Nov 25, 2015

Data and Discrimination: Women’s Ownership of Assets in India

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 Data and Discrimination: Women’s Ownership of Assets in India. A case of the official status. http://bit.ly/1QchnZd

 The status of gender statistics (and data) in India leaves much to be desired. Read more. http://bit.ly/1QchnZd

Data collection by government agencies and preparation of statistics by official experts sound like benign acts. Quite non-threatening. However, these processes can often become silent partners in further marginalising groups with what they choose to collect and analyse, or what they leave out or ignore

Contemporary world is seemingly becoming more aware of language that perpetuates stereotypes. There indeed is a welcome movement towards a language that is gender inclusive and respectful of all people.  However, the same cannot be said about statistics. There is a tendency for official data collection to perpetuate existing biases in the society, particularly by way of omissions. 

UN Gender Statistics Manual maintains that gender data or statistics (data in distilled form) are more than just data disaggregated by sex. While sex-disaggregated data fulfils only the first requirement in the list below, gender statistics incorporate all four requirements:

(a) Data are collected and presented by sex as a primary and overall classification;

(b) Data reflect gender issues;

(c) Data are based on concepts and definitions that adequately reflect the diversity of women and men and capture all aspects of their lives;

(d) Data collection methods take into account stereotypes and social and cultural factors that may induce gender bias in the data.

Data and statistics can be great tools in the fight against the status quo in any society. Especially when data is systematically and periodically collected and analysed by the government or large agencies with the wherewithal for such exercises. 

Often, people make the mistake of thinking that the phrase “better gender data” assumes that we are talking about collection of more disaggregated information around the factors of economy like labour force participation, wage rates, etc . However, we need better gender data for more than just the economy.

The Guardian observed about the importance of collecting gender data on disasters, through a tragic story. A household survey carried out by Oxfam in Indonesia following tsunami found that in the regions most devastated, up to four women died for every male. In some villages, all the deceased were women. 

Interestingly, cultural restrictions on women’s behaviour explained these discrepancies. In Aceh, women and girls were often not encouraged to learn to swim or climb trees (This must sound quite familiar to us Indians). At the time the tsunami hit, women were also in particularly vulnerable places, clustered near the shoreline at home, mostly caring for children. 

When we do look at the results of analysis of such data, the gender dimension becomes clear, and the dire need to address these faultlines in the society becomes all the more apparent.

The case of India i

India is often cited as one of the worst places in the world to be born in, if one is a woman. Gender violence, and clearly discriminatory behavior towards women remain some of India’s most embarrassing truths. It is well-recognised that for a sound understanding and analysis of women’s position in Indian society and economy, we require adequate and good quality data. Unfortunately, the status of gender statistics (and data) in India leaves much to be desired.

Much has been written already on the statistical invisibility of the care economy in India.  The National Sample Survey Organisation (NSSO) is planning Time Use surveys to estimate the value of unpaid work by the women of India, which will at least partially address the issue.  

However, data on women’s ownership of assets is a case where acute unavailability of even basic information persists.  No matter how absurd it may sound, hardly any nationally representative sample is collected in India which enables any analysis of women’s ownership of assets, particularly, land, livestock and housing. 

For all data that are collected by our government agencies at the household level such as land and asset ownership or indebtedness, the unit of analysis is the household and often the only gender disaggregation is in terms of sex of the head of household. Experts like Madhura Swaminathan argue that we need to move away from use of the “female head of household” category, as the definition of head of household is neither analytically helpful nor useful for policy action, in terms of actual ownership of assets. Numerically, the category of female-headed households is not very large, and it just signifies the absence of an adult male to head the household and nothing else. 

It is well recognized in the literature around women’s empowerment that enhancing women’s status in Indian society requires changes in ownership or control over property and other assets. Swaminathan observes further that “in the rural economy, land is the asset par excellence”.

Data around value of land ownership across the country is collected quite regularly by the Indian government. The decennial Land and Livestock Holding surveys of the NSSO collect data on area of land owned and operated by households. Estimates of agricultural land and homestead can be separately obtained in the most recent survey (2013). The All India Debt and Investment surveys provide estimates of the net value of land owned by household.

However, both these surveys consider a ‘household’ as the primary unit. Hence there is no information on area or value of land legally owned by female members of a household.  The only estimate that can be computed from unit-level data is the land area owned and operated and value of land owned by female-headed households. As observed earlier, the definition of head of household is neither analytically helpful nor useful for policy action.

The second most important asset after land is housing. Data on housing ownership are collected by the Census of India. Both NSSO Surveys and National Family Health Surveys (NFHS) collect data on some other aspects of housing but not ownership. The Census of India collects data on ownership status of houses but the response is given as ‘owned/rented/other.’ There is no information on the owner: whether it is singly or jointly owned and whether the women in a household have any ownership rights.

Ownership of assets have huge implications on the lives of women. Research by Panda and Agarwal(2005) in Kerala showed that among the property-less women(owning neither land nor house), 49% experienced physical violence and 84% experienced psychological violence. In contrast, those who owned both land and house reported dramatically less physical as well as psychological violence (7% and 16% respectively). 

Given the need for women to have independent collateral and for asset security in general, collection of information on the status of property ownership among women of India needs to be one of the first steps towards gender justice in the country.  Swaminathan’s paper, written for the National Statistical Commission makes several recommendations towards this end. 

 

Written by: Oommen C Kurian, who is part of the research team, Oxfam India

Photo credit: Oommen C Kurian

 

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i This section heavily relies on and often reproduces the work of Madhura Swaminathan. Please refer to: Madhura Swaminathan (2013), Gender Statistics in India, Paper prepared for the National Statistical Commission, Government of India, New Delhi available at: http://mospi.nic.in/Mospi_New/upload/ Them_paper_Gender.pdf

 

 

 

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