Table 4.3 | Structure of manufacturing
             
  About the data   Definitions   Sources

 

Manufacturing 
value added

     

$ millions

  
1990 2001

Food, beverages and tobacco

     

% of total

1990 2001

Textiles and 
clothing

     

% of total

  
1990 2001

Machinery and transport equipment

 % of total

  
1990 2001

Chemicals
  

     

% of total

  
1990 2001

Other manufacturinga

   

% of total

     
1990 2001
 
 
Afghanistan .. .. .. .. .. .. .. .. .. .. .. ..
Albania .. 389.5 23.6 .. 32.7 .. .. .. .. .. 43.8 ..
Algeria 6,452.3 4,062.7 12.8 .. 17.0 .. .. .. .. .. 70.3 ..
Angola 513.2 359.1 .. .. .. .. .. .. .. .. .. ..
Argentina 37,867.9 43,242.0 19.6 27.8 10.4 6.0 12.8 11.7 11.7 .. 45.5 54.4
Armenia 680.5 425.9 .. .. .. .. .. .. .. .. .. ..
Australia 38,866.6 39,663.8 18.0 .. 6.1 .. 20.2 .. 7.3 .. 48.5 ..
Austria 33,385.5 37,015.4 14.6 7.0 6.8 2.6 28.3 30.7 7.5 4.0 42.8 55.8
Azerbaijan 1,561.3 371.7 .. .. .. .. .. .. .. .. .. ..
Bangladesh 3,839.4 7,087.0 23.9 22.4 37.5 33.1 7.0 15.7 17.0 9.9 14.5 18.9
Belarus 6,630.1 3,300.2 .. .. .. .. .. .. .. .. .. ..
Belgium .. 39,291.2 16.9 18.6 7.3 6.2 .. .. 13.4 16.5 62.4 58.7
Benin 144.6 217.9 .. .. .. .. .. .. .. .. .. ..
Bolivia 825.7 1,060.0 27.7 30.7 5.3 4.5 0.9 1.1 2.8 3.2 63.3 60.5
Bosnia and Herzegovina .. 513.6 11.8 .. 14.7 .. 17.7 .. 7.3 .. 48.5 ..
Botswana 180.8 235.2 51.2 20.4 12.3 5.1 .. .. .. .. 36.5 74.5
Brazil 89,965.5 63,247.2 13.6 .. 12.2 .. 26.6 .. .. .. 47.5 ..
Bulgaria .. 2,107.8 21.9 .. 8.9 .. 18.6 .. 5.2 .. 45.4 ..
Burkina Faso 459.7 330.8 .. .. .. .. .. .. .. .. .. ..
Burundi 133.8 59.8 82.7 .. 8.8 .. .. .. 1.7 .. 6.9 ..
Cambodia 58.5 651.5 .. .. .. .. .. .. .. .. .. ..
Cameroon 1,580.9 909.3 60.8 47.5 -12.8 15.3 1.4 1.5 4.6 4.0 46.0 31.7
Canada 91,671.2 130,612.8 14.8 13.3 5.6 3.8 26.0 31.5 9.9 8.2 43.7 43.3
Central African Republic 154.2 81.3 57.5 .. 6.4 .. 2.0 .. 6.4 .. 27.7 ..
Chad 238.6 243.8 .. .. .. .. .. .. .. .. .. ..
Chile 5,613.4 9,279.8 25.3 31.5 7.5 3.9 5.1 5.0 9.9 14.2 52.2 45.4
China 116,572.9 407,513.6 14.5 15.2 14.8 12.0 23.8 32.4 13.1 12.4 33.8 28.1
