China recorded a Government Debt to GDP of 88.30 percent of the country's Gross Domestic Product in 2024. This dataset provides - China Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data package includes the PIIE dataset to replicate the data and charts presented in The rise of US economic sanctions on China: Analysis of a new PIIE dataset by Martin Chorzempa, Mary E. Lovely, and Christine Wan, PIIE Policy Brief 24-14.

If you use the dataset, please cite as: Chorzempa, Martin, Mary E. Lovely, and Christine Wan. 2024. The rise of US economic sanctions on China: Analysis of a new PIIE dataset, PIIE Policy Brief 24-14. Washington, DC: Peterson Institute for International Economics.

About this dataset

Context

The dataset tabulates the China population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of China across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of China was 1,282, a 0.71% increase year-by-year from 2022. Previously, in 2022, China population was 1,273, a decline of 0.70% compared to a population of 1,282 in 2021. Over the last 20 plus years, between 2000 and 2023, population of China increased by 120. In this period, the peak population was 1,289 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the China is shown in this column.
• Year on Year Change: This column displays the change in China population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 China Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the China population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of China across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of China was 1,273, a 0.55% decrease year-by-year from 2021. Previously, in 2021, China population was 1,280, a decline of 0.62% compared to a population of 1,288 in 2020. Over the last 20 plus years, between 2000 and 2022, population of China increased by 111. In this period, the peak population was 1,288 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the China is shown in this column.
• Year on Year Change: This column displays the change in China population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 China Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the China town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of China town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of China town was 4,568, a 0.88% increase year-by-year from 2022. Previously, in 2022, China town population was 4,528, an increase of 1.21% compared to a population of 4,474 in 2021. Over the last 20 plus years, between 2000 and 2023, population of China town increased by 461. In this period, the peak population was 4,568 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the China town is shown in this column.
• Year on Year Change: This column displays the change in China town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 China town Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the China township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of China township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of China township was 3,513, a 0.11% increase year-by-year from 2021. Previously, in 2021, China township population was 3,509, an increase of 0.11% compared to a population of 3,505 in 2020. Over the last 20 plus years, between 2000 and 2022, population of China township increased by 151. In this period, the peak population was 3,692 in the year 2007. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the China township is shown in this column.
• Year on Year Change: This column displays the change in China township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 China township Population by Year. You can refer the same here

This dataset presents country-level tariff rates charged to the United States during the Trump administration, alongside discounted reciprocal tariffs the U.S. might have charged in return. It highlights the trade imbalances and protectionist policies in place at the time. Useful for trade policy analysis, political science research, and data visualization. The values were originally expressed in decimal format (e.g., 0.10 = 10%) but have been converted to percentage format for clarity. 📊 Column Descriptions ..Country The name of the country or economic union (e.g., China, European Union).

..Tariffs charged to the USA (%) The average tariff percentage imposed by each country on goods imported from the United States.

..U.S.A. Discounted Reciprocal Tariffs (%) Hypothetical reciprocal tariff rates the U.S. would charge if it applied the same discount factor used by the other country toward the U.S.

About this dataset

Context

The dataset illustrates the median household income in China town, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for China town increased by $18,418 (24.42%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 6 years and declined for 7 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 China town median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the China Grove population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of China Grove across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of China Grove was 4,572, a 1.17% increase year-by-year from 2022. Previously, in 2022, China Grove population was 4,519, an increase of 0.96% compared to a population of 4,476 in 2021. Over the last 20 plus years, between 2000 and 2023, population of China Grove increased by 876. In this period, the peak population was 4,572 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the China Grove is shown in this column.
• Year on Year Change: This column displays the change in China Grove population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 China Grove Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the East China township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of East China township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of East China township was 3,648, a 0.44% decrease year-by-year from 2022. Previously, in 2022, East China township population was 3,664, a decline of 0.84% compared to a population of 3,695 in 2021. Over the last 20 plus years, between 2000 and 2023, population of East China township increased by 12. In this period, the peak population was 3,865 in the year 2007. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the East China township is shown in this column.
• Year on Year Change: This column displays the change in East China township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 East China township Population by Year. You can refer the same here

United States Exports to China was US$143.55 Billion during 2024, according to the United Nations COMTRADE database on international trade. United States Exports to China - data, historical chart and statistics - was last updated on June of 2025.

