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 November 2017.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Tonga 50.70 2017
2 Turkmenistan 38.20 2017
3 Moldova 34.40 2017
4 Algeria 34.20 2017
5 Tunisia 32.00 2017
6 Belarus 30.80 2017
7 Sudan 30.40 2017
8 Djibouti 29.70 2017
9 Congo 26.40 2017
10 Macedonia 25.50 2017
11 Sri Lanka 25.30 2017
12 Libya 25.20 2017
13 Niger 24.90 2017
14 Iran 24.50 2017
15 Czech Republic 22.50 2017
16 Bulgaria 22.30 2017
17 Dem. People's Rep. Korea 22.00 2017
18 Ukraine 21.60 2017
19 Honduras 20.80 2017
19 Uzbekistan 20.80 2017
21 Thailand 19.30 2017
22 Romania 19.20 2017
23 Angola 19.00 2017
24 Malaysia 18.80 2017
25 Slovak Republic 18.70 2017
26 Vietnam 18.60 2017
27 Bosnia and Herzegovina 18.50 2017
28 Cambodia 18.30 2017
28 India 18.30 2017
30 Hungary 18.20 2017
31 Lesotho 17.40 2017
32 El Salvador 17.10 2017
33 Estonia 17.00 2017
34 Serbia 16.90 2017
35 Turkey 16.80 2017
36 Mexico 16.60 2017
37 Mauritius 16.50 2017
38 Slovenia 16.40 2017
38 Guatemala 16.40 2017
40 Russia 16.30 2017
40 China 16.30 2017
42 Indonesia 15.70 2017
43 Lithuania 15.50 2017
43 Nigeria 15.50 2017
43 Poland 15.50 2017
46 Morocco 15.40 2017
46 Japan 15.40 2017
48 Bangladesh 14.80 2017
48 Croatia 14.80 2017
50 Portugal 14.60 2017
51 Germany 13.60 2017
52 Mongolia 13.50 2017
52 Italy 13.50 2017
54 Korea 13.30 2017
55 Mali 13.20 2017
56 Syrian Arab Republic 12.90 2017
57 Austria 12.50 2017
58 New Caledonia 12.40 2017
59 Myanmar 12.20 2017
60 South Africa 12.10 2017
61 Singapore 12.00 2017
61 Latvia 12.00 2017
63 Chile 11.30 2017
63 Brunei 11.30 2017
65 Kazakhstan 11.20 2017
66 Brazil 10.90 2017
67 Kyrgyz Republic 10.80 2017
68 Colombia 10.60 2017
68 Albania 10.60 2017
70 Ghana 10.50 2017
70 Ecuador 10.50 2017
72 Switzerland 10.40 2017
72 Nicaragua 10.40 2017
74 Guyana 10.20 2017
74 Bolivia 10.20 2017
74 Pakistan 10.20 2017
77 Trinidad and Tobago 9.80 2017
78 Philippines 9.70 2017
78 Botswana 9.70 2017
78 New Zealand 9.70 2017
78 France 9.70 2017
82 Uruguay 9.60 2017
83 Paraguay 9.50 2017
83 Senegal 9.50 2017
85 Barbados 9.40 2017
85 Costa Rica 9.40 2017
85 Peru 9.40 2017
88 Venezuela 9.30 2017
88 Malta 9.30 2017
90 Panama 9.20 2017
90 Bhutan 9.20 2017
92 Denmark 9.10 2017
93 Ethiopia 8.80 2017
94 Finland 8.70 2017
94 Dominican Republic 8.70 2017
96 Canada 8.60 2017
96 Macao SAR, China 8.60 2017
98 Jordan 8.50 2017
99 Argentina 8.30 2017
100 Australia 8.20 2017
101 Spain 8.10 2017
101 Belgium 8.10 2017
103 Haiti 7.90 2017
104 Israel 7.80 2017
104 Belize 7.80 2017
104 Bahrain 7.80 2017
107 Yemen 7.70 2017
108 St. Lucia 7.50 2017
108 United Kingdom 7.50 2017
108 Greece 7.50 2017
111 Iceland 7.30 2017
111 Norway 7.30 2017
111 Armenia 7.30 2017
114 Samoa 7.20 2017
115 United States 7.00 2017
115 Ireland 7.00 2017
117 Montenegro 6.90 2017
117 Cuba 6.90 2017
119 Sweden 6.80 2017
120 Cyprus 6.60 2017
121 Lebanon 6.50 2017
121 Nepal 6.50 2017
121 Cameroon 6.50 2017
124 Qatar 6.40 2017
125 Puerto Rico 6.30 2017
125 Benin 6.30 2017
127 Kuwait 6.20 2017
128 Azerbaijan 6.00 2017
129 Hong Kong SAR, China 5.90 2017
130 Jamaica 5.80 2017
131 Netherlands 5.70 2017
132 Liberia 5.40 2017
132 Gabon 5.40 2017
132 Togo 5.40 2017
135 Afghanistan 5.30 2017
136 Egypt 5.20 2017
137 Namibia 5.00 2017
138 Oman 4.90 2017
139 United Arab Emirates 4.80 2017
139 São Tomé and Principe 4.80 2017
141 Equatorial Guinea 4.70 2017
141 Suriname 4.70 2017
143 Madagascar 4.50 2017
143 Uganda 4.50 2017
145 Iraq 3.90 2017
146 The Bahamas 3.80 2017
147 Luxembourg 3.70 2017
147 St. Vincent and the Grenadines 3.70 2017
149 Georgia 3.60 2017
150 Tajikistan 3.50 2017
151 Zambia 3.40 2017
152 Burkina Faso 3.00 2017
152 The Gambia 3.00 2017
152 Tanzania 3.00 2017
155 Vanuatu 2.80 2017
156 Swaziland 2.70 2017
157 Kenya 2.60 2017
158 Lao PDR 2.30 2017
158 Sierra Leone 2.30 2017
160 Zimbabwe 2.20 2017
161 Solomon Islands 2.00 2017
162 Papua New Guinea 1.90 2017
163 Dem. Rep. Congo 1.70 2017
164 Fiji 1.60 2017
165 Saudi Arabia 1.50 2017
165 Mauritania 1.50 2017
165 Rwanda 1.50 2017
168 Timor-Leste 1.40 2017
169 Cabo Verde 1.30 2017
169 Guinea 1.30 2017
171 Guinea-Bissau 1.10 2017
171 Malawi 1.10 2017
173 Central African Republic 1.00 2017
173 Somalia 1.00 2017
173 Eritrea 1.00 2017
176 Burundi 0.90 2017
176 Côte d'Ivoire 0.90 2017
178 Chad 0.70 2017
179 Comoros 0.60 2017
180 Mozambique 0.20 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.