Hong Kong, China 12,639.3 8,144.8 8.2 9.0 36.0 18.8 21.3 30.2 1.8 3.6 32.7 38.3
Colombia 8,034.3 11,633.8 30.5 33.5 15.3 9.4 9.2 5.2 14.2 16.9 30.8 35.0
Congo, Dem. Rep. 1,028.8 200.4 .. .. .. .. .. .. .. .. .. ..
Congo, Rep. 233.6 123.6 .. .. .. .. .. .. .. .. .. ..
Costa Rica 1,106.9 3,242.9 47.1 47.5 8.0 5.6 6.5 5.5 8.6 10.6 29.7 30.9
Côte d'Ivoire 2,256.8 1,524.7 .. 42.0 .. 10.1 .. 3.0 .. 12.0 .. 32.9
Croatia 6,475.0 3,475.2 21.9 .. 14.5 .. 19.8 .. 7.8 .. 36.0 ..
Cuba .. .. .. .. .. .. .. .. .. .. .. ..
Czech Republic .. 15,333.8 .. .. .. .. .. .. .. .. .. ..
Denmark 20,756.7 22,164.8 21.9 .. 4.2 .. 23.9 .. 11.5 .. 38.5 ..
Dominican Republic 1,270.4 3,475.4 .. .. .. .. .. .. .. .. .. ..
Ecuador 1,987.7 2,466.2 22.0 38.2 9.5 6.0 4.8 2.6 7.8 4.0 56.0 50.0
Egypt, Arab Rep. 7,295.6 17,726.7 18.8 .. 15.5 .. 9.0 .. 13.8 .. 42.9 ..
El Salvador 1,043.9 3,161.7 35.6 29.2 14.3 28.2 3.8 3.1 23.8 16.1 22.5 23.5
Eritrea 35.2 67.3 .. .. .. .. .. .. .. .. .. ..
Estonia 1,985.2 923.3 .. .. .. .. .. .. .. .. .. ..
Ethiopia 624.3 .. 61.6 55.0 21.0 12.3 1.1 4.2 2.4 4.7 14.0 23.7
Finland 27,530.7 26,503.8 12.7 1.1 3.5 5.7 24.4 .. 7.7 3.1 51.7 90.2
France 228,270.2 217,534.7 12.8 .. 6.3 .. 30.9 .. 9.1 .. 40.9 ..
Gabon 332.4 211.2 44.7 .. 2.1 .. 1.2 .. 6.8 .. 45.2 ..
Gambia, The 17.5 19.4 .. .. .. .. .. .. .. .. .. ..
Georgia 1,773.0 535.9 .. .. .. .. .. .. .. .. .. ..
Germany 456,405.4 385,923.9 .. 8.1 .. 2.3 .. 41.3 .. 9.9 .. 38.3
Ghana 574.6 478.0 .. .. .. .. .. .. .. .. .. ..
Greece .. 12,646.1 22.4 24.9 19.5 12.5 11.8 14.2 9.8 9.8 36.4 38.6
Guatemala 1,151.4 2,727.5 .. .. .. .. .. .. .. .. .. ..
Guinea 126.1 119.6 .. .. .. .. .. .. .. .. .. ..
Guinea-Bissau 19.2 19.7 .. .. .. .. .. .. .. .. .. ..
Haiti .. 272.0 50.9 .. 9.1 .. .. .. .. .. 40.0 ..
Honduras 443.3 1,133.5 45.4 .. 10.3 .. 3.1 .. 5.5 .. 35.6 ..
Hungary 6,612.9 10,371.6 13.5 14.9 9.2 6.0 26.0 36.7 12.0 10.1 39.3 32.2
India 48,807.9 67,143.5 11.7 13.2 15.2 12.6 25.5 19.1 13.9 21.1 33.7 34.0
Indonesia 23,642.7 36,343.4 27.5 22.3 14.6 13.4 11.8 22.6 8.9 11.7 37.2 29.9
