In 2023, the GDP of Maine amounted to around 75.2 billion U.S. dollars. The finance, insurance, real estate, rental, and leasing industry added the most real value to the gross domestic product of Maine, amounting to around 17.51 billion U.S. dollars. In the same year, the manufacturing industry contributed around 6.81 billion U.S. dollars.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the Industry town 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 town 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 town was 801, a 0.50% increase year-by-year from 2022. Previously, in 2022, Industry town population was 797, an increase of 0.63% compared to a population of 792 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Industry town increased by 16. In this period, the peak population was 928 in the year 2019. 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).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town Population by Year. You can refer the same here
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Graph and download economic data for Gross Domestic Product: Primary Metal Manufacturing (331) in Maine (MEPRIMETMANNGSP) from 1997 to 2023 about primary metals, ME, primary, metals, GSP, durable goods, private industries, goods, private, manufacturing, industry, GDP, and USA.
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License information was derived automatically
Gross Domestic Product: Primary Metal Manufacturing (NAICS 331) in Maine was 45.70000 Mil. of $ in January of 2023, according to the United States Federal Reserve. Historically, Gross Domestic Product: Primary Metal Manufacturing (NAICS 331) in Maine reached a record high of 45.70000 in January of 2023 and a record low of 19.90000 in January of 2017. Trading Economics provides the current actual value, an historical data chart and related indicators for Gross Domestic Product: Primary Metal Manufacturing (NAICS 331) in Maine - last updated from the United States Federal Reserve on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Industry, Maine, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Real Gross Domestic Product: Primary Metal Manufacturing (NAICS 331) in Maine was 50.80000 Mil. of Chn. 2009 $ in January of 2023, according to the United States Federal Reserve. Historically, Real Gross Domestic Product: Primary Metal Manufacturing (NAICS 331) in Maine reached a record high of 50.80000 in January of 2023 and a record low of 15.70000 in January of 2006. Trading Economics provides the current actual value, an historical data chart and related indicators for Real Gross Domestic Product: Primary Metal Manufacturing (NAICS 331) in Maine - last updated from the United States Federal Reserve on August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Industry town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.
Key observations: Insights from 2023
Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Industry town, the median income for all workers aged 15 years and older, regardless of work hours, was $50,000 for males and $30,400 for females.
These income figures highlight a substantial gender-based income gap in Industry town. Women, regardless of work hours, earn 61 cents for each dollar earned by men. This significant gender pay gap, approximately 39%, underscores concerning gender-based income inequality in the town of Industry town.
- Full-time workers, aged 15 years and older: In Industry town, among full-time, year-round workers aged 15 years and older, males earned a median income of $57,981, while females earned $46,250, leading to a 20% gender pay gap among full-time workers. This illustrates that women earn 80 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Industry town.
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.
Gender classifications include:
Employment type classifications include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town median household income by race. You can refer the same here
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Graph and download economic data for Chain-Type Quantity Index for Real GDP: Primary Metal Manufacturing (331) in Maine (MEPRIMETMANQGSP) from 1997 to 2023 about primary metals, quantity index, ME, primary, metals, GSP, durable goods, private industries, goods, private, manufacturing, industry, GDP, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Industry town population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Industry town. The dataset can be utilized to understand the population distribution of Industry town by age. For example, using this dataset, we can identify the largest age group in Industry town.
