About this dataset

Context

The dataset tabulates the population of Economy by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Economy. The dataset can be utilized to understand the population distribution of Economy by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Economy. 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 Economy.

Key observations

Largest age group (population): Male # 65-69 years (412) | Female # 60-64 years (490). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

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

• Age Group: This column displays the age group for the Economy population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Economy is shown in the following column.
• Population (Female): The female population in the Economy is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Economy for each age group.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

United States US: GDP: Growth: Gross Value Added: Services data was reported at 2.621 % in 2015. This records an increase from the previous number of 2.221 % for 2014. United States US: GDP: Growth: Gross Value Added: Services data is updated yearly, averaging 2.335 % from Dec 1998 (Median) to 2015, with 18 observations. The data reached an all-time high of 4.456 % in 1999 and a record low of -1.772 % in 2009. United States US: GDP: Growth: Gross Value Added: Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Annual Growth Rate. Annual growth rate for value added in services based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average; Note: Data for OECD countries are based on ISIC, revision 4.

Claims on other sectors of the domestic economy (% of GDP) in Belarus was reported at 46.48 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Belarus - Claims on other sectors of the domestic economy (% of GDP) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Hungary under Orbán: Can Central Planning Revive Its Economy?, PIIE Policy Brief 15-11. If you use the data, please cite as: Djankov, Simeon. (2015). Hungary under Orbán: Can Central Planning Revive Its Economy?. PIIE Policy Brief 15-11. Peterson Institute for International Economics.

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

ABSTRACT This article seeks to show two interconnected phenomena in China. The first is a historical process that took place in the past 40 years involving institutional and qualitative changes in the state-controlled portion of the Chinese economy. Such changes have brought about new and superior forms of economic planning, based on which a higher stage of development pattern has emerged. We call this new development pattern "New Projectment Economy" and it synthesizes a series of state capacities built over time. The second phenomenon relates to how the state capacities created in the past decades have allowed the country to show adaptive flexibility and rapid efficiency in the containment of Covid-19 crisis internally and thus explain China's successful response in the fight against the coronavirus. Such phenomena, pari passu, show China's potential and projection as an international political actor.

Claims on other sectors of the domestic economy include gross credit from the financial system to households, nonprofit institutions serving households, nonfinancial corporations, state and local governments, and social security funds. This indicator is expressed as a percentage of Gross Domestic Product (GDP) which is the total income earned through the production of goods and services in an economic territory during an accounting period.

In 2023, Shanghai was the city with the largest GDP in China, reaching a value added of approximately *** trillion yuan. The four Chinese first-tier cites Beijing, Shanghai, Shenzhen, and Guangzhou had by far the strongest economic performance. Development of Chinese cities Rapid urbanization and economic growth have reshaped all Chinese cities since the economic opening up of China. While the first-tier cities have overall benefitted most from this development, the last two decades have seen many second-tier cities catching up. For many years already, growth rates in Qingdao, Hangzhou, Changsha, and Zhengzhou have been higher than in Shanghai or Beijing.This development was driven by lower costs in smaller cities, a specialization of their economies, and political measures to support inland cities and ease the pressure on the largest municipalities. Today, per capita GDP in cities such as Suzhou, Nanjing, and Shenzhen is already higher than in Beijing or Shanghai. Future perspectives Competition between cities will further change China’s urban landscape in the future. Medium-sized cities that can provide an attractive economic environment have the potential to grow their economy at a faster pace, attract immigration, and further increase their relative importance. Cities that are losing their competitive edge, however, like Shenyang, Dalian, and other cities in the northeastern rustbelt, are increasingly confronted by economic stagnation and demographic decline.

As of the second quarter of 2022, around 34 percent of employed internet users surveyed in Chile engaged in gig economy activities. Among unemployed Chilean online users, the share amounted to 60 percent. Regardless of employment status, food was the main complementary income activity for internet users in this Latin American country.

Denton economic data from the American Community Survey (ACS)

This dataset is about books. It has 2 rows and is filtered where the book series is Economy and environment. It features 9 columns including author, publication date, language, and book publisher.

This paper analyzes the role of specialized high-skilled labor in the disproportionate growth of the service sector. Empirically, the importance of skill-intensive services has risen during a period of increasing relative wages and quantities of high-skilled labor. We develop a theory in which demand shifts toward more skill- intensive output as productivity rises, increasing the importance of market services relative to home production. Consistent with the data, the theory predicts a rising level of skill, skill premium, and relative price of services that is linked to this skill premium. (JEL J24, L80, L90)

