The Household Finance Research Initiative (HFRI) at Dvara Research aims to understand how low-income households use financial and non-financial instruments to attain their objectives. Through this initiative, we aim to generate and catalyse insightful and rigorous research on low-income households that is customer-centric as well as relevant and responsive to the Indian policy context and financial landscape. To further this initiative and encourage collective learning from academic and non-academic research institutions, the Household Finance practice will be conducting a Household Finance Research Conference in mid-2021 in collaboration with Northern Arc Capital, Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI) at IIT-Madras and Omidyar Network. As part of this conference, we announced a global call for proposals, in May 2020, under the following three themes of financial inclusion and Household Finance Research.
Understanding financial decisions that households make and strategies they adopt to achieve their objectives
Understanding household financial behaviour and its impact in shaping household outcomes
Understanding the interaction of financial products with portfolios of household
Based on these three themes, researchers were asked to submit their proposals under two different research tracks depending on the methodology of their analysis.
Track 1 – Applied Data Science in Household Finance: The purpose of this track was to facilitate research using novel analytical methods of applied data science research in household finance. The maximum grant under this track was Rs. 4 lacs per proposal.
Track 2 – Primary Research in Household Finance: The purpose of this track was to facilitate primary research using innovative and well-recognized methodologies in the field of household finance in India. The maximum grant under this track was Rs. 15 lacs per proposal.
To ensure wide dissemination of research findings, selected research papers under both the research tracks will be published in the Journal of Emerging Market Finance (published by Sage Publishers, and IFMR/KREA Graduate School of Business). In addition to the publication of research in an indexed- journal, the researchers will be required to write a blog series and fact sheet for the Dvara Research website summarizing the key findings from their research. The findings from the research will also be disseminated at the Household Finance Research Conference scheduled for mid-2021. We envision the conference to be attended by not just researchers but also practitioners and policymakers for well rounded discussions on challenges faced by low-income households in accessing and using formal financial services and potential policy solutions around these problems.
The initiative is delighted to announce that the response to the call for proposals has been overwhelming as we received over 75 proposals across disciplines of social sciences. After multiple rounds of screening, we have selected a total of 10 research teams (5 proposals under track 1, and 5 proposals under track 2), as the recipients of the grant. Below are the shortlisted researchers, their profiles, and a brief summary of the project that they will be working on as collaborators for the Household Finance Research Conference Program.
To determine formal financial products that are appropriate to low-income households (HHs) remains a crucial question. As part of answering this question, using the KGFS Administrative Dataset (2018), this study aims to find patterns in borrowing in households with similar demographics. The patterns of interest are type of loan; loan amount; time of borrowing and evidence of cyclic borrowing; and success in repayment or default.
To analyse these patterns, techniques offered by Event History Analysis (EHA) will be used. EHA considers HH parameters, such as occupation and income, and their variations in time. A concept that particularly distinguishes EHA is its ability to handle missing or incomplete data. Discovering such patterns will help in understanding loan distress or overindebtedness and the factors that determine the choice of formal financial products and services by low-income HHs. These results can provide insights into how financial products can be tailored to specific HHs.
In the aftermath of the global financial crisis in 2008, a great deal of research has been conducted to assess the financial vulnerability of households across the world. Given the multidimensional nature of vulnerability, researchers have focused on different dimensions and approaches to analyze the status of vulnerability of the households. The proposed work attempts to analyze household’s financial vulnerability employing the machine learning and deep learning techniques using the data from a financial services provider which covers household-level information about demographics, income, expenditure, savings and borrowings for its clients for the states of Tamil Nadu, Odisha, and Uttarakhand. The vulnerability analysis is carried out in two parts. In the first part, homogenous clusters of households are identified and analyzed to further identify the cluster of financially vulnerable households. In the second part, the households’ probability of being financially vulnerable based on economic and demographic characteristics is estimated. The results of the proposed research would be important for designing and implementation of financial sector policies focused on redistribution of income and strengthening the risk management strategies of the households.
The interlinkage between health and wealth is a well-established fact, but the direction of the causation is still a debate among researchers. Theoretically, health can impact wealth and vice-versa. A large body of literature has empirically examined the role of health status on wealth and the impact of wealth status on health. Among other factors, savings and portfolio choices are a means to create wealth. Household saving behavior and portfolio choices may be crucial in shaping their healthcare-seeking behaviors by easing out any stress about paying for care due to unexpected future health shocks. However, there is hardly any empirical research that has examined the role of household saving behavior and portfolio choices on their healthcare services use. Hence, we attempt to fill this gap by examining the role of both savings behavior and portfolio choice on the health-seeking behavior and health outcomes of women in their reproductive age (15-49 years) in India.
