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 September 2019.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Qatar 54.47 2019
2 Czech Republic 37.67 2019
3 Slovak Republic 36.81 2019
4 Oman 36.19 2019
5 Bahrain 35.24 2019
6 Turkmenistan 33.72 2019
7 Burkina Faso 33.25 2019
8 Slovenia 32.86 2019
9 Tunisia 32.75 2019
10 Iran 31.92 2019
11 Poland 31.34 2019
12 Hungary 31.17 2019
13 Belarus 30.74 2019
14 Algeria 30.69 2019
15 North Macedonia 30.37 2019
16 Uzbekistan 30.36 2019
17 Romania 30.01 2019
18 Bosnia and Herzegovina 29.73 2019
19 Bulgaria 29.69 2019
20 Tonga 29.66 2019
21 Estonia 29.64 2019
22 Syrian Arab Republic 28.84 2019
23 China 28.27 2019
24 Sri Lanka 28.27 2019
25 Trinidad and Tobago 27.35 2019
26 Malaysia 27.22 2019
27 Mauritius 27.07 2019
28 Cambodia 26.98 2019
29 Russia 26.93 2019
30 Germany 26.88 2019
31 Libya 26.59 2019
32 Egypt 26.59 2019
33 Croatia 26.13 2019
34 Turkey 26.12 2019
35 Mexico 25.89 2019
36 Vietnam 25.84 2019
37 Guyana 25.69 2019
38 Italy 25.62 2019
39 Kuwait 25.37 2019
40 Serbia 25.09 2019
41 India 24.89 2019
42 Lithuania 24.86 2019
43 Korea 24.84 2019
44 Suriname 24.74 2019
45 Jordan 24.70 2019
46 Austria 24.47 2019
47 Portugal 24.40 2019
48 Japan 24.38 2019
49 Eswatini 24.38 2019
50 Saudi Arabia 24.37 2019
51 Ukraine 24.22 2019
52 Pakistan 23.67 2019
53 Iraq 23.51 2019
54 Thailand 23.49 2019
55 United Arab Emirates 23.32 2019
56 South Africa 23.18 2019
57 Latvia 23.02 2019
58 Chile 22.75 2019
59 Argentina 22.37 2019
60 Lebanon 22.30 2019
61 Congo 22.23 2019
62 Kyrgyz Republic 22.20 2019
63 St. Lucia 22.13 2019
64 Indonesia 21.98 2019
65 Cabo Verde 21.98 2019
66 New Caledonia 21.96 2019
67 Finland 21.81 2019
68 Bolivia 21.74 2019
69 Morocco 21.62 2019
70 El Salvador 21.57 2019
71 Kazakhstan 21.36 2019
72 Venezuela 21.07 2019
73 Guatemala 20.62 2019
74 Bangladesh 20.53 2019
75 St. Vincent and the Grenadines 20.49 2019
76 Belgium 20.46 2019
77 Brazil 20.40 2019
78 New Zealand 20.40 2019
79 Honduras 20.32 2019
80 France 20.15 2019
80 Switzerland 20.15 2019
82 Paraguay 20.08 2019
83 Uruguay 19.71 2019
84 Spain 19.71 2019
85 Togo 19.71 2019
86 Benin 19.59 2019
87 Canada 19.39 2019
88 Colombia 19.35 2019
89 Dominican Republic 19.34 2019
90 Australia 19.33 2019
91 Albania 19.33 2019
92 Namibia 19.32 2019
93 Malta 19.31 2019
94 Barbados 19.19 2019
95 United States 19.18 2019
96 Norway 19.09 2019
97 Mongolia 18.95 2019
98 Ghana 18.62 2019
99 Panama 18.62 2019
100 Ecuador 18.53 2019
101 Denmark 18.46 2019
102 Philippines 18.39 2019
103 Costa Rica 18.37 2019
104 Ireland 18.27 2019
105 Botswana 18.07 2019
106 United Kingdom 17.97 2019
107 São Tomé and Principe 17.87 2019
108 Sweden 17.81 2019
109 Afghanistan 17.80 2019
110 Macao SAR, China 17.22 2019
111 Israel 17.22 2019
112 Iceland 17.13 2019
113 Montenegro 17.04 2019
114 Puerto Rico 17.03 2019
115 Cyprus 16.95 2019
116 Dem. People's Rep. Korea 16.89 2019
117 Tajikistan 16.80 2019
118 Cuba 16.79 2019
119 Moldova 16.61 2019
120 Nicaragua 16.56 2019
121 Equatorial Guinea 16.52 2019
122 Singapore 16.51 2019
123 Netherlands 16.14 2019
124 The Bahamas 16.09 2019
125 Myanmar 16.05 2019
126 The Gambia 16.04 2019
127 Brunei 16.00 2019
128 Armenia 15.75 2019
129 Jamaica 15.66 2019
130 Peru 15.64 2019
131 Greece 15.27 2019
132 Sudan 14.99 2019
133 Samoa 14.66 2019
134 Belize 14.64 2019
135 Azerbaijan 14.45 2019
136 Cameroon 14.14 2019
137 Comoros 14.12 2019
138 Senegal 13.88 2019
139 Georgia 13.27 2019
140 Nepal 13.15 2019
141 Fiji 13.08 2019
142 Ethiopia 12.57 2019
143 Hong Kong SAR, China 11.74 2019
144 Nigeria 11.55 2019
145 Liberia 11.43 2019
146 Mauritania 11.17 2019
147 Zambia 10.74 2019
148 Dem. Rep. Congo 10.56 2019
149 Yemen 10.50 2019
150 Luxembourg 10.39 2019
151 Haiti 10.24 2019
152 Lesotho 10.11 2019
153 Gabon 9.95 2019
154 Bhutan 9.80 2019
155 Timor-Leste 9.41 2019
156 Central African Republic 9.35 2019
157 Lao PDR 9.15 2019
158 Solomon Islands 9.11 2019
159 Rwanda 9.10 2019
160 Guinea-Bissau 8.83 2019
161 Malawi 8.40 2019
162 Eritrea 8.33 2019
163 Angola 8.29 2019
164 Niger 8.22 2019
165 Djibouti 8.18 2019
166 Mozambique 8.05 2019
167 Kenya 7.67 2019
168 Uganda 7.53 2019
169 Madagascar 7.50 2019
170 Tanzania 7.31 2019
171 Zimbabwe 7.17 2019
172 Guinea 7.05 2019
173 Mali 6.63 2019
174 Vanuatu 6.56 2019
175 Somalia 6.46 2019
176 Côte d'Ivoire 6.22 2019
177 Sierra Leone 5.84 2019
178 Papua New Guinea 5.00 2019
179 Chad 3.10 2019
180 Burundi 2.04 2019

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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