The Milaap Summit

We wanted to reach out to our readers to inform them about an upcoming conference in Delhi, organized by Milaap, which is a mission driven company changing the way people fund and impact communities in need. 

They work to connect borrowers looking to start a small business, pay for education, install better facilities in their households, and more – with people around the world willing to lend and rally their friends and family with as little as Rs. 500 ($25)

Here's their event note:

We're a social fund which provides low-cost debt financing for education, enterprise development and building essential household assets. We work with credible community partners and in less than two years, have deployed over INR 6 Crores in Karnataka, West Bengal, Odisha, Maharashtra, Tamil Nadu, Uttar Pradesh, Rajasthan, Bihar and Mizoram. We bring visibility to our partners among global investor communities, individuals and interest groups across the world through our curated personalized stories of borrowers, case studies and impact videos. We also provide our partners with a state-of-the-art Enterprise Information Management (EIM*) system to manage their borrower's social data. We're inviting NGO-MFIs and livelihood organizations to participate in our first summit to learn more about how they can associate with Milaap for funding opportunities. The summit will also showcase the work of our existing partners and serve as a platform for collaboration and for forging partnerships. Who is this for: CEO/Management of ·       NGO-MFIs ·       Livelihoods Organizations ·       Producer Groups ·       Crafts Promotion Groups ·       Skill Enhancement Organizations *EIM is a cloud based data management solution customized to align with the operations architecture of Milaap's community partners. This system holds and analyses the social data of borrowers, & thereby aids in management decision making. Link for Registration: https://docs.google.com/a/milaap.org/forms/d/1ojm9ErmZwlikXNbw-Ju6S2YWMdm12h8hN6kTcMRdpBQ/viewform

Our Partners

Find out more about our Field Partners

In case of any queries, you can also write to us at summit2013@milaap.org

Price Information: Leading to Roads Less taken

For many of India’s 850 million rural inhabitants, 40 per cent of whom live in poverty, delivering agricultural output in a timely manner is a significant challenge. Poor infrastructure, lack of scale  economies (70 per cent of landholdings are less than one hectare, or 2.5 acres), and costly transportation means smallholders routinely sell their output to traders. However, this potentially efficient division of labour suffers from limited competition among these middlemen, who are able to exploit their bargaining power to extract a surplus. On the other hand, farmers who sell their produce directly to end consumers face difficult timing and/or locational decisions, uncertainty about prevailing market prices and an inability to visit every market every day.

CMF's “Increasing rural incomes by expanding access to agricultural price information” in Karnataka intends to rigorously evaluate the “success or failure” of Fasal (a cell-phone based service that provides current price information on a variety of agricultural outputs at a range of markets on demand) within the context of an RCT with an encouragement design.

The study is being conducted in three districts of Karnataka. Currently, the study is in the baseline data collection stage. The sampling criteria for the selection of the villages in the district was multiple market access , so that there could be an option for the farmer to decide the harvesting and selling based on the crop prices (through Fasal). In the three districts identified for the study there are eleven major markets where the farmers sell their crops mostly. However as we sampled the villages based on the multiple market access criteria it became evident that for any village the distance between  village and the market will not be exactly same as between the alternate market. Thus, the selection of the village was to be done keeping in mind the geographical constraints and  sampling criteria. For this we used symmetry in geometrical shapes

The market networks in the selected districts are of two types

•      Two Market Area Access
•      Three Market Area Access

This means that the village has access to either two or three markets respectively. The market pair or triangle was selected based on the infrastructure (Road Network) facility available for the farmers from the villages to the selling markets. The distance in kilometres was an important criterion for selection of Market Pair/Area.

Mapping of the Villages

Once the selection of the districts and market networks was completed, the villages needed to be mapped. The villages being selected had to have access to a minimum of two markets within the same or the neighbouring district.

A total number of 190 villages were mapped in 12 market pairs selected across the three districts of Karnataka. The villages are not equally distributed across different districts or market pairs.