The dissertation addresses the growth of government commitments to the provision of social insurance, the provision of "public" goods, and the political management of the macroeconomy. It does so in three parts: (a) a study of the determinants and consequences of transfers growth, (b) a study of the determinants and consequences of public-debt growth, and (c) a study of the interactions of monetary-policy institutions with wage-/price-bargaining institutions and the sectoral composition of employment. Highlighting and summarizing some key arguments and findings: (a) The first study argues that demand for transfers would increase with income inequality, as has previously been noted, but only to the degree that the poor participate in the democracy (e.g., vote). The findings from a test of this and other propositions emerging from the literature include that transfer tends to grow more quickly where both the distribution of income is more unequal and the percentage of the population voting is high. The chapter then proceeds to evaluate the economic and political consequences for the functioning of the Keynesian Welfare State (KWS). (b) The second study presents a series of tests of the theoretical literature on the rise of public debt in developed democracies since the oil crises, in many cases representing the first empirical analysis of these propositions. Many of the arguments considered receive broad support from the available data, but the tests also reveal significant weaknesses and suggest some corrections. Again, the chapter proceeds to evaluate the consequences of these trends in debt for the KWS. (c) The third study derives a model showing that the real economic effects of central bank independence are not, in general, zero, as had been argued, but rather depend on the institutional structure of wage-/price-bargaining and the sectoral composition of employment: traded, private non-traded, and public. The findings indicate that central bank independence is less costly where bargaining is more coordinated and conversely that coordination is more beneficial where the bank is more independent. They also indicate that central bank independence is more (less) costly where the public (traded) sector is large. Again, the political ramifications of these arguments and findings are considered.

Economic Activity Rate: NW: Republic of Karelia data was reported at 57.700 % in 2024. This records a decrease from the previous number of 58.100 % for 2023. Economic Activity Rate: NW: Republic of Karelia data is updated yearly, averaging 67.000 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 69.300 % in 2008 and a record low of 57.100 % in 2022. Economic Activity Rate: NW: Republic of Karelia data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.GB006: Economic Activity Rate: by Region: Annual.

Digital commerce was the highest earning digital economy segment in Romania, with a value of nearly ** billion euros in 2021. However, in 2030, the information, communications, and technology (ICT) industry was expected to be the leading segment. In total, the value of Romania's digital economy was forecast to reach ** billion euros in 2030. Romania had one of the largest digital economies in Central and Eastern Europe (CEE).

Geoscience Australia's National Earth Observation Group commissioned this study through the Cooperative Research Centre for Spatial Information. The primary aim of this study was to determine the value of Earth observation from space activities to the Australian economy. The three main objectives of this study were to: 1. estimate the direct and indirect economic value of space based Earth Observation activities to the Australian community in 2008-09 year 2. determine the direct and indirect economic impact of an unplanned denial of all Earth Observation data to the Australian economy in 2008-09 year 3. identify contemplated large-scale government applications of Earth Observation data and estimate their direct and indirect economic value. In subsequent discussions it was agreed that the report would also provide an estimate of the size of the Earth observation from space industry, particularly the small-medium enterprise sector in the 2008-09 financial year. The scope of this report did not include the value of Earth observation from space services for national security or defence.

We argue that governments allocate adjustment burdens strategically to protect their supporters, imposing adjustment costs upon the supporters of their opponents, who then protest in response. Using large-N micro-level survey data from three world regions and a global survey, it discusses the local political economy of International Monetary Fund (IMF) lending. It finds that opposition supporters in countries under an IMF structural adjustment program (SAP) are more likely to report that the IMF SAP increased economic hardships than government supporters and countries without IMF exposure. In addition, it finds that partisan gaps in IMF SAP evaluations widen in IMF program countries with an above-median number of conditions, suggesting that opposition supporters face heavier adjustment burdens, and that opposition supporters who think SAPs made their lives worse are more likely to protest.

According to a survey conducted by Ipsos on predictions for global issues in 2019, ** percent of Malaysian respondents somewhat agree with the statement that the global economy would be better in the current year compared to the last. Malaysians were more optimistic this year about the global economy compared to the previous year.

Latvia LV: BOP: Current Account: Exports: Service: Travel: % of Service Exports data was reported at 16.043 % in 2017. This records a decrease from the previous number of 17.127 % for 2016. Latvia LV: BOP: Current Account: Exports: Service: Travel: % of Service Exports data is updated yearly, averaging 15.893 % from Dec 1992 (Median) to 2017, with 18 observations. The data reached an all-time high of 18.501 % in 2015 and a record low of 2.498 % in 1992. Latvia LV: BOP: Current Account: Exports: Service: Travel: % of Service Exports data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Latvia – Table LV.World Bank: Balance of Payments: Current Account. Travel covers goods and services acquired from an economy by travelers for their own use during visits of less than one year in that economy for either business or personal purposes. Travel includes local transport (i.e., transport within the economy being visited and provided by a resident of that economy), but excludes international transport (which is included in passenger transport. Travel also excludes goods for resale, which are included in general merchandise.; ; International Monetary Fund, Balance of Payments Statistics Yearbook and data files.; Weighted average; Note: Data are based on the sixth edition of the IMF's Balance of Payments Manual (BPM6) and are only available from 2005 onwards.

Examining the most heavily cited publications in labor economics from the early 1990s, I show that few of over 3,000 articles, citing them directly, replicates them. They are replicated more frequently using data from other time periods and economies, so that the validity of their central ideas has typically been verified. This pattern of scholarship suggests, beyond the currently required depositing of data and code upon publication, that there is little need for formal mechanisms for replication. The market for scholarship already produces replications of non-laboratory applied research.