Monthly and long-term Canada GDP Per Capita data: historical series and analyst forecasts curated by FocusEconomics.

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

This data presents statistics for Utilities: Exported Energy to Canada and Mexico for the U.S.

About this dataset

Context

The dataset presents median household incomes for various household sizes in New Canada, Maine, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, New Canada town did not include 6, or 7-person households. Across the different household sizes in New Canada town the mean income is $103,835, and the standard deviation is $59,699. The coefficient of variation (CV) is 57.49%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $16,552. It then further increased to $136,465 for 5-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/new-canada-me-median-household-income-by-household-size.jpeg" alt="New Canada, Maine median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 New Canada town median household income. You can refer the same here

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in New Canada town: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 5(4.10%) households where the householder is under 25 years old, 21(17.21%) households with a householder aged between 25 and 44 years, 50(40.98%) households with a householder aged between 45 and 64 years, and 46(37.70%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the town of New Canada town, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 New Canada town median household income by age. You can refer the same here

This product provides Selected Economic Indicators for a thirty-five year period, such as Alberta vs. Canada's Consumer Price Index; Canada Interest (Bank and Prime) Rates; and the Trend of Canada -United States Exchange Rate (US$ per Canada$) for a twenty-five year period.

This data release accompanies USITC Publication 4889, United States-Mexico-Canada Agreement: Likely Impact on the U.S. Economy and on Specific Industry Sectors, USITC investigation no. TPA 105-003. The data were used to perform the collective bargaining econometric modeling analysis as described in appendix F of the report.

Canada and United States bilateral trade in goods data produced by Statistics Canada and the United States Census Bureau (customs basis) and the United States Bureau of Economic Analysis (balance of payments basis). Data are presented before and after adjustments made to standardize definitions. Quarterly data are available on Customs and on Balance of payments basis and are not seasonally adjusted.

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

Canada recorded a Current Account deficit of 9680 CAD Million in the third quarter of 2025. This dataset provides - Canada Current Account - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This table contains 624 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 ...) North American Industry Classification System (NAICS) (312 items: All industries; Agriculture; forestry; fishing and hunting; Crop production; Animal production ...).

Techsalerator’s Import/Export Trade Data for Canada

Techsalerator’s Import/Export Trade Data for Canada provides a comprehensive and insightful collection of information on international trade activities involving Canadian companies. This dataset offers a detailed examination of trade transactions, documenting and classifying imports and exports across various industries within Canada. ** To obtain Techsalerator’s Import/Export Trade Data for Canada, please reach out to info@techsalerator.com or to https://www.techsalerator.com/contact-us **

with your specific requirements. Techsalerator will provide a customized quote based on your data needs, with delivery available within 24 hours. Ongoing access options can also be discussed.

Techsalerator's Import/Export Trade Data for Canada delivers a thorough analysis of trade activities, integrating data from customs reports, trade agreements, and shipping records. This comprehensive dataset helps businesses, investors, and trade analysts understand Canada’s trade landscape in detail.

Key Data Fields

Company Name: Lists the companies involved in trade transactions. This information helps identify potential partners or competitors and track industry-specific trade patterns. Trade Volume: Details the quantity or value of goods traded, providing insights into the scale and economic impact of trade activities. Product Category: Specifies the types of goods traded, such as raw materials or finished products, aiding in understanding market demand and supply chain dynamics. Import/Export Country: Identifies the countries of origin or destination for traded goods, offering insights into regional trade relationships and market access. Transaction Date: Records the date of transactions, revealing seasonal trends and shifts in trade dynamics over time. Top Trade Trends in Canada

Trade Balance Dynamics: Canada’s trade balance fluctuates with major partners such as the United States and China. Ongoing trade negotiations and policy adjustments aim to address imbalances and foster more equitable trade relationships. U.S.-Canada Trade Relations: The trade relationship with the U.S. remains central, influenced by agreements like the USMCA. This partnership shapes significant aspects of Canada's trade policy and practices. Expansion of Global Trade Networks: Canada is increasingly diversifying its trade partners and markets beyond traditional partners, reflecting a trend toward broader global trade engagement. Growth in Resource Exports: Canada continues to see substantial trade in natural resources, including oil, minerals, and timber, which play a critical role in its export economy. Emphasis on Sustainable Trade Practices: There is a growing focus on integrating sustainability into trade policies, promoting environmentally friendly practices and technologies. Notable Companies in Canadian Trade Data