The villages were first identified on the District and Block level maps and checked in the Census list. Based on certain selection criteria the villages were selected for further sampling.  The methodology has been discussed in detail below

Plotting of Villages on District/Block Maps 

Firstly the Paper Map plotting of the villages had to be done for the villages. To do so the District and Block level maps for the three districts were purchased from the Department of Settlement and Land Records from State Revenue Office of Karnataka.

1.      Market Pair network was drawn on the District Maps

2.      Two types of villages were identified

A.    Two Market Access: The connecting road between any two market pair was bisected. The Villages on the perpendicular bisector were selected

B.     Three Market Access: A circle was drawn in the triangular area between the three markets. The villages within the Circle were selected.

Once the village was identified on the Hard Copy of the Maps, they were tallied with the latest Census List. Only the villages which existed in the Census -2011 list were selected for further sampling. The following information were collected from the Census -2011 list for the selected villages

• Total Number of Households in every village
• Total Population of the Village
• Total Cultivator Population in the village.

Based on the above data the Outlier villages were dropped. The villages with extremely low number of Households or Cultivator populations were dropped. The villages were coded sequentially and a list of 190 villages was finalised for the baseline study. These villages were also mapped on the Google Map, creating a customized Map.

Whenever we plan to conduct a study in the remote villages, I am sure many of us come across the complicated question of successfully locating the villages where we plan to administer our survey. At times the administrative maps are also not very helpful in identifying the exact location of these villages. Also with time the government definition of the village boundaries change, which might not be reflected in the block and district maps created years before the change. To add to this the residents of the village who might not be very well aware about such recent definition change may continue to mention a different village name which can lead to mismatch of number villages in the sample. Though these are unavoidable realities some ground level planning can be done to prepare a list of the most updated village names. What is more important is the identification of the village on the maps to verify the location which may be important from  the sample selection point of view , like in the Price Information study.

The mapping is sometimes different as was observed when the field data collection actually started. The villages which seemed to be just few kilometres away (as seen on the Maps) from each other are actually separated by uneven terrain, forests or water bodies because of which the road takes a roundabout and longer route. The bigger challenge is the frequency of transport to get to these villages which are at a great distance from the main Blocks/Taluks. It will be interesting to see if the Farmers actually give up the closest and most convenient markets where they have been regularly selling and tread a road which takes them to a further but more profitable option.

“Development as Freedom” - Amartya Sen’s Grand Reconception of Development

I believe Amartya Sen’s famous Book, “Development as Freedom” has contributed to setting a whole new direction on the basis of which policy can be formulated and this is the primary criterion on which his work in this area needs to be studied and  assessed. The concept of 'Development as Freedom' is really a culmination of Sen’s capability approach which he had developed earlier. This line of thinking in development is also manifested in the approach of developing the UN Human Development Index which was formulated by Pakistani economist Mahbub ul Haq and Professor Amartya Sen.

Sen has developed “an alternative approach to evaluation that focuses directly on freedom, seen in the form of individual capabilities to do things that a person has reason to value” (Sen 2000, 56). Sen emphasises this distinction with the traditional approach when he remarks that “the discipline of economics has tended to move away from focussing on the value of freedoms to that of utilities, incomes and wealth” (Sen 2000, 27) and that this leads to a “narrowing of focus” (Sen 2000, 27).

He then moves on to make two key assertions which run through his whole approach of Development as Freedom.

First, he defines development as expansion of freedoms, or the removal of various types of unfreedoms (Sen 2000, xii) such as undernutrition, lack of access to health care or premature mortality (Sen 2000, 15).

He then states that there is empirical evidence to show that there are positive linkages between different types of freedoms and that “they may also serve to complement each other” (Sen 2000, 10).

Another key concept Sen emphasises is “human agency”. He stresses that Individuals have to play a positive role in bringing about the change they wish to see. They should move from being passive recipients of cunning development programmes to being seen as active agents of change (Sen 2000, 13).