Key observations
The largest age group in Industry, Maine was for the group of age 30 to 34 years years with a population of 114 (11.17%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Industry, Maine was the 80 to 84 years years with a population of 9 (0.88%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
Age groups:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town Population by Age. You can refer the same here
Significant mineral commodities - Mining in Maine has a long history unknown to many citizens. Some of us have seen the granite quarries which remain from an industry established more than 150 years ago. Gravel pits are a common sight today, and many people are familiar with Maine's limestone, slate, and crushed stone operations. However, the well-known resources of modern times are but a few of the mineral products that have been produced in Maine. This view gives a general overview of the mineral commodities important to Maine's economic history.Significant metal deposits - Prospectors have searched for metals in Maine since the 1800's. During a flurry of excitement in the early 1880's, metal deposits were mined along the coastal volcanic belt from Blue Hill to Lubec. Extensive manganese deposits were delineated during World War II. More intensive exploration from the mid-1970's to early 1990's produced several important discoveries. This view locates nine of the largest known metal deposits in the state.Selected historical mines - Mining and quarrying have been an integral part of Maine's economy since the 1800's. Over time, changing economic conditions created boom and bust cycles in the demand for different commodities. Witness the Maine granite industry which reached its high point in 1901, with 152 quarries employing at least 3,500 men. However, the development of Portland cement as a building material in the early 1900's, and the depression of the 1930's, dealt Maine's granite industry a blow from which it would never recover. The mines and quarries in this view were selected to give an overview of the activities that were important in Maine's history of mineral production.Pegmatite quarriesStone quarriesMineral Resources Data System - All sites
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The global lobster market, valued at $5,208 million in 2025, is projected to experience robust growth, driven by increasing consumer demand for premium seafood and the rising popularity of lobster in diverse culinary applications. The market's Compound Annual Growth Rate (CAGR) of 12.8% from 2025 to 2033 indicates significant expansion opportunities. Key drivers include growing disposable incomes in emerging economies, fueling demand for luxury seafood products like lobster. Furthermore, the increasing adoption of sustainable fishing practices and aquaculture initiatives are contributing to a more stable supply chain, partially mitigating concerns about overfishing. Market segmentation reveals strong performance across various lobster types, with Japanese, Maine, and Chilean lobsters leading in popularity. The foodservice sector remains a dominant channel, encompassing high-end restaurants and casual dining establishments. However, the retail segment is also witnessing substantial growth as consumers increasingly seek convenient, high-quality lobster options for home consumption. Geographic analysis shows strong market presence in North America and Europe, while Asia-Pacific presents considerable growth potential due to rising seafood consumption and economic development. Challenges include price volatility due to fluctuating supply and demand, as well as environmental concerns related to lobster fishing and aquaculture. Nevertheless, the market’s long-term outlook remains positive, fueled by sustained consumer demand and ongoing industry efforts to ensure sustainability. The competitive landscape is characterized by a mix of established players and regional producers. Key players like Boston Lobster and Clearwater Seafoods are leveraging their brand recognition and established distribution networks to maintain their market share. However, smaller, regional companies are also successfully catering to specific niche markets and regional preferences. Future market growth will depend on several factors, including the success of sustainable aquaculture initiatives, evolving consumer preferences, and regulatory developments related to fishing and seafood trade. Effective marketing strategies that highlight the premium quality and culinary versatility of lobster will be crucial in driving continued market expansion. Innovation in processing and packaging is also expected to play a significant role in enhancing the accessibility and appeal of lobster to a broader consumer base.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Industry town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Industry town. The dataset can be utilized to understand the population distribution of Industry town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Industry town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Industry town.
Key observations
Largest age group (population): Male # 30-34 years (72) | Female # 0-4 years (80). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
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.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town Population by Gender. You can refer the same here
Survey participants plotted activity points using an interactive mapping tool.The 2012 Northeast Recreational Boater Survey was conducted by SeaPlan, the Northeast Regional Ocean Council (NROC), states’ coastal agencies, marine trade associations composed of many private industry representatives, and the First Coast Guard District. The methodology for the 2012 Northeast Recreational Boater Survey follows a protocol similar to the 2010 Massachusetts Survey with modifications based on the lessons learned and recommendations suggested in the Massachusetts Survey Final Report.The methodology consists of surveying a random sample of selected boat owners throughout the Northeast through a series of monthly online surveys. The surveying period lasted throughout the 2012 boating season (May 1 through October 31, 2012), which was identified by the advisory committee (consisting of NROC and representatives from the recreational boating industry).The project team decided to use a random sample survey approach because it successfully gathered statistically robust economic and spatial data on recreational boating activity by Massachusetts registered boaters during the 2010 boating season. This was also the only approach that would allow for the calculation of statistically robust economic impact estimates for both the states and the region, which was identified as a priority (along withspatial data) by both NROC and the boating industry.
This dataset can be used by coastal planners in ocean planning activities to develop a better understanding of how and where humans use the ocean in the Northeast to inform regional ocean planning and minimize ocean use conflicts. This effort also fulfilled a recommendation from the 2010 Massachusetts Survey to expand the survey’s geographic range to the Northeast Region, allowing for the capture of interstate traffic between states in the Northeast. Furthermore, this dataset can also be used by the boating industry to show the importance of recreational boating to the region and to inform business planning.
