Description: This dataset contains historical economic data spanning from 1871 to 2024, used in Jaouad Karfali’s research on Economic Cycle Analysis with Numerical Time Cycles. The study aims to improve economic forecasting accuracy through the 9-year cycle model, which demonstrates superior predictive capabilities compared to traditional economic indicators.

Dataset Contents: The dataset includes a comprehensive range of economic indicators used in the research, such as:

USGDP_1871-2024.csv – U.S. Gross Domestic Product (GDP) data. USCPI_cleaned.csv – U.S. Consumer Price Index (CPI), cleaned and processed. USWAGE_1871-2024.csv – U.S. average wages data. EXCHANGEGLOBAL_cleaned.csv – Global exchange rates for the U.S. dollar. EXCHANGEPOUND_cleaned.csv – U.S. dollar to British pound exchange rates. INTERESTRATE_1871-2024.csv – U.S. interest rate data. UNRATE.csv – U.S. unemployment rate statistics. POPTOTUSA647NWDB.csv – U.S. total population data. Significance of the Data: This dataset serves as a foundation for a robust economic analysis of the U.S. economy over multiple decades. It was instrumental in testing the 9-year economic cycle model, which demonstrated an 85% accuracy rate in economic forecasting when compared to traditional models such as ARIMA and VAR.

Applications:

Economic Forecasting: Predicts a 1.5% decline in GDP in 2025, followed by a gradual recovery between 2026-2034. Economic Stability Analysis: Used for comparing forecasts with estimates from institutions like the IMF and World Bank. Academic and Institutional Research: Supports studies in economic cycles and long-term forecasting. Source & Further Information: For more details on the methodology and research findings, refer to the full paper published on SSRN:

https://ssrn.com/author=7429208 https://orcid.org/0009-0002-9626-7289

• Jaouad Karfali

Graph and download economic data for Gross Domestic Product: Implicit Price Deflator (GDPDEF) from Q1 1947 to Q1 2025 about implicit price deflator, headline figure, inflation, GDP, and USA.

Non-Standard Total Coliform Analysis: North: Rondônia data was reported at 2.890 % in 2022. This records an increase from the previous number of 0.690 % for 2021. Non-Standard Total Coliform Analysis: North: Rondônia data is updated yearly, averaging 3.820 % from Dec 2012 (Median) to 2022, with 11 observations. The data reached an all-time high of 7.990 % in 2019 and a record low of 0.690 % in 2021. Non-Standard Total Coliform Analysis: North: Rondônia data remains active status in CEIC and is reported by Ministry of Cities. The data is categorized under Brazil Premium Database’s Environmental, Social and Governance Sector – Table BR.EVB015: Quality Indicators: Incidence of Analyzes.

This filtered view presents Real Gross Domestic Product for the accommodation and food services sector and its subsectors in the State of Iowa by year beginning in 1997.

Gross domestic product (GDP) is the measure of the market value of all final goods and services produced within Iowa in a particular period of time. In concept, an industry's GDP by state, referred to as its "value added", is equivalent to its gross output (sales or receipts and other operating income, commodity taxes, and inventory change) minus its intermediate inputs (consumption of goods and services purchased from other U.S. industries or imported). The Iowa GDP a state counterpart to the Nation's GDP, the Bureau's featured and most comprehensive measure of U.S. economic activity. Iowa GDP differs from national GDP for the following reasons: Iowa GDP excludes and national GDP includes the compensation of federal civilian and military personnel stationed abroad and government consumption of fixed capital for military structures located abroad and for military equipment, except office equipment; and Iowa GDP and national GDP have different revision schedules. GDP is reported in millions of current dollars.

Real GDP is an inflation-adjusted measure of Iowa's gross product that is based on national prices for the goods and services produced within Iowa. The real estimates of gross domestic product (GDP) are measured in millions of chained dollars, but have been multiplied by 1,000,000 to display in dollars for visualization purposes. Values are only accurate to the nearest $100,000.

