Source ID: rgdpna When using these data in your research, please make the following reference: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt For more information, see http://www.rug.nl/research/ggdc/data/pwt/.

The All industry total includes all Private industries and Government. Real GDP by metropolitan area is an inflation-adjusted measure of each metropolitan area's gross product that is based on national prices for the goods and services produced within the metropolitan area. For more information about this release go to http://www.bea.gov/newsreleases/regional/gdp_metro/gdp_metro_newsrelease.htm.

Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).

GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. World Bank national accounts data, and OECD National Accounts data files.

The All industry total includes all Private industries and Government. A chained-type index is based on the linking (chaining) of indexes to create a time series. Annual chained-type Fisher indices are used in BEA's national income and product accounts (NIPAs) whereby Fisher ideal price indices are calculated using the weights of adjacent years. Those annual changes are then multiplied (chained) together, forming the chained-type index time series. Chain-type indexes or chain-dollar estimates are used when you want to show how output or spending has changed over time. The percent changes in quantity indexes exactly match the percent changes in chained dollars, so they can be used interchangeably for making comparisons. Real estimates remove the effects of price changes, which can obscure changes in output or spending in current dollars. For more information about this release go to http://www.bea.gov/newsreleases/regional/gdp_metro/gdp_metro_newsrelease.htm.

The All industry total includes all Private industries and Government. Real GDP by metropolitan area is an inflation-adjusted measure of each metropolitan area's gross product that is based on national prices for the goods and services produced within the metropolitan area. Gross Domestic Product of a given area divided by the resident population of the area. For more information about this release go to http://www.bea.gov/newsreleases/regional/gdp_metro/gdp_metro_newsrelease.htm.

Observations for the current and future years are projections. The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis. For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications. Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).

Source ID: rgdpo When using these data in your research, please make the following reference: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt For more information, see http://www.rug.nl/research/ggdc/data/pwt/.

Source ID: cgdpe When using these data in your research, please make the following reference: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt For more information, see http://www.rug.nl/research/ggdc/data/pwt/.

Source ID: cgdpo When using these data in your research, please make the following reference: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt For more information, see http://www.rug.nl/research/ggdc/data/pwt/.

GDP by county is a measure of the market value of final goods and services produced within a county area in a particular period. While other measures of county economies rely mainly on labor market data, these statistics incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the capital-intensive industries are captured more fully than when measured solely by labor data.

Source ID: rgdpe When using these data in your research, please make the following reference: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt For more information, see http://www.rug.nl/research/ggdc/data/pwt/.

For more information and proper citation see http://www.rug.nl/research/ggdc/data/pwt/pwt-7.1 Source Indicator: ki

For more information and proper citation see http://www.rug.nl/research/ggdc/data/pwt/pwt-7.1 Source Indicator: kc

For more information and proper citation see http://www.rug.nl/research/ggdc/data/pwt/pwt-7.1 Source Indicator: kg

Source ID: pl_gdpo When using these data in your research, please make the following reference: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt For more information, see http://www.rug.nl/research/ggdc/data/pwt/.

Source ID: pl_gdpe When using these data in your research, please make the following reference: Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2013), "The Next Generation of the Penn World Table" available for download at www.ggdc.net/pwt For more information, see http://www.rug.nl/research/ggdc/data/pwt/.

GDP by county is a measure of the market value of final goods and services produced within a county area in a particular period. While other measures of county economies rely mainly on labor market data, these statistics incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the capital-intensive industries are captured more fully than when measured solely by labor data.

GDP by county is a measure of the market value of final goods and services produced within a county area in a particular period. While other measures of county economies rely mainly on labor market data, these statistics incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the capital-intensive industries are captured more fully than when measured solely by labor data.

GDP by county is a measure of the market value of final goods and services produced within a county area in a particular period. While other measures of county economies rely mainly on labor market data, these statistics incorporate multiple data sources that capture trends in labor, revenue, and value of production. As a result, the capital-intensive industries are captured more fully than when measured solely by labor data.