Iran, Islamic Rep. 14,502.9 15,008.9 12.2 9.6 20.0 6.0 19.6 22.6 8.0 18.8 40.3 43.0
Iraq .. .. 19.9 .. 15.6 .. 4.4 .. 11.2 .. 48.8 ..
Ireland 11,981.6 28,969.5 26.8 15.9 4.0 0.9 29.2 30.8 16.5 36.1 23.5 16.3
Israel .. .. 13.7 9.5 8.9 4.7 31.6 33.2 9.0 2.2 36.8 50.5
Italy 247,917.1 203,247.7 8.4 8.6 12.9 12.5 34.5 27.2 6.8 7.9 37.4 43.8
Jamaica 853.4 1,049.0 41.4 .. 5.0 .. .. .. .. .. 53.5 ..
Japan 810,231.9 865,809.7 8.9 12.0 4.7 2.9 39.9 37.7 9.5 10.8 37.0 36.5
Jordan 520.3 1,176.0 27.8 29.6 6.7 7.2 3.7 4.5 14.8 17.6 46.9 41.1
Kazakhstan 1,941.3 3,629.5 .. .. .. .. .. .. .. .. .. ..
Kenya 863.6 1,234.3 38.5 48.3 9.6 7.6 9.6 8.6 9.2 7.8 33.2 27.7
Korea, Dem. Rep. .. .. .. .. .. .. .. .. .. .. .. ..
Korea, Rep. 64,604.4 117,575.8 10.7 8.1 11.9 7.8 32.2 45.0 9.1 9.5 36.0 29.6
Kuwait 2,142.4 .. 4.1 6.9 3.2 3.9 2.2 3.7 2.7 2.2 87.8 83.3
Kyrgyz Republic 706.4 148.4 .. .. .. .. .. .. .. .. .. ..
Lao PDR 85.5 309.6 .. .. .. .. .. .. .. .. .. ..
Latvia 2,474.2 1,009.1 .. 26.6 .. 11.3 .. 9.5 .. 3.5 .. 49.1
Lebanon .. 1,571.8 .. .. .. .. .. .. .. .. .. ..
Lesotho 70.5 122.5 .. .. .. .. .. .. .. .. .. ..
Liberia .. 34.0 .. .. .. .. .. .. .. .. .. ..
Libya .. .. .. .. .. .. .. .. .. .. .. ..
Lithuania 2,164.0 2,191.9 .. .. .. .. .. .. .. .. .. ..
Macedonia, FYR 1,410.5 581.8 20.1 .. 26.4 .. 13.6 .. 8.9 .. 30.9 ..
Madagascar 313.6 519.5 .. .. .. .. .. .. .. .. .. ..
Malawi 313.1 177.4 37.7 43.7 10.4 7.8 1.4 4.5 17.6 15.6 32.9 28.4
Malaysia 10,664.7 26,772.4 13.2 8.0 6.5 4.1 30.7 41.4 10.8 7.9 38.8 38.6
Mali 200.4 75.0 .. .. .. .. .. .. .. .. .. ..
Mauritania 94.0 80.8 .. .. .. .. .. .. .. .. .. ..
Mauritius 491.5 933.3 30.4 30.6 45.7 47.6 2.4 2.0 4.2 4.5 17.4 15.3
Mexico 49,992.3 110,381.6 21.6 25.4 4.8 3.9 24.2 27.1 17.6 15.4 31.8 28.3
Moldova .. 234.5 .. .. .. .. .. .. .. .. .. ..
Mongolia .. 61.0 33.0 .. 37.4 .. 0.8 .. 1.4 .. 27.4 ..
Morocco 4,753.5 5,739.1 21.9 35.6 17.3 16.5 7.7 8.0 12.2 13.4 40.9 26.6
Mozambique 230.1 475.9 .. .. .. .. .. .. .. .. .. ..
Myanmar .. .. .. .. .. .. .. .. .. .. .. ..