NOTE: The included files cover the data and replication code for each of the three working papers that comprise this dissertation. By the time these files are available, it is likely that the author will have updated versions of each of these files. If you are interested in using these data, please contact the author directly or visit his website for the most updated versions. Concerns about domestic authority shape how governments conduct their foreign policies. However, this influence is often difficult to observe in highly opaque, non-democratic political systems. In the first part of the dissertation, I investigate the link between domestic authority and foreign policy in the context of diplomacy and trade in late imperial China, a period that spans the Ming (1368-1644) and Qing (1644-1911) dynasties. I argue that international diplomacy can serve leaders’ domestic political needs when it is highly visible to relevant audiences; conducted with counterparts held in relatively high esteem domestically; when certain diplomatic practices are historically associated with regime authority; or when diplomacy is wielded by leaders with relatively low levels of legitimacy. Using an original dataset of over 5,000 Ming and Qing tribute exchanges, I demonstrate that Chinese emperors newly in power conducted a disproportionately high volume of diplomatic activity. I find weaker evidence that this effect was more salient among low-legitimacy emperors. An accompanying case study illustrates how the Yongle Emperor deployed tribute diplomacy as a tool for domestic authority consolidation. Turning to the trade policies of the same period, I argue that beyond leaders, other autocratic elites who participate in foreign policy making are motivated by similar authority concerns. Extant research on non-democratic trade policy has largely neglected this group of actors. I develop a theory that predicts variation in elite policy preferences based on top-down and bottom-up authority relations with the leader and local trading communities, respectively. To assess these claims, I introduce a dataset on the maritime trade preferences of several hundred individual elite officials in late imperial China created through 10 months of archival work in Beijing and Taipei. The data suggest that coastal provincial officials became key pro-trade advocates during the Qing dynasty. The findings offer an example of how trade preferences can vary within a non-democratic regime, and how historical cases can be especially useful for empirically studying these preferences. In the third paper, the dissertation then flips the focus from the domestic politics of Chinese foreign policy to how other states’ internal politics shape their engagement with contemporary China. I argue that leaders of small developing countries can seek greater domestic authority by acquiring “prestige projects,” defined as highly visible, nationally salient international development projects. After identifying a set of Chinese government-financed prestige projects using a new dataset on Chinese development finance, I show that these projects are overwhelmingly concentrated in the world’s poorest and smallest countries, and that their implementation may be associated with higher public support for recipient governments. I also find that China’s government supplies more prestige projects to states that increase their support for Chinese diplomatic objectives.

📈 Daily Historical Stock Price Data for China State Construction International Holdings Limited (2000–2025)

A clean, ready-to-use dataset containing daily stock prices for China State Construction International Holdings Limited from 2000-01-04 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: China State Construction International Holdings Limited Ticker… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-china-state-construction-international-holdings-limited-20.

