About

The UNIDO Industrial Analytics Platform is an innovative tool providing data on select indicators of industrial development and relevant research by leading experts in an accessible format.

Methodological overview

The UNIDO Industrial Analytics Platform provides data on a set of tailored indicators relevant to industrial development. To ensure that the best available sources are used for each indicator, data are derived from internal as well as external databases. Where possible, data are presented at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) to identify trends at the industry level.

Comments

  • While regional/development status aggregates cover all available countries, some countries and territories are not considered in the country-level analyses:

    • Countries/territories that do not feature both trade and national accounts data

    • Countries/territories with a population of less than 300,000 in 2018

    • Countries with significant data inconsistencies

  • Data of former territories (Netherlands Antilles, Serbia and Montenegro, Sudan (Former)) are included in the regional/development status aggregates.
  • Regional/development status aggregates in CEPII BACI and UNIDO INDSTAT 2 are calculated on the basis of an unbalanced panel of countries, which may lead to biased results due to countries entering and exiting the sample. 

  • By default, countries are compared to the largest economy in their home region (subject to data availability).

Main data sources

This section contains information on the platform's data sources. Due to analytical procedures applied to improve data coverage and consistency, results may – in some cases – diverge from official data.

SDG-9 Industry Indicators and Index

UNIDO serves as the custodian agency for six industry-related indicators under Sustainable Development Goal 9 adopted by the General Assembly on 6 July 2017 (A/RES/71/313). To produce data on these indicators, UNIDO draws on data from and collaborates closely with other UN agencies, such as the ILO (employment) and the IEA (CO2 emissions).

For more detailed information on UNIDO's role in monitoring the progress made in SDG-9, please refer to the following report.

A multidimensional index is calculated using the available data. The indicators are normalized to values between 0 (worst performance) and 1 (best performance). The geometric mean across all dimensions is used to determine the composite index.

For further details on the Index's methodology, please refer to Composite index as a measure on achieving Sustainable Development Goal 9 (SDG-9) industry-related targets: The SDG-9 index (Kynčlová, Upadhyaya and Nice 2020, Applied Energy 265 (May 2020), 114755)

Information used

Data on all indicators and the Index for 128 economies between 2000 and 2017.

Comments

  • Due to insufficient country and time coverage, SDG indicators 9.3.1 and 9.3.2 (Proportion of small-scale industries in total industry value added and Proportion of small-scale industries with a loan or line of credit) are not reported.  
  • The SDG-9 Industry Index and rankings are only calculated for those countries for which all reported indicators are available.

SDG-9 Industry Progress and Outlook assessment

With the exception of the doubling of manufacturing's share in GDP and total employment in Least Developed Countries from 2015 to 2030, no clearly defined benchmarks have been defined in the official documents to measure progress made and assess the outlook for successful achievement of the SDG-9 Industry targets by 2030. To fill this gap, UNIDO, in collaboration with UNESCAP, has developed a global methodology that defines benchmarks based on the relative performance of a country compared to the top 3 performing countries in its respective region.

Two measures are introduced to gauge the achievements made in SDG-9 Industry:

  • Progress assesses the country’s development since 2000 relative to the advancements needed to achieve the target in 2030
  • Outlook projects the country’s past trend into the future to evaluate its likelihood of achieving the targets in 2030.

For more details on the calculation of benchmarks and countries' Progress and Outlook status, please refer to the methodological note.

Information used

Data on the Progress and Outlook status of 128 economies.

Comments

  • For Least Developed Countries, doubling the share of manufacturing in GDP and total employment from 2015 is defined as the 2030 target for the respective indicators.
  • SDG regions rather than M49 regions are used to calculate the benchmarks and measure country performance.

UNSD National Accounts Main Aggregates Database (December 2019)

The UNSD National Accounts Main Aggregates Database contains national accounts data for over 200 countries and territories since 1970. It is maintained by the Economic Statistics Branch of the United Nations Statistics Division (UNSD). It combines data from UNSD with that from statistical agencies of international organizations and national statistical offices.

