economy Database (CPEDB) began at the Centre for Learning, Social Economy and Work (CLSEW) at the Ontario Institute for Studies in Education at the University of Toronto (OISE/UT) as part of the Changing Workplaces in a Knowledge Economy (CWKE) project. This data base was initially conceived and developed by Dr. Wally Seccombe (independent scholar) and Dr. D.W. Livingstone (Professor Emeritus at the University of Toronto). Seccombe has conducted internationally recognized historical research on evolving family structures of the labouring classes (A Millennium of Family Change: Feudalism to Capitalism in Northwestern Europe and Weathering the Storm: Working Class Families from the Industrial Revolution to the Fertility Decline). Livingstone has conducted decades of empirical research on class and labour relations. A major part of this research has used the Canadian Class Structure survey done at the Institute of Political Economy (IPE) at Carleton University in 1982 as a template for Canadian national surveys in 1998, 2004, 2010 and 2016, culminating in Tipping Point for Advanced Capitalism: Class, Class Consciousness and Activism in the ‘Knowledge Economy’ (https://fernwoodpublishing.ca/book/tipping-point-for-advanced-capitalism) and a publicly accessible data base including all five of these Canadian surveys (https://borealisdata.ca/dataverse/CanadaWorkLearningSurveys1998-2016). Seccombe and Livingstone have collaborated on a number of research studies that recognize the need to take account of expanded modes of production and reproduction. Both Seccombe and Livingstone are Research Associates of CLSEW at OISE/UT. The CPEDB Main File (an SPSS data file) covers the following areas (in order): demography, family/household, class/labour, government, electoral democracy, inequality (economic, political & gender), health, environment, internet, macro-economic and financial variables. In its present form, it contains annual data on 725 variables from 12 countries (alphabetically listed): Canada, Denmark, France, Germany, Greece, Italy, Japan, Norway, Spain, Sweden, United Kingdom and United States. A few of the variables date back to 1928, and the majority date from 1960 to 1990. Where these years are not covered in the source, a minority of variables begin with more recent years. All the variables end at the most recent available year (1999 to 2022). In the next version developed in 2025, the most recent years (2023 and 2024) will be added whenever they are present in the sources’ datasets. For researchers who are not using SPSS, refer to the Chart files for overviews, summaries and information on the dataset. For a current list of the variable names and their labels in the CPEDB data base, see the excel file: Outline of SPSS file Main CPEDB, Nov 6, 2023. At the end of each variable label in this file and the SPSS datafile, you will find the source of that variable in a bracket. If I have combined two variables from a given source, the bracket will begin with WS and then register the variables combined. In the 14 variables David created at the beginning of the Class Labour section, you will find DWL in these brackets with his description as to how it was derived. The CPEDB’s variables have been derived from many databases; the main ones are OECD (their Statistics and Family Databases), World Bank, ILO, IMF, WHO, WIID (World Income Inequality Database), OWID (Our World in Data), Parlgov (Parliaments and Governments Database), and V-Dem (Varieties of Democracy). The Institute for Political Economy at Carleton University is currently the main site for continuing refinement of the CPEDB. IPE Director Justin Paulson and other members are involved along with Seccombe and Livingstone in further development and safe storage of this updated database both at the IPE at Carleton and the UT dataverse. All those who explore the CPEDB are invited to share their perceptions of the entire database, or any of its sections, with Seccombe generally (wseccombe@sympatico.ca) and Livingstone for class/labour issues (davidlivingstone@utoronto.ca). They welcome any suggestions for additional variables together with their data sources. A new version CPEDB will be created in the spring of 2025 and installed as soon as the revision is completed. This revised version is intended to be a valuable resource for researchers in all of the included countries as well as Canada.

This table contains 909 series, with data for years 1981 - 2012 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...) Seasonal adjustment (2 items: Seasonally adjusted at annual rates; Trading-day adjusted ...) Prices (2 items: Chained (2002) dollars; 2002 constant prices ...) North American Industry Classification System (NAICS) (303 items: All industries; Business sector industries; Business sector; goods; Business sector; services ...).

