The Indian Household Finance Landscape

Badarinza, Cristian; Balasubramaniam, Vimal; Ramadorai, Tarun

doi:10.2139/ssrn.2797680

Cited by 17 publications

(17 citation statements)

References 28 publications

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“…Many of the studies on this topic are limited to a smaller geographical area, thereby lacking generalizability in a larger context. The handful number of studies using country-wide data also confine themselves into cross-sectional analysis (Badarinza et al 2016). Even though the study by Burgess and Pande (2005) uses panel data for their analysis, the data are aggregated at state level.…”

Section: Introductionmentioning

confidence: 99%

Financial Inclusion and Household Welfare: An Entropy-Based Consumption Diversification Approach

Chakrabarty

Mukherjee

2021

Eur J Dev Res

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State-led financial inclusion programmes have been implemented in many developing countries, but their effectiveness in raising welfare remains widely debated. In this article, we report evidence on this issue, against the backdrop of recent policy initiatives on financial inclusion in India. We employ Theil’s entropy-based index to estimate diversification in consumption expenditure, and use this as a measure of welfare. Using household-level panel data across all regions of the country, we find evidence that greater financial inclusion increases diversity in non-food items. Further, we also notice that there is a shift in consumption basket from food items to non-food items. These findings suggest an improvement in welfare for both rural as well as urban households.

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Section: Introductionmentioning

confidence: 99%

Financial Inclusion and Household Welfare: An Entropy-Based Consumption Diversification Approach

Chakrabarty

Mukherjee

2021

Eur J Dev Res

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“…3 India is a large country with a rapidly growing middle class that is starting to use risky …nancial markets for the …rst time. During our sample period, Indians primarily invest directly in stocks rather than through mutual funds or diversi…ed retirement savings vehicles (Badarinza, Balasubramaniam, and Ramadorai 2017). In these respects India has much in common with other developing countries, but di¤ers from developed countries (Badarinza, Campbell, and Ramadorai 2016).…”

Section: Introductionmentioning

confidence: 99%

Do the Rich Get Richer in the Stock Market? Evidence from India

Campbell

Ramadorai²,

Ranish

2019

American Economic Review: Insights

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We collect stock-level data on monthly total returns, market capitalization, and book value from three sources: Compustat Global, Datastream, and Prowess. Prowess reports data from both of India's major stock exchanges, the Bombay and National Stock Exchanges (BSE and NSE). In addition, monthly price returns can be inferred from the month-end holding values and quantities in the NSDL database. We link the datasets by ISIN. 2 To verify reliability of returns data, we compare total returns from the available data sources, computing the absolute differences in returns series across sources. For each stockmonth, we use returns from one of the datasets for which returns match another dataset most closely, where the source from amongst those datasets is selected in the following order of priority: Compustat Global, Prowess NSE, then Prowess BSE. If returns are available from only one source, or the difference(s) between the multiple sources all exceed 5% then we compare price returns from each source with price returns from NSDL. We then use total returns from the source for which price returns most closely match NSDL price returns, provided the discrepancy is less than 5%.After computing total returns, we drop extended zero-return periods which appear for non-traded securities. We also drop first (partial) month returns on IPOs and re-listings, which are reported inconsistently. For the 25 highest and 25 lowest remaining total monthly returns, we use internet sources such as Moneycontrol and Economic Times to confirm that the returns are valid. We also use internet sources to look up and confirm returns for stockmonths where returns are missing and the stock comprises at least one percent of stock holdings for the representative individual investor for either the previous or current month.We follow a similar data verification procedure for market capitalization and book value, confirming that the values used are within 5% of that reported by another source. Where market capitalization cannot be determined for a given month, we extrapolate it from the previous month using price returns. Where book value is unknown, we extrapolate it forward using the most recent observation over the past year.

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“…Finally, the size of India's market and the diversity of areas of possible innovations in financial products and services, are strongly indicative of the need to conduct further studies of patterns of household financial behavior. Badarinza et al (2017), though not an IGC-sponsored project, is a good example of preliminary work on documenting these patterns, but much more needs to be done. Campbell et al (2012) conducted a useful study of India's mortgage market, and the plan in the latest Union Budget to expand low income housing will increase the need for further such studies that emphasize financial inclusion.…”

Section: Lessons and Conclusionmentioning

confidence: 99%

Financial Inclusion: Concepts, Issues and Policies for India

Singh

2018

SSRN Journal

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This paper lays out some of the basic concepts surrounding financial inclusion, including access to banking, digital payments and financial literacy, as well as markets for health insurance, crop insurance, agricultural credit, small firm finance, and microcredit/ microfinance. It goes on to discuss various empirical and institutional studies of these dimensions of financial inclusion in the context of developing countries. The paper then outlines several recent studies for India sponsored by the International Growth Centre, which pertain to these specific aspects of financial inclusion. Finally, the paper draws lessons for policy-making and future research directions. Important considerations that emerge from the overview are the significance of social and economic context, the need to consider behavioral biases connected to situations involving time and risk, the interaction of different dimensions of financial inclusion, the importance of details of policy design, and the limited understanding we still have of many of the factors underlying the functioning of financial markets.. * I am grateful to Eilin Francis and Arshad Mirza for valuable research assistance, and to Dilip Mookherjee for incisive comments on an earlier draft. Sole responsibility for shortcomings is mine.

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The Indian Household Finance Landscape

Cited by 17 publications

References 28 publications

Financial Inclusion and Household Welfare: An Entropy-Based Consumption Diversification Approach

Financial Inclusion and Household Welfare: An Entropy-Based Consumption Diversification Approach

Do the Rich Get Richer in the Stock Market? Evidence from India

Financial Inclusion: Concepts, Issues and Policies for India

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