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 45.00 2019
2 Samoa 37.23 2019
3 Turkmenistan 36.35 2019
4 Tunisia 32.57 2019
5 Iran 26.70 2019
6 Cambodia 26.29 2019
7 North Macedonia 26.19 2019
8 Sri Lanka 25.87 2019
9 Burkina Faso 25.16 2019
10 Afghanistan 25.02 2019
11 Czech Republic 23.64 2019
12 Algeria 23.48 2019
13 Vietnam 23.28 2019
14 Ghana 23.11 2019
15 China 23.06 2019
16 Bulgaria 22.23 2019
16 Congo 22.23 2019
18 Eswatini 22.17 2019
19 Romania 20.92 2019
20 Slovenia 20.51 2019
21 Slovak Republic 20.26 2019
22 Malaysia 20.05 2019
23 Hungary 19.99 2019
24 Thailand 19.76 2019
25 Honduras 19.04 2019
26 Serbia 18.96 2019
27 Belarus 18.75 2019
28 Togo 17.78 2019
29 El Salvador 17.67 2019
30 Bangladesh 17.66 2019
31 Poland 17.49 2019
32 Mauritania 17.43 2019
33 India 17.35 2019
34 Guatemala 17.07 2019
35 Mexico 17.06 2019
36 Estonia 17.05 2019
37 Libya 16.97 2019
38 Myanmar 16.96 2019
39 Bosnia and Herzegovina 16.85 2019
40 Pakistan 16.82 2019
41 Indonesia 16.67 2019
42 Lithuania 16.55 2019
43 Comoros 16.39 2019
44 Albania 16.31 2019
45 Iraq 16.18 2019
46 Croatia 16.16 2019
46 Benin 16.16 2019
48 Turkey 15.85 2019
49 Russia 15.45 2019
50 Mauritius 15.13 2019
51 Portugal 15.01 2019
52 Moldova 14.99 2019
53 Kyrgyz Republic 14.87 2019
54 Mongolia 14.43 2019
55 Colombia 14.40 2019
56 Uzbekistan 14.29 2019
57 Ukraine 13.99 2019
58 Germany 13.90 2019
58 Japan 13.90 2019
60 Morocco 13.30 2019
61 Yemen 13.08 2019
62 Italy 13.02 2019
63 Jordan 12.97 2019
64 Lebanon 12.93 2019
65 Nigeria 12.87 2019
66 Korea 12.81 2019
67 Vanuatu 12.54 2019
68 Trinidad and Tobago 12.37 2019
69 Nicaragua 12.29 2019
70 South Africa 11.99 2019
71 Latvia 11.92 2019
72 Kazakhstan 11.83 2019
73 Lesotho 11.80 2019
74 Austria 11.76 2019
75 Equatorial Guinea 11.65 2019
76 Cabo Verde 11.41 2019
77 Armenia 11.40 2019
78 Cameroon 10.98 2019
78 Singapore 10.98 2019
80 Guyana 10.95 2019
81 Brazil 10.57 2019
82 Côte d'Ivoire 10.47 2019
83 Cuba 10.42 2019
84 Bolivia 10.24 2019
85 Chile 10.16 2019
86 Switzerland 10.13 2019
87 Costa Rica 10.03 2019
88 Ecuador 9.81 2019
89 Philippines 9.70 2019
90 Bhutan 9.57 2019
91 France 9.54 2019
92 Panama 9.50 2019
93 Spain 9.42 2019
93 Brunei 9.42 2019
95 Lao PDR 9.37 2019
96 Niger 9.35 2019
97 Dominican Republic 9.28 2019
98 Belize 9.26 2019
99 Botswana 9.24 2019
100 Argentina 9.20 2019
101 Ethiopia 9.10 2019
102 Barbados 9.01 2019
103 New Zealand 8.94 2019
104 Madagascar 8.93 2019
105 United States 8.87 2019
106 Ireland 8.84 2019
107 Finland 8.79 2019
107 Denmark 8.79 2019
109 Malta 8.77 2019
110 Paraguay 8.69 2019
111 Nepal 8.62 2019
112 Uruguay 8.59 2019
113 Bahrain 8.57 2019
114 Belgium 8.41 2019
115 Canada 8.35 2019
116 Dem. People's Rep. Korea 8.33 2019
117 Peru 8.28 2019
118 Syrian Arab Republic 8.27 2019
119 Egypt 8.01 2019
120 Israel 7.95 2019
121 Namibia 7.89 2019
122 Puerto Rico 7.87 2019
123 Greece 7.83 2019
123 Montenegro 7.83 2019
125 United Kingdom 7.70 2019
126 Timor-Leste 7.57 2019
127 Suriname 7.54 2019
128 Fiji 7.51 2019
129 New Caledonia 7.47 2019
130 Australia 7.45 2019
131 Tajikistan 7.37 2019
132 Iceland 7.35 2019
133 Sweden 7.14 2019
134 Venezuela 7.08 2019
135 Cyprus 7.07 2019
136 Norway 6.87 2019
137 Djibouti 6.80 2019
138 St. Lucia 6.34 2019
139 St. Vincent and the Grenadines 6.30 2019
140 Netherlands 6.26 2019
141 Qatar 6.16 2019
142 Azerbaijan 5.91 2019
143 Guinea-Bissau 5.77 2019
144 Jamaica 5.72 2019
145 Georgia 5.58 2019
146 Solomon Islands 5.50 2019
147 United Arab Emirates 5.42 2019
147 Senegal 5.42 2019
149 Mali 5.27 2019
150 Liberia 5.16 2019
151 Papua New Guinea 5.12 2019
152 Sudan 4.69 2019
153 Central African Republic 4.57 2019
154 Eritrea 4.50 2019
155 Luxembourg 4.33 2019
156 Zambia 4.30 2019
157 Oman 4.10 2019
158 The Gambia 4.04 2019
159 Dem. Rep. Congo 3.48 2019
160 Hong Kong SAR, China 3.43 2019
161 São Tomé and Principe 3.25 2019
162 Mozambique 3.22 2019
163 Uganda 3.19 2019
164 Tanzania 3.08 2019
165 Kuwait 2.97 2019
166 The Bahamas 2.91 2019
167 Malawi 2.86 2019
168 Rwanda 2.74 2019
169 Gabon 2.72 2019
170 Macao SAR, China 2.30 2019
171 Saudi Arabia 2.11 2019
172 Haiti 2.00 2019
173 Guinea 1.98 2019
174 Zimbabwe 1.93 2019
175 Kenya 1.62 2019
176 Sierra Leone 1.53 2019
177 Angola 0.92 2019
178 Burundi 0.91 2019
179 Somalia 0.79 2019
180 Chad 0.54 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