We publish our out-of-sample estimates on historical GDP per capita levels between the years 1300 and 2000 together with the collected source data on countries and regions in a comprehensive dataset comprising 5,690 observations (1,313 source data observations, and 4,377 out-of-sample estimates). All references to the source data are provided in the manuscript.Locations refer to NUTS-2 regions in Europe (2021 edition), metro- and micropolitan statistical areas for the United States, metropolitan areas for Canada, and regions of similar size for other countries, e.g. oblasts in Russia. For countries, we use ISO 3166-1 alpha-3 country codes.The column GDPpc is denoted in 2011 USD PPP, matching the unit provided in the Maddison project. The column flag describes whether the value in column GDPpc is taken from source data (see manuscript for references) or an out-of-sample estimate. If it is an out-of-sample estimate, the columns GDPpc_lower and GDPpc_upper provide 90 percent confidence intervals obtained by bootstrapping.The code to generate all estimates will be published soon to ensure reproducibility of results.

A cross-national data archive located in Luxembourg that contains two primary databases: the Luxembourg Income Study Database (LIS Database) includes income microdata from a large number of countries at multiple points in time. The newer Luxembourg Wealth Study Database(LWS Database) includes wealth microdata from a smaller selection of countries. Both databases include labor market and demographic data as well. Our mission is to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes. Since its beginning in 1983, the LIS has grown into a cooperative research project with a membership that includes countries in Europe, North America, and Australia. The database now contains information for more than 30 countries with datasets that span up to three decades. The LIS databank has a total of over 140 datasets covering the period 1968 to 2005. The primary objectives of the LIS are as follows: * Test the feasibility for creating a database containing social and economic data collected in household surveys from different countries; * Provide a method which allows researchers to use the data under restrictions required by the countries providing the data; * Create a system that allows research requests to be received from and returned to users at remote locations; and * Promote comparative research on the social and economic status of various populations and subgroups in different countries. Data Availability: The dataset is accessed globally via electronic mail networks. Extensive documentation concerning technical aspects of the survey data, variables list, and the social institutions of income provision in member countries are also available to users through the project Website. * Dates of Study: 1968-present * Study Features: International * Sample Size: 30+ Countries Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00150

From February 10, 2018 to April 11, 2018, the Government of Canada invited comments from all stakeholders on potential areas for regulatory cooperation with the E.U. under the newly established Canada-E.U. Comprehensive Economic and Trade Agreement Regulatory Cooperation Forum. This consultation included soliciting proposals on how to: align existing regulatory systems; streamline duplicative procedures; and/or work collaboratively in areas that are not currently regulated, such as emerging technologies.

Primary reason business or organization does not carry out trade under the Canadian-European Union Comprehensive Economic and Trade Agreement (CETA), by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, fourth quarter of 2021.

The “Employment by activites and status (ALFS)” dataset is a subset of the Annual Labour Force Statistics database which presents annual labour force statistics for OECD member countries, Brazil and 4 geographical areas (Major Seven, Euro zone, European Union and OECD-Total).

This dataset contains employment statistics broken down by economic activities as defined by the ISIC Rev. 4 classification and by professional status as defined by the ICSE-1993 including employees, employers and own-account workers, and unpaid family workers. It also shows the number of employees broken down by economic activities (ISIC Rev. 4).

Economic activities are defined according to the Major divisions of the International standard International Classification (ISIC) Rev. 4 with the exception of the United-States wich compiled since 2003, employment data by sector following the North American Industrial Classification System (NAICS); NAICS sector are then proxied to ISIC Rev. 4 and are therefore not strictly comparable with other countries’ data.

The professional status is defined in the International Classification by status in Employment (ICSE-1993). To be considered as an unpaid family worker, the hour-threshold varies from one hour to 18 hours a week.

Data are presented in thousands of persons, or as indices with base year 2015=100.

Annual data in this dataset are typically calculated as averages of infra-annual estimates. This can lead to differences with annual data published by National Statistics Institutes.

Historical data of employment statistics defined according to " https://stats.oecd.org/wbos/fileview2.aspx?IDFile=c2fdf1ac-9dba-4317-8a8d-d872f514a7d8"> ISIC Rev. 2 are also available from 1970 to 2014

Historical data of employment statistics defined according to ISIC Rev. 3 are available from 1983 to 2023. Data for Canada are currently only available in ISIC Rev. 3

Executive Order 80: North Carolina's Commitment to Address Climate Change and Transition to a Clean Energy Economy. North Caroline (US)

This study deals with three questions: What does gas from coal cost and what affects this cost; How do different approaches and processes compare; and How near to competitive cost-levels is present-day technology. Discussion covers production of both substitute natural gas (SNG) and medium calorific gas (MCG: 10-16 MJ/Nm3 or 250-400 Btu/SCF). Conclusions are that SNG from low-cost U.S. coal and West German brown coal are, on the basis of mature technology and Government rates-of-return, roughly competitive with gas imports into the U.S. and Europe respectively. Similarly MCG from second-generation gasifiers is competitive with gas-oil or No. 2 heating oil in Europe, North America and Japan. However, capital costs form about half total gas costs at 10 percent rate-of-return, so that the competitiveness of gas from coal is sensitive to capital costs: this is the area of greatest uncertainty.

Get data on the agri-food trade by region.

This statistical dataset shows agri-food exports and imports between Ontario and major trading partners such as:

• The United States
• Mexico
• Latin America (excluding Mexico)
• Caribbean
• The European Union
• Western Europe
• Eastern Europe
• Middle East
• Africa
• Japan
• Asia (excluding Japan)
• Oceania

The dataset contains the following statistics: 1) Global Food Security Index 2022 (The Economist Intelligent Unit, 2022); 2) The result of the implementation of the sustainable development goal number 2 (SDG Goal 2 Score,) at the end of 2022 (UNDP, 2022); 3) Industrial robots per 10,000 employees in the manufacturing industry (International Federation of Robotics, 2022); 4) Use of big data and analytics 2022 (IMD, 2022). The dataset contains statistics for 38 countries of the world with different economic and geographical characteristics. Countries are organized into the following categories: E. Europe & C. Asia; East & South Asia; LAC; OECD Africa; OECD, Asia; OECD, Europe; OECD, North America; OECD, Oceania; OECD, South America; Sub-Saharan Africa.

Four marine fish species are among the most important on the world market: cod, salmon, tuna, and sea bass. While the supply of North American and European markets for two of these species - Atlantic salmon and European sea bass - mainly comes from fish farming, Atlantic cod and tunas are mainly caught from wild stocks. We address the question what will be the status of these wild stocks in the midterm future, in the year 2048, to be specific. Whereas the effects of climate change and ecological driving forces on fish stocks have already gained much attention, our prime interest is in studying the effects of changing economic drivers, as well as the impact of variable management effectiveness. Using a process-based ecological-economic multispecies optimization model, we assess the future stock status under different scenarios of change. We simulate (i) technological progress in fishing, (ii) increasing demand for fish, and (iii) increasing supply of farmed fish, as well as the interplay of these driving forces under different sce- narios of (limited) fishery management effectiveness. We find that economic change has a substantial effect on fish populations. Increasing aquaculture production can dampen the fishing pressure on wild stocks, but this effect is likely to be overwhelmed by increasing demand and technological progress, both increasing fishing pressure. The only solution to avoid collapse of the majority of stocks is institutional change to improve management effectiveness significantly above the current state. We conclude that full recognition of economic drivers of change will be needed to successfully develop an integrated ecosystem management and to sustain the wild fish stocks until 2048 and beyond.