For detailed information on the methodology as well as access to the database, please refer to the UNSD website.

Information used

Data on gross domestic product and value added of seven economic sectors for 214 economies (including former territories) between 1990 and 2018 (in current and constant 2015 US dollars).

Comments

  • In this version of the UNSD National Accounts Main Aggregates Database, data on China’s manufacturing value added was unavailable for the years 1990 to 2003/2004 (current/constant prices). Data on China’s manufacturing value added between 1990 and 2003/2004 has been sourced from UNIDO MVA 2020. For access to the latest version of UNIDO MVA, please refer to the UNIDO Statistics Data Portal.

  • The value added in “Mining and utilities” is calculated as a residual of the sector “Mining, Manufacturing, Utilities” after deducting value added under “Manufacturing”.

  • The value added in “Wholesale, retail trade, restaurants and hotels”, “Transport, storage and communication” and “Other Activities” has been combined under “Services”.

  • “U.R. of Tanzania: Mainland” and “Zanzibar”, which are reported separately in the original data, have been merged under “Tanzania” for consistency with other datasets.

  • In some instances, the original data contained duplicate country-year observations at the time of country mergers or separations. To avoid double-counting, the datasets include:

    • Netherlands Antilles - from 1990 to 2009 (replaced by Curaçao and Sint Maarten (Dutch part) from 2010 onwards)

    • Sudan (Former) - from 1990 to 2007 (replaced by Sudan and South Sudan from 2008 onwards)

    • Timor-Leste - included in Indonesia from 1990 to 1998. Reported separately from 1999 onwards.

ILO modelled estimates (November 2019)

The ILO modelled estimates provide internationally comparable labour statistics, including both official data reported by national statistical bodies, as well as imputed data for countries with missing data. The imputations are performed through a series of econometric models maintained by the ILO. This way, the ILO can obtain a balanced panel data set, for which regional and global aggregates with consistent country coverage can be computed for every year.

For more information on the methodology behind the ILO modelled estimates series and access to the data, please refer to the ILO website.

Information used

Data on the number of employees for six economic sectors of 189 economies between 1991 and 2018.

Comments

  • Aggregated sectors have been used to achieve higher consistency, regardless of any changes in the data due to revisions of the ISIC classification. The number of employees in “Trade, Transportation, Accommodation and Food, and Business and Administrative Services” and “Public Administration, Community, Social and other Services and Activities” have been combined under “Services”.

CEPII BACI (March 2020) 

BACI is a trade database developed by the French research institute CEPII (Centre d’Etudes Prospectives et d’Informations Internationales). It provides data on trade flows at a high level of product disaggregation (HS 6-digit) for over 200 countries from 1995 onwards. BACI derives its source data from the United Nations COMTRADE database. CEPII BACI extends country coverage considerably compared with the original data based on elaborate harmonization procedures.

For a detailed description of BACI's methodology, please refer to BACI: International Trade Database at the Product-Level. The 1994-2007 version (Gaulier/Zignago 2010, CEPII Working Paper No. 2010-23)

After registering on the website, access to CEPII BACI is free of charge.

Information used

Data on trade flows for 224 economies (including former territories) between 1995 and 2018.

Trade flows for Belgium, Luxembourg and member states of the Southern African Customs Union (Botswana, Eswatini, Lesotho, Namibia, South Africa) are reported in the aggregates “Belgium-Luxembourg” and “South African Customs Union”.

Comments

  • BACI contains datasets from different versions of the Harmonized System (HS) product classification. To obtain coverage from 1995 to 2018, data classified by HS92 has been selected for further processing.

  • HS92 6-digit codes were translated into ISIC Rev. 3 2-digit industries and Broad Economic Categories (BEC) Rev. 4 with the help of concordance tables from World Integrated Trade Solution (WITS).

  • BEC codes were used to map trade flows to basic classes of goods in the SNA (capital goods, intermediate goods, consumption goods) in accordance with BEC Rev. 4.

  • Trade flows reported under “European Free Trade Association, nes” have been excluded from the dataset.