This U.S. Geological Survey (USGS) data release provides the descriptions of the only U.S. sites—including mineral regions, mineral occurrences, and mine features—that have reported production and (or) resources of tantalum (Ta). The sites in this data release have contained resource and (or) past production of more than 900 metric tons Ta metal, which was the approximate average annual consumption of Ta in the U.S. from 2016 through 2020. This dataset contains the Bokan Mountain deposit in Alaska and the Round Top deposit in Texas. Tantalum primarily occurs in the mineral tantalite, which may be found in carbonatites, alkaline granite-syenite complexes, and lithium-cesium-tantalum (LCT) pegmatites. The largest Ta deposits can be found in Australia, where the Greenbushes and Wodgina Mines have been producing Ta from pegmatites since the late 1880s. The Greenbushes is an LCT pegmatite deposit that contains more than 135 million metric tons of ore with an average grade of 0.022 percent Ta2O5. The Wodgina LCT pegmatite deposit contains more than 85 million metric tons of ore at a grade of 0.032 percent Ta2O5 (Schulz and others, 2017). In comparison, the largest Ta deposit in the U.S. is the Round Top deposit in Texas, which has reported resources of more than 480 million metric tons with an average grade of 67.2 grams per metric ton Ta2O5 (Hulse and others, 2019). There are no current U.S. producers of Ta. Tantalum is necessary for strategic, consumer, and commercial applications. Tantalum is highly conductive to heat and electricity and known for its resistance to acidic corrosion, thereby making this metal an ideal component for electronic capacitors, telecommunications, data storage, and implantable medical devices. In 2020, the U.S. was 100 percent net import reliant on Ta from countries such as China, Germany, Australia, and others. Tantalum is imported to the U.S. as ore and concentrate, metal and powder, as well as waste and scrap (U.S. Geological Survey, 2021). The entries and descriptions in the database were derived from published papers, reports, data, and internet documents representing a variety of sources, including geologic and exploration studies described in State, Federal, and industry reports. Resources extracted from older sources might not be compliant with current rules and guidelines in minerals industry standards such as National Instrument 43-101 (NI 43-101). The presence of a Ta mineral deposit in this database is not meant to imply that the deposit is currently economic. Rather, these deposits were included to capture the characteristics of the largest Ta deposits in the United States. Inclusion of material in the database is for descriptive purposes only and does not imply endorsement by the U.S. Government. The authors welcome additional published information in order to continually update and refine this dataset. Hulse, D.E., Malhotra, D., Matthews, T., and Emanuel, C., 2019, NI 43-101 preliminary economic assessment Round Top project, Sierra Blanca, Texas, prepared for USA Rare Earth LLC and Texas Mineral Resources Corp. [Filing Date July 1, 2019]: Gustavson Associates, LLC, 218 p., accessed October 17, 2019, at http://usarareearth.com/. Schulz, K.J., Piatak, N.M., and Papp, J.F., 2017, Niobium and tantalum, chap. M of Schulz, K.J., DeYoung, J.H., Jr., Seal, R.R., II, and Bradley, D.C., eds., Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply: U.S. Geological Survey Professional Paper 1802, p. M1–M34, https://doi.org/10.3133/pp1802M. U.S. Geological Survey, 2021, Mineral commodity summaries 2021: U.S. Geological Survey, 200 p., https://doi.org/10.3133/mcs2021.

This dataset presents information concerning 8- and 10-digit trade codes related to the rechargeable lithium-ion battery (LIB) supply chain for the People's Republic of China (PRC) and the European Union, and the United States as classified by Customs and Border Protection (CBP) rulings. Note that this dataset is not intended to be a complete or comprehensive list of trade codes for the LIB supply chain; rather, it presents trade codes from the PRC and the EU that more granularly classify products related to LIB supply chain in comparison to the Harmonized Tariff Schedule of the United States (HTSUS). CBP rulings are included to indicate existing classification decisions for relevant products related to the LIB supply chain. Disaggregated trade codes offer more detailed insight into trade flows, supply chains, and the state of domestic and international industries. The dataset covers raw materials, refined and processed materials, battery materials, cell components, batteries and ...

Abstract (en): The China Multi-Generational Panel Dataset - Liaoning (CMGPD-LN) is drawn from the population registers compiled by the Imperial Household Agency (neiwufu) in Shengjing, currently the northeast Chinese province of Liaoning, between 1749 and 1909. It provides 1.5 million triennial observations of more than 260,000 residents from 698 communities. The population mainly consists of immigrants from North China who settled in rural Liaoning during the early eighteenth century, and their descendants. The data provide socioeconomic, demographic, and other characteristics for individuals, households, and communities, and record demographic outcomes such as marriage, fertility, and mortality. The data also record specific disabilities for a subset of adult males. Additionally, the collection includes monthly and annual grain price data, custom records for the city of Yingkou, as well as information regarding natural disasters, such as floods, droughts, and earthquakes. This dataset is unique among publicly available population databases because of its time span, volume, detail, and completeness of recording, and because it provides longitudinal data not just on individuals, but on their households, descent groups, and communities. Possible applications of the dataset include the study of relationships between demographic behavior, family organization, and socioeconomic status across the life course and across generations, the influence of region and community on demographic outcomes, and development and assessment of quantitative methods for the analysis of complex longitudinal datasets. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Smallest Geographic Unit: Chinese banners (8) The data are from 725 surviving triennial registers from 29 distinct populations. Each of the 29 register series corresponded to a specific rural population concentrated in a small number of neighboring villages. These populations were affiliated with the Eight Banner civil and military administration that the Qing state used to govern northeast China as well as some other parts of the country. 16 of the 29 populations are regular bannermen. In these populations adult males had generous allocations of land from the state, and in return paid an annual fixed tax to the Imperial Household Agency, and provided to the Imperial Household Agency such home products as homespun fabric and preserved meat, and/or such forest products as mushrooms. In addition, as regular bannermen they were liable for military service as artisans and soldiers which, while in theory an obligation, was actually an important source of personal revenue and therefore a political privilege. 8 of the 29 populations are special duty banner populations. As in the regular banner population, the adult males in the special duty banner populations also enjoyed state allocated land free of rent. These adult males were also assigned to provide special services, including collecting honey, raising bees, fishing, picking cotton, and tanning and dyeing. The remaining populations were a diverse mixture of estate banner and servile populations. The populations covered by the registers, like much of the population of rural Liaoning in the eighteenth and nineteenth centuries, were mostly descendants of Han Chinese settlers who came from Shandong and other nearby provinces in the late seventeenth and early eighteenth centuries in response to an effort by the Chinese state to repopulate the region. 2016-09-06 2016-09-06 The Training Guide has been updated to version 3.60. Additionally, the Principal Investigator affiliation has been corrected, and cover sheets for all PDF documents have been revised.2014-07-10 Releasing new study level documentation that contains the tables found in the appendix of the Analytic dataset codebook.2014-06-10 The data and documentation have been updated following re-evaluation.2014-01-29 Fixing variable format issues. Some variables that were supposed to be s...

