BACI Dataset Documentation BACI provides data on bilateral trade flows for 200 countries at the product level (5000 products). Products correspond to the "Harmonized System" nomenclature (6 digit code). BACI relies on data from the United Nations Statistical Division (Comtrade dataset). Since countries report both their imports and their exports to the United Nations, the raw data we use may have duplicates flows: trade from country i to country j may be reported by i as an export to j and by j as an import from i. The reported values should match, but in practice are virtually never identical, for two reasons: Import values are reported CIF (cost, insurance and freight) while exports are reported FOB (free on board). Mistakes are made, because of uncertainty on the final destination of exports, discrepancies in the classification of a given product, etc... Licensed EtaLab Open Licence v2.0, original data downloaded from http://www.cepii.fr/CEPII/en/bdd_modele/bdd_modele_item.asp?id=37"

The dataset contains import and export data of traded goods corresponding to ecoinvent products from the BACI database (https://www.cepii.fr/CEPII/en/bdd_modele/bdd_modele_item.asp?id=37), as well as data used to estimation total production volumes from various sources.

The only purpose of this dataset is to be used as an input to the Regioinvent Python package which can be found here: https://github.com/CIRAIG/Regioinvent

v3.1 changes: New commodities added.

The CEPII BACI database provides harmonized bilateral trade data at the 6-digit HS level for over 200 countries.

CHELEM-TRADE contains bilateral flows of goods expressed in millions of current US dollars since 1967. Data from UN-COMTRADE and complementary sources are harmonized and made consistent in a multi-level classification spanning the entire world (95 CHELEM individual countries or statistical territories and zones and additional aggregates). Goods are detailed in 71 categories, non-ventilated products (NV) and total products (TT). The elementary product categories can be aggregated by production chains and stages, sections or sectors. Data are harmonized by country pairs and product category; exports from country A to country B are equal to imports of country B from country A.

Code and Data needed to replicate the results of the paper "Production Relocation to the South and Within-Country Inequality". The ZIP file contains a folder structure that must be preserved when unzipping. Data on BACI folder is missing due to the restrictions. Please contact the Centre d’études prospectives et d’informations internationales (CEPII: http://cepii.fr) for accession, and then contact the authors.

CHELEM-TRADE-INDIC contains 7 indicators on goods and services based on the CEPII International Trade, Balance of Payments and Gross Domestic Product databases: coverage ratio between the values of exports and imports; the degree of openness (average of exports and imports related to current GDP); market position (balance related to average of world exports and imports); exports, imports and balances related to current GDP; and comparative advantages (contribution to the balance). Data are displayed in a multi-level classification spanning the entire world (95 CHELEM individual countries or statistical territories and zones and additional aggregates). Goods are displayed in the 3 classifications of CHELEM-TRADE (CHEL, GTAP and ISIC), detailed in respectively 71, 43 and 147 categories, non-ventilated products (NV) and total products (TT), as well as production chains, stages, sections, sectors or technological levels. Services are detailed in 16 elementary items, without processing (already integrated in goods). All data are expressed in %, except comparative advantages which are in thousandths of current GDP and market position in % of World trade of goods and services.

Industry-level measures of export quality that take global input-output linkages into account and associated code; as described in Wacker et al. (2025). The main repository folders are: - codes/: a folder with python codes performing the four steps explained in the Usage Notes below. - data/QualEst/: a folder with zipped CSV files (QualEst_YYYY.zip, where YYYY stands for the year), storing the quality estimate for bilateral traded products () based on Trenczek and Wacker [15]. This folder will also store the quality aggregations generated as intermediate products in the codes. Those estimates are ultimately based on the BACI database for bilateral trade flows [13], version 202301-HS07. Quality estimates and trade flows are available for bilateral trade between countries and administrative regions for the entire world, and data for each year are provided in separated CSV files with the following columns: identifier of importing and exporting countries (i and j), product code in 6-digit HS2007 classification (hs6digit), value of export in thousand US dollars (v), and quality estimates (qual_idx). Country identifiers are integers that follow the classification in the BACI database; more details can be obtained from https://cepii.fr/CEPII/en/bdd_modele/bdd_modele_item.asp?id=37. - data/ICIO/: An empty folder, to which one should download and unzip the Regular ICIO input-output tables from the official OECD website (https://oe.cd/icio) and place them in this folder. We used the 2023 December release of Regular ICIO input-output tables from OECD. ICIO are available for 76 countries and regions, plus a "rest-of-world" entry covering all other economies, and 46 industries based on 2-digit ISIC Rev. 4 classification. The input-output tables are provided in CSV format. More details on the data structure and the definitions for rows and columns can be found in https://oe.cd/icio - data/keys/: folder with correspondence tables for country and product-industry identifiers used in the export quality dataset and ICIO input-output tables; both are in CSV format. The file for product-industry identifiers includes a column (TYPE) that describe the property of traded products: 0: intermediates, 1: mixed-use products, 2: final products for consumption or capital investment only. Further details can be found in the ReadMe.txt file placed in the root folder of the replication package.