  • Trade data of some countries includes information from other countries or territories:

    • Trade data for France includes Monaco

    • Trade data for Switzerland includes Liechtenstein

    • Trade data for the United States includes Puerto Rico

  • Trade flows reported under “Other Asia, nes” are labelled “China, Taiwan Province”. While this is expected to be largely correct, some flows to other Asian economies might be incorrectly attributed.

UNIDO INDSTAT 2 2018

UNIDO INDSTAT 2 combines historical time series data on industrial statistics for over 170 countries from 1963 onwards. It provides data for seven principle indicators (number of establishments; employment; wages and salaries; output; value added; gross fixed capital formation and number of female employees) and the index of industrial production. For fully reporting countries, data are available for all 23 industries representing the manufacturing sector at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev. 3.

For detailed information on the methodology and access to the latest version of the database, please refer to the UNIDO Statistics Data Portal (full access to the database is available with subscription only).

Information used

Data on value added, employment and gross output for 17 industries of 78 economies between 1990 and 2018 (value added and gross output in current prices).

Comments

  • 17 ISIC Rev.3 2-digit industry combinations were chosen for consistency purposes, while maintaining a detailed set of industries and relatively high country coverage. Countries that did not provide data on the value added of and employment in these 17 industries for at least one year were excluded from the database, while still including countries that do not produce in certain industries at all.

  • To improve consistency over time, time series were created by linking various procedures. First, a baseline year for which the country provided full data coverage for value added and employment was selected. The time series were then extrapolated forward and backward using the growth rates of the industry-level series of value added and employment. This linking of procedures smoothed breaks in the time series that arise due to changes in classifications and definitions of variables over time (e.g. employment may be reported in terms of persons engaged or in terms of number of employees).
  • Due to the changes in the classification and definitions of variables, growth rates had to be compiled on the basis of one specific definition. Gaps were filled by linear interpolation, higher aggregates of industry classifications and by value added (employment) growth rates if employment (value added) was not available.

  • Gross output was obtained as a ratio to value added. The ratio of output to value added was calculated for any year with data on gross output and value added. The ratio was interpolated or kept constant between the first and last year with available data for the years that had no data on gross output and value added. Subsequently, output was calculated by multiplying the obtained ratio with the final value added series.

OECD Trade in Value Added (TiVA) Database 2018 

The OECD Trade in Value Added (TiVA) Database provides indicators designed to illustrate linkages in global production networks and supply chains for over 60 countries between 2005 and 2015. It contains, among others, data on “Origin of value added in gross exports” calculated from the OECD Inter-Country Input-Output (ICIO) database. With the help of input-output tables, a country’s trade flows can be disaggregated by the source country of the embodied value added.

For indicator definitions, access to the latest version of the database (in ISIC Rev. 4) and a detailed overview of the OECD TiVA methodology, please refer to the OECD website.

Information used

Data on the indicators “Foreign value added in gross exports” and “Domestic value added embodied in gross exports” of 64 economies between 2005 and 2015.

Comments

  • While the other platform data sets use ISIC Rev. 3, OECD TiVA 2018 uses the fourth revision of the classification. An approximated correspondence to ISIC Rev.3 at the 2-digit level was used to align the industry combinations. As the OECD demonstrates, however, the differences between indicators based on ISIC Rev. 3 and ISIC Rev. 4 can be significant in some cases.

Supplementary data sources for country profiles

Population data were taken from UNDESA World Population Prospects 2019.

Score and country ranking for the UNIDO Competitive Industrial Performance Index in the years 2017 and 2018 were derived from the UNIDO Statistics Data Portal.

Score and country rankings for “Ease of Doing Business” in 2020 were obtained from the World Bank’s Doing Business Report 2020.

Score and country rankings in the UNDP Human Development Index for the years 2017 and 2018 were taken from UNDP’s Human Development Report 2019.