I now give three examples of the broad policy implications that follow from Sen’s distinctive approach.

First, Sen has very clearly brought out the positive linkages between economic and social freedoms by contrasting the examples of China, which met with considerable success when economic reforms were introduced in 1979 and India, which met with only limited success when economic reforms were introduced in 1991. According to Sen, China did better because it had better social freedoms at the time of introducing its reforms. China had a more educated and healthy population, which was able to make better use of the reforms as compared to a socially more backward India (Sen 2000, 42). This provides an important guideline for policy.

Second, in the case of poverty, Sen approaches it from a capability deprivation perspective. Addressing the causes of capability poverty can help in the removal of income poverty. Better basic education and health care improve the quality of life directly; they also increase a person’s ability to earn an income and be free from income poverty as well. Thus, the capability perspective enhances the understanding of the causes of poverty and helps in its mitigation as well (Sen 2000, 90).

Third, Sen has pointed out that even in developed countries, there can be deprived sections. In the United States, Sen gives figures to show that the mortality rate of Blacks is much higher than those of Whites (Sen 2000, 97). Thus, Sen has given policy formulation a new meaning by applying development concepts to rich countries as well.

It has also been argued that Sen’s concept of 'Development as Freedom' is not always explicit at a specific (as opposed to broad, directional) policy level. It very clearly states what needs to be done but it isn't always so forthcoming on how this can be achieved. Also, Sen treats all freedoms as foundational. This has been one of the major criticisms levelled against Sen that he not given a specific list of freedoms that he considers essential. This may be contrasted to Martha Nussbaum who has clearly given a specific list of essential freedoms. This would help in prioritising policy goals.

Yet, overall, Sen’s conceptualization of development as freedom needs to be recognised as a bold new step in the study of development. It brings both practical and ethical considerations into the picture and significantly broadens the understanding of development. It stresses the importance of empowering people and increasing their choices to enable them to have more fulfilling and enriching lives. 

From Sen’s perspective, the area that CMF is researching may be broadly considered as one that focuses on how to how to remove certain financial unfreedoms (lack of access to a means of saving, credit, insurance, pensions etc.) among deprived sections of society. Addressing this set of issues, as he has pointed out would have positive spin offs on other types of freedoms as well (such as the capability to access quality healthcare or education).

The importance of Sen’s work, I believe, lies in changing the goal posts for policy formulation. 'Development as Freedom' is an eloquent argument for a new and more sensitive direction in policy to improve the quality of life of all human beings.

Note

All references given above are from:

Sen, Amartya. 2000 (1999). Development as Freedom. New Delhi: Oxford University Press.

Comments on the Implementation of the Indian Government’s Welfare Schemes

We feature a guest post from Arushi Agarwal, an intern on our livelihoods project. 

The Centre for Micro Finance recently created a database of welfare schemes that have been launched by the Government of India; the database also has state and sector wise information for easier information retrieval. While working on the database, I was struck by the number of programs that have been set in motion by the government till date, along with the large sums of money which have been allocated for the same. Looking at these programs, there remains no doubt about the government’s intention to provide assistance to the poor and facilitating their upliftment, but it is the implementation bit that leaves a lot to be desired. The causes of this inadequate execution are mostly insufficient monitoring by the central government, misalignment of incentives which encourage rent seeking activities and finally, a lack of accountability which distorts the management of funds. These are some of the common trends witnessed in the poor implementation of many schemes such as ICDS in Bihar, NREGA in Maharashtra, Madhya Pradesh and Orissa, Mid day Meal in Madhya Pradesh, Health Insurance Scheme in Maharashtra, Old Age Pension scheme in Chhattisgarh and Bihar and the Integrated Housing and Slum Development Program in Punjab and Himachal Pradesh among others. Here, I intend to discuss the implementation of three of the largest schemes by the Indian government.

