Employment in services, 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 services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (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 Macao SAR, China 97.59 2019
2 Saudi Arabia 97.56 2019
3 Kuwait 97.00 2019
4 The Bahamas 96.75 2019
5 Hong Kong SAR, China 96.46 2019
6 Oman 95.60 2019
7 Luxembourg 95.25 2019
8 United Arab Emirates 94.57 2019
9 Qatar 93.83 2019
10 Netherlands 92.36 2019
11 Sweden 92.16 2019
12 Norway 92.09 2019
13 Venezuela 92.00 2019
14 Puerto Rico 91.82 2019
15 United Kingdom 91.72 2019
16 New Caledonia 91.68 2019
17 Cyprus 91.64 2019
18 Israel 91.59 2019
19 Bahrain 91.39 2019
20 Iceland 91.26 2019
21 Belgium 90.97 2019
22 Australia 90.83 2019
23 Malta 90.78 2019
24 Argentina 90.77 2019
24 St. Lucia 90.77 2019
26 Canada 90.64 2019
27 United States 90.37 2019
28 Denmark 90.10 2019
29 Ireland 89.96 2019
30 Brunei 89.86 2019
31 St. Vincent and the Grenadines 89.44 2019
32 Barbados 89.41 2019
33 Dominican Republic 89.33 2019
34 Finland 89.14 2019
35 Singapore 89.01 2019
36 France 88.97 2019
37 Spain 88.55 2019
38 São Tomé and Principe 88.19 2019
39 Suriname 87.93 2019
40 Switzerland 87.89 2019
41 Uruguay 87.57 2019
42 New Zealand 87.34 2019
43 Trinidad and Tobago 86.29 2019
44 Jordan 86.27 2019
45 Jamaica 86.06 2019
46 Belize 86.05 2019
47 Costa Rica 85.92 2019
48 Montenegro 85.56 2019
49 Brazil 85.41 2019
50 Germany 85.27 2019
51 Chile 85.10 2019
52 Austria 85.05 2019
53 Haiti 84.90 2019
54 Syrian Arab Republic 84.88 2019
55 Italy 84.60 2019
56 Fiji 84.29 2019
57 South Africa 84.23 2019
58 Latvia 83.73 2019
59 Japan 83.15 2019
60 Cabo Verde 83.12 2019
61 Korea 82.36 2019
62 Cuba 82.31 2019
63 Panama 82.26 2019
64 Greece 81.58 2019
65 Estonia 81.44 2019
66 Portugal 81.37 2019
67 Guyana 81.18 2019
68 Mauritius 80.94 2019
69 Russia 80.54 2019
70 Nicaragua 79.48 2019
71 Croatia 79.41 2019
72 Mexico 79.33 2019
73 Lithuania 79.30 2019
74 Colombia 79.01 2019
75 El Salvador 78.90 2019
76 Paraguay 78.50 2019
77 Slovak Republic 78.40 2019
78 Lebanon 77.59 2019
79 Hungary 77.17 2019
80 Philippines 76.69 2019
81 Slovenia 76.01 2019
82 Botswana 75.48 2019
83 Kazakhstan 74.92 2019
84 Czech Republic 74.62 2019
85 Ukraine 74.60 2019
86 Poland 74.43 2019
87 Malaysia 74.06 2019
88 Belarus 73.74 2019
89 Bulgaria 73.48 2019
90 Guatemala 73.15 2019
91 Algeria 73.13 2019
92 Honduras 72.70 2019
93 Namibia 72.01 2019
94 Djibouti 71.06 2019
95 Egypt 70.78 2019
96 Senegal 69.84 2019
97 Iraq 68.77 2019
98 Moldova 68.08 2019
99 Serbia 67.78 2019
100 Eswatini 67.73 2019
101 Libya 67.14 2019
102 Kyrgyz Republic 66.32 2019
103 Peru 65.39 2019
104 Nigeria 63.57 2019
105 Ecuador 63.05 2019
106 The Gambia 62.90 2019
107 Bosnia and Herzegovina 62.68 2019
108 Mongolia 62.22 2019
109 Uzbekistan 61.93 2019
110 Armenia 61.71 2019
111 North Macedonia 60.80 2019
112 Mauritania 60.63 2019
113 Bolivia 59.45 2019
114 Turkey 59.10 2019
115 Côte d'Ivoire 58.49 2019
116 Tunisia 58.47 2019
117 Romania 58.07 2019
118 Indonesia 56.97 2019
119 Solomon Islands 56.89 2019
120 Samoa 56.13 2019
121 Togo 55.36 2019
122 China 54.92 2019
123 Ghana 54.80 2019
124 Iran 54.51 2019
124 Liberia 54.51 2019
126 Georgia 54.33 2019
127 Benin 54.08 2019
128 Tonga 53.48 2019
129 Burkina Faso 53.43 2019
130 Timor-Leste 53.26 2019
131 Azerbaijan 52.29 2019
132 Comoros 52.05 2019
133 Thailand 51.97 2019
134 Gabon 51.52 2019
135 Lesotho 48.37 2019
136 Sierra Leone 47.01 2019
137 Sri Lanka 46.50 2019
138 Equatorial Guinea 45.85 2019
139 Congo 45.73 2019
140 Turkmenistan 44.97 2019
141 Yemen 44.64 2019
142 Dem. People's Rep. Korea 44.52 2019
143 Sudan 43.48 2019
144 Angola 42.30 2019
145 Albania 42.06 2019
146 Cameroon 41.32 2019
147 Zambia 41.04 2019
148 Myanmar 40.60 2019
149 Kenya 39.04 2019
150 Vietnam 38.42 2019
151 Cambodia 37.14 2019
152 Guinea 36.22 2019
153 Papua New Guinea 34.75 2019
154 Morocco 34.58 2019
155 Tajikistan 32.58 2019
156 Ethiopia 32.19 2019
157 Mali 32.16 2019
158 Madagascar 31.13 2019
159 Vanuatu 30.67 2019
160 Tanzania 30.22 2019
161 Guinea-Bissau 30.09 2019
162 Zimbabwe 28.59 2019
163 India 27.96 2019
164 Eritrea 27.15 2019
165 Lao PDR 27.09 2019
166 Bhutan 26.43 2019
167 Rwanda 26.28 2019
168 Chad 26.07 2019
169 Dem. Rep. Congo 25.01 2019
170 Bangladesh 24.77 2019
171 Central African Republic 22.82 2019
172 Niger 21.18 2019
173 Uganda 20.04 2019
174 Pakistan 18.01 2019
175 Nepal 17.30 2019
176 Mozambique 17.00 2019
177 Somalia 15.32 2019
178 Malawi 15.13 2019
179 Afghanistan 10.02 2019
180 Burundi 5.43 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 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