Dvara Research BlogDvara Research Blog
Dvara Research Blog
Doorway to Financial Access
  • Home
  • Our Work
  • Themes
  • Subscribe
    • Email Subscription
    • Feed
  • Contact Us
Menu back  

Comparing Participation in Formal Financial Services across Two Nationally Representative Surveys: CPHS vs. AIDIS

April 26, 2022Leave a commentResearch Viewed : 677

Authors:

Niyati Agrawal
Rakshith S. Ponnathpur
Sahana Seetharaman
Intern

The All-India Debt and Investment Survey (AIDIS) carried out by the National Sample Survey Organisation (NSSO) and the Consumer Pyramids Household Survey (CPHS) carried out by the Centre for Monitoring Indian Economy (CMIE) are two nationally representative surveys that document how households borrow, save, spend and invest. In the wake of the Ministry of Statistics and Programme Implementation (MOSPI) releasing numbers from the latest (77th) round of AIDIS, we compare what both the surveys say about the participation in formal financial services by Indian households.[1] We expect reasonable similarity between them, given that both are considered nationally representative, and the essence of the questions asked to elicit household financial decisions are fundamentally the same. We acknowledge, however, that there are bound to be minor differences as the surveys differ in their design, sampling strategy, sampled households, and therefore the responses elicited.

AIDIS is a cross-sectional survey that interviews a different set of households roughly once every ten years, whereas CPHS is a panel survey that interviews the same set of households once every four months. Since it is a one-time survey, AIDIS collects detailed information on both household participation in and allocation towards a suite of financial instruments whereas CPHS only captures the former.[2] AIDIS follows a two-stage stratified sampling strategy[3] while CPHS follows a multi-stage stratified sampling strategy.[4] AIDIS sample comprises more rural than urban households, whereas the vice-versa holds true for CPHS.[5][6] Keeping these caveats about the surveys in mind, we proceed to look at how the numbers stack up vis-à-vis participation in formal financial assets first, and liabilities later.

Participation in formal financial assets

Table 1 describes household participation in formal financial assets according to the two surveys. Both the surveys report more than 90 per cent of households owning at least one bank account and roughly one-two percent of households investing in mutual funds, stocks and shares. But CPHS reports significantly higher participation in post office savings accounts, pension/PF accounts, life insurance, and health insurance. Some of these differences can be attributed to the way in which the questions are framed, and data is collected across the two surveys.

For example, CPHS has a direct question on members’ coverage under health insurance and we consider households with at least one member covered under health insurance to measure health insurance participation. However, in AIDIS, we can only use payment of premium for health insurance as a proxy for coverage, thus potentially excluding those covered under state and employer sponsored health insurance. This may explain, at least in part, the significantly higher figure for health insurance in CPHS. For some of the other financial assets however, the manner in which the questions are asked and participation measured is broadly the same, yet large differences prevail across the findings of the two surveys. Differences in the percentage of households with pensions, life insurance and post office account is more than double across the two surveys.[7] [8]

Participation in liabilities

Household participation in liabilities, both formal and informal,[9] are compiled in Table 2. Both surveys report a third of the households to be indebted and one in five households to have a formal loan. But, CPHS reports a significantly higher share of households having an informal loan (33%) than AIDIS (14%). On closer analysis, we find this difference to be mainly because CPHS, unlike AIDIS, also documents credit taken from shops under informal loans. The numbers converge when we exclude these loans while measuring informal loan participation in CPHS. However, CPHS still reports a substantially higher share of urban households having informal loan(s) while AIDIS reports a significantly higher share of rural households having formal loan(s).

Finally, we check household participation in loans taken for different purposes that are documented in both the surveys. These numbers are compiled in Table 3. Both surveys report reasonably similar share of households that have taken loans for housing improvements, health and education expenses, and investment. CPHS reports a substantially higher share of households that have taken loans for consumption expenditure, and here again, the numbers converge when we exclude credit taken from shops. AIDIS reports a significantly higher share of households that have taken loans for investments in business. This can be because AIDIS probes its respondents on business related loans in greater detail, under four separate categories of revenue and capital expenditure on farm and non-farm businesses, whereas CPHS collects this information under a common head of loans taken for business investment. A higher share of households report taking loans for repaying debt in CPHS (4.2%) than in AIDIS (0.8%).