NREGA, which guarantees 100 days of employment in a year to anyone who is willing to do unskilled manual labour, is facing severe criticism for corruption. The Asian Human Rights Commission reported, in its urgent appeals programme, that implementation in Uttar Pradesh suffers due to its dependency on the local self government (often the village panchayats) and faces caste prejudices, politicisation and a complete lack of accountability. People belonging to the lower castes suffer from discrimination and do not enjoy equal rights of employment and wages they are entitled to under the scheme. According to a CAG report on NREGA in 2013, the scheme has failed in Karnataka and Bihar due to misappropriation and subversion of funds. Moreover, since the scheme mandates manual “unskilled” labour, it has given rise to some underlying doubts about the framework of the scheme since the work does not cause any form of skill up-gradation of the NREGA workers and thus their future employment opportunities remain bleak.

Further, the National Health Insurance Scheme- Rashtriya Swasthya Bima Yojana- which aims to improve the poor’s access to healthcare services has witnessed failure in its operation and execution in states where the scheme has been analyzed. In the states of Maharashtra and Karnataka, studies (here and here) have reported that even though a large proportion of households were aware of the scheme and its benefits, the beneficiaries had either not received their cards for access to those benefits or they were not educated about the treatment centres where they could avail those services. Furthermore, the RSBY hospitals were not fully equipped for treatment and lacked proper facilities and training. The hospitals in turn complained about shortage of funds and even delays in reimbursement of their expenses on treatment under the scheme, leading to reduced incentives.

Old age pension schemes which have been designed to provide social security to those more vulnerable also suffer from corruption in several states. Surveys in Chhattisgarh, Jharkhand and have shown that beneficiaries face excessive delays in receiving their pensions. There are also cases where the pension gets disbursed to the beneficiary after his/her death and since there is nobody to claim it, that money ends up filling up pockets of the officials in charge. This problem, however, can be handled if funds are released in time and carefully monitored.

Having studied the reasons for poor performance of these schemes, we also brainstormed about possible ways to rectify them. With the kind of heterogeneity that Indian states possess in their demographics, culture, traditions and economy- it would be a futile exercise to carry out one model of any scheme uniformly across all states. It is thus important to delegate some freedom to the states or field staff to be able to change the schemes to suit local conditions. At the same time, this freedom should be awarded at the price of responsibility, implying an enhancement of financial monitoring, timely evaluations and increased accountability. 

The successful implementation of social sector schemes requires a great deal of commitment and administrative coordination. NREGA in Kerala, mid day meal in Tamil Nadu and the Antyodaya (AAY) scheme in Rajasthan are some examples. Moreover, a good deal of time and energy is spent in village and block level data collection, which is only useful if all the information is properly analysed and this knowledge is disseminated to officials in time to allow for remedial action. However, remedial measures can only be taken when the shortcomings are recognised, accepted and finally addressed. I believe that a fundamental problem lies with social norms in India, accepting injustice as it comes, living in the dark and in turn decreasing the cost of corruption. And last but not the least; skill development is an exercise which needs to be carefully designed and efficiently implemented in such disadvantaged areas which otherwise carry such huge amounts of human capital that can be resourcefully used to better the development of the nation.

____________________________________________

Arushi Agarwal completed her bachelors in Mathematics from St. Stephen’s College, University of Delhi and plans to do her post graduation in Economics with a specialisation in development and policy. Before working with the Centre for Microfinance, she worked at ICICI Prudential Life Insurance, Mumbai with their actuarial department to understand risk management and product pricing. 
Note: The views expressed in this blog are solely those of the author and should not be taken as representative of the views of IFMR Research.

India's Invisible Population

We feature an article published in The Hindu on the work done by Transparent Chennai, which is a part of the Centre for Development Finance (CDF). 