Namibia 291.8 302.5 .. .. .. .. .. .. .. .. .. ..
Nepal 208.9 482.9 37.2 .. 31.0 .. 1.3 .. 5.0 .. 25.5 ..
Netherlands 52,329.7 53,769.1 20.8 0.8 3.1 4.6 25.1 .. 16.5 .. 34.6 94.6
New Zealand 7,574.3 8,185.9 28.0 .. 7.6 .. 13.3 .. 6.6 .. 44.4 ..
Nicaragua 170.1 582.2 .. .. .. .. .. .. .. .. .. ..
Niger 163.4 127.7 37.3 19.8 29.2 9.1 .. .. .. .. 33.5 71.1
Nigeria 1,561.8 1,810.6 15.2 .. 46.1 .. 13.0 .. 4.1 .. 21.6 ..
Norway 13,450.5 16,473.2 18.1 17.5 2.0 1.5 24.9 24.3 8.9 7.5 46.0 49.2
Oman 396.4 .. .. 8.6 .. 2.2 .. 2.9 .. 2.7 .. 83.6
Pakistan 6,184.3 10,445.0 23.9 .. 27.5 .. 9.1 .. 15.0 .. 24.6 ..
Panama 502.2 1,033.8 50.9 58.1 8.1 5.5 1.6 .. 8.3 6.9 31.1 29.5
Papua New Guinea 288.9 253.7 .. .. .. .. .. .. .. .. .. ..
Paraguay 883.3 964.2 55.5 .. 15.7 .. .. .. .. .. 28.8 ..
Peru 3,926.5 7,762.1 22.8 .. 11.4 .. 7.8 .. 9.0 .. 49.0 ..
Philippines 11,007.6 16,308.2 38.9 33.0 10.7 9.5 12.6 15.4 11.8 12.9 26.0 29.2
Poland .. 28,824.6 20.9 6.1 8.8 14.2 25.5 8.0 7.4 .. 37.3 71.7
Portugal 13,630.2 17,331.8 14.9 12.6 21.4 18.1 13.0 19.0 6.1 5.4 44.6 44.9
Puerto Rico 12,125.8 27,099.0 16.2 7.8 5.3 2.4 17.7 17.7 44.3 60.5 16.5 11.6
Romania 9,151.8 6,063.7 19.2 .. 18.3 .. 13.6 .. 3.9 .. 44.9 ..
Russian Federation .. .. .. 19.4 .. 2.3 .. 23.5 .. 5.3 .. 49.5
Rwanda 473.1 199.5 .. .. .. .. .. .. .. .. .. ..
Saudi Arabia 10,049.4 18,479.6 .. .. .. .. .. .. .. .. .. ..
Senegal 747.4 600.8 60.3 43.8 3.0 5.2 5.2 3.4 8.7 26.2 22.7 21.4
Serbia and Montenegro .. .. .. 33.0 .. 8.3 .. 13.8 .. 10.1 .. 34.9
Sierra Leone 31.1 33.8 .. .. .. .. .. .. .. .. .. ..
Singapore .. 20,399.3 4.4 2.8 3.2 0.8 53.1 59.2 9.9 16.5 29.3 20.8
Slovak Republic .. 4,631.5 .. 9.4 .. 6.9 .. 18.8 .. 5.3 .. 59.6
Slovenia 5,190.5 4,692.9 11.7 10.3 15.1 10.1 16.1 14.2 9.4 10.7 47.6 54.7
Somalia 40.6 .. .. .. .. .. .. .. .. .. .. ..
South Africa 24,043.4 19,320.2 14.5 10.8 8.4 3.7 17.7 17.2 9.4 9.8 50.0 58.4
Spain .. 96,059.1 17.9 14.0 7.9 6.7 25.1 22.9 10.3 9.6 38.7 47.0
Sri Lanka 1,076.5 2,219.7 50.6 38.6 24.3 31.3 4.0 5.6 4.2 3.8 17.0 20.7
Sudan .. 1,360.8 .. .. .. .. .. .. .. .. .. ..
