Employment in agriculture, female (% of female 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 93.66 2019
2 Somalia 83.89 2019
3 Malawi 82.00 2019
4 Mozambique 79.78 2019
5 Uganda 76.77 2019
6 Nepal 74.08 2019
7 Chad 73.39 2019
8 Central African Republic 72.61 2019
9 Dem. Rep. Congo 71.51 2019
10 Rwanda 70.98 2019
11 Zimbabwe 69.48 2019
12 Niger 69.47 2019
13 Eritrea 68.35 2019
14 Tanzania 66.71 2019
15 Pakistan 65.18 2019
16 Afghanistan 64.96 2019
17 Guinea-Bissau 64.14 2019
18 Bhutan 64.01 2019
19 Lao PDR 63.54 2019
20 Mali 62.58 2019
21 Guinea 61.80 2019
22 Papua New Guinea 60.14 2019
23 Tajikistan 60.05 2019
24 Madagascar 59.94 2019
25 Kenya 59.34 2019
26 Ethiopia 58.71 2019
27 Bangladesh 57.57 2019
28 Vanuatu 56.79 2019
29 Angola 56.78 2019
30 India 54.69 2019
31 Zambia 54.66 2019
32 Morocco 52.12 2019
33 Sudan 51.83 2019
34 Sierra Leone 51.47 2019
35 Cameroon 47.70 2019
36 Dem. People's Rep. Korea 47.15 2019
37 Gabon 45.76 2019
38 Equatorial Guinea 42.50 2019
39 Myanmar 42.44 2019
40 Yemen 42.28 2019
41 Azerbaijan 41.80 2019
42 Albania 41.63 2019
43 Liberia 40.33 2019
44 Georgia 40.09 2019
45 Lesotho 39.83 2019
46 Timor-Leste 39.17 2019
47 Vietnam 38.30 2019
48 Solomon Islands 37.62 2019
49 Cambodia 36.57 2019
50 The Gambia 33.07 2019
51 Congo 32.04 2019
52 Comoros 31.57 2019
53 Côte d'Ivoire 31.04 2019
54 Bolivia 30.31 2019
55 Benin 29.76 2019
56 Thailand 28.27 2019
57 Sri Lanka 27.63 2019
58 Ecuador 27.14 2019
59 Armenia 26.89 2019
60 Togo 26.87 2019
61 Indonesia 26.36 2019
62 Peru 26.34 2019
63 Turkey 25.05 2019
64 Senegal 24.75 2019
65 Uzbekistan 23.79 2019
66 Nigeria 23.57 2019
67 Mongolia 23.35 2019
68 Djibouti 22.14 2019
69 Ghana 22.10 2019
70 China 22.01 2019
71 Mauritania 21.94 2019
72 Burkina Faso 21.41 2019
73 Egypt 21.21 2019
74 Romania 21.01 2019
75 Bosnia and Herzegovina 20.47 2019
76 Namibia 20.10 2019
77 Kyrgyz Republic 18.81 2019
78 Iran 18.79 2019
79 Turkmenistan 18.68 2019
80 Moldova 16.93 2019
81 Libya 15.89 2019
82 Botswana 15.28 2019
83 Iraq 15.05 2019
84 Philippines 13.61 2019
85 Serbia 13.27 2019
86 Kazakhstan 13.25 2019
87 Haiti 13.10 2019
88 North Macedonia 13.01 2019
89 Paraguay 12.81 2019
90 Ukraine 11.41 2019
91 Greece 10.60 2019
92 Eswatini 10.10 2019
93 Guatemala 9.78 2019
94 Lebanon 9.49 2019
95 Tunisia 8.96 2019
96 São Tomé and Principe 8.56 2019
97 Honduras 8.27 2019
98 Panama 8.25 2019
99 Nicaragua 8.23 2019
100 Jamaica 8.22 2019
101 Fiji 8.21 2019
102 Poland 8.08 2019
103 Guyana 7.88 2019
104 Belarus 7.51 2019
105 Cuba 7.27 2019
106 Syrian Arab Republic 6.85 2019
107 Samoa 6.64 2019
108 Montenegro 6.61 2019
109 Colombia 6.60 2019
110 Malaysia 5.89 2019
111 Cabo Verde 5.47 2019
112 Korea 4.83 2019
113 Chile 4.74 2019
114 Belize 4.69 2019
115 Suriname 4.52 2019
116 Croatia 4.43 2019
117 Latvia 4.35 2019
118 Bulgaria 4.30 2019
119 St. Vincent and the Grenadines 4.25 2019
120 Lithuania 4.15 2019
121 Costa Rica 4.05 2019
122 Brazil 4.02 2019
123 Russia 4.01 2019
124 Mauritius 3.93 2019
125 Uruguay 3.84 2019
126 South Africa 3.79 2019
127 New Zealand 3.72 2019
128 Portugal 3.62 2019
129 Mexico 3.61 2019
130 Slovenia 3.48 2019
131 El Salvador 3.44 2019
132 Algeria 3.38 2019
133 Austria 3.18 2019
134 Japan 2.95 2019
135 St. Lucia 2.89 2019
136 Hungary 2.84 2019
137 Italy 2.38 2019
138 Finland 2.07 2019
139 Spain 2.04 2019
140 Switzerland 1.98 2019
141 Czech Republic 1.74 2019
142 Australia 1.71 2019
143 Barbados 1.58 2019
144 Tonga 1.52 2019
145 Estonia 1.51 2019
146 France 1.49 2019
147 Iceland 1.40 2019
148 Dominican Republic 1.39 2019
149 Netherlands 1.38 2019
150 Trinidad and Tobago 1.34 2019
150 Slovak Republic 1.34 2019
152 Cyprus 1.28 2019
153 Ireland 1.21 2019
154 Denmark 1.11 2019
155 Norway 1.04 2019
156 Canada 1.00 2019
157 Venezuela 0.92 2019
158 New Caledonia 0.85 2019
159 Germany 0.83 2019
160 United States 0.76 2019
161 Jordan 0.75 2019
162 Brunei 0.72 2019
163 Sweden 0.70 2019
164 Belgium 0.63 2019
165 United Kingdom 0.58 2019
166 Israel 0.46 2019
167 Malta 0.45 2019
168 Luxembourg 0.43 2019
169 The Bahamas 0.34 2019
170 Saudi Arabia 0.33 2019
171 Puerto Rico 0.31 2019
172 Oman 0.30 2019
173 Hong Kong SAR, China 0.11 2019
173 Macao SAR, China 0.11 2019
175 Bahrain 0.04 2019
176 Kuwait 0.03 2019
176 Argentina 0.03 2019
178 United Arab Emirates 0.01 2019
178 Qatar 0.01 2019
178 Singapore 0.01 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