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Friday, May 24, 2019

Household debt over time

by Subhamoy Chakraborty and Renuka Sane.

In a previous article, Estimates of household debt in India, we presented some basic facts about household borrowings in the months of May - August 2018. We found that 46% of households in India had debt outstanding. There was a significant reliance on informal sources for the purpose of borrowing. Consumption expenditure was the most important purpose for which households borrowed followed by housing and business.

In this article, we use the same dataset, the Consumer Pyramids Household Survey (CPHS) to understand household borrowing across time. We present metrics on household indebtedness across 3 waves (January-April 2016, January-April 2017, January-April 2018). We have chosen the first wave of each year so that comparisons are made at the same point of time each year. We use household weights for each wave provided by CPHS to get population estimates for share of households having debt and the distribution of debt across different sources and purposes. CPHS does not provide information on the value of debt outstanding. Our analysis, therefore, is restricted to understanding the proportion of households borrowing from various sources for different purposes.

Overall level of Borrowing

Table 1 presents percentage of households having debt outstanding in Wave 1 in each of the three years. This has increased dramatically over the last three years. In January - April 2016, only 12% of the population had debt outstanding. This increased to 39% by January - April 2018. There has been an increase in household indebtedness in urban regions - by 2018, 40% of urban households had debt outstanding relative to 37% of rural households.

Table 1: Borrowing Share in Population
WAVE NATIONAL RURAL URBAN
Jan16 - Apr16 33 million
(11.6%)
21.0 million
(11.1%)
11.4 million
(12.6%)
Jan17 - Apr17 67 million
(23%)
45.3 million
(23.1%)
20.8 million
(22.4%)
Jan18 - Apr18 114 million
(38.8%)
79.8 million
(40.0%)
34.3 million
(36.5%)

Share of sources in the population

Figure 1 presents the percentage of households in the population who have borrowed from the different sources. This throws up several interesting facts. First, the share of households who have debt outstanding from a bank has been steadily rising, consistent with rise in personal loans from banking data. The same is true for debt from relatives and friends. Second, there has been a reversal of borrowing from money-lenders. In 2016, less than 3% of households claimed to have debt outstanding from money lenders. In 2017, this rose to a little over 7.5%, and since then has fallen to 4.5% in 2018. Third, there has been a dramatic increase in borrowing from shops. In 2016, less than 1% of households had debt outstanding from shops. In 2018, this number was about 11%.

Figure 1:Share of borrowing in the population

Figure 2 presents the percentage of households who have borrowed from shops in each income decile. Borrowing from shops increased remarkably in 2018 across all income deciles. The increase was highest for the lowest income decile from 2% in 2017 to 15.5% in 2018. The corresponding increase in highest income decile was from 3% to 7.5%.

Figure 2:Borrowing from Shops across Income

Reasons for borrowing

Figure 3 presents the percentage of households who have borrowed for various purposes. Consumption expenditure remains the single largest reason behind household borrowing. Although in 2016 borrowing for consumption and housing were at the same level, housing grew slowly compared to consumption. Borrowings for business and repaying outstanding debt saw a sudden jump in overall share in 2018.

Figure 3:Reasons for borrowing in the population

Figure 4 presents the the percentage of household who have borrowed for consumption across income deciles. In 2016 the share of borrowing for consumption was almost equal across income deciles, around 2-3 %. However, by 2018, there was a huge difference between the deciles. The share of borrowing in the lowest income decile increased from 2% in 2016 to 21% in 2018. The corresponding rise in the highest income decile was from 2.5% to 10%. In 2018 21% of households in the lowest decile had borrowed for consumption expenditure as compared to 10% in the highest income decile.

Figure 4:Borrowing for Consumption across Income

Conclusion

In this article we have presented some facts about the change in household borrowings in India between 2016 and 2018. These are:

  • The percentage of households who have debt outstanding has increased from 12% of the population in 2016 to 39% of the population in 2018. The increase has been slightly higher in urban India relative to rural India.
  • There has been an increase in borrowing from banks, relative and friends, and shops. In fact, shops have seen the largest increase as the source of borrowing.
  • The incidence of borrowing from shops has been higher for the lower income deciles.
  • The biggest jump in the reasons for borrowing has been on consumption expenditure.
  • Borrowing for consumption expenditure increased more for lower income deciles.