Country groupings

Country grouping by geographical region

The country grouping by geographical region is based on the UN M49 classification (as of July 2020). Data for former territories (Netherlands Antilles, Serbia and Montenegro, Sudan (Former)) are classified in accordance with the latest retrievable version of M49, which includes these territories. The grouping for country aggregates reported in trade data from CEPII BACI (South African Customs Union, Belgium-Luxembourg) is clearly defined by the grouping of the individual countries.

A table outlining data coverage and the composition of country groups by geographical region is available for download.

Country grouping by development status

The country grouping by development status is based on UNIDO’s International Yearbook of Industrial Statistics 2020 and on decisions of the United Nations General Assembly (Least Developed Countries). Data for former territories (Netherlands Antilles, Serbia and Montenegro, Sudan (Former)) are classified in accordance with the latest version of UNIDO’s International Yearbook of Industrial Statistics, which includes these territories. China is grouped under “Emerging Industrial Economies”. The grouping for the aggregate “South African Customs Union” reported in CEPII BACI’s trade data is not uniquely defined by individual country groupings. Since “Other Developing Economies” is the most common grouping, data under “South African Customs Union” are allocated to this group for the calculation of aggregates.

A table outlining data coverage and the composition of country groups by development status is available for download.

Industry classifications

While the UNIDO Industrial Analytics Platform’s aim is to report industry-disaggregated data at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev. 3, this is not always possible. Industry-disaggregated data are frequently already reported in industry combinations for practical and analytical reasons. In other cases, the decision to collapse certain industries might be taken at a later stage to arrive at a more consistent dataset (see e.g. UNIDO INDSTAT 2 2020). However, where possible, data is reported at the highest level of disaggregation to preserve the granularity of the original sources.

Classification by technology group

The classification of industries by technology is based on UNIDO’s manual Industrial Statistics. Guidelines and Methodology (pp. 244, see document). It largely reflects the efforts of the OECD to group industries by their R&D intensity (latest version based on ISIC Rev. 4, see here). Rather than differentiating between “Medium-high technology” and “high technology”, the UNIDO classification combines both categories under “Medium-high and high technology (MHT)”. While it is generally acknowledged that such classifications may not fully capture the technology content of a specific industry, they are widely used in the literature.

Within the data explorer, technology groups are labelled as Low tech (L, “Low technology”), Mid tech (M, “Medium-low-technology”) and High tech (H, “Medium-high and high technology (MHT)”).

A table outlining the concordance between the different industry classifications used in the platform datasets and their technology grouping is available for download.

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Citation

When citing or reproducing any data or material from iap.unido.org, please use the following reference:

UNIDO, ‘Industrial Analytics Platform’, https://iap.unido.org/

Contact us

The Industrial Analytics Platform (iap.unido.org) is a UNIDO initiative.

Contact us: iap@unido.org

Disclaimers

UNIDO data represented on the platform have been treated for analytical purposes as documented above and shall by no means be considered official UNIDO records or estimates. For the official statistical products of UNIDO, please refer to stat.unido.org.

The designations employed and the presentation of material on the platform do not imply the expression of any opinion whatsoever on the part of the Secretariat of UNIDO concerning the legal status of any country, territory, city or area, or of its authorities, or concerning the delimitations of its frontiers or boundaries.

Designations such as "industrialized", "emerging" and "developing" are intended for statistical convenience and do not necessarily express a judgement about the state researched by a particular country or area in the development process.

Acknowledgements

  • National accounts indicators are calculated from source data and used with the permission of the United Nations Statistical Division

  • Trade indicators are calculated from source data and used in compliance with the conditions under the Permission for re-dissemination and use of data within applications in the Policy on use and re-dissemination of UN COMTRADE data and with permission from CEPII

  • Employment indicators are calculated from source data by the ILO and used under licence

  • GVC indicators are calculated from source data by the OECD and used under licence

  • Population data is used with permission from UNDESA

  • Data from the World Bank Doing Business project is used under licence

  • UNDP Human Development Index data is used under Creative Commons Attribution 3.0 IGO

  • Site by Applied Works

  • Generously supported and funded by the German Federal Ministry for Economic Cooperation and Development (BMZ)