Employment in agriculture (% 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 agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (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 Burundi 86.21 2019
2 Somalia 80.28 2019
3 Malawi 76.36 2019
4 Chad 75.06 2019
5 Niger 72.54 2019
6 Uganda 72.13 2019
7 Mozambique 70.22 2019
8 Central African Republic 69.85 2019
9 Ethiopia 66.63 2019
10 Zimbabwe 66.19 2019
11 Tanzania 65.09 2019
12 Nepal 64.38 2019
13 Dem. Rep. Congo 64.30 2019
14 Madagascar 64.12 2019
15 Eritrea 63.12 2019
16 Mali 62.44 2019
17 Rwanda 62.29 2019
18 Lao PDR 61.44 2019
19 Guinea 60.65 2019
20 Guinea-Bissau 60.48 2019
21 Vanuatu 56.78 2019
22 Papua New Guinea 56.15 2019
23 Bhutan 55.78 2019
24 Sierra Leone 54.49 2019
25 Kenya 54.34 2019
26 Angola 50.73 2019
27 Zambia 49.64 2019
28 Myanmar 48.85 2019
29 Tajikistan 44.72 2019
30 Lesotho 44.30 2019
31 Dem. People's Rep. Korea 43.82 2019
32 Cameroon 43.49 2019
33 Liberia 42.62 2019
34 India 42.60 2019
35 Afghanistan 42.50 2019
36 Côte d'Ivoire 40.15 2019
37 Equatorial Guinea 39.51 2019
38 Timor-Leste 39.28 2019
39 Sudan 38.37 2019
40 Bangladesh 38.30 2019
41 Benin 38.27 2019
42 Georgia 38.15 2019
43 Solomon Islands 37.26 2019
44 Vietnam 37.22 2019
45 Pakistan 36.92 2019
46 Albania 36.42 2019
47 Azerbaijan 36.00 2019
48 Nigeria 34.97 2019
49 Cambodia 34.53 2019
50 Comoros 34.38 2019
51 Congo 33.53 2019
52 Morocco 33.25 2019
53 Togo 32.38 2019
54 Thailand 31.43 2019
55 Guatemala 31.30 2019
56 Mauritania 30.83 2019
57 Nicaragua 30.60 2019
58 Bolivia 30.54 2019
59 Samoa 30.21 2019
60 Senegal 30.10 2019
61 Gabon 29.96 2019
62 Ghana 29.75 2019
63 Ecuador 29.74 2019
64 Honduras 29.49 2019
65 Haiti 29.03 2019
66 Indonesia 28.50 2019
67 Yemen 27.55 2019
68 Peru 27.37 2019
69 The Gambia 27.03 2019
70 Burkina Faso 26.21 2019
71 Uzbekistan 25.71 2019
72 China 25.33 2019
73 Mongolia 25.32 2019
74 Sri Lanka 24.98 2019
75 Djibouti 24.55 2019
76 Armenia 24.05 2019
77 Philippines 22.86 2019
78 Namibia 21.85 2019
79 Romania 21.24 2019
80 Moldova 20.96 2019
81 Turkmenistan 20.68 2019
82 Egypt 20.62 2019
83 Botswana 19.90 2019
84 Tonga 19.37 2019
85 Kyrgyz Republic 19.32 2019
86 São Tomé and Principe 19.14 2019
87 Paraguay 18.72 2019
88 Iraq 18.27 2019
89 Turkey 18.11 2019
90 Bosnia and Herzegovina 17.96 2019
91 Fiji 17.61 2019
92 Cuba 17.40 2019
93 Iran 17.37 2019
94 Belize 16.80 2019
95 Libya 16.41 2019
96 El Salvador 16.29 2019
97 Colombia 15.77 2019
98 Serbia 15.61 2019
99 Guyana 15.44 2019
100 Jamaica 15.22 2019
101 Kazakhstan 14.86 2019
102 Panama 14.41 2019
103 North Macedonia 13.92 2019
104 Ukraine 13.82 2019
105 Tunisia 13.80 2019
106 Mexico 12.48 2019
107 Eswatini 12.15 2019
108 Costa Rica 11.97 2019
109 Greece 11.60 2019
110 Lebanon 11.32 2019
111 Belarus 11.06 2019
112 Cabo Verde 10.60 2019
113 Malaysia 10.28 2019
114 Syrian Arab Republic 10.13 2019
115 St. Vincent and the Grenadines 10.08 2019
116 St. Lucia 9.97 2019
117 Algeria 9.60 2019
118 Poland 9.15 2019
119 Brazil 9.08 2019
120 Chile 8.98 2019
121 Dominican Republic 8.78 2019
122 Uruguay 8.41 2019
123 Suriname 8.08 2019
124 Venezuela 7.86 2019
125 Latvia 7.29 2019
126 Montenegro 7.15 2019
127 Bulgaria 6.62 2019
128 Lithuania 6.44 2019
129 Croatia 6.19 2019
130 Mauritius 5.97 2019
131 New Zealand 5.84 2019
132 Russia 5.83 2019
133 Portugal 5.50 2019
134 South Africa 5.28 2019
135 Korea 5.14 2019
136 Hungary 4.72 2019
137 Ireland 4.43 2019
138 Slovenia 4.28 2019
139 Iceland 4.04 2019
140 Spain 4.03 2019
141 Oman 3.99 2019
142 Italy 3.89 2019
143 Finland 3.78 2019
144 Austria 3.66 2019
145 Japan 3.38 2019
146 Estonia 3.17 2019
147 Trinidad and Tobago 3.03 2019
148 Slovak Republic 2.79 2019
149 Czech Republic 2.66 2019
150 Barbados 2.65 2019
151 Switzerland 2.59 2019
152 Australia 2.56 2019
153 France 2.53 2019
154 Jordan 2.47 2019
155 Saudi Arabia 2.41 2019
155 Cyprus 2.41 2019
157 Denmark 2.22 2019
158 The Bahamas 2.20 2019
159 Netherlands 2.08 2019
160 Norway 2.04 2019
161 Brunei 1.95 2019
162 New Caledonia 1.87 2019
163 Kuwait 1.78 2019
164 Sweden 1.69 2019
165 Canada 1.51 2019
166 United Arab Emirates 1.39 2019
167 United States 1.36 2019
168 Germany 1.21 2019
169 Qatar 1.17 2019
170 Puerto Rico 1.09 2019
171 United Kingdom 1.05 2019
172 Malta 1.02 2019
173 Bahrain 0.94 2019
174 Belgium 0.92 2019
174 Israel 0.92 2019
176 Luxembourg 0.68 2019
177 Macao SAR, China 0.40 2019
178 Hong Kong SAR, China 0.17 2019
179 Argentina 0.06 2019
180 Singapore 0.03 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 sectorsdata.

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