The Country and Regional Analysis (CRA) presents statistical estimates for the allocation of identifiable expenditure between the regions and nations of the UK. This year’s dataset covers the outturn period 2018-19 to 2022-23.
Alongside the main CRA release, the Treasury has published further analysis tools in the form of “interactive tables” and the full CRA database. These tools will allow users to manipulate the data to create their own views. The database contains the underlying “segment” level data used to construct the published tables in CRA 2023. Figures are in nominal terms. The “interactive tables” include both nominal and real terms data, but exclude the “segment” level information.
For statistical enquiries, please contact: Pesa.document@hmtreasury.gov.uk
The country and regional analysis (CRA) presents statistical estimates for the allocation of identifiable expenditure between the UK countries and 9 English regions. This year’s dataset covers the outturn period 2010-11 to 2014-15.
The country and regional analysis (CRA) presents statistical estimates for the allocation of identifiable expenditure between the UK countries and 9 English regions. This year’s dataset covers the outturn period 2015-16 to 2019-20.
Alongside the main CRA release, the Treasury has published further analysis tools in the form of “interactive tables” and the full CRA database. These tools will allow users to manipulate the data to create their own views. The database contains the underlying “segment” level data used to construct the published tables in CRA 2020. Figures are in nominal terms. The “interactive tables” include both nominal and real terms data, but exclude the “segment” level information.
For statistical enquiries, please contact: Pesa.document@hmtreasury.gov.uk
Spreadsheet detailing programme expenditure by region
http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence
Database of the Country and Regional Exercise (CRA) presenting the underlying data for the tables in chapter 9 of the Public Expenditure and Statistical Analyses (PESA) release from 1 July 2010. The database shows the geographic allocation of public spending at NUTS1 level broken down by function and programme object group.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
🇬🇧 영국
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Country, Regional and World GDP’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tunguz/country-regional-and-world-gdp on 28 January 2022.
--- Dataset description provided by original source is as follows ---
Country, regional and world GDP in current US Dollars ($). Regional means collections of countries e.g. Europe & Central Asia.
The data is sourced from the World Bank, which in turn lists as sources: World Bank national accounts data, and OECD National Accounts data files.
--- Original source retains full ownership of the source dataset ---
https://bisresearch.com/privacy-policy-cookie-restriction-modehttps://bisresearch.com/privacy-policy-cookie-restriction-mode
Ethylene Carbonate Market - A Global and Regional Analysis: Focus on Product, Application, and Country Analysis - Analysis and Forecast, 2025-2034
This report will be delivered in 7-10 working days.
TSGB1301: https://assets.publishing.service.gov.uk/media/6762dce4ff2c870561bde7e6/tsgb1301.ods">Public expenditure on transport (ODS, 6.88 KB)
TSGB1302: https://assets.publishing.service.gov.uk/media/6762dced3229e84d9bbde7dd/tsgb1302.ods">Public expenditure on transport by country and spending authority (ODS, 38 KB)
TSGB1303: https://assets.publishing.service.gov.uk/media/6762ddadbe7b2c675de3079c/tsgb1303.ods">Public expenditure on transport by function (ODS, 11.9 KB)
TSGB1304: https://assets.publishing.service.gov.uk/media/6762df8d3229e84d9bbde7e7/tsgb1304.ods">Total UK public corporation capital expenditure on transport (ODS, 7.83 KB)
TSGB1305 shows public expenditure on specific transport areas in Great Britain from the Financial Year Ending (FYE) 2006 to FYE 2020. Following a lack of demand and re-prioritisation of resources, this table has been discontinued. Information on regional public expenditure can be found in HMT鈥檚 Country and Regional Analysis in table 6.4.