Supplemental Information; SURVEY SAMPLING METHODOLOGY - The sample for this survey came from seven databases, including the U.S. Coast Guard Documented Vessel Database and databases of state registered boaters from New York, Connecticut, Rhode Island, Massachusetts, New Hampshire, and Maine. Recreational boaters who owned vessels that met the following criteria were eligible for the survey: * Registration: Currently registered with a state in the Northeast and/or registered as a documented vessel with the U.S. Coast Guard, with a hailing port in the Northeast * Primary Use: Recreational use designation * Length: At least 10 feet in length * Saltwater (if specified; only Maine and New Hampshire required this information) * Location: Located in a “coastal county”. The survey team defined “coastal counties” as those that border saltwater, or those that were highlighted by state coastal planners as likely containing large amount of saltwater boating activity. Based on the 2010 Massachusetts Survey and budgetary considerations, the project team determined an overall sample size that would provide sufficient spatial and economic data for both each state, as well as the whole Northeast. Because of the, at times, large discrepancies between the number of eligible boats in some states, the team decided that certain states with fewer eligible boats should also have a supplemental sample of boats in addition to the pure random sample. To ensure the sample represented the total population of registered boats in the Northeast, the sampling method included considerations of state, geography and size class. Of the 373,766 boats eligible for the survey, the base of randomly sampled boats included 50,000 boats from across all six states. In addition to this base, the survey team sampled 17,772 boats as a supplemental sample, including: 1,772 boats of 26 feet in length or more from across all six states to increase the number of large boats in the sample, and 16,000 additional boats to ensure each state had enough responses for the statistical analysis. These included 10,000 boats from Maine, 2,500 boats from Rhode Island, 2,000 boats from New Hampshire and 1,500 boats from Connecticut. This resulted in a total of 67,772 boaters invited to participate in the study. Boater Recruitment and Response: In the survey invitation package, the survey team also sent invited boaters a questionnaire to verify eligibility to participate in the survey. Eligibility requirements consist of: boat is used in saltwater; boat is used for recreational purposes; and boaters have access to the internet with a working email address. 12,218 boaters responded to the invitation; however only 7,800 of these respondents were found to meet all of the above criteria. From this sample, 4,297 individual boaters completed at least one monthly survey. Surveying Process: The study consisted of six monthly surveys and one end of season survey. The online monthly surveys gathered spatial and economic data on recreational boating activity that occurred during the previous month. The online survey had two parts: 1) a survey with questions about general boating activity during the previous month, and the boater’s last trip of the month (specifically focusing on spending), and 2) a mapping application developed by Ecotrust where boaters plotted their boating route and identified any areas where they participated in activities, such as fishing, diving, wildlife viewing, swimming and relaxing at anchor. The end of season survey gathered a variety of information that could not be gathered in the monthly surveys. The end of season survey contained questions about yearly boating-related expenditures (e.g., dockage, storage, taxes, yearly maintenance), feedback on the survey itself, and general boating-related questions (e.g. whether boaters have taken a boating safety course). Density Analysis: The density analysis described in the following paragraphs was vetted by a technical advisory team consisting of representatives from the Massachusetts Office of Coastal Zone Management (MA CZM), NROC, Maine Coastal Program and Applied Science Associates (ASA) and was based on mapping and analysis protocols from the 2010 Massachusetts Survey. To develop the density layer, vessel routes were drawn in WGS 1984 in the Ecotrust mapping application and were imported into Excel, then ArcMap using a data frame in that coordinate system. Routes from the random sample were selected from that data layer, and the data layer was re-projected into two separate shapefiles, one in UTM 18 and one in UTM 19. A line density analysis using a 250 m square grid cell with a 675 m neighborhood was applied to each shapefile. The 675 m neighborhood was applied to account for inherent user error in the mapping tool. The line density analysis resulted in a raster grid for each UTM zone. Each raster was clipped by the boundaries of its UTM zone, re-projected into the North American Albers Equal Area Conic Projection, and the separate rasters were mosaicked together. At the boundary of the two raster grids there was a line of cells with no data value. This was a result of mosaicking rasters that originated in different coordinate systems. To approximate values in the blank cells, each blank cell was populated by a value from a focal statistics calculation. The focal statistics expression took the mean of all cells in a 4x4 neighborhood around each blank cell. The values were then converted to Z-scores using the raster calculator by taking the log of the density values, subtracting the mean value, and dividing the resulting value by the standard deviation of the value. This layer was clipped again using