Shopify Inc.: A leading e-commerce company that has a significant impact on international trade through its global platform for online retail. Bombardier Inc.: A major player in aerospace, known for exporting aircraft and components, contributing significantly to Canada’s trade in the aerospace sector. Suncor Energy Inc.: A major exporter of energy products, including crude oil and refined products, impacting Canada's energy trade. Loblaw Companies Limited: A major retailer involved in both importing and exporting a range of consumer goods, reflecting its significant role in Canada’s trade dynamics. Nutrien Ltd.: A leading exporter of agricultural products and fertilizers, highlighting Canada’s role in global agriculture and food production. Accessing Techsalerator’s Data

To obtain Techsalerator’s Import/Export Trade Data for Canada, please contact us at info@techsalerator.com with your requirements. We will provide a customized quote based on the number of data fields and records needed, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields:

Company Name Trade Volume Product Category Import/Export Country Transaction Date Shipping Details Customs Codes Trade Value For detailed insights into Canada’s import and export activities and trends, Techsalerator’s dataset is an invaluable resource for staying informed and making strategic decisions.

This table contains 455 series, with data for years 1961 - 2008 (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 ...) Sector (3 items: Total economy; Business sector; Non-business sector ...) North American Industry Classification System (NAICS) (189 items: Crop and animal production; Crop and animal production; Forestry and logging; Crop and animal production ...).

Imports from Canada in the United States increased to 33395.17 USD Million in February from 33309.13 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Imports from Canada.

This table contains 936 series, with data for years 1981 - 2007 (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: Unadjusted; Seasonally adjusted at annual rates ...) Prices (2 items: 1997 constant dollars; Chained 1997 dollars ...) North American Industry Classification System (NAICS) (312 items: All industries; Agriculture; forestry; fishing and hunting; Animal production; Crop production ...).

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 benchmark interest rate in Canada was last recorded at 2.25 percent. This dataset provides - Canada Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This table contains 82 series, with data for years 1947 - 2009 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: United States);  Components (82 items: Gross national product; Capital consumption allowances; Net national product; Indirect business tax and non-tax liabilities; ...).

Explore the World Competitiveness Ranking dataset for 2016, including key indicators such as GDP per capita, fixed telephone tariffs, and pension funding. Discover insights on social cohesion, scientific research, and digital transformation in various countries.

Social cohesion, The image abroad of your country encourages business development, Scientific articles published by origin of author, International Telecommunication Union, World Telecommunication/ICT Indicators database, Data reproduced with the kind permission of ITU, National sources, Fixed telephone tariffs, GDP (PPP) per capita, Overall, Exports of goods - growth, Pension funding is adequately addressed for the future, Companies are very good at using big data and analytics to support decision-making, Gross fixed capital formation - real growth, Economic Performance, Scientific research legislation, Percentage of GDP, Health infrastructure meets the needs of society, Estimates based on preliminary data for the most recent year., Singapore: including re-exports., Value, Laws relating to scientific research do encourage innovation, % of GDP, Gross Domestic Product (GDP), Health Infrastructure, Digital transformation in companies is generally well understood, Industrial disputes, EE, Female / male ratio, State ownership of enterprises, Total expenditure on R&D (%), Score, Colombia, Estimates for the most recent year., Percentage change, based on US$ values, Number of listed domestic companies, Tax evasion is not a threat to your economy, Scientific articles, Tax evasion, % change, Use of big data and analytics, National sources, Disposable Income, Equal opportunity, Listed domestic companies, Government budget surplus/deficit (%), Pension funding, US$ per capita at purchasing power parity, Estimates; US$ per capita at purchasing power parity, Image abroad or branding, Equal opportunity legislation in your economy encourages economic development, Number, Article counts are from a selection of journals, books, and conference proceedings in S&E from Scopus. Articles are classified by their year of publication and are assigned to a region/country/economy on the basis of the institutional address(es) listed in the article. Articles are credited on a fractional-count basis. The sum of the countries/economies may not add to the world total because of rounding. Some publications have incomplete address information for coauthored publications in the Scopus database. The unassigned category count is the sum of fractional counts for publications that cannot be assigned to a country or economy. Hong Kong: research output items by the higher education institutions funded by the University Grants Committee only., State ownership of enterprises is not a threat to business activities, Protectionism does not impair the conduct of your business, Digital transformation in companies, Total final energy consumption per capita, Social cohesion is high, Rank, MTOE per capita, Percentage change, based on constant prices, US$ billions, National sources, World Trade Organization Statistics database, Rank, Score, Value, World Rankings

Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, China, Colombia, Croatia, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Kazakhstan, Latvia, Lithuania, Luxembourg, Malaysia, Mexico, Mongolia, Netherlands, New Zealand, Norway, Oman, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Saudi Arabia, Singapore, Slovenia, South Africa, Spain, Sweden, Switzerland, Thailand, Turkey, Ukraine, United Kingdom, Venezuela

Follow data.kapsarc.org for timely data to advance energy economics research.

General Abstract/Purpose (70 words): Data were collected to assist in cost-benefit analysis of flood mitigation actions that could be taken by the U.S. and Canada to prevent structural damage and associated costs and losses in future flood conditions, including conditions worse than the historical record flooding in spring of 2011. Data were commissioned to revise or fill gaps in estimates from structural damage modeling software commonly used for depth-damage economic assessments of flood impacts. The Summary text that immediately follows this introductory sentence offers overview information, but also includes context and detail that is not present in the Word document ("Principal Indicator Combo SET - REVIEW FINAL v2.docx") that constitutes the main body of this data release, supported by Excel files (that are copied without formatting in csv files for each Excel tab). Lake Champlain is a relatively large lake bordered by New York on the western side and Vermont on the eastern side, whose uppermost region spans the U.S.-Canadian border. The 436 mi^2 (1,130 km^2) lake sits within a 9,277 mi^2 (23,900 km^2) basin, and Champlain’s only drainage point is north into Canada via the Richelieu River into the province of Quebec. About 75% of the Lake Champlain shoreline of New York is within Adirondack State Park, covering all or part of Clinton, Essex, and Washington counties. Of Vermont’s 14 counties, Franklin, Chittenden, and Addison Counties border Lake Champlain, while Grand Isle is surrounded by Champlain and at its northern edge the Canadian border. Development and anthropogenic modifications, especially over the last 50 years, have converted wetlands, changed the timing and flows of water, and increased impervious surface area including new residences in floodplains on both sides of the border. Occasionally there is damaging flooding, with significant economic damages in New York, Vermont, and Quebec. With flood stage at 99.57’ (30.35m) and major flooding from 101.07’ (30.81m) over sea level, a 101.4’ (30.91m) flood in 1993 broke the previous recorded high flood in 1869. Following the third heaviest recorded snow, almost no seasonal snowmelt, then heavy rains, the spring of 2011 brought record flooding more than one foot over the 1993 record to 102.77’ (31.32m), expanding the lake’s area by 66 mi^2 (106.2 km^2, or about 5.8%). From reaching flood stage to peak and then returning to a lake level below flood stage took around six weeks. Wind-to-wave-driven erosion was up to 5 feet (1.5m) above static lake elevation in some areas. The record flood height (102.77’) is often reported as 103.07’ or 103.27’ in Burlington, owing to different vertical and horizontal datums and digital elevation models (DEMs), and some wave action. In a 1976 flood the U.S. side incurred more than 50% of the economic damages, but in 2011, Quebec experienced some 80% of structural and economic damages estimated at $82 million. Tropical Storm Irene hit the area in August of 2011 and did far more damage on the American side, for example spurring $29 million in home and business repair loans for damage across 12 of Vermont’s 14 counties. Co-reporting across the two events for 2011 confounded some data, making it impossible to separately identify spring flooding numbers. Following the Boundary Waters Treaty between the U.S. and Canada in 1909, from 1912 the International Joint Commission (IJC) handles boundary water issues between the two countries. The IJC Lake Champlain Richelieu River (LCRR) Study Project is a bi-national (U.S., Canada) multi-agency effort to assess flood risk and flood mitigation options as they affect potential structural damages and wider non-structural damages that include secondary economic, community, and psychological effects. Key economic parts of the report to the IJC LCRR Study Board are calculated using a new tool developed for the study project, an Integrated Socio-Economic-Environmental (ISEE) model, with forecasting for damages up to 105.57’ flood (105.9’, or 106’ [32.3m] for short, by alternative datum and DEMs, as apply in some of the modeling and estimations herein). There is also a Collaborative Decision Support Tool (CDST) that also processes non-structural economic damages, costs, or losses as inputs. CDST is a pared-down version of ISEE that applies historical estimates but does not project outcomes for higher floods in the future. Outputs from this data release are inputs to the ISEE or the CDST for calculations of the benefit-to-cost ratios projected to follow different structural interventions. For example adding a weir in the Richelieu River yielded a greater-than-one benefit-to-cost ratio in late-stage modeling, whereas a dam on either side, or an entirely new canal on the Canadian side, were never entertained as cost feasible or even appropriate. USGS economists were contracted to supply economic “principal indicators” for potential U.S.