Employment in industry, female (% of female 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 Tonga 54.84 2019
2 Burkina Faso 34.26 2019
3 Tunisia 33.26 2019
4 Turkmenistan 28.09 2019
5 China 27.75 2019
6 Sri Lanka 26.71 2019
7 Iran 25.07 2019
8 Cambodia 24.55 2019
9 North Macedonia 24.34 2019
10 Eswatini 23.74 2019
11 Czech Republic 23.74 2019
12 Congo 22.29 2019
13 Bulgaria 22.16 2019
14 Algeria 21.95 2019
15 Vietnam 21.51 2019
16 Romania 21.42 2019
17 Togo 21.17 2019
18 Slovak Republic 20.87 2019
19 Thailand 20.10 2019
20 Honduras 19.75 2019
21 Belarus 19.57 2019
22 Hungary 19.44 2019
23 Malaysia 19.43 2019
24 Ghana 19.32 2019
25 India 18.81 2019
26 Slovenia 18.64 2019
27 Mauritius 18.43 2019
28 Uzbekistan 18.42 2019
29 Guatemala 17.90 2019
30 Benin 17.70 2019
31 El Salvador 17.67 2019
32 Mexico 17.20 2019
33 Estonia 16.97 2019
34 Poland 16.85 2019
35 Bangladesh 16.70 2019
36 Serbia 16.61 2019
37 Indonesia 16.33 2019
38 Afghanistan 15.84 2019
39 Russia 15.62 2019
40 Bosnia and Herzegovina 15.49 2019
41 Turkey 15.31 2019
42 Yemen 15.26 2019
43 Jordan 15.26 2019
44 Myanmar 15.21 2019
45 Lithuania 15.17 2019
46 Albania 14.92 2019
47 Portugal 14.91 2019
48 Dem. People's Rep. Korea 14.31 2019
49 Pakistan 14.03 2019
50 St. Lucia 13.89 2019
51 Japan 13.89 2019
52 Colombia 13.69 2019
53 Ukraine 13.59 2019
54 Germany 13.42 2019
55 Korea 13.38 2019
56 Croatia 13.19 2019
57 Nicaragua 12.86 2019
58 Comoros 12.69 2019
59 Niger 12.59 2019
60 Latvia 12.49 2019
61 Italy 12.47 2019
62 Trinidad and Tobago 12.44 2019
63 Moldova 12.33 2019
64 South Africa 12.03 2019
65 Nigeria 11.95 2019
66 Cabo Verde 11.93 2019
67 Kazakhstan 11.74 2019
68 Morocco 11.71 2019
69 Singapore 11.69 2019
70 Mongolia 11.62 2019
71 Guyana 11.30 2019
72 Ethiopia 11.27 2019
73 Kyrgyz Republic 11.15 2019
74 Austria 11.04 2019
75 Ecuador 10.96 2019
76 Equatorial Guinea 10.74 2019
77 Venezuela 10.67 2019
78 Chile 10.62 2019
79 Syrian Arab Republic 10.56 2019
80 Brazil 10.45 2019
81 Cameroon 10.45 2019
82 Cuba 10.38 2019
83 Lesotho 10.15 2019
84 Bolivia 9.87 2019
85 Switzerland 9.85 2019
86 Lebanon 9.75 2019
87 Costa Rica 9.70 2019
88 Philippines 9.68 2019
89 Botswana 9.64 2019
90 Panama 9.54 2019
91 France 9.51 2019
92 Dominican Republic 9.40 2019
93 New Zealand 9.30 2019
94 Barbados 9.09 2019
95 Bhutan 9.06 2019
96 Malta 9.05 2019
97 Uruguay 9.02 2019
98 Brunei 8.97 2019
99 Bahrain 8.88 2019
100 Argentina 8.87 2019
101 Libya 8.82 2019
102 Peru 8.72 2019
103 Denmark 8.68 2019
104 Puerto Rico 8.67 2019
105 Spain 8.54 2019
106 Paraguay 8.51 2019
107 Canada 8.34 2019
108 Belgium 8.33 2019
109 United States 8.29 2019
110 Ireland 8.28 2019
111 Finland 8.27 2019
112 Suriname 8.26 2019
113 Macao SAR, China 8.19 2019
114 Fiji 8.12 2019
115 Belize 8.07 2019
116 Greece 8.01 2019
117 Armenia 7.68 2019
118 New Caledonia 7.67 2019
119 Iraq 7.63 2019
120 Israel 7.58 2019
121 Australia 7.52 2019
122 United Kingdom 7.48 2019
123 Timor-Leste 7.41 2019
124 Madagascar 7.35 2019
125 Central African Republic 7.26 2019
126 St. Vincent and the Grenadines 7.22 2019
127 Samoa 7.15 2019
128 Montenegro 7.09 2019
129 Namibia 6.93 2019
130 Sweden 6.88 2019
131 Mauritania 6.84 2019
132 Solomon Islands 6.83 2019
133 Cyprus 6.78 2019
134 Egypt 6.76 2019
135 Nepal 6.71 2019
136 Iceland 6.69 2019
137 Qatar 6.63 2019
138 Norway 6.60 2019
139 Lao PDR 6.50 2019
140 Guinea-Bissau 6.41 2019
141 Haiti 6.24 2019
142 Malawi 6.12 2019
143 Jamaica 6.02 2019
144 United Arab Emirates 6.01 2019
145 Azerbaijan 5.97 2019
146 Netherlands 5.95 2019
147 Liberia 5.82 2019
148 Senegal 5.74 2019
149 Georgia 5.43 2019
150 Oman 5.40 2019
151 Eritrea 5.30 2019
152 Tajikistan 4.78 2019
153 Kuwait 4.57 2019
154 Djibouti 4.53 2019
155 Dem. Rep. Congo 4.41 2019
156 The Gambia 4.37 2019
157 Mali 4.30 2019
158 Zambia 3.99 2019
159 Hong Kong SAR, China 3.91 2019
160 Sudan 3.74 2019
161 Somalia 3.73 2019
162 Uganda 3.66 2019
163 Côte d'Ivoire 3.59 2019
164 Tanzania 3.33 2019
165 The Bahamas 3.32 2019
166 Luxembourg 3.13 2019
167 São Tomé and Principe 3.12 2019
168 Rwanda 3.08 2019
169 Mozambique 2.62 2019
170 Vanuatu 2.44 2019
171 Guinea 2.39 2019
172 Gabon 2.34 2019
173 Kenya 2.34 2019
174 Zimbabwe 2.14 2019
175 Saudi Arabia 1.99 2019
176 Papua New Guinea 1.65 2019
177 Sierra Leone 1.40 2019
178 Angola 1.11 2019
179 Chad 1.05 2019
180 Burundi 0.76 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