the NOAA medium resolution shoreline dataset. DATA PROCESSING Processing environment: ArcGIS 10.05, Windows 7 Ultimate SP5, Intel Xeon CPU Process Steps Description 1 Raw routes from mapping application imported into ArcMap 2 Routes from random sample selected using select by attributes query 3 Routes projected into two separate shapefiles (UTM Zones 18 & 19) 4 LINE DENSITY tool in spatial analyst applied to each shapefile using a 250 m square grid with a 675 m neighborhood 5 Resulting rasters clipped to their respective UTM Zones using the EXTRACT BY MASK tool 6 Rasters reprojected to North America Albers Equal Area Conic Projection, using PROJECT tool 7 MOSAIC tool used to merge rasters 8 Focal mean expression (4x4 neighborhood) used to approximate and fill cells with no data at the boundary between mosaicked rasters 9 Raster calculator used to calculated Z-scores ([(Ln(Value))-Mean]/Std. Deviation) 10 Raster clipped by NOAA Medium Resolution Shoreline data using EXTRACT BY POLYGON tool QUALITY PROCESS Attribute Accuracy: The lines used to generate the density grid were derived from a mapping tool used by boaters to reconstruct their boating routes. To ensure that boaters included their round-trip route the mapping applications would send the user an error message asking them to re-plot the route or the program would automatically return the route to the starting point. This application also restricted the scale at which users could draw their routes, reducing the amount of error that could occur from plotting routes at too small a scale. Clipping this layer with a regional ocean shapefile derived from the NOAA medium resolution shoreline dataset excluded route density resulting from routes drawn over land, in freshwater, or outside of northeastern waters. Logical Consistency: None Completeness: Only reported routes from the random sample were included. Routes from the supplemental sample were excluded from this analysis. Route density occurring over land, freshwater areas, or outside northeastern waters was excluded by the final geoprocessing step. Positional Accuracy: The positional accuracy of the routes is dependent on the individual reporting routes through the
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Industry town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Industry town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 93.44% of the total residents in Industry town. Notably, the median household income for White households is $63,125. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $63,125.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset illustrates the median household income in Industry town, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.
Key observations:
From 2010 to 2023, the median household income for Industry town increased by $2,735 (4.82%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.
Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 6 years and declined for 7 years.
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 2022-inflation-adjusted dollars.
Years for which data is available:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Industry town by race. It includes the population of Industry town across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Industry town across relevant racial categories.
Key observations
The percent distribution of Industry town population by race (across all racial categories recognized by the U.S. Census Bureau): 93.44% are white, 0.49% are Black or African American, 0.20% are some other race and 5.88% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the data for the Industry, Maine population pyramid, which represents the Industry town population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Industry town Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Industry town, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Industry town.
Key observations
Among the Hispanic population in Industry town, regardless of the race, the largest group is of Other Hispanic or Latino origin, with a population of 11 (100% of the total Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Origin for Hispanic or Latino population include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Industry town. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Industry town. 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 2022
In terms of income distribution across age cohorts, in Industry town, the median household income stands at $71,152 for householders within the 45 to 64 years age group, followed by $61,173 for the 65 years and over age group. Notably, householders within the 25 to 44 years age group, had the lowest median household income at $51,446.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Industry town median household income by age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Industry town. The dataset can be utilized to gain insights into gender-based income distribution within the Industry town population, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
Employment type classifications include:
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.
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/.
This dataset is a part of the main dataset for Industry town median household income by race. You can refer the same here
In 2023, the GDP of Maine amounted to around 75.2 billion U.S. dollars. The finance, insurance, real estate, rental, and leasing industry added the most real value to the gross domestic product of Maine, amounting to around 17.51 billion U.S. dollars. In the same year, the manufacturing industry contributed around 6.81 billion U.S. dollars.