The impact of the COVID-19 epidemic on the socio-economic status of countries around the world should not be underestimated, when we consider the role it has played in various countries. Many people were unemployed, many households were careful about their spending, and a greater social divide in the population emerged in 14 different countries from the Organization for Economic Co-operation and Development (OECD) and from Africa (that is, in developed and developing countries) for which we have considered the epidemiological data on the spread of infection during the first and second waves, as well as their socio-economic data. We established a mathematical relationship between Theil and Gini indices, then we investigated the relationship between epidemiological data and socio-economic determinants, using several machine learning and deep learning methods. High correlations were observed between some of the socio-economic and epidemiological parameters and we predicted three of the socio-economic variables in order to validate our results. These results show a clear difference between the first and the second wave of the pandemic, confirming the impact of the real dynamics of the epidemic’s spread in several countries and the means by which it was mitigated.

This dataset provides quarterly personal income estimates for State of Iowa produced by the U.S. Bureau of Economic Analysis . Data includes the following estimates: personal income, per capita personal income, proprietors' income, farm proprietors' income, compensation of employees and private nonfarm earnings, compensation, and wages and salaries for wholesale trade. Personal income, proprietors' income, and farm proprietors' income available beginning 1997; per capita personal income available beginning 2010; and all other data beginning 1998.

Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income for Iowa is the income received by, or on behalf of all persons residing in Iowa, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s midquarter population estimates.

Proprietors' income is the current-production income (including income in kind) of sole proprietorships, partnerships, and tax-exempt cooperatives. Corporate directors' fees are included in proprietors' income. Proprietors' income includes the interest income received by financial partnerships and the net rental real estate income of those partnerships primarily engaged in the real estate business.

Farm proprietors’ income as measured for personal income reflects returns from current production; it does not measure current cash flows. Sales out of inventories are included in current gross farm income, but they are excluded from net farm income because they represent income from a previous year’s production.

Compensation to employees is the total remuneration, both monetary and in kind, payable by employers to employees in return for their work during the period. It consists of wages and salaries and of supplements to wages and salaries. Compensation is presented on an accrual basis - that is, it reflects compensation liabilities incurred by the employer in a given period regardless of when the compensation is actually received by the employee.

Private nonfarm earnings is the sum of wages and salaries, supplements to wages and salaries, and nonfarm proprietors' income, excluding farm and government.

Private nonfarm wages and salaries is wages and salaries excluding farm and government. Wages and salaries is the remuneration receivable by employees (including corporate officers) from employers for the provision of labor services. It includes commissions, tips, and bonuses; employee gains from exercising stock options; and pay-in-kind. Judicial fees paid to jurors and witnesses are classified as wages and salaries. Wages and salaries are measured before deductions, such as social security contributions, union dues, and voluntary employee contributions to defined contribution pension plans.

More terms and definitions are available on https://apps.bea.gov/regional/definitions/.

Brazil Social Security: Number of Benefits Under Analysis: South: Rio Grande do Sul data was reported at 28,532.000 Unit in Apr 2019. This records a decrease from the previous number of 29,046.000 Unit for Mar 2019. Brazil Social Security: Number of Benefits Under Analysis: South: Rio Grande do Sul data is updated monthly, averaging 35,155.000 Unit from Jan 2008 (Median) to Apr 2019, with 136 observations. The data reached an all-time high of 68,287.000 Unit in Apr 2017 and a record low of 11,327.000 Unit in May 2008. Brazil Social Security: Number of Benefits Under Analysis: South: Rio Grande do Sul data remains active status in CEIC and is reported by Ministry of Social Security. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBE024: Social Security: Number of Benefits Under Analysis: by Region and State.