Photocredit: The Hindu

Denying basic amenities to residents of ‘unrecognised’ slums is an affront to their dignity; resettling them fails to address their concerns and is unviable financially

Since 2005, the Central government has given significant amounts of money to the States to improve conditions for the country’s urban poor, first under the Jawaharlal Nehru National Urban Renewal Mission (JNNURM) and more recently through the slow-moving Rajiv Awas Yojana (RAY). Unfortunately, very few studies have looked at how effective these programmes have been in achieving their objectives. Our research in Chennai suggests that money from the JNNURM did not effectively address the needs of the city’s most vulnerable residents.

How could this happen in a programme explicitly designed for this purpose, and in a State known for its generosity to the poor? This is because Chennai faces a problem common to many cities across India: it has two tiers of slums — those with official government recognition and those without, and the JNNURM did not push cities hard enough to directly intervene in slum areas without recognition.

NO ACTION SINCE 1985

According to the Tamil Nadu Slum Clearance Act of 1971, the government is supposed to identify slums, officially recognise them as slums, and then improve these areas. As soon as the Act was passed, the Board identified and recognised 1,202 slums in Chennai, and added another 17 slums to the list in 1985. All of these slums were improved in situ, either by building tenements or by providing basic services. However, in a sharp break with this progressive history towards the urban poor, not a single new slum has been officially recognised in the city since 1985.

In the nearly three decades that have passed, hundreds of new slums have come up in the city. Unfortunately, because the Tamil Nadu Slum Clearance Act states that you must recognise a slum before you can intervene in it, government programmes to increase access to services for the poor, including the JNNURM, have not directly intervened in these areas — with predictably tragic results. Very little reliable information actually exists about these unrecognised slums but we found one study on them commissioned by the Tamil Nadu Slum Clearance Board in 2002. The study found a total of 444 unrecognised slums within the Chennai Metropolitan Area, with nearly half a million residents at the time, and an average of 620 people relying on a single public water facility in unrecognised slums within the city, far more than the norm of 75 people per water facility. Such numbers are shameful. What they show is that these unrecognised slums have effectively become an invisible Chennai, not counted in the official statistics of slum-dwellers used in the Master Plan and by the Slum Clearance Board, and largely ignored by the service provision agencies.

Read the Full Article 

Impact of Access to Finance: Network Level Effects

In the concluding post of our KGFS Blogseries, our research associate explains the implications of behavioral games being played to determine the impact of financial access on social networks.

Access to finance can have multiple effects on an individual’s life, especially on community behavior. Imagine that we had no banks, no financial services - Who would we borrow from?

The rent that informal service providers can extract from their clients is limited either by their willingness to pay, or their ability to borrow/save with other sources (outside options). In the absence of rural financial institutions, existing evidence shows that moneylenders and informal providers charge very high interest rates from their poor borrowers (60%-100% or more) and service savings at steep negative effective interest rates (Collins et al. 2009).

KGFS generally operates in areas with no competing formal institutions. Hence, in most cases, the prevailing source of financial services at the time of KGFS’s market entry are friends, family, and semi-formal lending institutions. So what happens when we introduce a new way to borrow, lend, save and insure within a community which had its own self-sustaining way of doing the same? How does this intervention affect social behavior and willingness to share within a community. This is one of the questions that the KGFS Impact evaluation aims to address.

To understand this community level effect, we need to look at the concept of social capital. I’d like you to think of the effort you put into building social networks as investing in social capital. In simpler terms, the stronger the networks you have, the higher your level of social capital. Social capital plays a very important role in joint liability group loans, where people borrow and repay as a group. If one defaults on their repayment, they not only lose the opportunity to borrow again, they lose access to the group they were a part of. Social capital is meant to act as a deterrent to default in joint liability contracts.

Previously, a few behavioral experiments have been conducted to measure the effect of change in social capital on risk sharing and hence, repayment behavior (Economic Returns of Social Interactions, Feigenberg et al.). Conversely, as a part of the ongoing study we aim to explore a key question: What is the impact of access to financial services on social capital, within a system of financial services which does not involve joint liability, and individuals maintain a one to one relationship with the financial institution?

