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 Burundi 87.29 2019
2 Chad 79.57 2019
3 Niger 79.13 2019
4 Lesotho 73.58 2019
5 Somalia 71.36 2019
6 Ethiopia 71.03 2019
7 Madagascar 71.00 2019
8 Central African Republic 70.67 2019
9 Malawi 67.35 2019
10 Mali 66.33 2019
11 Lao PDR 66.07 2019
12 Guinea-Bissau 65.99 2019
13 Uganda 65.50 2019
14 Papua New Guinea 65.02 2019
15 Zimbabwe 63.32 2019
16 Haiti 63.17 2019
17 Tanzania 62.78 2019
18 Guinea 62.21 2019
19 Dem. Rep. Congo 60.73 2019
20 Mozambique 60.61 2019
21 Solomon Islands 60.33 2019
22 Sierra Leone 60.31 2019
23 Vanuatu 59.90 2019
24 Eritrea 59.36 2019
25 Nepal 58.99 2019
26 Mauritania 55.41 2019
27 Dem. People's Rep. Korea 55.32 2019
28 Rwanda 55.13 2019
29 Myanmar 53.12 2019
30 Côte d'Ivoire 53.12 2019
31 Comoros 52.18 2019
32 Bhutan 51.11 2019
33 Kenya 50.98 2019
34 Timor-Leste 50.18 2019
35 Benin 48.38 2019
36 Djibouti 47.39 2019
37 Tonga 46.99 2019
38 Zambia 46.03 2019
39 Liberia 45.84 2019
40 Nigeria 44.89 2019
41 Nicaragua 44.80 2019
42 Honduras 44.63 2019
43 Angola 42.41 2019
44 Tajikistan 42.19 2019
45 Cameroon 41.20 2019
46 Equatorial Guinea 41.15 2019
47 Georgia 40.44 2019
48 Ghana 40.36 2019
49 Fiji 39.56 2019
50 Togo 39.54 2019
51 India 39.53 2019
52 Guatemala 39.37 2019
53 Sudan 38.27 2019
54 Vietnam 38.24 2019
55 Moldova 36.22 2019
56 Congo 35.26 2019
57 Burkina Faso 34.75 2019
58 Albania 34.68 2019
59 Senegal 34.58 2019
60 Yemen 33.94 2019
61 Pakistan 32.81 2019
62 Thailand 32.77 2019
63 Indonesia 31.55 2019
64 Bangladesh 31.43 2019
65 Morocco 31.29 2019
66 Philippines 31.16 2019
67 Mongolia 30.95 2019
68 Azerbaijan 30.48 2019
69 Armenia 30.39 2019
70 Uzbekistan 30.35 2019
71 Cambodia 30.15 2019
72 Ecuador 29.28 2019
73 São Tomé and Principe 29.06 2019
74 El Salvador 28.94 2019
75 Afghanistan 28.93 2019
76 Peru 28.60 2019
77 China 28.53 2019
78 Bolivia 27.84 2019
79 Botswana 26.84 2019
80 Gabon 26.61 2019
81 Kyrgyz Republic 25.66 2019
82 Belize 24.87 2019
83 Guyana 24.56 2019
84 Cuba 24.43 2019
85 The Gambia 24.27 2019
86 Sri Lanka 23.96 2019
87 Turkmenistan 23.20 2019
88 Paraguay 23.12 2019
89 Romania 22.89 2019
90 Colombia 22.42 2019
91 Jamaica 22.31 2019
92 Egypt 21.64 2019
93 Namibia 21.44 2019
94 Serbia 18.81 2019
95 St. Vincent and the Grenadines 18.47 2019
96 Mexico 18.13 2019
97 Cabo Verde 17.98 2019
98 Iraq 17.93 2019
99 Panama 17.90 2019
100 Ukraine 17.42 2019
101 Costa Rica 17.08 2019
102 Iran 16.45 2019
103 North Macedonia 16.27 2019
104 Bosnia and Herzegovina 16.26 2019
105 Tunisia 16.21 2019
106 Kazakhstan 15.62 2019
107 Turkey 15.08 2019
108 Syrian Arab Republic 14.84 2019
109 Dominican Republic 14.63 2019
110 St. Lucia 14.58 2019
111 Eswatini 14.46 2019
112 Belarus 13.90 2019
113 Malaysia 13.69 2019
114 Brazil 13.04 2019
115 Uruguay 12.42 2019
116 Greece 12.33 2019
117 Chile 11.77 2019
118 Poland 11.19 2019
119 Lebanon 10.85 2019
120 Venezuela 10.77 2019
121 Algeria 10.39 2019
122 Lithuania 10.14 2019
123 Latvia 9.45 2019
124 Bulgaria 9.03 2019
125 Suriname 8.73 2019
126 Montenegro 8.57 2019
127 Croatia 8.43 2019
128 Portugal 8.38 2019
129 Ireland 7.92 2019
130 New Zealand 7.86 2019
131 Mauritius 7.70 2019
132 Russia 7.49 2019
133 Libya 7.35 2019
134 Hungary 6.77 2019
135 Samoa 6.30 2019
136 South Africa 6.25 2019
137 Slovenia 6.13 2019
138 Spain 5.98 2019
139 Saudi Arabia 5.59 2019
140 Iceland 5.29 2019
141 Oman 5.23 2019
142 Finland 5.18 2019
143 Estonia 4.97 2019
144 Korea 4.92 2019
145 Italy 4.75 2019
146 The Bahamas 4.42 2019
147 Trinidad and Tobago 4.33 2019
148 United Arab Emirates 4.27 2019
149 Austria 4.11 2019
150 Jordan 3.87 2019
151 Slovak Republic 3.77 2019
152 Barbados 3.75 2019
153 Japan 3.73 2019
154 Cyprus 3.70 2019
155 Czech Republic 3.56 2019
156 Switzerland 3.52 2019
157 France 3.50 2019
158 New Caledonia 3.45 2019
159 Australia 3.35 2019
160 Denmark 3.24 2019
161 Kuwait 3.22 2019
162 Norway 3.03 2019
163 Macao SAR, China 2.92 2019
164 Netherlands 2.92 2019
165 Sweden 2.54 2019
166 Brunei 2.00 2019
167 Canada 1.99 2019
168 United States 1.98 2019
169 Puerto Rico 1.97 2019
170 Luxembourg 1.95 2019
171 Germany 1.60 2019
172 United Kingdom 1.58 2019
173 Belgium 1.53 2019
174 Malta 1.51 2019
175 Qatar 1.42 2019
176 Israel 1.40 2019
177 Bahrain 1.27 2019
178 Singapore 0.66 2019
179 Hong Kong SAR, China 0.27 2019
180 Argentina 0.09 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