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Selim Raihan Executive Director South Asian Network on Economic Modeling (SANEM) Prepared for ESCAP/UNDP/ARTNeT Workshop on Trade and Gender Linkages Bangkok, Thailand, 16 September 2010 1 Wage Discrimination High Female Domestic Work Low Female Labour Market Participation Concentration in Export-Oriented Activities Entry into Labour Market and Leisure/Welfare Implications for unskilled females 2 Country Female wage as a % of male wage Country Female wage as a % of male wage Mexico 86% (1995) Burkina Faso 70% in protected, 64% in unprotected sector (1996) Salvador 41% (1978) Cameroon 75% in protected, 42% in unprotected sector (1996) Bangkok formal 64% & informal 83%(1987) Guinea and Mali 62%in protected, 88% in unprotected sector (1996) South Korea 50% in manufacturing (1995) Nepal 58% (1998-99) Sri Lanka 88% in manufacturing (1995) Zambia Low education 65%, High education 95% (1995) Bangladesh: No education 50%, High education 70% (1993) World average: 75 % for non-agricultural occupations, somewhat lower in manufacturing (1998) 3 Female involvement in unpaid work and paid Informal sector Leisure decreases with increased demand for income earning activities Rural Urban Male Female Male Female Market Activities 35 17 36 12 Domestic Work 4 22 2 24 Personal Care 42 41 43 43 Leisure 9 20 19 21 Total 100 100 100 100 Bangladesh: Time allocation figures, 2005 (%) 4 Asia: Female participation in official labour force has increased in absolute terms, but varies around 12% of the total Asia and Latin America: Home workers in garments Africa: Female participation in both agricultural and non-agricultural activities is higher than male 5 Urban Rural Bangladesh Major Activity Male Female All Male Female All Male Female All Agriculture, Forestry 20.9 42.4 25.9 54.9 63.9 56.9 46.8 58.5 49.4 Fishing 1.3 0.1 1 3.5 0.2 2.8 3 0.2 2.4 Mining and Quarrying 0.1 0 0.1 0.3 0 0.2 0.2 0 0.2 Manufacturing 11.3 23 14 6.5 15.4 8.4 7.6 17.3 9.8 Electricity, Water and Gas 0.5 0.3 0.5 0.2 0 0.1 0.3 0.1 0.2 Construction 6.4 1.2 5.2 3.5 0.9 2.9 4.2 1 3.5 Trade Services 26.1 3.4 20.8 14.3 1.7 11.5 17.1 2.2 13.8 Hotel 2.5 0.6 2 1.2 0.2 1 1.5 0.3 1.3 Transport and Storage 12 0.6 9.3 7.6 0.1 6 8.7 0.3 6.8 Finance, Business, Services 1.7 0.6 1.4 0.2 0.1 0.2 0.6 0.2 0.5 Real Estate 1.2 0.2 1 0.3 0 0.3 0.5 0.1 0.4 Public Admin 5.8 2 4.9 1.6 0.5 1.4 2.6 0.9 2.2 Education 3.4 6.3 4 2.2 2.2 2.2 2.5 3.2 2.7 Health & Social Workers 1.8 2.6 2 0.8 1.1 0.9 1 1.5 1.1 Community, Personal Services 5 16.6 7.7 2.8 13.6 5.1 3.3 14.4 5.8 All Sector 100 100 100 100 100 100 100 100 100 6
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Page 1: Selim Raihan - ARTNeT: Asia-Pacific Research and Training ... · Selim Raihan Executive Director South Asian Network on Economic Modeling (SANEM) Prepared for ESCAP/UNDP/ARTNeT Workshop

Selim RaihanExecutive Director

South Asian Network on Economic Modeling (SANEM)

Prepared for ESCAP/UNDP/ARTNeT Workshop on

Trade and Gender Linkages

Bangkok, Thailand, 16 September 20101

� Wage Discrimination

� High Female Domestic Work

� Low Female Labour Market Participation

� Concentration in Export-Oriented Activities

� Entry into Labour Market and Leisure/Welfare Implications for unskilled females