Overview

The State Grid Corporation of China (SGCC) dataset with 1000 records was used in the model. This is a key resource in the field of power distribution and management, with a large and varied set of data about electricity transport and grid operations. This set of data contains a lot of different kinds of information, such as history and real-time data on energy use, grid infrastructure, the integration of green energy, and grid performance. It is a key part of making power distribution networks more reliable and efficient by helping with things like predicting demand, watching the grid, and finding problems. Researchers, energy providers, and law- makers can use this information to learn important things about electricity usage trends, the health of the grid, and the merging of green energy sources. This will help the electric power industry come up with new strategies and ideas that are based on data.

Description

Electricity theft detection released by the State Grid Corporation of China (SGCC) dataset data set.csv contains 1037 columns and 42,372 rows for electric consumption from January first 2014 to 30 October 2016. SGCC data first column is consumer ID that is alphanumeric. Then from column 2 to columns 1036 daily electricity consumption is given. Last column named flag is the labels in 0 and 1 values. the small version of the dataset datasetsmall.csv only contains the electric consumption for January 2014.

Features

• 'MM/DD/YYYY': The electric consumption on a given day .
• CONS_NO: Consumer Number stands for a customer ID of string type.
• FLAG: 0 indicating no theft and 1 for theft.

Useful for

• Binary Classification: The main intention of the dataset is for binary classification of electrical theft.
• Imbalanced Datasets Processing: Useful for exploring class balancing methods.
• Time Series Forecasting: Can be used for forecasting and predicting electrical consumption on a given day.

Notes

• This Dataset Contains missing values .
• This Dataset has dates of the form "MM/DD/YYYY".
• This Dataset requires slight cleaning.

About this dataset

Context

The dataset tabulates the China township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of China township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of China township was 3,519, a 0.34% increase year-by-year from 2022. Previously, in 2022, China township population was 3,507, a decline of 0% compared to a population of 3,507 in 2021. Over the last 20 plus years, between 2000 and 2023, population of China township increased by 157. In this period, the peak population was 3,692 in the year 2007. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the China township is shown in this column.
• Year on Year Change: This column displays the change in China township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 China township Population by Year. You can refer the same here

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in The US–China trade war and phase one agreement, PIIE Working Paper 21-2.

If you use the data, please cite as: Bown, Chad P. (2021). The US–China trade war and phase one agreement. PIIE Working Paper 21-2. Peterson Institute for International Economics.

About this dataset

Context

The dataset illustrates the median household income in China, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2021, the median household income for China decreased by $11,600 (14.42%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 5 years and declined for 6 years.

https://i.neilsberg.com/ch/china-tx-median-household-income-trend.jpeg" alt="China, TX median household income trend (2010-2021, 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. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2021
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 China median household income. You can refer the same here