Employment in industry, male (% of male 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 62.70 2017
2 Angola 52.40 2017
3 Czech Republic 48.30 2017
4 Trinidad and Tobago 47.60 2017
5 Slovak Republic 47.20 2017
6 Oman 43.40 2017
7 Syrian Arab Republic 42.80 2017
8 Poland 41.20 2017
9 Slovenia 40.70 2017
10 Estonia 40.30 2017
11 Hungary 39.60 2017
12 Bahrain 39.50 2017
12 Germany 39.50 2017
14 Venezuela 38.60 2017
15 Bosnia and Herzegovina 38.00 2017
16 Russia 37.50 2017
17 Croatia 37.00 2017
17 Austria 37.00 2017
19 Turkmenistan 36.80 2017
20 South Africa 36.70 2017
20 Italy 36.70 2017
22 Argentina 36.20 2017
22 Kuwait 36.20 2017
24 New Caledonia 36.10 2017
25 Bulgaria 35.60 2017
26 Japan 35.00 2017
27 Romania 34.60 2017
27 Algeria 34.60 2017
29 Finland 34.40 2017
30 Iran 34.10 2017
30 Latvia 34.10 2017
32 Lithuania 33.50 2017
33 Belarus 33.10 2017
34 Guyana 33.00 2017
35 Korea 32.80 2017
35 Malaysia 32.80 2017
37 Portugal 32.50 2017
38 Belgium 32.40 2017
39 Turkey 32.30 2017
40 New Zealand 32.10 2017
41 Australia 32.00 2017
42 Suriname 31.90 2017
43 Macedonia 31.70 2017
43 Norway 31.70 2017
45 Chile 31.00 2017
46 Mauritius 30.50 2017
47 France 30.40 2017
48 Egypt 30.30 2017
48 Mexico 30.30 2017
50 Serbia 30.20 2017
51 China 29.90 2017
52 Bolivia 29.60 2017
53 Canada 29.40 2017
54 Brazil 29.20 2017
55 Barbados 29.10 2017
56 Kazakhstan 29.00 2017
57 Switzerland 28.90 2017
58 Uruguay 28.70 2017
59 Tunisia 28.60 2017
59 Sweden 28.60 2017
61 Spain 28.30 2017
62 Denmark 28.20 2017
63 Senegal 28.00 2017
64 United Kingdom 27.90 2017
64 Malta 27.90 2017
64 Gabon 27.90 2017
67 Kyrgyz Republic 27.70 2017
68 Equatorial Guinea 27.60 2017
68 Moldova 27.60 2017
70 Ukraine 27.50 2017
71 Lebanon 27.40 2017
72 Iceland 27.20 2017
73 Vietnam 27.00 2017
74 Mongolia 26.90 2017
75 Israel 26.80 2017
76 Indonesia 26.50 2017
77 Ireland 26.40 2017
77 India 26.40 2017
79 Macao SAR, China 26.30 2017
80 Sri Lanka 26.20 2017
80 Puerto Rico 26.20 2017
82 Paraguay 26.10 2017
83 Uzbekistan 26.00 2017
83 Panama 26.00 2017
85 Saudi Arabia 25.90 2017
86 United States 25.80 2017
87 St. Lucia 25.70 2017
87 Swaziland 25.70 2017
89 Thailand 25.50 2017
90 Montenegro 25.30 2017
90 Congo 25.30 2017
92 St. Vincent and the Grenadines 25.10 2017
92 Libya 25.10 2017
94 Costa Rica 24.80 2017
95 Cyprus 24.70 2017
96 Ecuador 24.40 2017
96 Brunei 24.40 2017
96 Netherlands 24.40 2017
99 Iraq 24.20 2017
100 The Bahamas 23.80 2017
101 Peru 23.70 2017
101 Albania 23.70 2017
103 United Arab Emirates 23.30 2017
103 Namibia 23.30 2017
105 Armenia 23.20 2017
106 Hong Kong SAR, China 23.00 2017
107 The Gambia 22.60 2017
107 El Salvador 22.60 2017
109 Morocco 22.50 2017
110 Jamaica 22.40 2017
110 Pakistan 22.40 2017
112 Honduras 22.00 2017
113 Azerbaijan 21.90 2017
113 Lesotho 21.90 2017
115 Dominican Republic 21.70 2017
116 Bangladesh 21.30 2017
117 Tajikistan 21.10 2017
118 Singapore 21.00 2017
119 Belize 20.90 2017
119 Colombia 20.90 2017
119 Yemen 20.90 2017
119 Djibouti 20.90 2017
123 Cambodia 20.80 2017
124 Philippines 20.50 2017
125 Greece 20.20 2017
126 Guatemala 19.70 2017
127 Jordan 19.50 2017
128 Botswana 19.30 2017
129 São Tomé and Principe 18.60 2017
130 Cabo Verde 18.00 2017
131 Ghana 17.90 2017
132 Georgia 17.80 2017
133 Samoa 17.70 2017
134 Sudan 17.40 2017
134 Liberia 17.40 2017
136 Nicaragua 17.10 2017
137 Myanmar 17.00 2017
138 Dem. People's Rep. Korea 16.80 2017
139 Haiti 16.60 2017
140 Zambia 15.70 2017
141 Mali 15.50 2017
141 Nepal 15.50 2017
143 Luxembourg 15.20 2017
144 Cuba 14.70 2017
145 Nigeria 14.10 2017
145 Benin 14.10 2017
147 Rwanda 14.00 2017
148 Madagascar 13.90 2017
149 Kenya 13.60 2017
150 Eritrea 13.30 2017
151 Guinea 13.00 2017
152 Mauritania 12.90 2017
153 Tonga 12.40 2017
154 Togo 12.20 2017
155 Zimbabwe 12.10 2017
156 Afghanistan 10.90 2017
157 Cameroon 10.60 2017
157 Sierra Leone 10.60 2017
159 Uganda 10.20 2017
160 Bhutan 10.10 2017
161 Dem. Rep. Congo 9.90 2017
161 Guinea-Bissau 9.90 2017
163 Vanuatu 9.80 2017
164 Niger 9.50 2017
165 Tanzania 9.40 2017
166 Papua New Guinea 9.30 2017
167 Côte d'Ivoire 8.60 2017
168 Malawi 8.50 2017
169 Mozambique 8.40 2017
170 Ethiopia 8.00 2017
171 Central African Republic 7.30 2017
172 Comoros 7.10 2017
173 Burkina Faso 6.60 2017
174 Somalia 6.50 2017
175 Lao PDR 5.70 2017
176 Burundi 4.40 2017
177 Fiji 3.50 2017
178 Chad 3.00 2017
179 Solomon Islands 2.70 2017
180 Timor-Leste 2.30 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.