 

The authors are researchers with the National Institute of Public Finance and Policy.

The EVM – VVPAT saga

by Abhay Bhatt and Rajeeva Karandikar.

There has been lot of grumbling in the Indian media about Electronic voting machines (EVM), esspecially over last 3 months, with opposition parties accusing the government of manipulating EVMs. This reached a crescendo recently when all the opposition parties joined hands and filed a petition in the Supreme Court seeking a directive to the Election Commission to cross verify the vote count reported by the EVM, with that of paper slips produced by the VVPAT (Voter verifiable paper audit trail), in 50% of the booths.

The Election Commission had consulted us about the sampling plan to be put in place to instill confidence about the sanctity of the election process. Here is our take on how to think about these questions.

The background


  1. EVMs were first used in the Paravur Assembly constituency in Ernakulam district in the 1982 Assembly poll in about 50 booths. The CPI candidate, Mr. Pillai, defeated the Congress candidate, Mr. Jose, by a thin margin of 123 votes. Mr. Jose went to the High Court with the contention that the Representation of the People Act, 1951, and the Conduct of Elections Rules, 1961, did not empower the Election Commission to use EVMs. While the High Court dismissed the petition, subsequently the Supreme Court upheld the contention and ordered a repoll in these 50 booths. Mr. Jose won the election after this repoll.
  2. Subsequently, the Representation of the People Act was amended, and S.61A was inserted, in December 1988, empowering the use of EVMs.
  3. These EVMs were designed by public sector undertakings, BEL (a Defence Ministry PSU) and ECIL (an Atomic Energy Ministry PSU), who also manufacture the same. They are subjected to a thorough testing process.
  4. The design and production are overseen by a technical expert committee consisting of senior professors in electronics and computer science from leading Indian Institutions.
  5. The EVMs do not have any networking hardware. There is no ethernet port, no wifi or bluetooth capability, and thus it is not possible to alter or tamper the memory remotely.
  6. The names of candidates on the EVM appear in an order that is determined by the same convention that had been followed since the sixties for the order on the ballot paper. First, the candidates of the national parties appear, in an alphabetical order of their names, then candidates of state parties (again in an alphabetical order of their names) and lastly the rest, again in an alphabetical order of their names. Thus, the order gets determined only after the last date of withdrawal of nomination.
  7. The EVMs are distributed across the constituencies via randomisation. The EVMs used in India consist of two units: BU, the balloting unit and CU, the control unit. The BUs and CUs are distributed independently and on the day of polling, the two are connected. If one of them has been tampered or replaced, the handshake between the two units will fail and the pair will have to be replaced.
  8. After the voting, the machine is locked by the presiding officer and then the EVM are physically sealed using the same techniques that were used to seal the ballot boxes of old.
  9. In the parliamentary elections in 1999, EVMs were used in some constituencies and from 2004, all the elections to the parliament and to the state legislatures are conducted using the EVMs. It should be noted that in several instances, including in 2 out of three parliamentary elections – 2004, 2009 and 2014, the ruling party has lost the election.
  10. The fact that there was no way to do a recount, even if a court ordered the same, was a reason for the Supreme Court to ask the EC to find a way of generating a paper trail. The Election Commission appointed a committee of experts, who came up with a design of the VVPAT machine and the Supreme Court ordered that the same be introduced as soon as possible for all elections.
  11. The Supreme Court had not ordered the Election Commission to routinely carry out any cross verification of EVM and VVPAT count. The purpose of VVPAT was to have the possibility of a recount if a court so ordered, as a result of an election petition.
  12. Since so many doubts had been raised about EVMs, the Election Commission decided that in every assembly constituency, one booth will be picked at random by a draw of lots and for the chosen booth, the VVPAT slips will be counted and cross checked with the count on the EVM. This done in order to increase public confidence in elections.