The experiment will be conducted for about 700 households in Thanjavur, Ariyalur and Pudukkottai where KGFS operations are present. Since this is a Randomized Controlled Trial, half of them have had access to financial services since two years (the treatment group) and half of them have not had access to the same (control group). The data will give us an insight into the impact of access to finance on social behavior of an individual as well as a community.

This part of the survey delves into the behavioral economics of impact of access to finance which can always have surprising results which don’t necessarily have to conform with theory, which is what makes this experiment challenging as well as exciting.

Behavioral Game Setup:

We address this question by conducting a type of behavioral experiment with the respondent called the Dictator game. There are two types of Trust games – The Dictator Game and the Investment Game.

In the second phase of our survey, we played the investment game, but for the current phase, we are playing a slight variation of the Dictator Game. Here is a brief description of the Dictator Game-

• Respondents are asked to split sixty rupees between themselves and a second person. For the benefit of the post, let’s refer to the second person as player 2, and the respondent as player 1

• They are made to do the following two tasks twice -

          Task A: The amount being given to player 2 will be the same amount that player 1 

          decides to give to them.

          Task B: We double the amount that player 1 decides to give, and give that to player 2, i.e 

          We inform Player 1 that the money he/she allocates to Player 2 will be doubled before  

          we give it to player 2.

• In the latter case, player 1 allocates the money keeping in mind that player 2 would receive the double of whatever he/she chooses to give him/her.

• Player 2 is of two types, one is player 1’s friend and the other is a stranger.

• We randomly select a friend from player 1’s social network data that we collect beforehand, and assign him/her to be player 2 for the tasks. The fact that the recipient was randomly chosen creates exogenous variation in the type of relationship between players. Once, player 1 plays Task A and B with player2-friend, and then the second time player 1 plays Task A and B with player 2-stranger

For more technical details on the trust games, readers can refer to this link.

The motivation behind doubling the amount in Task B is to capture a sense of expectation of return that player 1 will have from player 2. To elaborate, if player 1 gives more, player 2 gets more and so player 1 can expect a return. There are two things to be pointed out here:

First, we do not ask player 2 to return any money to player 1, it is just an “expectation” of sharing back, that we want to capture via this game. Due to the possibility of future interaction, respondent behavior is likely to be in part motivated by reciprocity. This expectation is also called belief or trust, when we talk in terms of behavioral economics. Second, we would expect people not to expect anything back from strangers. But the point of playing this game with strangers is that we measure the general willingness to share and the “expectation” of return, that exists in the community and not just among friends/relatives.

To get the intuition behind this activity, you can make these decisions as if you’re player 1. The thoughts that influence your decisions translate into your willingness to share within your social circle. When administered to a larger population, this experiment aims to analyse the level of social capital in a society and how that changes when the respondents, in our case, residents of across districts of remote rural Tamil Nadu, have access to financial services.

As a Research Associate working on this project, I think there can be different outcomes of this study, with equally logical explanations. We can expect an increase in the willingness to share, since access to finance could potentially increase an individual’s lending capacity, and so the networks would become stronger with people being able to share more. The other expected outcome could be that we observe a decrease in willingness to share, since each individual will have more flexibility in terms of managing their finances, and with access to finance, they could become financially more independent of informal borrowing or sharing links. Any of the two effects can overplay the other, but that would depend on different factors like social structure of the village, strength of informal lending network which could be very community specific.

The results from this experiment aim to get a sense of how a community’s behavior as whole is affected when it is exposed to financial services, with a focus on willingness to share and, how each individual perceives his community’s sharing attitude. The challenge is to bridge this gap between the rural poor and access to finance in a sustainable way, unique to the rural setup, and not just extrapolate the urban financial services delivery model.