Discussion

To summarise the findings, we find numbers on bank account ownership as well as incidence of indebtedness to be comparable across both the surveys. However, CPHS reports significantly higher participation in other formal financial assets like post-office savings, pension/PF accounts, and life and health insurance, compared to AIDIS. Whether this is due to any inherent limitation of the CPHS sampling strategy as critiqued by Jean Dreze and Anmol Somanchi merits further investigation.[10][11]

We hope this comparison enables survey designers and researchers to deliberate on what can make both CPHS and AIDIS richer sources of information on Indian households than they already are. For instance, we see merit in CPHS adding questions about the participation in and usage of e-wallets and other digital financial services, that AIDIS has captured in this round. Similarly, CPHS has shown that shops are a major source of informal credit among Indian households, and this calls for other surveys like AIDIS to consider shops as a legitimate source of informal credit to get a more comprehensive and accurate picture of indebtedness among Indian households.


[1] AIDIS has collected household data as on June 30, 2018. We use data from the May-August 2018 wave of CPHS to make the numbers comparable

[2] A household’s participation in an asset or a liability refers to the household’s ownership of the asset or uptake of loan, whereas a household’s allocation towards an asset or a liability refers to the amount the household has invested in the asset or the loan amount that it has borrowed

[3] AIDIS follows two-stage stratified sampling where the census villages/sub-units of villages are the First Stage Units (FSUs) in rural areas and blocks/sub-units of blocks are the FSUs in urban areas. The Second Sampling Units (SSUs) are households situated in the FSUs. The selection of the FSUs and SSUs is done using Simple Random Sampling Without Replacement (SRSWOR)

[4] CPHS follows multi-stage stratified sampling strategy where homogeneous regions form the broadest level of stratification. Homogenous regions are neighbouring districts with similar agroclimatic conditions, urbanisation levels, and female literacy rates. CPHS divides India into 110 homogeneous regions. The villages and towns of 2011 Census then act as the Primary Sampling Units (PSUs) within these homogeneous regions. Households from these PSUs become the Ultimate Sampling Units (USUs)

[5] AIDIS interviewed 69,445 rural and 47,006 urban households during visit 1, and  68,291 rural and 44,781 urban households during visit 2. CPHS interviewed 53,337 rural and 95,823 urban households during the May-August 2018 wave

[6] After applying weights to the AIDIS sample, we have a total of 26.01 crore households all-India, with 17.24 crore rural and 8.77 crore urban households. After applying weights to the CPHS sample, we have a total of 29.37 crore households all-India, with 20.07 crore rural and 9.3 crore urban households

[7] CPHS collects information on outstanding savings as well as savings made during the data collection period (May-August 2018) across different savings instruments, and we consider these for measuring participation in post office savings accounts, pension/provident fund accounts, mutual funds and shares, and life insurance

[8] For measuring participation in AIDIS, we consider households having a non-zero balance in bank accounts, post office savings accounts, and mutual funds and shares. For pension accounts, we consider households with at least one member covered under Atal Pension Yojana, or which have made contributions to pension/PF accounts. For life insurance, we consider households which have paid premium for endowment/term-life insurance, households enrolled under Pradhan Mantri Jeevan Jyoti Bima Yojana (PMJJBY), households with at least one member having life insurance, or if the sum assured under life insurance is greater than zero for the household, as proxies

[9] Formal liabilities are loans taken from financial institutions such as banks, co-operatives, microfinance institutions, self-help groups, etc. whereas informal liabilities are loans taken from moneylenders, employers, friends, relatives, etc.