TSGB1305: https://assets.publishing.service.gov.uk/media/61b7d78be90e0704423dc10b/tsgb1305.ods">Public expenditure on specific transport areas: Great Britain (ODS, 16.6 KB)
TSGB1306: https://assets.publishing.service.gov.uk/media/6762df9a4e2d5e9c0bde9b03/tsgb1306.ods">Household expenditure on transport (ODS, 15.6 KB)
TSGB1307: https://assets.publishing.service.gov.uk/media/6762dfa5ff2c870561bde7ed/tsgb1307.ods">Retail and consumer prices indices: motoring costs (ODS, 8.82 KB)
TSGB1308: https://assets.publishing.service.gov.uk/media/6762dfaf4e2d5e9c0bde9b04/tsgb1308.ods">Retail prices index: transport components (ODS, 19.7 KB)
TSGB1309: https://assets.publishing.service.gov.uk/media/6762dfb8be7b2c675de307aa/tsgb1309.ods">GDP, RPI, Consumer Price Index deflators (ODS, 9.92 KB)
TSGB1310: https://assets.publishing.service.gov.uk/media/6762dfc3ff2c870561bde7ee/tsgb1310.ods">Fuel and vehicle excise duty (<abbr title="OpenDocument Spreads
https://bisresearch.com/privacy-policy-cookie-restriction-modehttps://bisresearch.com/privacy-policy-cookie-restriction-mode
Optical Ground Station Market - A Global and Regional Analysis: Focus on End User, Component, Type, Solution and Country - Analysis and Forecast, 2023-2033
This report will be delivered in 7-10 working days.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The aim of this study is to make a comparative study on the reproduction number R0 computed at the beginning of each wave for African countries and to understand the reasons for the disparities between them. The study covers the two first years of the COVID-19 pandemic and for 30 African countries. It links pandemic variables, reproduction number R0, demographic variable, median age of the population, economic variables, GDP and CHE per capita, and climatic variables, mean temperature at the beginning of each waves. The results show that the diffusion of COVID-19 in Africa was heterogeneous even between geographical proximal countries. The difference of the basic reproduction number R0 values is very large between countries and is significantly correlated with economic and climatic variables GDP and temperature and to a less extent with the mean age of the population.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This paper examines the effect of financial development, measured by broad money, domestic credit, and mobile money, on poverty and human development in the Southeast Asian economies, using the dataset from 1990 to 2017. The findings suggest that broad money and domestic credit contribute to poverty reduction and promote human development. The role of mobile money is seen to have a statistically positive impact only if we analyse it with human development. Additionally, when we take a closer look at the different stage of economic, political, and institutional development in this region, we found that the positive effect of broad money and domestic credit is mostly found only in the less developed and less democratic countries. The mobile money, on the other hand, is found to statistically promote the human development in both groups of countries, but there is no statistical relationship for poverty analysis.NOTE: The appendix files have been added from 31-08-2021
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Results of the regional analysis (two-step system GMM).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Summary of drivers of children’s diets per determinant based on key informant interviews, by country.
https://www.globaldata.com/privacy-policy/https://www.globaldata.com/privacy-policy/
This report focuses on the use of dry casks for the storage of SNF, and provides in-depth analysis of demand in three major regions of the world. The market demand and value analysis section contains details of the amount of cumulative SNF generated, SNF in dry storage, cumulative and annual dry cask demand and market value between 2006 and 2020. Geographical market analysis is achieved through the division of the global market into three major regions: Asia-Pacific, Europe and North America. Other regions such as South and Central America and Middle East and Africa have also been considered in estimating the size of the global market for dry storage casks. Read More
https://bisresearch.com/privacy-policy-cookie-restriction-modehttps://bisresearch.com/privacy-policy-cookie-restriction-mode
NGS Data Storage Market to reach $6.96 billion by 2033. BIS Research published NGS data storage market report which focus on offerings, read length, sourcing type, application, end user, and country analysis
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
A well-integrated agricultural market is a precondition for the sustainability of agri-food systems since it contributes to optimal resource and product allocation and encourages specialization according to comparative advantage. This study broadens the previous research on the spatial integration of the milk market with a regional analysis of four countries: Germany, Czechia, Poland, and Slovakia. The empirical analysis was conducted on monthly regional cow’s raw milk prices. The dataset covered the period January 2013 – December 2021. The length of the data sample was determined by the availability of the prices regional data. Agricultural prices were obtained from several sources: the Czech Statistical Office, the Statistical Office of the Slovak Republic, the Polish Statistical Office, and the German Federal Office for Agriculture and Food. Since not all prices were available in Euro, monthly exchange rates gained from Eurostat were used to express prices in the same currency (EUR).