The data set contains dyadic link specific variables for use in gravity models

CHELEM-TRADE contains bilateral flows of goods expressed in millions of current US dollars since 1967. Data from UN-COMTRADE and complementary sources are harmonized and made consistent in a multi-level classification spanning the entire world (95 CHELEM individual countries or statistical territories and zones and additional aggregates). Goods are detailed in 147 elementary (4-digits) categories, aggregated in 3-digits (79) and 2-digits (35), non-ventilated products (NV) and total products (TT). The elementary product categories can be aggregated by technological levels. Data are harmonized by country pairs and product category; exports from country A to country B are equal to imports of country B from country A.

This dataset contains panel data used to analyse the impact of Aid for Trade (AfT) on Nigeria’s agricultural export performance from 2005 to 2018. The data is structured at the bilateral level, capturing Nigeria’s trade with multiple partner countries over time. It includes detailed information on bilateral exports, disaggregated Aid for Trade flows (total, economic infrastructure, productive capacity, and trade policy), control variables such as GDP, distance, real and agricultural production, as well as dummy variables capturing trade agreements, linguistic ties, and regional integration (e.g. ECOWAS membership).

The dataset supports fixed effects gravity model estimations and includes relevant economic and institutional indicators drawn from a range of sources including UN COMTRADE, OECD CRS, World Bank World Development Indicators (WDI), CEPII, and the WTO.

This dataset is made available for academic and research purposes only. While every effort has been made to ensure the accuracy and consistency of the data, the compilers make no warranties regarding its completeness, reliability, or fitness for a particular purpose. Users are advised to consult original data sources (e.g. UN COMTRADE, OECD CRS, World Bank WDI, CEPII, WTO) for official statistics and definitions.

数据内容： 该数据集包含了全球范围内双边和单方面贸易伙伴关系的份额数据。具体而言，数据集包括以下字段： 1. Entity：标识数据对应的国家或地区。 2. Code：与Entity对应的编码。 3. Year：数据对应的年份。 4. Non-trading (Fouquin and Hugot (CEPII 2016))：非贸易伙伴关系的份额。 5. Bilateral trade partnerships (Fouquin and Hugot (CEPII 2016))：双边贸易伙伴关系的份额。 6. Unilateral trade partnerships (Fouquin and Hugot (CEPII 2016))：单方面贸易伙伴关系的份额。 数据来源：互联网公开数据 数据用途： 该数据集可用于多个行业的研究和分析，包括但不限于以下领域： 1. 国际贸易：分析全球贸易伙伴关系的变化趋势，研究双边和单方面贸易政策的影响。 2. 经济学研究：探讨贸易伙伴关系与经济发展的关系，评估贸易政策的效果。 3. 政策制定：为政府和国际组织提供数据支持，帮助制定更有效的贸易政策。 4. 数据分析：用于贸易数据的可视化和建模，支持商业决策和学术研究。 5. 全球经济研究：研究全球贸易格局的变化，预测未来贸易趋势。 标签：贸易伙伴关系,双边贸易,单方面贸易,CEPII研究,全球贸易分析,国际贸易数据,经济政策研究 行业分类： 1. 国际贸易 2. 经济学研究 3. 政策制定 4. 数据分析 5. 全球经济研究 分析： 该数据集包含多个关键字段，其中Year字段具有65种不同的值，表明数据覆盖了较长时间跨度。Non-trading, Bilateral trade partnerships, 和 Unilateral trade partnerships字段各有64种不同的值，说明数据反映了多个国家或地区在不同年份的贸易伙伴关系份额。这种多样性为研究全球贸易格局的变化提供了丰富的数据支持。

