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Employment Opportunity in Informal sector: A Case study of Delhi Slum

Employment Opportunity in Informal sector: A Case study of Delhi Slum

 
The informal sector plays a vital role in providing livelihood opportunity in terms of employment for urban poor and the informal sector has been contributing significantly in reducing poverty in the urban economy.

However, this not spillover across urban centers in general and in slum areas in particular. The recent study done by V. Jegatheesan, Council for Social Development on employment scenarios of informal sector in the slum resettlement colony of Delhi reveals the fact that the growing casualisation labour, high youth unemployment rate and feminization of labour force in informal sector. 

This study is based on sustainability and implications of the informal sector and the employment scenarios in the slum resettlement colony of Delhi.  The unorganized sector is called so because the activities in the sector cannot be accounted statistically. And they are generally accounted as a residual of the organized sector. Its employment in Delhi has been increasing since the 1990s. In 1993–94, unorganized sector workers accounted for 76 per cent of employment in Delhi. By 1999–2000, the proportion had risen to 81 per cent.

There is strong evidence to suggest the increasing informalization of Delhi’s economy as well.  The city peripheries are getting degenerated with low value employment, poor living condition, thus making the lot of the urban poor worse.   For the vast majority of them there is no fixed place of work, no fixed working hours, no regular wages, no job security. Thus they have become one of the most vulnerable to poverty.  Globalization is argued to be ‘informalising’ and ‘casualising’ the employment opportunities in the urban economy thus further expanding the unorganised form of employment. 

The slum labour market have been analyzed through binary logistic regression model with gender, age, education, caste and occupation and their food expenditure has been analyzed through the multivariate linear regression model with family size, number of earner, family type and income.

S. Venkatesan

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