By Correlates of War Project [source]
The World Religion Project (WRP) is an ambitious endeavor to conduct a comprehensive analysis of religious adherence throughout the world from 1945 to 2010. This cutting-edge project offers unparalleled insight into the religious behavior of people in different countries, regions, and continents during this time period. Its datasets provide important information about the numbers and percentages of adherents across a multitude of different religions, religion families, and non-religious affiliations.
The WRP consists of three distinct datasets: the national religion dataset, regional religion dataset, and global religion dataset. Each is focused on understanding individually specific realms for varied analysis approaches - from individual states to global systems. The national dataset provides data on number of adherents by state as well as percentage population practicing a given faith group in five-year increments; focusing attention to how this number evolves from nation to nation over time. Similarly, regional data is provided at five year intervals highlighting individual region designations with one modification – Pacific Ocean states have been reclassified into their own Oceania category according to Country Code Number 900 or above). Finally at a global level – all states are aggregated in order that we may understand a snapshot view at any five-year interval between 1945‐2010 regarding relationships between religions or religio‐families within one location or transnationally.
This project was developed in three stages: firstly forming a religions tree (a systematic classification), secondly collecting data such as this provided by WRP according to that classification structure – lastly cleaning the data so discrepancies may be reconciled and imported where needed with gaps selected when unknown values were encountered during collection process . We would encourage anyone wishing details undergoing more detailed reading/analysis relating various use applications for these rich datasets - please contact Zeev Maoz (University California Davis) & Errol A Henderson _(Pennsylvania State University)
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
The World Religions Project (WRP) dataset offers a comprehensive look at religious adherence around the world within a single dataset. With this dataset, you can track global religious trends over a period of 65 years and explore how they’ve changed during that time. By exploring the WRP data set, you’ll gain insight into cross-regional and cross-time patterns in religious affiliation around the world.
- Analyzing historical patterns of religious growth and decline across different regions
- Creating visualizations to compare religious adherence in various states, countries, or globally
- Studying the impact of governmental policies on religious participation over time
If you use this dataset in your research, please credit the original authors. Data Source
License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.
File: WRP regional data.csv | Column name | Description | |:-----------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------| | Year | Reference year for data collection. (Integer) | | Region | World region according to Correlates Of War (COW) Regional Systemizations with one modification (Oceania category for COW country code ...
https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy
Access Europe Food Delivery Industry Overview which includes Europe country analysis of (United Kingdom, France, Germany, Italy, Russia, Spain, Sweden, Denmark, Switzerland, Luxembourg, Rest of Europe), market split by Type, Platform, Model, Payment
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Descriptive statistics of the analytical sample by geographic macro-area (all countries (9); sample size (n) = 37,864).
The Country and Regional Analysis (CRA) presents statistical estimates for the allocation of identifiable expenditure between the regions and nations of the UK. This year’s dataset covers the outturn period 2018-19 to 2022-23.
Alongside the main CRA release, the Treasury has published further analysis tools in the form of “interactive tables” and the full CRA database. These tools will allow users to manipulate the data to create their own views. The database contains the underlying “segment” level data used to construct the published tables in CRA 2023. Figures are in nominal terms. The “interactive tables” include both nominal and real terms data, but exclude the “segment” level information.
For statistical enquiries, please contact: Pesa.document@hmtreasury.gov.uk