UNRISD interview with Supriya Garikipati, development economist, following the event “Gender and Agriculture after Neoliberalism” held at the Graduate Institute of International and Development Studies, Geneva, Switzerland.
To listen to the full podcast recording of this interview, use the media files link above.
UNRISD: Can you please describe your academic and research background, especially your work at Liverpool, the Development Studies Research Network and your fieldwork in Andhra Pradesh?
Supriya Garikipati: I am a development economist. My main research interests are in the area of women’s empowerment. I am particularly interested in studying public policy interventions that are professed to lead to women’s empowerment. So to give you an example, in some of my work I have examined the empowering potential of microfinance — an intervention that is commonly associated with improving women’s welfare. My work is mainly on India because it is a country I am most familiar with, and because of its sheer size and complexity, it continues to intrigue. I have carried out extensive fieldwork both in the western tribal belt of India and in the southern state of Andhra Pradesh. I have spent something like three and a half years of my life doing fieldwork.
UNRISD: Microcredit has been linked to so-called “women’s economic empowerment”, especially in rural areas. Underpinning this trend is a model of an “empowered” woman who invests money in a successful enterprise, uses the income to enhance the nutritional status of her family, educates her children and begins to participate in major family decisions. How accurate is this perception?
Based on your research findings, what effect has women's access to microcredit had on their decision-making power?
SG: This model of an empowered woman, who gets the loan, invests it and improves herself and her family’s condition is seriously flawed. Let me explain. Microcredit is widely used in developing countries because of its enormous potential for poverty alleviation. Over the last three decades, the microcredit industry has grown enormously. Just consider this: in 1997 the client base of microcredit was around 9 million. By the end of 2011 this was 190 million. So it is more than a 20-fold growth, and over 85 percent of the clients are women. Now the model of the empowered woman that you just described was largely the basis for the ideological drive behind targeting women as clients of microcredit. This ideological drive suited the commercial lenders, who preferred lending to women as they are considered a safer bet. It seemed like a win-win situation for everyone. However, when the relationship between microcredit and empowerment started to be studied in earnest, it was revealed that not everything was going according to plan. The main problem with the model of the empowered woman that was just described by you is that women are unable to use their loans to improve their own incomes. In most cases women's loans get diverted into household usage. Estimates differ but studies generally agree that microcredit without training and awareness building achieves very little in terms of women’s empowerment. In our study, which is based in south India, we find that in about 80 percent of the cases, microloans given to women are either used for household consumption or, in some cases, could be used to enhance household’s productive assets, like irrigation pumps for the farmland. And this land usually belongs to the man, to the husband. And it not only belongs to the man, it is controlled by the man.
Some women — in the minority however — have managed to use their loans to improve their own incomes. And in these cases, we find that women are indeed able to challenge the patriarchal norms surrounding their work and incomes. In these few cases, microcredit does indeed have a beneficial impact on women’s empowerment. So it is not loan procurement, but how women are able to use their loans that matters for empowerment. What also matters is that women are not just made ad hoc stakeholders but they’re turned into effective stakeholders in the process. We need to improve not only the outreach of microcredit but also improve training and capacity building. So I take serious objection to the generalization of the perception that microcredit automatically creates an empowered woman. In most cases it does not — in fact this model is more an exception to the rule.
UNRISD: Based on your village-level surveys on the provision of microcredit to poor women farmers in rural India, what sorts of changes have you noted in your research in terms of the efficiency of microcredit as a “gendered” public policy intervention. Have there been notable changes in patterns of female labour and entrepreneurship?
SG: In rural India, microcredit by and large has failed to have a notable impact on women’s work. The overall picture remains the same; as far as women’s work is concerned it remains unchanged. Women are seen to be heavily involved in agricultural wage labour. Let me again give you an example. Andhra Pradesh is the frontrunner in terms of outreach of microcredit — it has around 40 percent of all microcredit groups in India. Its efforts to spread microcredit have been commended, and it has been put forward as a model for others to follow. Let’s take the example of this frontrunner state. Over the last 10 years, the number of microcredit groups has grown from around 200,000 to over 1 million. That means in excess of 15 million women. In the same period, census figures tell us that women’s employment in rural Andhra has remained virtually unchanged. We find that of the rural workers, over 60 percent of the women work as agriculture labour and just 6 percent work in household industry — this means they’re self-employed. This figure has remained stubbornly sticky over the 10 years. Using village studies of course can throw more light on the overall census figures that I just spoke about. But even there, there is very little to write home about. Here and there in pockets we find some beneficial impact — for instance, in some villages women are able to mobilize themselves to sell milk via the institutional structures created by microcredit. But these achievements are limited. We once again go back to the point I was making earlier — very few women are able to use loans in a way that can change the way they work and live. So has microcredit lead to notable changes? No. Has it lead to some changes? Yes.
UNRISD: Finally, time use survey data has become more widely recognized as a means of understanding household patterns of work and participation to capture the complicated relationship between women's paid work and unpaid care responsibilities. First, are they a good (or even the best) way to capture patterns of labour? Why are they so important? Second, how can such a method be adapted to national statistical data collection? What role can village studies play in this trend?
SG: Time use surveys study the way people use their time; so what people do with the 24 hours they have in a day. Given the complexities surrounding women’s work, there is probably no better tool to understand the changing pattern of women's labour. And time use can give you a precise idea about that. So instead of saying that in Ghana, women work on the farm 12 hours, if you actually look at time use, the 12 hours might actually be used to do different things. The actual number of hours on the farm might be very different from this common perception of 12 hours.
But this is not the only use of time use data. There are several reasons that make time use data a good tool, or perhaps even the best, in assessing the impact of almost any public policy intervention that is expected to change the way people use their time. Take an intervention like introducing subsidized childcare; the expectation is that more women will take up paid work if you introduce subsidized childcare. How do you go about assessing whether your intervention has had the desired effect or not? There are several things you can do — for instance, you can look at what is happening to the income of women who use subsidized childcare. But the problem with doing this is that you are likely to exclude women who have not gone into formal employment and who have instead gone into education or training or the informal sector. So income alone gives you a very partial picture. You will encounter the same problem with other indicators of employment — for example, if you use change in women’s labour participation, the picture will still remain partial. This is where time use data can be very useful. Time use surveys use one of several well-tested methods — such as asking people simply about the activities on which they spend most of their time or asking respondents to maintain a 24-hour diary. In this case, women using subsidized childcare will be the respondents. If done properly, time use studies can be very revealing. They can give you a more complete picture of how the policy of subsidized childcare has changed women's time use. Not only in terms of regular employment but whether women have used their time in a different way. Time use studies have not been widely used because collecting the data can be cumbersome and costly. Asking a person to recollect in detail what he or she did the previous day can take in excess of an hour. A practical way of adapting time use data to national statistical data collection would be by using the idea of main activity, secondary activity and tertiary activity. This can be complimented by more detailed micro studies at the level of the relevant unit — be it a village or a township or a slum or any other form of urban dwelling, where more detailed time use data is collected from relevant individuals. This is an extremely useful tool but it is also a tool extremely underused by social scientists. It is about time that that changes.