Our analysis of the recent debate


Over the last year, demands started coming up for verification of much larger number of EVMs. Various petitions were filed. The election commission engaged the two of us along with Mr. Onkar Prasad Ghosh to advise on an appropriate sample size, so if that many EVMs are randomly chosen and the machine count is verified with the VVPAT count and if no mismatches are found, then we can be confident that defective EVMs, if any, are in insignificant proportion.

We felt that given that the EVM's are assigned randomly to constituencies and that the order of names on the EVMs is determined at a late stage, only after the last date of withdrawal, it is not possible to manipulate or tamper the EVMs centrally.

Given that there is no networking component in EVM, tampering is possible only by getting physical access. If someone can get physical access to an EVM and tamper with the EVM, then the VVPAT slips can also be tampered and so validating EVM count by VVPAT count does not give any guarantee that EVM has not been tampered with. For this we must rely on the elaborate process that the Election Commission has about sealing the EVM in a bag, closing the same and storing in such a way that tampering can be detected. This was also the case with the paper ballot and ballot box method of earlier years. We are no worse with EVMs as compared with the old ways, in this regard.

Also, if some smart mind does figure out a way of changing the memory of EVMs remotely, he/she will not stop with doing so in one or two booths. Certainly, the effort will be to tamper with a larger number of constituencies so as to make an impact on the national level.

That is the reason that we took our objective to be to conclude with high degree of confidence that defective EVMs, if any, are less than a certain percentage of all EVMs in use nationwide. In our report we had taken this as 2%, but it can be 1% or 0.5%.

It is true that our suggested method does not give a guarantee at constituency level. But in our view, such a guarantee is not needed. Our sampling scheme can guarantee that the national picture has not been distorted by tampering or by a manufacturing defect. To those who have been insisting upon constituency level guarantees, we would ask: Why stop at the constituency? Should not every voter be assured that his or her vote has been counted correctly? The only way to do so without compromising privacy is to use cryptography. This is the subject of present research, with Prof. Bimal Roy, former director of ISI involved with one such initiative along with a team in UK. But when such a solution would become available, it can and will be attacked as opaque!

The Election Commission, in its affidavit to the Supreme Court, stated that in the last 2 years, over 1500 EVM counts have been matched with VVPAT counts and in all cases the matching has been perfect. Statistically, this alone is sufficient to conclude that EVM-VVAPT in use currently along with all the safeguards and practices in place are good.

We believe there is a lot of misinformation in the media. Various cases of EVM malfunction are being reported in the media and social media. These relate to local body elections or even college student union elections etc., which are outside the purview of the Election Commission. Other reports of EVM malfunction on the day of election are mostly about EVMs which fail the test before voting starts and are replaced.

While our recommendation was to draw a random sample from the population of all the EVMs in use, the EC decided to continue with their policy (for operational simplicity) to draw one booth per assembly segment, which translates to verifying 4125 EVMs by cross checking VVPAT counts. Based on the data about the number of booths across 4125 assembly segments, we were able to assert that if no defective is found in these 4125 chosen booths, we can say with 99.99999% confidence confidence that the proportion defective is less than 1%. This bound is true irrespective of the configuration of the defective EVMs. For example, a group of miscreants could have tried to tamper with EVMs selectively across a few constituencies. However, as long as the number of defective EVMs is 1% or more, the sampling procedure will catch this with a high probability.

The Supreme Court has ordered or suggested that instead of 1 per segment, 5 EVMs per assembly segment be drawn and VVPAT count and EVM count be cross verified. Based on our calculations, we conclude that if there are no defectives found in the 20625 randomly chosen booths (5 per assembly segment), then with 99.99999% confidence, the proportion of defectives, if any, are less than 0.25%, irrespective of the configuration of the defectives.


The authors are Professor, Indian Statistical Institute, Delhi and Director, Chennai Mathematical Institute, respectively.

Saturday, May 11, 2019

Coincidences in investment newsletters, fund managers and bellwether constituences

by Ajay Shah.

Burton Malkiel's design of a newsletter scam


In his famous book, Burton Malkiel offers the following idea.

