Employment in agriculture, female (% of female employment) - 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, Key Indicators of the Labour Market database.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Burundi 96.60 1998
2 Equatorial Guinea 89.90 1983
2 Mozambique 89.90 2003
4 Chad 85.90 1993
5 Rwanda 84.40 2012
6 Nepal 84.30 2008
7 Guinea 82.00 2012
8 Uganda 77.50 2009
9 Pakistan 74.00 2014
10 Lao PDR 73.50 2010
11 Madagascar 73.20 2012
12 Zimbabwe 71.60 2011
13 Sierra Leone 71.10 2004
14 Tanzania 70.00 2014
15 Malawi 69.90 2013
16 Tajikistan 68.50 2009
17 Kenya 68.00 2005
18 Burkina Faso 67.30 2007
19 Bhutan 65.70 2013
20 Bangladesh 64.80 2010
21 Cameroon 64.70 2001
21 Ethiopia 64.70 2013
23 Mali 63.90 2006
24 Vanuatu 62.30 2009
25 Sudan 60.70 2011
26 Morocco 59.90 2012
27 India 59.70 2012
28 Albania 56.90 2009
29 Georgia 56.60 2007
30 Cambodia 55.40 2010
31 Zambia 53.40 2012
32 Iraq 50.70 2008
33 Timor-Leste 50.20 2010
34 Senegal 49.10 2011
35 Vietnam 48.80 2013
36 Togo 48.20 2006
37 Liberia 46.40 2010
38 Armenia 44.50 2013
39 Azerbaijan 43.50 2013
40 Egypt 42.90 2013
41 Nigeria 41.50 2007
42 Ghana 41.40 2013
43 Congo 39.30 2005
43 Thailand 39.30 2013
45 The Gambia 38.20 2014
46 Niger 37.80 2005
46 Benin 37.80 2010
48 Haiti 37.30 1999
49 Bolivia 34.70 2008
50 Mongolia 34.20 2012
51 Sri Lanka 33.90 2014
52 Gabon 33.70 2005
53 Indonesia 33.40 2013
54 Kyrgyz Republic 32.90 2013
55 Turkey 31.70 2014
56 Namibia 30.90 2013
57 Yemen 28.00 2010
58 Romania 25.60 2014
59 Moldova 25.40 2013
60 São Tomé and Principe 23.70 2012
61 Kazakhstan 23.20 2013
62 Tunisia 22.70 1989
63 Iran 21.80 2014
64 Botswana 21.30 2010
65 Ecuador 20.30 2013
66 Philippines 20.10 2013
67 Serbia 19.80 2013
68 Macedonia 18.10 2014
69 Paraguay 16.60 2014
70 Ukraine 13.00 2014
71 Greece 12.40 2014
72 Syrian Arab Republic 12.30 2011
73 Guatemala 10.90 2013
74 Honduras 10.30 2013
75 Brazil 10.10 2013
76 Poland 10.00 2014
77 Grenada 9.70 1998
78 Kiribati 9.00 2010
79 Mauritius 8.50 2014
79 Panama 8.50 2012
79 St. Lucia 8.50 2006
82 St. Vincent and the Grenadines 8.40 2008
83 Dominica 8.30 2001
83 Malaysia 8.30 2013
85 Jamaica 8.20 2013
86 Belarus 7.80 2009
87 Cuba 7.70 2013
88 Slovenia 7.60 2014
89 Croatia 7.10 2014
89 Guyana 7.10 2002
91 Colombia 6.60 2014
91 Lithuania 6.60 2014
93 Nicaragua 6.20 2008
93 Korea 6.20 2013
95 Peru 5.50 2008
96 Russia 5.20 2014
97 Lesotho 4.60 2008
97 Tonga 4.60 2003
97 Montenegro 4.60 2014
97 Chile 4.60 2013
101 Bulgaria 4.50 2014
101 El Salvador 4.50 2013
103 Uruguay 4.40 2013
104 Latvia 4.20 2014
104 New Zealand 4.20 2013
106 Portugal 4.10 2014
106 New Caledonia 4.10 1996
106 Austria 4.10 2014
109 Mexico 3.70 2013
110 Samoa 3.50 2012
110 China 3.50 2007
112 Costa Rica 3.40 2013
113 Belize 3.30 2005
113 Japan 3.30 2013
115 South Africa 3.20 2014
116 Palau 3.10 2000
117 Algeria 2.90 2011
118 Dominican Republic 2.80 2014
119 Hungary 2.60 2014
120 Switzerland 2.40 2014
121 Italy 2.30 2014
121 Estonia 2.30 2014
123 Finland 2.20 2014
123 Spain 2.20 2014
125 Iceland 1.90 2014
126 Cyprus 1.80 2014
126 Trinidad and Tobago 1.80 2008
126 The Bahamas 1.80 2011
129 Australia 1.70 2013
129 Suriname 1.70 2013
129 Slovak Republic 1.70 2014
132 Ireland 1.60 2014
132 France 1.60 2014
132 Venezuela 1.60 2011
132 Czech Republic 1.60 2014
132 Barbados 1.60 2013
137 Antigua and Barbuda 1.20 2008
137 Canada 1.20 2014
137 Netherlands 1.20 2014
140 Norway 1.00 2014
141 Denmark 0.90 2014
141 Germany 0.90 2014
143 Belgium 0.80 2014
143 Sweden 0.80 2014
143 United States 0.80 2010
143 Singapore 0.80 2006
147 Luxembourg 0.70 2014
147 Seychelles 0.70 2011
149 United Kingdom 0.60 2014
150 Oman 0.50 2010
150 Jordan 0.50 2014
152 Fiji 0.40 2007
152 Malta 0.40 2014
152 Brunei 0.40 2014
155 Greenland 0.30 2011
155 Israel 0.30 2014
157 Puerto Rico 0.20 2011
157 Argentina 0.20 2014
157 Cayman Islands 0.20 2013
157 San Marino 0.20 2010
157 Saudi Arabia 0.20 2013
162 United Arab Emirates 0.10 2009
162 Hong Kong SAR, China 0.10 2007
162 St. Kitts and Nevis 0.10 2001
165 Macao SAR, China 0.00 2014
165 Kuwait 0.00 2014
165 Bahrain 0.00 2010
165 Qatar 0.00 2013

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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. Data on employment are drawn from a variety of sources including labor force surveys, household surveys, official estimates, and censuses. In a very few cases and only where other types of sources are not available, information is derived from insurance records and establishment surveys Employment data include both full-time and part-time workers.

Aggregation method: Weighted average

Periodicity: Annual

General Comments: Relevance to gender indicator: Men still make up the majority of people employed in all three sectors, but the gender gap is biggest in industry. Employment in agriculture is also male-dominated, although not as much as industry. 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. There are several explanations for the rising importance of service jobs for women. Many service jobs— such as nursing and social and clerical work—are considered “feminine” because of a perceived similarity to women’s traditional roles. Women often do not receive the training needed to take advantage of changing employment opportunities. And the greater availability of part-time work in service industries may lure more women, although it is unclear whether this is a cause or an effect