The Demographic Trade Database is an ongoing project compiling multiple sources of information on bilateral trade, macroeconomic variables, and population demographics into easy to use resource. This data is made available to provide researchers with the tools needed to further explore questions relating to how underlying population movements affect the bilateral flow of trade between countries, and the degree to which projected changes in demographics may affect the global trade landscape in years to come.TradeDemography.dta provides the main dataset which contains trade and demographic values for 39,601 country-pairs from 1970-2019. The dataset TradeDemography_wProj.dta has the same economic, but also includes medium variant projections for demographic variables from 2020-2100. For a detailed documentation and discussion of constructed demographic variables: https://www.josephkopecky.com/Source used to construct this database come from the CEPII Gravity database and the UN World Population Prospects database:Conte, M., P. Cotterlaz and T. Mayer (2022), "The CEPII Gravity database". CEPII Working Paper N°2022-05, July 2022. United Nations, Department of Economic and Social Affairs, Population Division (2022). World Population Prospects 2022: Methodology of the United Nations population estimates and projections. UN DESA/POP/2022/TR/NO. 4.

EU KLEMS Growth and Productivity Accounts: October 2012 Releaes, data in the ISIC Rev. 4 industry classification All series derived from this database need to be referred to as follows: O’Mahony, Mary and Marcel P. Timmer (2009), “Output, Input and Productivity Measures at the Industry Level: the EU KLEMS Database”, Economic Journal, 119(538), pp. F374-F403 For more details and analysis, see: Timmer, Inklaar , O'Mahony and van Ark, Economic Growth in Europe, Cambridge University Press, 2010 Introduction The 2012 EU KLEMS release follows up from the previous release in 2009 which showed detailed growth accounts up to 2007. This new release is similar in concepts and methodologies to calculate the various growth and productivity variables as its predecessors, but it also has a number of new features; It provides updates and data for additional years and revisions of longer time-series in case national statistical institutes (NSIs) provided these. For labour composition use has been made of the micro-data underlying the European Labour Force Survey (LFS) for recent years. New investment data has been provided by the EU KLEMS consortium partners. Most importantly, a new industrial classification is used based on the new international ISIC Revision 4 industry classification, which is consistent with the European NACE 2 industry classification. The National Accounts (NA) data in the new classification is typically provided for shorter time series than were previously available in the ISIC Rev. 3 (NACE 1) classification. We back-cast time series of output and labour data using growth rates from the earlier data in the ISIC Rev. 3 classification. These imputations are denoted in grey in the new release. Sources and methods The EU KLEMS updates in the new ISIC Rev. 4 industry classification are being done on a country by country basis. Sources and methods documentation is available separately for each country. The following institutes have partnered with us to construct these data, additional information can be found on their respective websites: STATSWE (Sweden) STATFI (Finland) FPB (Belgium) JIP (Japan) BEA/BLS (United States) CBS (Netherlands) NIESR (United Kingdom) DIW (Germany) ISTAT (Italy) WIFO (Austria) CEPII (France) IVIE (Spain) More information on additional EU KLEMS releases can be found on the website of the Groningen Growth and Development Centre (GGDC). The original website of the EU KLEMS project, on which these data were first released, has been archived, but is still available through the Internet Archive. This update of the EU KLEMS database is part of the INDICSER project. This project is funded by the European Commission, Research Directorate General as part of the 7th Framework Programme, Theme 8: Socio-Economic Sciences and Humanities. Grant Agreement no: 244 709 Any errors or omissions in this update of the EU KLEMS database are entirely the responsibility of the GGDC (Groningen Growth and Development Centre).

