Employment in services, 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 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 Luxembourg 82.78 2019
2 Macao SAR, China 82.69 2019
3 Hong Kong SAR, China 81.14 2019
4 Singapore 81.12 2019
5 Puerto Rico 77.31 2019
6 Israel 73.10 2019
7 Netherlands 72.73 2019
8 Malta 72.70 2019
9 United Kingdom 71.20 2019
10 The Bahamas 71.15 2019
11 Jordan 70.46 2019
12 Denmark 69.50 2019
13 Kuwait 69.42 2019
14 Saudi Arabia 69.10 2019
15 Canada 68.89 2019
16 United States 68.81 2019
17 Argentina 68.73 2019
18 Sweden 68.72 2019
19 Cyprus 68.66 2019
20 Brunei 68.09 2019
21 Barbados 67.78 2019
22 Switzerland 67.63 2019
23 Australia 67.54 2019
24 Belgium 67.23 2019
25 Venezuela 67.15 2019
26 Greece 67.01 2019
27 Iceland 66.97 2019
28 Norway 66.46 2019
29 France 65.98 2019
30 Ireland 65.61 2019
31 Spain 64.79 2019
32 Montenegro 64.15 2019
33 Japan 63.93 2019
34 Mauritius 63.82 2019
35 Gabon 63.71 2019
36 Syrian Arab Republic 63.63 2019
37 New Zealand 63.62 2019
38 Yemen 63.49 2019
39 South Africa 63.09 2019
40 St. Lucia 63.02 2019
41 New Caledonia 61.81 2019
42 Dominican Republic 61.61 2019
43 Eswatini 61.58 2019
44 Korea 61.47 2019
45 Lebanon 61.25 2019
46 Finland 61.00 2019
47 Uruguay 60.88 2019
48 Fiji 60.48 2019
49 Brazil 60.24 2019
50 Italy 59.83 2019
51 Germany 59.73 2019
52 Oman 59.72 2019
53 Costa Rica 59.23 2019
54 Portugal 58.84 2019
55 Austria 58.78 2019
56 Trinidad and Tobago 58.52 2019
57 Panama 58.33 2019
58 United Arab Emirates 58.27 2019
59 Iraq 57.59 2019
60 Algeria 57.52 2019
61 Bahrain 57.17 2019
62 Chile 56.99 2019
63 Belize 56.53 2019
64 St. Vincent and the Grenadines 56.23 2019
65 Lithuania 56.18 2019
66 Djibouti 56.05 2019
67 Suriname 55.97 2019
68 Estonia 55.88 2019
69 Malaysia 55.69 2019
70 Libya 55.41 2019
71 Turkey 55.39 2019
72 Cabo Verde 55.21 2019
73 Cuba 54.99 2019
74 Russia 54.91 2019
75 Croatia 54.73 2019
76 Bulgaria 54.62 2019
77 Jamaica 54.42 2019
78 Kazakhstan 54.33 2019
79 The Gambia 54.30 2019
80 Latvia 53.99 2019
81 Colombia 53.48 2019
82 Paraguay 53.01 2019
83 Hungary 51.52 2019
84 Mexico 51.45 2019
85 Namibia 51.42 2019
86 North Macedonia 51.26 2019
87 Botswana 51.12 2019
88 Tunisia 50.94 2019
89 Peru 50.74 2019
90 São Tomé and Principe 50.56 2019
91 Iran 50.53 2019
92 Slovenia 49.35 2019
93 Ukraine 49.20 2019
94 Kyrgyz Republic 48.69 2019
95 Czech Republic 48.40 2019
95 Serbia 48.40 2019
97 El Salvador 48.34 2019
98 Senegal 48.01 2019
99 Egypt 47.61 2019
100 Sri Lanka 47.48 2019
101 Mauritania 47.47 2019
102 Tonga 47.40 2019
103 Bangladesh 46.99 2019
104 Haiti 46.90 2019
105 Slovak Republic 46.82 2019
106 Moldova 46.59 2019
107 Afghanistan 46.55 2019
108 Morocco 46.49 2019
109 Azerbaijan 46.34 2019
109 Guyana 46.34 2019
111 Philippines 46.24 2019
112 Ecuador 46.22 2019
113 Poland 46.12 2019
114 Mongolia 45.32 2019
115 Sudan 45.28 2019
116 Burkina Faso 44.77 2019
117 Solomon Islands 44.67 2019
118 Albania 44.41 2019
119 Ghana 44.37 2019
120 Congo 44.29 2019
121 Nigeria 44.25 2019
122 Indonesia 44.05 2019
123 Uzbekistan 43.89 2019
124 Tajikistan 43.71 2019
125 Belarus 43.61 2019
126 Pakistan 43.24 2019
127 Comoros 43.10 2019
128 Bosnia and Herzegovina 42.82 2019
129 Cameroon 42.77 2019
130 Angola 42.65 2019
131 Bolivia 42.62 2019
132 Dem. People's Rep. Korea 42.49 2019
133 Armenia 42.46 2019
134 Georgia 41.94 2019
135 Romania 41.54 2019
136 Togo 41.43 2019
137 China 41.23 2019
138 Liberia 40.57 2019
139 Thailand 40.50 2019
140 Kenya 39.82 2019
141 Bhutan 39.24 2019
142 Samoa 39.17 2019
143 Côte d'Ivoire 38.82 2019
144 Zambia 38.74 2019
145 Guatemala 38.70 2019
146 Equatorial Guinea 38.42 2019
147 Cambodia 37.95 2019
148 Lesotho 37.91 2019
149 Qatar 37.47 2019
150 Timor-Leste 37.15 2019
151 Nicaragua 36.64 2019
152 Turkmenistan 35.58 2019
153 Honduras 34.93 2019
154 India 33.37 2019
155 Benin 33.12 2019
156 Vietnam 32.51 2019
157 Rwanda 32.07 2019
158 Eritrea 31.68 2019
159 Guinea-Bissau 31.65 2019
160 Sierra Leone 30.47 2019
161 Guinea 30.34 2019
162 Myanmar 29.86 2019
163 Mali 28.35 2019
164 Vanuatu 27.95 2019
165 Tanzania 26.81 2019
166 Papua New Guinea 26.69 2019
167 Dem. Rep. Congo 26.68 2019
168 Zimbabwe 25.85 2019
169 Mozambique 25.75 2019
170 Central African Republic 24.78 2019
171 Nepal 24.58 2019
172 Lao PDR 24.19 2019
173 Madagascar 23.35 2019
174 Uganda 22.64 2019
175 Malawi 21.21 2019
176 Chad 20.54 2019
177 Niger 20.43 2019
178 Somalia 17.91 2019
179 Ethiopia 17.05 2019
180 Burundi 15.91 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