-side depth-damage effects from lake-rise flooding. The scope of this analysis is limited by several factors associated with the objectives of the IJC LCRR Study Board. Damages from tributary flooding were defined out of a project focused on joint-management options for mitigating flood effects, as tributary flows would be managed only by the U.S. Uncommonly low Lake Champlain levels were also ultimately considered as a stakeholder concern (the weir option also addressed this concern). It is standard to model economic damages to structures and related economic costs due to flooding using the FEMA-designed Hazus®-MH (Multi-Hazard) Flood Model of structural damages (https://www.fema.gov/flood-maps/products-tools/hazus; the Hazus-MH Technical Manual, 2011, 569pp, which explains definitions and parameterization of the tool rather than use of the tool itself, is a frequently referred source here). “Hazus” (tool) modeling is used in the LCRR Study Board research to estimate structural damages at different flood depths, and the primary work presented in this data release estimates depth-damage values for “Principal Indicators” (PIs) that were defined to supplement or alternatively estimate results from applying Hazus, where gaps exist or where straight Hazus values may be questionable in the LCRR context. A number of Principal Indicators were estimated on the Canadian and U.S. sides, where no PIs include any estimates for repair of structural damage, as those calculations are done separately using the Hazus tool (or the ISEE model application with Hazus outputs as inputs). In the final list, the USGS team produced estimates for six PIs: temporary lodging costs, residential debris clean-up and disposal, damage to roads and bridges, damage to water treatment facilities, income loss from industrial or commercial properties, and separately and specifically recreation sector income loss. So associated with residential damage, the costs of securing emergency and longer-term lodging when a household is displaced by lake-rise flooding are estimated, and the costs of cleaning up and removing and disposing of debris from residential property damage are estimated. In the public sector, costs of clean up and repair of damages to roads and bridges from lake-rise flooding are calculated, as are damages and potential revenue losses from flood mitigation measures and service reductions where public or private water utilities are inundated by lake-rise flooding. In the commercial sector, revenue losses from being closed for business due to flooding are calculated outside of the recreation sector, and then also for the recreation sector as lakeside campgrounds, marinas, and ferry services (where the last is also used for local commercial traffic). All of these PIs are characterized by being little-discussed in the literature. To derive information necessary to bound economic estimates for each of the 6 PIs, consultation with subject-matter experts in New York and Vermont (or at agencies covering these areas) was employed more often than anything in peer-reviewed literature specifically applied. Depth-damage functions that result are not formal mathematical functions, and across the six PIs calculations and results tend to be in increments of one foot or more. Results thus suggest magnitudes of costs that comply with reasonable scenario assumptions for a small but fairly consistent set of flood depths from 99.57’ to 105.57’, where the latter value is almost three feet (1m) above the historic maximum flood. Nothing reported in these estimates is empirically deterministic, or capable of including probabilistic error margins. Simplifying assumptions serve first to actually simplify the calculations and legibility of estimated results, and second to avoid the impression that specifically calibrated empirical estimations are being conducted. This effort offers plausible, logical, reliable, and reproducible magnitudes for estimates, using a method that can be easily modified if better information becomes available for future estimations. Certain worksheets and specific results are withheld to avoid the outright identification of specific businesses (or homes). Facts in this abstract generally attribute to: International Lake Champlain-Richelieu River Study Board, 2019. The Causes and Impacts of Past Floods in the Lake Champlain-Richelieu River Basin – Historical Information on Flooding, A Report to the International Joint Commission, 108pp (https://ijc.org/en/lcrr). Some supplemental factual support is from: Lake Champlain Basin Program, 2013. Flood Resilience in the Lake Champlain Basin and Upper Richelieu River, 93 pp (https://ijc.org/en/lcrr).