[10] https://economictimes.indiatimes.com/opinion/et-commentary/view-the-new-barometer-of-indias-economy-fails-to-reflect-the-deprivations-of-poor-households/articleshow/83696115.cms

[11] https://economictimes.indiatimes.com/opinion/et-commentary/view-there-are-practical-limitations-in-cmies-cphs-sampling-but-no-bias/articleshow/83788605.cms


Cite this item:

APA

Niyati Agarwal, R. S. (2022). Comparing Participation in Formal Financial Services across Two Nationally Representative Surveys: CPHS vs. AIDIS. Retrieved from Dvara Research.

MLA

Niyati Agarwal, Rakshith S. Ponnathpur & Sahana Seetharaman. “Comparing Participation in Formal Financial Services across Two Nationally Representative Surveys: CPHS vs. AIDIS.” 2022. Dvara Research.

Chicago

Niyati Agarwal, Rakshith S. Ponnathpur & Sahana Seetharaman. 2022. “Comparing Participation in Formal Financial Services across Two Nationally Representative Surveys: CPHS vs. AIDIS.” Dvara Research.

Share Via :Tweet about this on Twitter
Twitter
Share on Facebook
Facebook
Share on LinkedIn
Linkedin
Email this to someone
email
AIDISCMIECPHSFinancial servicesHousehold FinanceSurvey
Leave Comment

Cancel reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

19 − 16 =

clear formSubmit

Related posts
Approaches to Assessing Household Income for Microfinance Clients
June 24, 2022
Incremental Adoption of Managed Competition in Germany
June 20, 2022
Note on RBI’s Prompt Corrective Action Framework for Non-Banking Financial Companies
June 17, 2022
Financial portfolio of Indian households – A data book
June 14, 2022
State of Exclusion : Delivery of Government-to-Citizen Cash Transfers in India
June 3, 2022
‘Buy Now, Pay Later’: What is it, and how does it affect customer protection?
May 5, 2022
Search
Recent Comments
  • Prasanna Srinivasan on Care through competition: The case of the Netherlands: “This made interesting and informative reading. Thank you. Inevitably, the mind ran a comparison with the Indian context even while…”
  • Misha Sharma on Direct Benefit Transfers in Assam, Chhattisgarh, and Andhra Pradesh: Introducing the Dvara-Haqdarshak Study on Exclusion in Government to Person Payments: “Great post, Aarushi. It will also be interesting to document the challenges faced in accessing these transfers and experiences with…”
  • Misha Sharma on What is Social Protection?: “Thanks for writing this, Anupama. A much needed piece and looking forward to the second post in this series. It…”
Subscribe and Follow Us

Popular Post

Popular Post
  • Approaches to Assessing Household Income for Microfinance Clients
    June 24, 2022
  • Incremental Adoption of Managed Competition in Germany
    June 20, 2022
  • Note on RBI’s Prompt Corrective Action Framework for Non-Banking Financial Companies
    June 17, 2022

Categories

Categories
  • Channels(88)
  • Consumer Protection(33)
  • Events(30)
  • Featured(42)
  • Field Reports(6)
  • From the field(9)
  • General(22)
  • Guest(30)
  • Household Research(75)
  • Long Term Debt Markets(9)
  • News(45)
  • Origination(30)
  • Products(42)
  • Regulation(112)
  • Research(253)
  • Risk Aggregation(26)
  • Risk transmission(63)
  • Small Cities(21)
  • Technology(25)
  • Uncategorized(105)
  • Unemployment Support(5)

