Employment in services (% of total 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 89.94 2019
2 Hong Kong SAR, China 88.75 2019
3 Luxembourg 88.51 2019
4 Singapore 84.41 2019
5 Puerto Rico 83.70 2019
6 The Bahamas 83.31 2019
7 Israel 81.86 2019
8 Netherlands 81.81 2019
9 United Kingdom 80.83 2019
10 Malta 80.07 2019
11 Sweden 79.89 2019
12 Canada 79.24 2019
13 Denmark 79.23 2019
14 Cyprus 79.16 2019
15 United States 78.74 2019
16 Norway 78.54 2019
17 Iceland 78.49 2019
18 Barbados 78.42 2019
19 Australia 78.38 2019
20 Belgium 78.24 2019
21 Argentina 78.10 2019
22 Brunei 77.28 2019
23 Switzerland 77.07 2019
24 France 77.04 2019
25 Venezuela 76.81 2019
26 Ireland 76.80 2019
27 Kuwait 76.07 2019
28 Spain 75.54 2019
29 St. Lucia 75.34 2019
30 New Caledonia 75.26 2019
31 New Zealand 74.87 2019
32 Finland 74.58 2019
33 Montenegro 73.44 2019
34 Jordan 73.09 2019
35 Greece 73.06 2019
36 Saudi Arabia 72.79 2019
37 Uruguay 72.76 2019
38 South Africa 72.41 2019
39 Japan 72.40 2019
39 Dominican Republic 72.40 2019
41 Germany 71.61 2019
42 Austria 70.99 2019
43 Brazil 70.94 2019
44 Mauritius 70.35 2019
45 Trinidad and Tobago 70.34 2019
46 Korea 70.28 2019
47 Italy 70.24 2019
48 St. Vincent and the Grenadines 70.04 2019
49 Portugal 69.83 2019
50 Costa Rica 69.22 2019
51 Latvia 68.99 2019
52 Chile 68.78 2019
53 Jamaica 68.60 2019
54 Fiji 68.26 2019
55 Estonia 68.13 2019
56 Panama 67.88 2019
57 Lithuania 67.86 2019
58 Belize 67.61 2019
59 Cabo Verde 67.60 2019
60 Suriname 67.59 2019
61 Russia 67.38 2019
62 Syrian Arab Republic 66.69 2019
63 Croatia 66.14 2019
64 Cuba 65.49 2019
65 Lebanon 65.10 2019
66 Eswatini 64.46 2019
67 United Arab Emirates 64.39 2019
68 Haiti 64.31 2019
69 Kazakhstan 64.16 2019
70 Colombia 64.11 2019
71 Oman 63.99 2019
72 Bahrain 63.81 2019
73 Bulgaria 63.36 2019
74 Hungary 63.19 2019
75 Paraguay 63.14 2019
76 São Tomé and Principe 62.92 2019
77 Malaysia 62.72 2019
78 Botswana 62.49 2019
79 Yemen 62.25 2019
80 Djibouti 62.00 2019
81 Mexico 61.97 2019
82 Namibia 61.75 2019
83 Slovenia 61.61 2019
84 Ukraine 61.22 2019
85 El Salvador 61.20 2019
86 Slovak Republic 61.12 2019
87 Czech Republic 60.09 2019
88 Algeria 59.99 2019
89 Guyana 59.60 2019
90 Gabon 59.30 2019
91 Libya 59.17 2019
92 Iraq 58.80 2019
93 Poland 58.71 2019
94 Belarus 58.56 2019
95 Philippines 58.03 2019
96 The Gambia 57.96 2019
97 Peru 57.43 2019
98 Moldova 57.32 2019
99 Serbia 56.96 2019
100 Senegal 56.78 2019
101 Turkey 56.57 2019
102 Kyrgyz Republic 55.33 2019
103 North Macedonia 54.95 2019
104 Nicaragua 53.16 2019
105 Mongolia 53.11 2019
106 Ecuador 53.04 2019
107 Nigeria 53.03 2019
108 Tunisia 52.75 2019
109 Egypt 52.44 2019
110 Mauritania 51.56 2019
111 Uzbekistan 51.27 2019
112 Iran 51.24 2019
113 Armenia 51.20 2019
114 Solomon Islands 50.61 2019
115 Bosnia and Herzegovina 50.33 2019
116 Bolivia 50.05 2019
117 Guatemala 49.98 2019
118 Tonga 49.76 2019
119 Azerbaijan 49.22 2019
120 Ghana 49.21 2019
121 Indonesia 49.14 2019
122 Honduras 49.12 2019
123 Romania 48.69 2019
124 Burkina Faso 48.64 2019
125 Togo 48.41 2019
126 Georgia 47.59 2019
127 China 47.25 2019
128 Liberia 47.23 2019
129 Sri Lanka 47.15 2019
130 Côte d'Ivoire 46.99 2019
131 Comoros 46.79 2019
132 Thailand 45.73 2019
133 Qatar 45.14 2019
134 Congo 44.99 2019
135 Samoa 44.91 2019
136 Sudan 44.81 2019
137 Timor-Leste 44.40 2019
138 Morocco 43.66 2019
139 Dem. People's Rep. Korea 43.45 2019
140 Albania 43.43 2019
141 Benin 43.42 2019
142 Angola 42.47 2019
143 Lesotho 42.39 2019
144 Cameroon 42.09 2019
145 Equatorial Guinea 41.14 2019
146 Bangladesh 40.38 2019
147 Zambia 39.83 2019
148 Turkmenistan 39.49 2019
148 Tajikistan 39.49 2019
150 Kenya 39.44 2019
151 Afghanistan 38.96 2019
152 Sierra Leone 38.76 2019
153 Pakistan 38.13 2019
154 Cambodia 37.56 2019
155 Vietnam 35.34 2019
156 Myanmar 34.21 2019
157 Bhutan 34.06 2019
158 Guinea 33.56 2019
159 India 32.28 2019
160 Guinea-Bissau 30.91 2019
161 Papua New Guinea 30.63 2019
162 Mali 30.00 2019
163 Eritrea 29.59 2019
164 Vanuatu 29.14 2019
165 Rwanda 29.08 2019
166 Tanzania 28.44 2019
167 Zimbabwe 27.24 2019
168 Madagascar 27.15 2019
169 Dem. Rep. Congo 25.86 2019
170 Lao PDR 25.62 2019
171 Ethiopia 24.05 2019
172 Central African Republic 23.89 2019
173 Chad 23.06 2019
174 Uganda 21.36 2019
175 Mozambique 21.19 2019
176 Niger 20.75 2019
177 Nepal 20.52 2019
178 Malawi 18.27 2019
179 Somalia 17.31 2019
180 Burundi 10.45 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