  1. Start 16 newsletters. In 8 of them, scream for a year that Nifty will go up, and in 8 of them, do the opposite.
  2. At the end of year 1, you have 8 successful newsletters. Close down the losers. Now repeat this, with 4 forecasting up and 4 forecasting down.
  3. At the end of year 2, you have 4 successful newsletters, shut down the others.
  4. At the end of year 3, you have 2 successful newsletters.
  5. At the end of year 4, you are solid gold: you are holding one newsletter which correctly timed the market for 4 years in a row. Now make a lot of money selling subscriptions to this newsletter.

While this is a neat design of a scam, the world is actually, inadvertently, running something like this. A large number of newsletters are born every year. Some of them are lucky, they forecast the market correctly, and they stay alive. The losers tend to shut down.

At every point in time, you see a pool of successful newsletters. This need not imply that they have forecasting capabilities. It could just be survivorship bias at work.

Fund management


This same idea would work in fund management. You could start 16 funds, and at the end of 4 years, you would be holding 1 fund with a remarkable track record. This is possible even if you have no ability to forecast asset prices at all.

Once again, the world is actually running such a system. A large number of money managers spring up all the time. When the bets don't work out, the organisation collapses. The survivors stay in the game.

The world is initiating much more than 16 funds. Thousands of fund managers take a stab at the trade. It is not surprising that at any point in time, we see five or ten of them with five or ten years of a successful track record. While some ability may exist in the world, there is certainly a simple process of survivorship bias going on, which generates a few fund managers with a good track record.

Bellwether constituencies


Suppose you have 500 constituencies, and suppose all election outcomes are roughly 50/50. That is, there are exactly two parties and they each win about half the seats. Suppose that in truth, the outcome of each constituency is completely random and it is just like tossing a coin.

At the end of one election, you have 250 constituencies where the winner of the overall election won.

At the end of two elections, you will have 125 constituencies which were with the winner for two elections in a row.

At the end of three elections, there will be 62. At the end of four elections there will be 31.

This tells us that if we see about 30 constituencies in India, where the winner in each of these constituencies was the ruling coalition that came out of the Lok Sabha elections for 1999, 2004, 2009, and 2014, this might just be simple randomness at work. There may be nothing special about these `bellwether constituencies'.

Wednesday, May 01, 2019

Announcements

Job Opening:

Manager, Centre for Development Economics, Delhi

Centre for Development Economics (CDE) is a research adjunct of the Delhi School of Economics (Department of Economics). It was established in 1992 with a grant from the Ministry of Finance, Government of India. CDE is a small non-profit organisation that supports research activities of the Department of Economics. This includes, inter alia, organising international and national seminars, workshops and lectures, managing research projects, hosting academic visitors, providing IT services to faculty and students and any other research support department faculty may require. The management of CDE is through a Council comprising faculty members.

As the administrative head the Manager has a leadership role and is responsible for managing all of the above activities. Inter alia, s/he (i) communicates with national and international funding agencies, (ii) handles logistics of prestigious international and national conferences and workshops, (iii) coordinates with CDE auditors to ensure accounts are maintained properly and with faculty members in maintaining project records. In these functions s/he is assisted by office staff that report to her/him and is guided and mentored by faculty.

Minimum Educational Qualifications:

Bachelor’s degree in any subject. Other things equal a higher degree would be an advantage.

Work experience:

At least 2-3 years in a similar role.

Other requirements:

  • Proven track record of strong written and oral communication skills including the ability to independently draft letters, memos and emails.
  • Demonstrable fluency in written and spoken English is essential.
  • High level of competence with commonly used software such as Word, Excel and PowerPoint.
  • Ability to manage research projects.
  • Ability to manage a team of 6-7 staff.

The ideal candidate will be a dynamic self-starting person with a willingness to learn. This position offers high visibility and scope for professional growth. An earlier occupant of this position has gone on to become Registrar at a top university.

Remuneration will be based on qualifications and experience. It includes medical insurance and leave benefits.

Please apply with a CV and names of three references to jobs@econdse.org

The position is available immediately.

Applications will be accepted till it is filled.

Only shortlisted candidates will be contacted and invited for a face to face interaction.