VITAL SIGNS INDICATOR Jobs by Industry (EC1)

FULL MEASURE NAME Employment by place of work by industry sector

LAST UPDATED July 2019

DESCRIPTION Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

DATA SOURCE Bureau of Labor Statistics: Current Employment Statistics 1990-2017 http://data.bls.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment by place of work and by industry. Industries are classified by their North American Industry Classification System (NAICS) code. Vital Signs aggregates employment into 11 industry sectors: Farm, Mining, Logging and Construction, Manufacturing, Trade, Transportation and Utilities, Information, Financial Activities, Professional and Business Services, Educational and Health Services, Leisure and Hospitality, Government, and Other. EDD counts all public-sector jobs under Government, including public transportation, public schools, and public hospitals. The Other category includes service jobs such as auto repair and hair salons and organizations such as churches and social advocacy groups. Employment in the technology sector are classified under three categories: Professional and Business Services, Information, and Manufacturing. The latter category includes electronic and computer manufacturing. For further details of typical firms found in each sector, refer to the 2012 NAICS Manual (http://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2012).

The Bureau of Labor Statistics (BLS) provides industry estimates for non-Bay Area metro areas. Their main industry employment estimates, the Current Employment Survey and Quarterly Census of Employment and Wages, do not provide annual estimates of farm employment. To be consistent, the metro comparison evaluates nonfarm employment for all metro areas, including the Bay Area. Industry shares are thus slightly different for the Bay Area between the historical trend and metro comparison sections.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of the nation’s employment in that same sector. Because BLS does not provide national farm estimates, note that there is no LQ for regional farm employment. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

Gross Domestic Product (GDP) is a measure of the economic production which takes place within the geographical boundaries of a province or country. It can be measured at basic prices (by industry) or at market prices.

Multifactor productivity and related variables in the aggregate business sector and major sub-sectors, by North American Industry Classification System (NAICS), provinces.

About this dataset

Context

The dataset tabulates the Industry population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Industry across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Industry was 257, a 0.77% decrease year-by-year from 2022. Previously, in 2022, Industry population was 259, a decline of 1.15% compared to a population of 262 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Industry decreased by 271. In this period, the peak population was 651 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Industry is shown in this column.
• Year on Year Change: This column displays the change in Industry population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Industry Population by Year. You can refer the same here

Percentage of enterprises for which specific events occurred in the main geographical market, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Specific events include entry of new competitor(s), exit of competitor(s), increase in competitive behaviour from existing competitors, and decrease in competitive behaviour from existing competitors.

The Ontario Economic Accounts (OEA) is a public document, released four times a year that provides an overall assessment of the current state of the Ontario economy. OEA estimates are based on Statistics Canada data. Its primary audience includes economists in both public and private sectors and credit rating agencies.

*[OEA]: Ontario Economic Accounts

This table contains 30 series, with data for years 1981 - 2006 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...) Prices (2 items: 1997 constant dollars; Chained 1997 dollars ...) Special industry aggregations (15 items: Business sector industries; Business sector; goods; Non-business sector industries; Business sector; services ...).

Survey of innovation, logging and manufacturing industries, percentage of the plant's total revenue that came from the most important customer or client who was not a part of the firm by type of plant, percentage range of the plant's total revenue and the North American Industry Classification System (NAICS) for Canada, provinces and territories in 2005. (Terminated)

About this dataset

Context

The dataset tabulates the Industry population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Industry across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Industry was 255, a 0.78% decrease year-by-year from 2021. Previously, in 2021, Industry population was 257, a decline of 1.15% compared to a population of 260 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Industry decreased by 273. In this period, the peak population was 651 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Industry is shown in this column.
• Year on Year Change: This column displays the change in Industry population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Industry Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Industry by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Industry across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 59.67% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Industry is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Industry total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Industry Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Industry population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Industry. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 91 (50.28% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Industry population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Industry is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Industry is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Industry Population by Age. You can refer the same here