Employment in industry (% of total employment) (modeled ILO estimate) - Country Ranking

Definition: Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).

Source: International Labour Organization, ILOSTAT database. Data retrieved in November 2017.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Qatar 54.10 2017
2 Oman 39.60 2017
3 Syrian Arab Republic 39.20 2017
4 Angola 37.60 2017
5 Turkmenistan 37.40 2017
6 Czech Republic 37.00 2017
7 Algeria 34.50 2017
7 Slovak Republic 34.50 2017
9 Bahrain 33.40 2017
10 Iran 32.50 2017
11 Belarus 32.00 2017
12 Trinidad and Tobago 31.60 2017
13 Moldova 30.90 2017
14 Bosnia and Herzegovina 30.40 2017
15 Hungary 29.80 2017
16 Poland 29.60 2017
16 Slovenia 29.60 2017
18 Bulgaria 29.40 2017
18 Tunisia 29.40 2017
20 Macedonia 29.20 2017
21 Estonia 29.00 2017
22 Tonga 28.20 2017
23 Romania 27.70 2017
24 Germany 27.50 2017
24 Turkey 27.50 2017
26 Kuwait 27.30 2017
26 Malaysia 27.30 2017
28 Russia 27.10 2017
28 Italy 27.10 2017
30 New Caledonia 26.90 2017
31 Venezuela 26.80 2017
31 Croatia 26.80 2017
33 Japan 26.50 2017
34 South Africa 26.20 2017
35 Sri Lanka 25.90 2017
36 Congo 25.80 2017
37 Austria 25.60 2017
38 Guyana 25.40 2017
39 Egypt 25.30 2017
40 Mexico 25.20 2017
40 Mauritius 25.20 2017
42 Libya 25.10 2017
43 Argentina 24.80 2017
44 Korea 24.70 2017
45 Ukraine 24.60 2017
46 Serbia 24.50 2017
46 Lithuania 24.50 2017
46 India 24.50 2017
49 Djibouti 23.90 2017
49 Uzbekistan 23.90 2017
49 China 23.90 2017
52 Portugal 23.80 2017
53 Latvia 23.00 2017
54 Vietnam 22.90 2017
54 Chile 22.90 2017
56 Saudi Arabia 22.70 2017
56 Thailand 22.70 2017
58 Indonesia 22.40 2017
58 Lebanon 22.40 2017
60 Suriname 22.30 2017
61 Finland 22.00 2017
62 Honduras 21.60 2017
63 Brazil 21.50 2017
64 New Zealand 21.40 2017
65 Australia 21.20 2017
65 Belgium 21.20 2017
67 United Arab Emirates 21.10 2017
67 Bolivia 21.10 2017
69 Iraq 21.00 2017
69 Kyrgyz Republic 21.00 2017
71 Malta 20.90 2017
72 Senegal 20.70 2017
72 Morocco 20.70 2017
72 Mongolia 20.70 2017
75 France 20.50 2017
75 Uruguay 20.50 2017
77 Switzerland 20.40 2017
77 Kazakhstan 20.40 2017
77 Sudan 20.40 2017
80 El Salvador 20.20 2017
80 Norway 20.20 2017
82 Lesotho 20.00 2017
83 Pakistan 19.80 2017
84 Panama 19.60 2017
84 Cambodia 19.60 2017
86 Canada 19.50 2017
86 Paraguay 19.50 2017
88 Brunei 19.40 2017
89 Barbados 19.30 2017
89 Dem. People's Rep. Korea 19.30 2017
91 Spain 19.20 2017
91 Ecuador 19.20 2017
91 Denmark 19.20 2017
94 Costa Rica 19.10 2017
94 Gabon 19.10 2017
94 Bangladesh 19.10 2017
97 Guatemala 18.50 2017
98 United Kingdom 18.40 2017
99 Albania 18.30 2017
100 Sweden 18.20 2017
101 Equatorial Guinea 18.00 2017
102 Israel 17.90 2017
102 Yemen 17.90 2017
104 Jordan 17.80 2017
105 Ireland 17.70 2017
105 Iceland 17.70 2017
105 Macao SAR, China 17.70 2017
108 St. Lucia 17.60 2017
109 Puerto Rico 17.50 2017
110 Montenegro 17.30 2017
110 Peru 17.30 2017
112 United States 17.20 2017
113 Singapore 17.00 2017
113 Swaziland 17.00 2017
115 Dominican Republic 16.90 2017
116 Cyprus 16.70 2017
117 Colombia 16.60 2017
118 Philippines 16.30 2017
119 St. Vincent and the Grenadines 16.10 2017
120 Netherlands 15.90 2017
120 Belize 15.90 2017
122 Armenia 15.70 2017
123 Jamaica 15.30 2017
124 Greece 15.00 2017
125 Botswana 14.90 2017
125 Hong Kong SAR, China 14.90 2017
127 Samoa 14.80 2017
128 Nigeria 14.70 2017
128 Mali 14.70 2017
130 Myanmar 14.60 2017
130 Namibia 14.60 2017
132 Nicaragua 14.50 2017
133 Niger 14.40 2017
133 The Gambia 14.40 2017
135 Ghana 14.20 2017
135 Azerbaijan 14.20 2017
135 The Bahamas 14.20 2017
138 São Tomé and Principe 13.50 2017
139 Tajikistan 13.40 2017
140 Haiti 12.60 2017
141 Liberia 11.70 2017
141 Cuba 11.70 2017
143 Cabo Verde 11.50 2017
144 Georgia 11.20 2017
145 Nepal 10.90 2017
146 Luxembourg 10.20 2017
146 Benin 10.20 2017
148 Afghanistan 10.00 2017
149 Zambia 9.90 2017
150 Bhutan 9.70 2017
151 Mauritania 9.50 2017
152 Madagascar 9.40 2017
153 Cameroon 8.70 2017
153 Togo 8.70 2017
155 Kenya 8.60 2017
156 Ethiopia 8.40 2017
157 Eritrea 7.60 2017
158 Uganda 7.40 2017
158 Guinea 7.40 2017
160 Zimbabwe 7.30 2017
161 Rwanda 7.20 2017
162 Vanuatu 6.80 2017
163 Sierra Leone 6.50 2017
164 Tanzania 6.40 2017
165 Dem. Rep. Congo 5.90 2017
166 Guinea-Bissau 5.80 2017
167 Papua New Guinea 5.70 2017
167 Côte d'Ivoire 5.70 2017
169 Comoros 5.20 2017
170 Burkina Faso 4.90 2017
171 Malawi 4.80 2017
171 Somalia 4.80 2017
173 Central African Republic 4.30 2017
174 Mozambique 4.10 2017
175 Lao PDR 4.00 2017
176 Fiji 2.90 2017
177 Burundi 2.60 2017
178 Solomon Islands 2.40 2017
179 Timor-Leste 2.00 2017
179 Chad 2.00 2017

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Development Relevance: Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment. Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries.

Limitations and Exceptions: There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source. Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries. The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data.

Statistical Concept and Methodology: The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity. The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available.

Aggregation method: Weighted average

Periodicity: Annual

General Comments: Data up to 2016 are estimates while data from 2017 are projections.