Archives

Archives
  • June 2022 (5)
  • May 2022 (2)
  • April 2022 (4)
  • March 2022 (2)
  • February 2022 (3)
  • January 2022 (3)
  • December 2021 (4)
  • November 2021 (6)
  • October 2021 (4)
  • September 2021 (4)
  • August 2021 (6)
  • July 2021 (6)
  • June 2021 (10)
  • May 2021 (7)
  • April 2021 (9)
  • March 2021 (9)
  • February 2021 (7)
  • January 2021 (3)
  • December 2020 (7)
  • November 2020 (6)
  • October 2020 (10)
  • September 2020 (9)
  • August 2020 (12)
  • July 2020 (3)
  • June 2020 (5)
  • May 2020 (8)
  • April 2020 (4)
  • March 2020 (8)
  • February 2020 (3)
  • January 2020 (9)
  • December 2019 (4)
  • November 2019 (3)
  • October 2019 (7)
  • September 2019 (3)
  • August 2019 (2)
  • July 2019 (4)
  • June 2019 (4)
  • May 2019 (4)
  • April 2019 (7)
  • March 2019 (2)
  • February 2019 (3)
  • January 2019 (3)
  • December 2018 (5)
  • November 2018 (2)
  • October 2018 (5)
  • September 2018 (2)
  • August 2018 (2)
  • July 2018 (2)
  • June 2018 (2)
  • May 2018 (1)
  • April 2018 (1)
  • March 2018 (5)
  • February 2018 (2)
  • January 2018 (2)
  • December 2017 (5)
  • November 2017 (4)
  • October 2017 (3)
  • September 2017 (1)
  • August 2017 (3)
  • July 2017 (1)
  • June 2017 (3)
  • May 2017 (4)
  • April 2017 (3)
  • March 2017 (4)
  • February 2017 (3)
  • January 2017 (6)
  • December 2016 (5)
  • November 2016 (2)
  • October 2016 (3)
  • September 2016 (5)
  • August 2016 (4)
  • July 2016 (4)
  • June 2016 (8)
  • May 2016 (4)
  • April 2016 (5)
  • March 2016 (4)
  • February 2016 (3)
  • January 2016 (3)
  • December 2015 (3)
  • November 2015 (1)
  • October 2015 (2)
  • September 2015 (3)
  • August 2015 (5)
  • July 2015 (3)
  • June 2015 (3)
  • May 2015 (3)
  • April 2015 (2)
  • March 2015 (3)
  • February 2015 (1)
  • January 2015 (1)
  • December 2014 (5)
  • November 2014 (4)
  • October 2014 (3)
  • September 2014 (4)
  • August 2014 (4)
  • July 2014 (4)
  • June 2014 (8)
  • May 2014 (1)
  • April 2014 (4)
  • March 2014 (5)
  • February 2014 (6)
  • January 2014 (8)
  • December 2013 (7)
  • November 2013 (8)
  • October 2013 (7)
  • September 2013 (7)
  • August 2013 (5)
  • July 2013 (6)
  • June 2013 (7)
  • May 2013 (6)
  • April 2013 (8)
  • March 2013 (9)
  • February 2013 (6)
  • January 2013 (9)
  • December 2012 (8)
  • November 2012 (7)
  • October 2012 (5)
  • September 2012 (5)
  • August 2012 (5)
  • July 2012 (7)
  • June 2012 (4)
  • May 2012 (6)
  • April 2012 (4)
  • March 2012 (7)
  • February 2012 (6)
  • January 2012 (8)
  • December 2011 (8)
  • November 2011 (7)
  • October 2011 (8)
  • September 2011 (7)
  • August 2011 (3)
  • July 2011 (6)
  • June 2011 (11)
  • May 2011 (8)
  • April 2011 (9)
  • March 2011 (13)
  • February 2011 (10)
  • January 2011 (8)
  • December 2010 (10)
  • November 2010 (10)
  • October 2010 (10)
  • September 2010 (7)
  • August 2010 (13)
  • July 2010 (10)
  • June 2010 (6)
  • May 2010 (13)
  • April 2010 (7)
  • March 2010 (10)
  • February 2010 (5)
  • January 2010 (4)
  • December 2009 (3)
  • November 2009 (1)
  • October 2009 (6)
  • August 2009 (1)
  • July 2009 (2)
  • June 2009 (1)
  • May 2009 (1)
  • April 2009 (1)
  • March 2009 (1)

Share Via :Tweet about this on Twitter

Twitter

Share on Facebook

Facebook

Share on LinkedIn

Linkedin

Email this to someone

email

Site Map

www.dvara.com