Swaziland 250.2 324.5 69.4 .. 7.7 .. 0.9 .. 0.0 .. 22.1 ..
Sweden .. 40,381.3 10.2 7.3 1.7 1.0 32.5 38.9 8.8 11.2 46.8 41.7
Switzerland .. .. 9.6 9.3 3.8 3.2 34.1 27.1 .. .. 52.5 60.3
Syrian Arab Republic 2,508.0 4,862.5 35.0 27.3 28.8 23.8 .. .. .. .. 36.2 48.9
Tajikistan 653.4 250.2 .. .. .. .. .. .. .. .. .. ..
Tanzaniab 361.3 644.3 51.2 45.1 2.8 0.1 6.5 4.8 11.0 7.1 28.5 42.9
Thailand 23,216.8 38,619.2 23.7 .. 29.7 .. 19.1 .. 1.6 .. 25.9 ..
Togo 161.7 118.0 .. .. .. .. .. .. .. .. .. ..
Trinidad and Tobago 680.7 653.7 30.5 .. 2.7 .. 3.3 .. 19.4 .. 44.2 ..
Tunisia 2,075.5 3,692.5 18.6 16.0 20.3 34.0 5.3 9.9 4.1 8.9 51.8 31.1
Turkey 26,881.5 19,686.1 16.0 3.3 14.9 0.5 16.1 .. 9.9 .. 43.1 96.2
Turkmenistan .. 491.1 .. .. .. .. .. .. .. .. .. ..
Uganda 229.9 497.4 .. .. .. .. .. .. .. .. .. ..
Ukraine 32,977.4 6,625.3 .. .. .. .. .. .. .. .. .. ..
United Arab Emirates 2,642.6 .. .. .. .. .. .. .. .. .. .. ..
United Kingdom 206,718.7 220,429.0 13.4 .. 5.3 .. 31.9 .. 11.4 .. 38.0 ..
United States 1,040,600.0 1,422,999.9 12.4 .. 4.9 .. 31.1 .. 11.7 .. 39.9 ..
Uruguay 2,597.0 3,024.5 31.3 37.5 18.2 12.3 9.3 3.3 9.6 7.9 31.6 39.0
Uzbekistan .. 890.4 .. .. .. .. .. .. .. .. .. ..
Venezuela, RB 7,152.0 11,479.8 17.0 22.0 4.8 2.4 5.1 10.4 9.1 11.0 64.1 75.6
Vietnam 793.2 6,465.9 .. .. .. .. .. .. .. .. .. ..
West Bank and Gaza .. 488.9 .. .. .. .. .. .. .. .. .. ..
Yemen, Rep. 448.9 503.1 .. .. .. .. .. .. .. .. .. ..
Zambia 1,047.6 358.1 44.1 .. 11.5 .. 7.2 .. 8.6 .. 28.7 ..
Zimbabwe 1,799.3 1,115.4 27.6 .. 19.3 .. 9.5 .. 5.7 .. 37.9 ..
World 4,412,837.7t 5,404,373.8t
Low income 84,536.2 113,823.9
Middle income 634,890.4 1,099,974.3
Lower middle income 464,789.0 799,636.6
Upper middle income 174,698.5 300,541.9
Low & middle income 725,615.8 1,213,957.1
East Asia & Pacific 187,470.2 536,083.3
Europe & Central Asia .. ..
Latin America & Carib. 204,582.2 285,233.3
Middle East & N. Africa 47,257.6 80,631.8
South Asia 60,476.2 87,909.2
Sub-Saharan Africa 43,345.1 36,630.2
High income 3,673,504.4 4,192,708.1
Europe EMU 1,216,519.1 1,120,403.7

