What is manufacturing value added?
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Manufacturing value added (MVA) of an economy is the total estimate of net-output of all resident manufacturing activity units obtained by adding up outputs and subtracting intermediate inputs. Measurement of MVA requires appropriate demarcation of the type of economic activity and of the territory in which the activity takes place. The boundary of manufacturing as an economic activity is defined by the https://stat.unido.org/content/learning-center/international-standard-industrial-classification-of-all-economic-activities-%2528isic%2529International Standard Industrial Classification of All Economic Activities (ISIC). 

Revision 4 is the latest version of ISIC, which is being progressively introduced in national statistical systems around the world. There are regional (such as NACE in Europe and NAICS in North America) and national versions of ISIC which are largely compatible with ISIC. For more details see the ISIC Rev. 4 pages at the UNSD web site.

In terms of territory, UNIDO Statistics uses the national account concept of resident units. Data are compiled for an economy rather than a country within its political boundary. Many territories function as a separate economy, occasionally with a different currency from that of the country they belong to in terms of political and administrative sovereignty.

UNIDO produces value added estimates of manufacturing activities at two levels – the sector level (often termed industry value added) and the aggregated level, referred to in this paper as manufacturing value added:

  1. The value added of a manufacturing industry (industry value added) is a survey concept that refers to the given industry’s net output derived from the difference of gross output and  intermediate consumption. Value added is calculated without deducing consumption of fixed assets represented by depreciation in economic accounting concepts. The social cost of  producing value added is higher than that considered in the existing statistical practice, as it takes the depletion and degradation of natural resources into account. Depending on the  survey method selected, industry value added may often refer to census value added which disregards the margin between the receipt from and payment for non-industrial services. Survey  data on industry value added may also disregard the contribution of small and household-based manufacturing units which are often excluded from the regular industrial survey programme.  Estimates for such units are made separately for the compilation of national accounts. For these reasons, industry value added is used to measure the growth and structure, but not the level. 

    The UNIDO Industrial Statistics database presents industry value added at the 2-, 3- and 4-digit level of ISIC. This is the lowest possible industry group level which is, in many cases, almost equivalent to the product group. For example, at the 4-digit level of ISIC Revision 4, data are presented for 151 manufacturing industry groups. Detailed description of UNIDO’s databases INDSTAT2 and INDSTAT4 are provided on the statistics-related pages of UNIDO’s website.

  2. The value added of the entire manufacturing sector is, theoretically, the sum of the value added of all manufacturing activities. However, in practice, MVA cannot simply be derived by adding up all industry value added figures because of the complexity associated with survey methods. Industry value added may not cover all activity units engaged in  manufacturing due to the incomplete frame used in the survey. On the other hand, activity units are often classified as manufacturing based on their primary activity. This implies that secondary activity can often be of a non-manufacturing nature. Such discrepancies are resolved in the process of compiling national accounts using supply use or input-output tables. Thus, MVA measures an exclusive and exhaustive contribution of manufacturing to GDP.

Statistics from INDSTAT databases are widely used to conduct analyses on structural change and demand supply balances. This paper analyses MVA as a measure of industrialization. Data for this purpose are taken from UNIDO’s MVA database.

While GDP provides an important point of reference for analysis of a country’s overall economic development, it does not reveal any specific information about sectoral composition and, in particular, the different degrees of industrial development. Countries show profound structural differences which tend to relate to their stage of overall economic development and the difference contribution of the various sectors (agriculture, industry – and manufacturing as part of it – and services) their economic system is composed of. To capture the different levels of countries’ industrial development, UNIDO generally uses MVA per capita as the main indicator. In most cases, MVA per capita is used, i.e. a relative value of net manufacturing output to the population size, to measure a country’s level of industrialization. Highly service-oriented offshore economies, who have achieved relatively high levels of overall income with a marginal contribution of manufacturing, are an exception. 


Statistical usage
One of the statistical uses of MVA per capita is classifying country groups according to the stage of industrial development. While there is a common standard for country classifications  by geographical region, international agencies apply their own country groups that reflect their primary mandate in international development. The World Bank presents data based on  gross national income per capita, i.e. three major income categories: low, middle and high-income countries. These categories are based on the Bank's operational lending categories.  The United Nation’s Human Development Report (HDR) uses four country groups based on the human development index. The basic principle of UNIDO’s country classification is to  differentiate countries based on their stage of industrial development.

See MVA in use in UNIDO's Industrial Development Report 2016.

Read more about MVA here.


Relevant databases
MVA 2016 Database

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