2

Country Female wage as a % of male wage

Country Female wage as a % of male wage

Mexico 86% (1995) Burkina Faso 70% in protected, 64% in unprotected

sector (1996) Salvador 41% (1978) Cameroon 75% in protected,

42% in unprotected sector (1996)

Bangkok formal 64% & informal 83%(1987)

Guinea and Mali 62%in protected, 88% in unprotected

sector (1996) South Korea 50% in

manufacturing (1995) Nepal 58% (1998-99)

Sri Lanka 88% in manufacturing (1995)

Zambia Low education 65%, High education 95%

(1995) Bangladesh: No education 50%, High education 70% (1993)

World average: 75 % for non-agricultural occupations, somewhat lower in manufacturing (1998)

3

� Female involvement in unpaid work and paid Informal sector

� Leisure decreases with increased demand for income earning activities

Rural Urban

Male Female Male Female

Market Activities 35 17 36 12

Domestic Work 4 22 2 24

Personal Care 42 41 43 43

Leisure 9 20 19 21

Total 100 100 100 100

Bangladesh: Time allocation figures, 2005 (%)

4

� Asia: Female participation in official labour force has increased in absolute terms, but varies around 12% of the total

� Asia and Latin America: Home workers in garments

� Africa: Female participation in both agricultural and non-agricultural activities is higher than male

5

Urban Rural Bangladesh

Major Activity Male Female All Male Female All Male Female All

Agriculture, Forestry 20.9 42.4 25.9 54.9 63.9 56.9 46.8 58.5 49.4

Fishing 1.3 0.1 1 3.5 0.2 2.8 3 0.2 2.4

Mining and Quarrying 0.1 0 0.1 0.3 0 0.2 0.2 0 0.2

Manufacturing 11.3 23 14 6.5 15.4 8.4 7.6 17.3 9.8

Electricity, Water and Gas 0.5 0.3 0.5 0.2 0 0.1 0.3 0.1 0.2

Construction 6.4 1.2 5.2 3.5 0.9 2.9 4.2 1 3.5

Trade Services 26.1 3.4 20.8 14.3 1.7 11.5 17.1 2.2 13.8

Hotel 2.5 0.6 2 1.2 0.2 1 1.5 0.3 1.3

Transport and Storage 12 0.6 9.3 7.6 0.1 6 8.7 0.3 6.8

Finance, Business, Services 1.7 0.6 1.4 0.2 0.1 0.2 0.6 0.2 0.5

Real Estate 1.2 0.2 1 0.3 0 0.3 0.5 0.1 0.4

Public Admin 5.8 2 4.9 1.6 0.5 1.4 2.6 0.9 2.2

Education 3.4 6.3 4 2.2 2.2 2.2 2.5 3.2 2.7

Health & Social Workers 1.8 2.6 2 0.8 1.1 0.9 1 1.5 1.1

Community, Personal Services 5 16.6 7.7 2.8 13.6 5.1 3.3 14.4 5.8

All Sector 100 100 100 100 100 100 100 100 1006

Page 2: Selim Raihan - ARTNeT: Asia-Pacific Research and Training ... · Selim Raihan Executive Director South Asian Network on Economic Modeling (SANEM) Prepared for ESCAP/UNDP/ARTNeT Workshop

� In the Asian context, the fast-growing East Asian countries’ labour markets experienced declining female participation in the manufacturing and services sector with increased globalisation (Joekes 1995, World Bank 1993)

� In some other Asian countries like Bangladesh, India, Sri Lanka, Vietnam and China, the situation was the reverse (Mitter and Rowbotham 1995, Pearson and Mitter 1993).

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� An increase in female labour force participation does not necessarily reflect female welfare increase; the maintenance of a ‘care economy’ has absolute female labour intensity without a matched increase in male participation in domestic work to address the decline in female labour hours devoted to such work.

� As a result, time for personal care and leisure declines with increased female labour force participation, and this has a negative impact on their welfare.

� Men and women may be affected differently by a state’s macroeconomic policies, depending on the sectors in which they work.

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