a. Includes unallocated data.
b. Data cover mainland Tanzania only.

          
 About the data
   

The data on the distribution of manufacturing value added by industry are provided by the United Nations Industrial Development Organization (UNIDO). UNIDO obtains data on manufacturing value added from a variety of national and international sources, including the United Nations Statistics Division, the World Bank, the Organisation for Economic Co-operation and Development, and the International Monetary Fund. To improve comparability over time and across countries, UNIDO supplements these data with information from industrial censuses, statistics supplied by national and international organizations, unpublished data that it collects in the field, and estimates by the UNIDO Secretariat. Nevertheless, coverage may be less than complete, particularly for the informal sector. To the extent that direct information on inputs and outputs is not available, estimates may be used, which may result in errors in industry totals. Moreover, countries use different reference periods (calendar or fiscal year) and valuation methods (basic, producer, or purchaser prices) to estimate value added. (See also About the data for table 4.2.)

   The data on manufacturing value added in U.S. dollars are from the World Bank’s national accounts files. These figures may differ from those used by UNIDO to calculate the shares of value added by industry, in part because of differences in exchange rates. Thus estimates of value added in a particular industry calculated by applying the shares to total manufacturing value added will not match those from UNIDO sources.

 
4.3a
Manufacturing continues to show strong growth in East Asia

 

The classification of manufacturing industries in the table accords with the United Nations International Standard Industrial Classification (ISIC) revision 2. First published in 1948, the ISIC has its roots in the work of the League of Nations Committee of Statistical Experts. The committee’s efforts, interrupted by the Second World War, were taken up by the United Nations Statistical Commission, which at its first session appointed a committee on industrial classification. The latest revision, ISIC revision 3, was completed in 1989, and many countries have now switched to it. But revision 2 is still widely used for compiling cross-country data. Concordances matching ISIC categories to national systems of classification and to related systems such as the Standard International Trade Classification (SITC) are readily available.

   In establishing a classification system, compilers must define both the types of activities to be described and the organizational units whose activities are to be reported. There are many possibilities, and the choices made affect how the resulting statistics can be interpreted and how useful they are in analyzing economic behavior. The ISIC emphasizes commonalities in the production process and is explicitly not intended to measure outputs (for which there is a newly developed Central Product Classification). Nevertheless, the ISIC views an activity as defined by “a process resulting in a homogeneous set of products” (United Nations 1990 [ISIC, series M, no. 4, rev. 3], p. 9).

   Firms typically use a multitude of processes to produce a final product. For example, an automobile manufacturer engages in forging, welding, and painting as well as advertising, accounting, and many other service activities. In some cases the processes may be carried out by different technical units within the larger enterprise, but collecting data at such a detailed level is not practical. Nor would it be useful to record production data at the very highest level of a large, multiplant, multiproduct firm. The ISIC has therefore adopted as the definition of an establishment “an enterprise or part of an enterprise which independently engages in one, or predominantly one, kind of economic activity at or from one location...for which data are available...” (United Nations 1990, p. 25). By design, this definition matches the reporting unit required for the production accounts of the UN System of National Accounts.

   

   
 Definitions
   

• Manufacturing value added is the sum of gross output less the value of intermediate inputs used in production for industries classified in ISIC major division 3. • Food, beverages, and tobacco correspond to ISIC division 31. • Textiles and clothing correspond to ISIC division 32. • Machinery and transport equipment correspond to ISIC groups 382–84. • Chemicals correspond to ISIC groups 351 and 352. • Other manufacturing covers wood and related products (ISIC division 33), paper and related products (ISIC division 34), petroleum and related products (ISIC groups 353–56), basic metals and mineral products (ISIC divisions 36 and 37), fabricated metal products and professional goods (ISIC groups 381 and 385), and other industries (ISIC group 390). When data for textiles and clothing, machinery and transport equipment, or chemicals are shown in the table as not available, they are included in “other manufacturing.”

   

   
 Data sources
 

The data on value added in manufacturing in U.S. dollars are from the World Bank’s national accounts files. The data used to calculate shares of value added by industry are provided to the World Bank in electronic files by UNIDO. The most recent published source is UNIDO’s International Yearbook of Industrial Statistics 2004. The ISIC system is described in the United Nations’ International Standard Industrial Classification of All Economic Activities, Third Revision (1990). The discussion of the ISIC draws on Jacob Ryten’s paper “Fifty Years of ISIC: Historical Origins and Future Perspectives” (1998).