Employment in agriculture, 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 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 Somalia 79.19 2019
2 Burundi 78.10 2019
3 Chad 76.46 2019
4 Niger 74.79 2019
5 Ethiopia 73.44 2019
6 Malawi 71.08 2019
7 Madagascar 68.11 2019
8 Uganda 67.66 2019
9 Central African Republic 67.54 2019
10 Tanzania 63.61 2019
11 Zimbabwe 62.81 2019
12 Mali 62.33 2019
13 Mozambique 59.82 2019
14 Lao PDR 59.42 2019
15 Guinea 59.24 2019
16 Eritrea 58.66 2019
17 Sierra Leone 57.52 2019
18 Dem. Rep. Congo 57.43 2019
19 Guinea-Bissau 57.14 2019
20 Vanuatu 56.78 2019
21 Myanmar 53.21 2019
22 Rwanda 53.01 2019
23 Papua New Guinea 52.33 2019
24 Nepal 52.11 2019
25 Bhutan 50.21 2019
26 Kenya 49.55 2019
27 Lesotho 47.65 2019
28 Côte d'Ivoire 46.62 2019
29 Benin 46.49 2019
30 Zambia 45.06 2019
31 Liberia 44.72 2019
32 Angola 44.65 2019
32 Nicaragua 44.65 2019
34 Nigeria 44.48 2019
35 Haiti 42.50 2019
36 Honduras 42.27 2019
37 Samoa 42.26 2019
38 Guatemala 41.77 2019
39 Dem. People's Rep. Korea 40.82 2019
40 Cameroon 39.79 2019
41 India 39.56 2019
42 Timor-Leste 39.37 2019
43 Togo 37.92 2019
44 Equatorial Guinea 37.79 2019
45 Solomon Islands 36.93 2019
46 Afghanistan 36.60 2019
47 Georgia 36.52 2019
48 Ghana 36.38 2019
49 Comoros 36.35 2019
50 Vietnam 36.23 2019
51 Tajikistan 35.35 2019
52 Congo 34.95 2019
53 Mauritania 34.85 2019
54 Thailand 34.07 2019
55 Senegal 33.70 2019
56 Sudan 33.62 2019
57 Albania 32.71 2019
58 Cambodia 32.62 2019
59 Ecuador 31.52 2019
60 Bolivia 30.73 2019
61 Tonga 30.67 2019
62 Azerbaijan 30.57 2019
63 Bangladesh 30.14 2019
64 Burkina Faso 30.07 2019
65 Indonesia 29.88 2019
66 Pakistan 29.74 2019
67 Philippines 28.70 2019
68 Peru 28.25 2019
69 China 27.94 2019
70 Morocco 27.36 2019
71 Uzbekistan 27.04 2019
72 Mongolia 27.00 2019
73 Yemen 26.51 2019
74 Djibouti 26.14 2019
75 El Salvador 25.63 2019
76 Moldova 24.98 2019
77 São Tomé and Principe 24.32 2019
78 Belize 24.07 2019
79 Botswana 23.94 2019
80 Cuba 23.73 2019
81 Sri Lanka 23.63 2019
82 Namibia 23.62 2019
83 Paraguay 22.62 2019
84 The Gambia 22.56 2019
85 Colombia 22.31 2019
86 Fiji 22.17 2019
87 Turkmenistan 22.10 2019
88 Armenia 21.69 2019
89 Romania 21.42 2019
90 Gabon 20.99 2019
91 Jamaica 20.91 2019
92 Egypt 20.46 2019
93 Guyana 20.08 2019
94 Kyrgyz Republic 19.62 2019
95 Iraq 18.66 2019
96 Panama 18.50 2019
97 Mexico 17.85 2019
98 Serbia 17.47 2019
99 Iran 17.06 2019
100 Costa Rica 16.72 2019
101 Libya 16.65 2019
102 Bosnia and Herzegovina 16.44 2019
103 Kazakhstan 16.33 2019
104 Ukraine 15.99 2019
105 St. Lucia 15.63 2019
106 Tunisia 15.32 2019
107 Turkey 14.85 2019
108 Cabo Verde 14.70 2019
109 Belarus 14.55 2019
110 North Macedonia 14.49 2019
111 St. Vincent and the Grenadines 14.23 2019
112 Eswatini 13.96 2019
113 Dominican Republic 13.49 2019
114 Malaysia 12.99 2019
115 Brazil 12.81 2019
116 Greece 12.31 2019
117 Venezuela 12.27 2019
118 Uruguay 12.08 2019
119 Chile 12.04 2019
120 Lebanon 11.88 2019
121 Algeria 10.76 2019
122 Syrian Arab Republic 10.68 2019
123 Latvia 10.29 2019
124 Suriname 10.11 2019
125 Poland 10.01 2019
126 Lithuania 8.77 2019
127 Bulgaria 8.63 2019
128 New Zealand 7.74 2019
129 Croatia 7.71 2019
130 Montenegro 7.57 2019
130 Russia 7.57 2019
132 Portugal 7.28 2019
133 Mauritius 7.23 2019
134 Ireland 7.18 2019
135 South Africa 6.46 2019
136 Iceland 6.42 2019
137 Hungary 6.29 2019
138 Spain 5.68 2019
139 Finland 5.38 2019
140 Korea 5.37 2019
141 Italy 4.99 2019
142 Slovenia 4.97 2019
143 Estonia 4.70 2019
144 Oman 4.49 2019
145 Trinidad and Tobago 4.28 2019
146 Austria 4.07 2019
147 Slovak Republic 3.98 2019
148 The Bahamas 3.89 2019
149 Japan 3.72 2019
150 Barbados 3.69 2019
151 France 3.50 2019
152 Czech Republic 3.41 2019
153 Cyprus 3.36 2019
154 Australia 3.29 2019
155 Denmark 3.22 2019
156 Switzerland 3.12 2019
157 Norway 2.93 2019
158 Brunei 2.85 2019
159 Jordan 2.81 2019
160 Saudi Arabia 2.72 2019
161 New Caledonia 2.70 2019
162 Netherlands 2.68 2019
163 Sweden 2.59 2019
164 Kuwait 2.34 2019
165 Canada 1.97 2019
166 United States 1.87 2019
167 Puerto Rico 1.71 2019
168 United Arab Emirates 1.67 2019
169 Germany 1.53 2019
170 United Kingdom 1.46 2019
171 Malta 1.40 2019
172 Qatar 1.35 2019
173 Israel 1.32 2019
174 Belgium 1.17 2019
175 Bahrain 1.16 2019
176 Luxembourg 0.90 2019
177 Macao SAR, China 0.67 2019
178 Hong Kong SAR, China 0.23 2019
179 Argentina 0.08 2019
180 Singapore 0.05 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