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 September 2019.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Qatar 61.18 2019
2 Slovak Republic 49.20 2019
3 Czech Republic 48.20 2019
4 Slovenia 45.68 2019
5 Poland 43.87 2019
6 Turkmenistan 42.32 2019
7 Hungary 42.19 2019
8 Belarus 41.84 2019
9 Bahrain 41.67 2019
10 Bosnia and Herzegovina 40.74 2019
11 United Arab Emirates 40.06 2019
12 Estonia 39.42 2019
13 Germany 38.74 2019
14 Croatia 37.56 2019
15 Russia 37.53 2019
16 Trinidad and Tobago 37.19 2019
17 Austria 37.16 2019
18 Romania 37.05 2019
19 Bulgaria 36.75 2019
20 Armenia 35.85 2019
21 Oman 35.79 2019
22 Latvia 35.72 2019
23 New Caledonia 35.49 2019
24 Italy 35.19 2019
25 Lithuania 35.05 2019
26 Ukraine 34.81 2019
27 North Macedonia 34.24 2019
28 Serbia 34.13 2019
29 Suriname 33.92 2019
30 Portugal 33.88 2019
31 Tunisia 33.74 2019
32 Finland 33.63 2019
33 Guyana 33.58 2019
34 Korea 33.16 2019
35 Iran 32.42 2019
36 Japan 32.36 2019
37 Egypt 31.93 2019
38 Algeria 31.71 2019
39 Kyrgyz Republic 31.68 2019
40 Belgium 31.60 2019
41 Malaysia 31.32 2019
42 Vietnam 31.26 2019
43 Argentina 31.20 2019
44 Chile 30.97 2019
45 China 30.83 2019
46 Mexico 30.70 2019
47 Norway 30.61 2019
48 France 30.52 2019
49 South Africa 30.44 2019
50 Cabo Verde 30.10 2019
51 Turkey 29.76 2019
52 St. Vincent and the Grenadines 29.55 2019
53 Spain 29.53 2019
54 Cambodia 29.43 2019
55 Kazakhstan 29.34 2019
56 United States 29.33 2019
57 Switzerland 29.25 2019
58 Australia 29.17 2019
59 Canada 29.14 2019
60 Uzbekistan 29.07 2019
61 Brunei 29.06 2019
62 Mauritius 28.95 2019
63 Sri Lanka 28.89 2019
64 Sweden 28.69 2019
65 New Zealand 28.64 2019
66 Barbados 28.53 2019
67 Moldova 28.43 2019
68 Montenegro 28.29 2019
69 Kuwait 28.24 2019
70 Saudi Arabia 28.18 2019
71 Cyprus 27.99 2019
72 Libya 27.94 2019
73 Mongolia 27.68 2019
74 United Kingdom 27.34 2019
75 Denmark 27.28 2019
76 Ireland 27.22 2019
77 India 27.07 2019
78 Uruguay 27.04 2019
79 Pakistan 27.03 2019
80 Brazil 26.95 2019
81 Lebanon 26.87 2019
82 Jordan 26.73 2019
83 Bolivia 26.65 2019
84 Iceland 26.61 2019
85 Morocco 26.15 2019
86 Indonesia 26.07 2019
87 El Salvador 26.03 2019
88 Malta 25.90 2019
89 Syrian Arab Republic 25.69 2019
90 Israel 25.58 2019
91 Thailand 25.43 2019
92 Burkina Faso 25.15 2019
93 São Tomé and Principe 25.13 2019
94 Philippines 25.07 2019
95 Namibia 24.96 2019
95 The Bahamas 24.96 2019
97 Botswana 24.95 2019
98 Dominican Republic 24.90 2019
99 Jamaica 24.68 2019
100 Netherlands 24.59 2019
101 Eswatini 24.46 2019
102 Paraguay 24.38 2019
103 Colombia 24.21 2019
104 Costa Rica 24.05 2019
105 Equatorial Guinea 23.80 2019
106 Iraq 23.75 2019
107 Timor-Leste 23.49 2019
108 Nepal 23.31 2019
109 Panama 23.17 2019
110 The Gambia 23.14 2019
111 Azerbaijan 23.09 2019
112 Albania 22.88 2019
113 Bangladesh 22.87 2019
114 Honduras 22.80 2019
115 Ecuador 22.27 2019
116 Tonga 21.92 2019
117 Georgia 21.54 2019
118 St. Lucia 21.36 2019
119 Cuba 21.28 2019
120 Sudan 21.10 2019
121 Peru 21.01 2019
122 Papua New Guinea 20.99 2019
123 Puerto Rico 20.98 2019
124 Tajikistan 20.95 2019
125 Congo 20.76 2019
126 Greece 20.68 2019
127 Togo 20.65 2019
128 Venezuela 20.58 2019
129 Comoros 20.54 2019
130 Benin 20.38 2019
131 Guatemala 19.53 2019
132 Belize 19.40 2019
133 Ghana 19.26 2019
134 Singapore 18.83 2019
135 Nicaragua 18.72 2019
136 Hong Kong SAR, China 18.64 2019
137 Samoa 18.58 2019
138 Solomon Islands 18.40 2019
139 Senegal 18.29 2019
140 Djibouti 17.81 2019
141 Mauritania 17.68 2019
142 Cameroon 17.44 2019
143 Fiji 17.36 2019
144 Myanmar 16.93 2019
145 Afghanistan 16.85 2019
146 Dem. People's Rep. Korea 16.70 2019
147 Macao SAR, China 16.64 2019
148 Lao PDR 16.39 2019
149 Luxembourg 16.32 2019
150 Zambia 16.21 2019
151 Dem. Rep. Congo 15.89 2019
152 Gabon 15.29 2019
153 Vanuatu 15.27 2019
154 Rwanda 14.92 2019
155 Liberia 14.72 2019
156 Côte d'Ivoire 14.56 2019
157 Lesotho 14.44 2019
158 Mozambique 14.43 2019
159 Angola 12.70 2019
160 Sierra Leone 12.02 2019
161 Zimbabwe 11.34 2019
162 Nigeria 11.27 2019
163 Guinea-Bissau 11.21 2019
164 Kenya 10.63 2019
165 Haiti 10.59 2019
166 Bhutan 10.55 2019
167 Guinea 10.41 2019
168 Yemen 10.00 2019
169 Uganda 9.70 2019
170 Eritrea 9.67 2019
171 Tanzania 9.59 2019
172 Ethiopia 9.51 2019
173 Mali 9.32 2019
174 Madagascar 8.55 2019
175 Malawi 7.71 2019
176 Central African Republic 7.68 2019
177 Burundi 5.99 2019
178 Niger 4.77 2019
179 Chad 3.00 2019
180 Somalia 2.90 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