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 96.33 2019
2 Chad 83.65 2019
3 Mozambique 81.49 2019
4 Nepal 79.81 2019
5 Dem. Rep. Congo 76.62 2019
6 Malawi 76.48 2019
7 Somalia 76.28 2019
8 Rwanda 76.22 2019
9 Uganda 75.69 2019
10 Central African Republic 74.64 2019
11 Pakistan 72.50 2019
12 Zimbabwe 71.61 2019
13 Niger 71.18 2019
14 Guinea 69.97 2019
15 Papua New Guinea 69.94 2019
16 Guinea-Bissau 69.92 2019
17 Lao PDR 69.34 2019
18 Tanzania 68.86 2019
19 Tajikistan 68.81 2019
20 Eritrea 66.25 2019
21 Dem. People's Rep. Korea 64.84 2019
22 Madagascar 64.61 2019
23 Bhutan 64.32 2019
24 Kenya 63.38 2019
25 Mali 63.02 2019
26 Comoros 62.73 2019
27 Vanuatu 62.28 2019
28 Solomon Islands 62.20 2019
29 Zambia 61.79 2019
30 Bangladesh 59.03 2019
31 Morocco 58.98 2019
32 Yemen 58.85 2019
33 Ethiopia 58.76 2019
34 Sudan 58.67 2019
35 Lesotho 57.88 2019
36 Sierra Leone 56.57 2019
37 India 56.50 2019
38 Gabon 56.39 2019
39 Afghanistan 55.42 2019
40 Angola 55.25 2019
41 Mauritania 54.00 2019
42 Djibouti 51.94 2019
43 Cameroon 51.53 2019
44 Timor-Leste 49.41 2019
45 Liberia 45.77 2019
46 Georgia 45.24 2019
47 Myanmar 44.44 2019
48 Albania 42.04 2019
49 Azerbaijan 41.69 2019
50 Equatorial Guinea 41.36 2019
51 Vietnam 40.74 2019
52 Côte d'Ivoire 39.71 2019
53 Fiji 38.35 2019
54 Uzbekistan 37.23 2019
55 Armenia 36.44 2019
56 The Gambia 36.44 2019
57 Egypt 36.42 2019
58 Congo 36.42 2019
59 Haiti 34.07 2019
60 Benin 33.36 2019
61 Cambodia 30.03 2019
62 Sri Lanka 29.04 2019
63 Togo 28.61 2019
64 Indonesia 28.24 2019
65 Bolivia 28.13 2019
66 Moldova 27.67 2019
67 Turkey 27.65 2019
68 Thailand 27.64 2019
69 Kyrgyz Republic 27.48 2019
70 Senegal 26.80 2019
71 Nigeria 26.14 2019
72 Ghana 26.04 2019
73 Mongolia 25.81 2019
74 Peru 25.55 2019
75 Ecuador 24.36 2019
76 China 24.03 2019
77 Iraq 23.34 2019
78 Romania 21.88 2019
79 Turkmenistan 21.80 2019
80 Iran 20.84 2019
81 Burkina Faso 19.84 2019
82 Botswana 17.62 2019
83 Namibia 17.34 2019
84 Bosnia and Herzegovina 16.54 2019
85 North Macedonia 15.55 2019
86 Lebanon 15.45 2019
87 Philippines 14.98 2019
88 Paraguay 14.66 2019
89 Serbia 14.57 2019
90 Kazakhstan 14.10 2019
91 Syrian Arab Republic 13.39 2019
92 Ukraine 12.90 2019
93 São Tomé and Principe 12.14 2019
94 Tunisia 11.41 2019
95 Greece 11.18 2019
96 Eswatini 10.79 2019
97 Honduras 9.34 2019
98 Guatemala 9.21 2019
99 Nicaragua 9.14 2019
100 Libya 8.99 2019
101 Jamaica 8.93 2019
102 Poland 8.65 2019
103 Panama 8.46 2019
104 Cabo Verde 8.05 2019
105 Colombia 7.51 2019
106 Cuba 7.51 2019
107 Belarus 7.14 2019
108 Montenegro 6.74 2019
109 St. Vincent and the Grenadines 6.61 2019
110 Malaysia 6.53 2019
111 Guyana 6.13 2019
112 Mauritius 5.82 2019
113 Lithuania 5.22 2019
114 Belize 5.18 2019
115 Chile 5.17 2019
116 Croatia 4.98 2019
117 Slovenia 4.69 2019
118 Costa Rica 4.42 2019
119 Bulgaria 4.40 2019
120 Korea 4.36 2019
121 Brazil 4.16 2019
122 New Zealand 4.15 2019
123 Portugal 4.05 2019
124 Latvia 4.05 2019
125 St. Lucia 4.04 2019
126 Russia 3.95 2019
127 El Salvador 3.88 2019
128 Suriname 3.87 2019
129 Uruguay 3.74 2019
130 Mexico 3.64 2019
131 South Africa 3.61 2019
132 Austria 3.58 2019
133 Tonga 3.39 2019
134 Samoa 3.22 2019
135 Algeria 3.09 2019
136 Japan 2.92 2019
137 Hungary 2.75 2019
138 Switzerland 2.52 2019
139 Italy 2.28 2019
140 Spain 2.18 2019
141 Finland 2.08 2019
142 Iceland 1.89 2019
143 Estonia 1.86 2019
144 Barbados 1.77 2019
145 Czech Republic 1.74 2019
146 Australia 1.61 2019
147 Trinidad and Tobago 1.54 2019
148 France 1.53 2019
149 Ireland 1.49 2019
150 Netherlands 1.41 2019
151 New Caledonia 1.33 2019
152 Slovak Republic 1.33 2019
153 Venezuela 1.30 2019
154 Dominican Republic 1.27 2019
155 Macao SAR, China 1.13 2019
156 Jordan 1.11 2019
157 Cyprus 1.04 2019
158 Sweden 0.98 2019
159 Denmark 0.97 2019
160 Canada 0.93 2019
161 Norway 0.91 2019
162 Germany 0.86 2019
163 United States 0.74 2019
164 Belgium 0.68 2019
165 Luxembourg 0.67 2019
166 United Kingdom 0.62 2019
167 Israel 0.49 2019
168 Puerto Rico 0.47 2019
169 The Bahamas 0.43 2019
170 Brunei 0.42 2019
171 Oman 0.38 2019
172 Singapore 0.23 2019
173 Malta 0.21 2019
174 Hong Kong SAR, China 0.13 2019
175 United Arab Emirates 0.13 2019
176 Saudi Arabia 0.11 2019
177 Bahrain 0.05 2019
178 Kuwait 0.04 2019
179 Qatar 0.03 2019
180 Argentina 0.02 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