Gross Value Added Index: sa: YoY: State of São Paulo: Services: Transport, Storage & Mail data was reported at 5.603 % in Dec 2024. This records an increase from the previous number of -0.030 % for Sep 2024. Gross Value Added Index: sa: YoY: State of São Paulo: Services: Transport, Storage & Mail data is updated quarterly, averaging 1.109 % from Mar 2003 (Median) to Dec 2024, with 88 observations. The data reached an all-time high of 28.545 % in Jun 2021 and a record low of -19.870 % in Jun 2020. Gross Value Added Index: sa: YoY: State of São Paulo: Services: Transport, Storage & Mail data remains active status in CEIC and is reported by State System of Data Analysis Foundation. The data is categorized under Brazil Premium Database’s National Accounts – Table BR.AH023: SNA 2008: Gross Value Added: Southeast: São Paulo: State System of Data Analysis Foundation: Quarterly. [COVID-19-IMPACT]

Gross Value Added Index: State of São Paulo: Industry: Manufacturing data was reported at 79.438 2010=100 in Dec 2024. This records a decrease from the previous number of 89.784 2010=100 for Sep 2024. Gross Value Added Index: State of São Paulo: Industry: Manufacturing data is updated quarterly, averaging 88.688 2010=100 from Mar 2002 (Median) to Dec 2024, with 92 observations. The data reached an all-time high of 112.930 2010=100 in Sep 2008 and a record low of 67.271 2010=100 in Jun 2020. Gross Value Added Index: State of São Paulo: Industry: Manufacturing data remains active status in CEIC and is reported by State System of Data Analysis Foundation. The data is categorized under Brazil Premium Database’s National Accounts – Table BR.AH023: SNA 2008: Gross Value Added: Southeast: São Paulo: State System of Data Analysis Foundation: Quarterly. [COVID-19-IMPACT]

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Hotchkiss: 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 0 households where the householder is under 25 years old, 77(18.97%) households with a householder aged between 25 and 44 years, 193(47.54%) households with a householder aged between 45 and 64 years, and 136(33.50%) 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 Hotchkiss, 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) 2019-2023 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 Hotchkiss median household income by age. 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 Onslow: 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 2(1.94%) households where the householder is under 25 years old, 55(53.40%) households with a householder aged between 25 and 44 years, 26(25.24%) households with a householder aged between 45 and 64 years, and 20(19.42%) households where the householder is over 65 years old.
• The age group of 45 to 64 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the city of Onslow, 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) 2019-2023 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 Onslow median household income by age. 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 Longstreet: 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 0 households where the householder is under 25 years old, 17(22.67%) households with a householder aged between 25 and 44 years, 34(45.33%) households with a householder aged between 45 and 64 years, and 24(32%) 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 village of Longstreet, 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) 2019-2023 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 Longstreet median household income by age. 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 Allison: 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 30(6.52%) households where the householder is under 25 years old, 165(35.87%) households with a householder aged between 25 and 44 years, 157(34.13%) households with a householder aged between 45 and 64 years, and 108(23.48%) households where the householder is over 65 years old.
• The age group of under 25 years exhibits the highest median household income, while the largest number of households falls within the 25 to 44 years bracket. This distribution hints at economic disparities within the city of Allison, 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) 2019-2023 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 Allison median household income by age. You can refer the same here

Implementation of the residual heterogeneity test, 1991–2020, Taiwan.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Afton: 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 13(3.50%) households where the householder is under 25 years old, 123(33.15%) households with a householder aged between 25 and 44 years, 127(34.23%) households with a householder aged between 45 and 64 years, and 108(29.11%) 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 city of Afton, 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) 2019-2023 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 Afton median household income by age. You can refer the same here

Gross Value Added Index: State of São Paulo: sa: Industry data was reported at 90.960 2010=100 in Feb 2025. This records a decrease from the previous number of 92.088 2010=100 for Jan 2025. Gross Value Added Index: State of São Paulo: sa: Industry data is updated monthly, averaging 91.261 2010=100 from Jan 2002 (Median) to Feb 2025, with 278 observations. The data reached an all-time high of 110.325 2010=100 in Sep 2013 and a record low of 71.766 2010=100 in Jan 2002. Gross Value Added Index: State of São Paulo: sa: Industry data remains active status in CEIC and is reported by State System of Data Analysis Foundation. The data is categorized under Brazil Premium Database’s National Accounts – Table BR.AH022: SNA 2008: Gross Value Added: Southeast: São Paulo: State System of Data Analysis Foundation. [COVID-19-IMPACT]

