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 62.35 2019
2 Slovak Republic 50.15 2019
3 Czech Republic 48.79 2019
4 Slovenia 45.15 2019
5 Poland 43.17 2019
6 Belarus 42.17 2019
7 Estonia 41.68 2019
8 Bahrain 41.67 2019
9 Hungary 40.97 2019
10 Oman 40.10 2019
11 Uzbekistan 38.82 2019
12 Germany 38.66 2019
13 Trinidad and Tobago 38.40 2019
14 Bosnia and Herzegovina 38.27 2019
15 Turkmenistan 37.85 2019
16 Russia 37.54 2019
17 Croatia 37.12 2019
18 Romania 36.68 2019
19 Austria 36.26 2019
20 Bulgaria 36.24 2019
21 Italy 35.13 2019
22 Lithuania 34.90 2019
23 Kuwait 34.72 2019
24 North Macedonia 34.32 2019
25 Finland 34.32 2019
26 Suriname 34.26 2019
27 Ukraine 34.01 2019
28 Latvia 33.72 2019
29 New Caledonia 33.66 2019
30 Portugal 33.36 2019
31 Iran 33.33 2019
32 Guyana 33.19 2019
32 Korea 33.19 2019
34 Tunisia 32.59 2019
35 Japan 32.55 2019
36 Burkina Faso 32.49 2019
37 Mauritius 32.39 2019
38 Algeria 32.38 2019
39 Malaysia 32.00 2019
40 South Africa 31.87 2019
41 Argentina 31.83 2019
42 Serbia 31.74 2019
43 Egypt 31.73 2019
44 Libya 31.72 2019
45 Syrian Arab Republic 31.44 2019
46 Chile 31.25 2019
47 Turkey 31.12 2019
48 Cabo Verde 31.00 2019
49 Mexico 30.85 2019
50 Belgium 30.71 2019
51 St. Vincent and the Grenadines 30.46 2019
52 Namibia 30.41 2019
53 New Zealand 30.34 2019
54 Norway 30.31 2019
55 Kazakhstan 30.28 2019
56 Bolivia 30.22 2019
57 Vietnam 29.87 2019
58 France 29.54 2019
59 Australia 29.53 2019
60 Canada 29.37 2019
61 Kyrgyz Republic 29.30 2019
62 Cambodia 29.26 2019
63 Barbados 29.18 2019
64 Switzerland 29.08 2019
65 Sri Lanka 29.07 2019
66 Spain 28.86 2019
67 China 28.67 2019
68 St. Lucia 28.66 2019
69 United States 28.44 2019
70 Uruguay 28.29 2019
71 Saudi Arabia 28.02 2019
72 Sweden 27.84 2019
73 Brazil 27.70 2019
74 Venezuela 27.67 2019
75 Paraguay 27.64 2019
76 Denmark 27.24 2019
77 United Kingdom 27.21 2019
78 The Bahamas 26.99 2019
79 Ireland 26.69 2019
80 India 26.58 2019
81 Jordan 26.53 2019
82 Iceland 26.49 2019
83 Thailand 26.33 2019
84 Pakistan 26.32 2019
85 United Arab Emirates 26.27 2019
86 Lebanon 26.23 2019
87 Iraq 26.06 2019
88 Malta 26.04 2019
89 Macao SAR, China 25.81 2019
90 Dominican Republic 25.78 2019
91 Israel 25.78 2019
92 Cyprus 25.66 2019
93 Indonesia 25.60 2019
94 São Tomé and Principe 25.28 2019
95 Mongolia 25.11 2019
96 The Gambia 24.90 2019
97 Botswana 24.88 2019
98 Netherlands 24.85 2019
99 Montenegro 24.84 2019
100 Eswatini 24.81 2019
101 Morocco 24.71 2019
102 Panama 24.49 2019
103 El Salvador 24.37 2019
104 Philippines 23.81 2019
105 Ecuador 23.79 2019
106 Costa Rica 23.58 2019
107 Colombia 23.40 2019
108 Jamaica 23.29 2019
109 Puerto Rico 23.19 2019
110 Tajikistan 22.58 2019
111 Albania 22.56 2019
112 Armenia 22.53 2019
113 Azerbaijan 22.40 2019
114 Congo 22.18 2019
115 Bangladesh 22.17 2019
116 Guatemala 22.02 2019
117 Benin 21.42 2019
118 Peru 21.42 2019
119 Brunei 21.33 2019
120 Moldova 20.71 2019
121 Honduras 20.65 2019
122 Cuba 20.61 2019
123 Singapore 20.46 2019
124 Greece 20.37 2019
125 Nepal 20.08 2019
126 Georgia 20.08 2019
127 Equatorial Guinea 19.89 2019
128 Hong Kong SAR, China 19.44 2019
129 Dem. People's Rep. Korea 19.25 2019
130 Senegal 19.07 2019
131 Nicaragua 18.93 2019
132 Samoa 18.90 2019
133 Afghanistan 18.88 2019
134 Belize 18.63 2019
135 Sudan 18.39 2019
136 Togo 18.28 2019
137 Ghana 17.97 2019
138 Cameroon 17.36 2019
139 Zambia 17.01 2019
140 Liberia 16.76 2019
141 Myanmar 16.60 2019
142 Luxembourg 16.55 2019
143 Dem. Rep. Congo 16.40 2019
144 Rwanda 15.57 2019
145 Fiji 15.50 2019
146 Angola 15.46 2019
147 Comoros 15.18 2019
148 Gabon 14.24 2019
149 Tonga 14.22 2019
150 Mozambique 13.79 2019
151 Ethiopia 13.69 2019
152 Haiti 13.69 2019
153 Mauritania 13.07 2019
154 Kenya 12.75 2019
155 Zimbabwe 11.97 2019
156 Lao PDR 11.76 2019
157 Guinea 11.72 2019
158 Nigeria 11.22 2019
159 Central African Republic 11.09 2019
160 Uganda 11.08 2019
161 Tanzania 11.08 2019
162 Guinea-Bissau 11.00 2019
163 Djibouti 10.94 2019
164 Eritrea 10.94 2019
165 Solomon Islands 10.87 2019
166 Malawi 10.46 2019
167 Sierra Leone 10.45 2019
168 Timor-Leste 10.32 2019
169 Bhutan 10.29 2019
170 Yemen 10.15 2019
171 Lesotho 10.07 2019
172 Vanuatu 9.73 2019
173 Mali 8.37 2019
174 Papua New Guinea 8.23 2019
175 Côte d'Ivoire 8.06 2019
176 Madagascar 7.64 2019
177 Somalia 7.17 2019
178 Niger 4.89 2019
179 Chad 4.80 2019
180 Burundi 3.46 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