EU KLEMS Growth and Productivity Accounts: March 2008 Release All series derived from this database need to be referred to as follows: Source: EU KLEMS Database, March 2008, see Marcel Timmer, Mary O'Mahony & Bart van Ark, The EU KLEMS Growth and Productivity Accounts: An Overview, University of Groningen & University of Birmingham; downloadable at www.euklems.net Documentation on the sources and methods have been published with the March 2007 Release of the EU KLEMS dataset: Methodology of the March 2007 Release Sources of the March 2007 Release More information on additional EU KLEMS releases can be found on the website of the Groningen Growth and Development Centre (GGDC). The original website of the EU KLEMS project, on which these data were first released, has been archived, but is still available through the Internet Archive. Consortium members EU KLEMS Project: University of Groningen, Groningen Growth and Development Centre (GGDC, Groningen) National Institute of Economic and Social Research (NIESR, London) Centre d'études prospectives et d'informations internationales (CEPII, Paris) Centre for Economic and Business Research (CEBR, Copenhagen) Netherlands Bureau for Economic Policy Analysis (CPB, The Hague) Deutsches Institut für Wirtschaftsforschung (DIW, Berlin) Federaal Planbureau (FPB, Brussels) Information on the Istituto di Studi e Analisi Economica (ISAE, Roma) Instituto Valenciano de Investigationes Económicas (IVIE, Valencia) Helsinki School of Economics (HSE, Helsinki) Österreichisches Institut für Wirtschaftsforschung (WIFO, Vienna) Wiener Institut für Internationale Wirtschaftsvergleiche AMsterdam Institute for Business and Economic Research, Free University Amsterdam (AMBER) The Conference Board Europe (TCB, Brussels) Fachhochschule Konstanz (FK, Konstanz) University of Birmingham (UNI-BHAM, Birmingham) Pellervo Economic Research Institute (PTT, Helsinki) This project was funded by the European Commission, Research Directorate General as part of the 6th Framework Programme, Priority 8, "Policy Support and Anticipating Scientific and Technological Needs". More about this project.

This is a data repository that could be used to replicate the results found in the text: EU enlargements, Brexit and value-added trade. A structural gravity approach by Jan Hagemejer & Jakub Mućk. This dataset is based on the following datasets:OECD Trade in Value Added Database, https://www.oecd.org/sti/ind/measuring-trade-in-value-added.htmConte M, Cotterlaz P, Mayer T. The CEPII Gravity database. CEPII Working Paper N°2022-05. July 2022.The Hagemejer_Muck_2004.dta is a Stata file with aggregate-level variables.The Hagemejer_Muck_2024_Industry.dta is a Stata file that contains the sectoral data. dataset.txt contains the properties of the dataset and variables definitions.

EU KLEMS Growth and Productivity Accounts: November 2009 Release, updated March 2011 All series derived from this database need to be referred to as follows: O’Mahony, Mary and Marcel P. Timmer (2009), “Output, Input and Productivity Measures at the Industry Level: the EU KLEMS Database”, Economic Journal, 119(538), pp. F374-F403 For more details and analysis, see: Timmer, Inklaar , O'Mahony and van Ark, Economic Growth in Europe, Cambridge University Press, 2010 Documentation on the sources and methods have been published with the March 2007 Release of the EU KLEMS dataset: Methodology of the March 2007 Release Sources of the March 2007 Release More information on additional EU KLEMS releases can be found on the website of the Groningen Growth and Development Centre (GGDC). The original website of the EU KLEMS project, on which these data were first released, has been archived, but is still available through the Internet Archive. Consortium members EU KLEMS Project: University of Groningen, Groningen Growth and Development Centre (GGDC, Groningen) National Institute of Economic and Social Research (NIESR, London) Centre d'études prospectives et d'informations internationales (CEPII, Paris) Centre for Economic and Business Research (CEBR, Copenhagen) Netherlands Bureau for Economic Policy Analysis (CPB, The Hague) Deutsches Institut für Wirtschaftsforschung (DIW, Berlin) Federaal Planbureau (FPB, Brussels) Information on the Istituto di Studi e Analisi Economica (ISAE, Roma) Instituto Valenciano de Investigationes Económicas (IVIE, Valencia) Helsinki School of Economics (HSE, Helsinki) Österreichisches Institut für Wirtschaftsforschung (WIFO, Vienna) Wiener Institut für Internationale Wirtschaftsvergleiche AMsterdam Institute for Business and Economic Research, Free University Amsterdam (AMBER) The Conference Board Europe (TCB, Brussels) Fachhochschule Konstanz (FK, Konstanz) University of Birmingham (UNI-BHAM, Birmingham) Pellervo Economic Research Institute (PTT, Helsinki) The construction of this database is financially supported by the European Commission, Research Directorate General as part of the 6th Framework Programme, Priority 8, “Policy Support and Anticipating Scientific and Technological Needs” and as part of the 7th Framework Programme, Theme 8: Socio-Economic Sciences and Humanities, Grant agreement no: 225 281. Any errors or omissions are entirely the responsibility of the GGDC (Groningen Growth and Development Centre). More about this project.