Gross Value Added Index: sa: State of São Paulo: Industry: Construction data was reported at 122.167 2010=100 in Dec 2024. This records a decrease from the previous number of 123.249 2010=100 for Sep 2024. Gross Value Added Index: sa: State of São Paulo: Industry: Construction data is updated quarterly, averaging 90.706 2010=100 from Mar 2002 (Median) to Dec 2024, with 92 observations. The data reached an all-time high of 123.249 2010=100 in Sep 2024 and a record low of 66.102 2010=100 in Sep 2003. Gross Value Added Index: sa: State of São Paulo: Industry: Construction data remains active status in CEIC and is reported by State System of Data Analysis Foundation. The data is categorized under Brazil Premium Database’s National Accounts – Table BR.AH023: SNA 2008: Gross Value Added: Southeast: São Paulo: State System of Data Analysis Foundation: Quarterly. [COVID-19-IMPACT]

LE: Interest Expenses & Income Before Income Taxes to Total Assets data was reported at 5.150 % in 2016. This records an increase from the previous number of 4.990 % for 2015. LE: Interest Expenses & Income Before Income Taxes to Total Assets data is updated yearly, averaging 5.070 % from Dec 2015 (Median) to 2016, with 2 observations. The data reached an all-time high of 5.150 % in 2016 and a record low of 4.990 % in 2015. LE: Interest Expenses & Income Before Income Taxes to Total Assets data remains active status in CEIC and is reported by The Bank of Korea. The data is categorized under Global Database’s Korea – Table KR.S028: Financial Statement Analysis: 2015 Survey: Complete Enumeration: Large Enterprises.

Gross Value Added Index: Year to Date: YoY: State of São Paulo: Taxes Net of Subsidies data was reported at 4.980 % in Dec 2024. This records a decrease from the previous number of 5.479 % for Sep 2024. Gross Value Added Index: Year to Date: YoY: State of São Paulo: Taxes Net of Subsidies data is updated quarterly, averaging 2.868 % from Mar 2003 (Median) to Dec 2024, with 88 observations. The data reached an all-time high of 17.666 % in Jun 2021 and a record low of -10.225 % in Mar 2003. Gross Value Added Index: Year to Date: YoY: State of São Paulo: Taxes Net of Subsidies data remains active status in CEIC and is reported by State System of Data Analysis Foundation. The data is categorized under Brazil Premium Database’s National Accounts – Table BR.AH023: SNA 2008: Gross Value Added: Southeast: São Paulo: State System of Data Analysis Foundation: Quarterly. [COVID-19-IMPACT]

Gross Value Added Index: 3 Mos Moving Ave: State of São Paulo: Industry data was reported at 81.245 2010=100 in Feb 2025. This records a decrease from the previous number of 83.821 2010=100 for Jan 2025. Gross Value Added Index: 3 Mos Moving Ave: State of São Paulo: Industry data is updated monthly, averaging 92.240 2010=100 from Mar 2002 (Median) to Feb 2025, with 276 observations. The data reached an all-time high of 116.577 2010=100 in Oct 2013 and a record low of 68.383 2010=100 in Mar 2002. Gross Value Added Index: 3 Mos Moving Ave: State of São Paulo: Industry data remains active status in CEIC and is reported by State System of Data Analysis Foundation. The data is categorized under Brazil Premium Database’s National Accounts – Table BR.AH022: SNA 2008: Gross Value Added: Southeast: São Paulo: State System of Data Analysis Foundation. [COVID-19-IMPACT]