The study intends to identify the profiles of households that invest in risky assets such as mutual funds, bonds, or equities. The study will incorporate household-level factors such as nature of employment (formal or informal), educational attainment, household wealth and income, caste, family size, dependency ratio, social network and access to information along with community-level factors for risk profiling. Further, it will assess the transition of household portfolios over-time and the covariates that can explain this transition. The study will be using the data from the two rounds of the India Human Development Survey (IHDS) collected in the years 2004-05 and 2011-12, which covers around 41500 households in 1503 villages and 971 urban neighborhoods across India. It aims to provide policy insights into the financial preferences of low and middle-income households and the investment products preferred by them.
Gold plays a dominant role in the portfolio of Indian households. Financial policy in India has persistently tried to incentivise households to switch away from physical gold through import duties, quantity limits, and taxes, and towards financial products based on gold such as gold ETFs and sovereign gold bonds. However, households still seem to continue with their preference for physical gold, though the popularity of gold ETFs is also on the rise. Despite the importance of gold in household portfolios, there is no systematic study of gold as an asset class under Indian macro and financial conditions. This project aims to investigate the properties of gold as an asset class that may contribute to its place in portfolios of Indian households. In doing so, it focuses on: a) the long-term returns on physical gold and gold ETFs, b) The performance of gold vis-a-vis other asset classes such as fixed deposits, and equity, especially in times of extremely volatile market conditions, and consequently its role in diversification and c) The relationship between gold and inflation, especially in times of high inflation that were characteristic of India prior to the inflation targeting regime. This analysis will help shed light on the market for gold, and explain some of Indian households’ preference for gold.
The study seeks to understand which factors determine household financial decision-making through a migration lens and how that differs among different types of comparable migrant and non-migrant households. Focusing on Jharkhand, Bihar, and eastern Uttar Pradesh to New Delhi/NCR migration corridor, the study adopts a mixed-methods design to determine how factors like gender, household composition, financial literacy, and collective decision-making as well as, migration intent and preferences influence financial decisions on savings, investment, and consumption in migrant households. Furthermore, it examines intra and inter-group variations in financial behaviour, in terms of bank account ownership, appetite for risk in their financial preferences, and likelihood to allocate finances for productive consumption like health and education.
Much of financial inclusion literature and interventions designed have focused on the “representative individual” and therefore have not accounted for the complexity of environmental and contextual factors within households that affect financial behaviors of the household. This is especially important in India, where inter and intra-level household dynamics heavily influence financial decisions taken by individuals within them. This study aims to understand household financial decision-making, by focusing on the various inter-household dynamics, household norms, and behavioural factors at play. By using a mixed- methods approach and leveraging a mix of in-depth interviews and non-traditional research tools such as participatory photography, gamification of household decisions, etc. this study will generate insights which will help designing behavioral interventions and testing them in a lab-in-field experiment. These insights will likely provide a preliminary understanding of how to design behavioral interventions to improve financial products and their take up, but also create new products that better cater to the needs of households.
Drylands make up 41% of the world land, 44% of the cultivated land, one-third of the world food production and 50% of the world livestock. They are home for 2.3 billion people, of which about 50% are living in poverty. 66% of Africa and 40% of Asia are drylands. Farm distress is more concentrated in drylands in India. Farm distress in drylands was caused by frequent droughts and consequent crop failures. Since last two decades there are number of crop insurance schemes to mitigate crop losses, but their effect in alleviating farm distress is not studied thoroughly. This study aims to assess crop insurance coverage among dryland farmers, explore farmers understanding about various risk types, identify the mitigation and adoption strategies and lastly it develops farmer distress index to measure degree of farm distress.
The economic impact of COVID-19 in India has been devastating and has disproportionately affected low-income migrant households. It has brought the lack of social security and risk mitigating strategies with such households to light and in this context, it is important to understand the changes in financial decision making, resource allocation, and financial priorities of such migrant households. With this study, the researchers aim to present a snapshot of the current household portfolio of migrant households and discern the impact that COVID-19 has on it, along with exploring the possible shifts in resource allocation priorities, household goals, and risk mitigation strategies. It will also gather the migrant households’ response to Unconditional Cash Transfers. The aim of the study is to generate insights to inform future policy making and programming strategies for improving the financial resilience of migrant households in catastrophic situations.
Household savings have important implications for their welfare. Saving in financial and non-financial assets smoothen their consumption, safeguard them against economic shocks and help accumulate assets. But low-income households’ savings remain under-appreciated and under-researched in India. In this context, this study has two objectives. The first will be to study saving behavior of low-income households in urban areas of Telangana through a primary survey. For the second objective, the researchers will do rigorous cross-country comparison to study saving instruments and schemes available in other developing as well as developed countries which are exclusively designed for low-income households. While the primary data-based analysis will help to understand the savings behavior, practices and aspirations of low-income households, the secondary data based cross-country investigation will highlight global practices of addressing saving needs of such households.