Mota Bhai, Let’s Listen to the Messages from NOTA

In India, NOTA i.e., ‘None of the Above’ was introduced as a choice for the Electronic Voting Machines and Postal Ballots in the General Elections in 2014. It is widely accepted that a NOTA vote is lack of endorsement by the voter for any of the candidates contesting in a given constituency. Regarding NOTA, the Election Commission of India has clarified the following:

1. Even in the extreme case when the NOTA votes in a constituency are higher than any of the candidates, the candidate securing the highest votes will be declared the winner. In other words, as per the norms of first past the post, NOTA cannot be declared the winner.
2. NOTA votes will not be considered for forfeiture of deposits in an election. Please note that in an election in India, if a candidate fails to secure at least 1/6^th (16.67%) of the valid votes cast, he or she forfeits the security deposit.     

A lot has been talked about NOTA and political scientists have put forward different viewpoints on NOTA. I am not discussing or debating these viewpoints. In this blog, I will analyze the NOTA votes cast in 2014 and try to draw some conclusions objectively.

In the general elections in 2014, roughly 1.08% of the votes cast were NOTA. This amounts to 5.99 million votes out of a total of 547 million votes. Some of the basic statistics pertaining to NOTA votes are in the table below.

 Table I: Summary Statistics of NOTA Votes by Constituency, 2014 General Elections

As we can see, the average NOTA votes in a constituency were 1.12%. In a large democracy like India which has more than 800 million voters, such NOTA votes represent a very small percentage. Therefore, there could always be an attempt to brush the NOTA votes under the carpet or to treat them as having nuisance value at best. However, we can also see from the table above that the maximum NOTA votes in a constituency were slightly higher than 5% and that the 90^th percentile is 2.4%. As with any statistical analysis, it is important to look at the frequency distribution instead of just the mean. The frequency distribution of the percentage of NOTA votes in all Lok Sabha constituencies is presented below in Chart A.

Chart A: Frequency distribution of the percentage of NOTA votes in All Lok Sabha Constituencies

 

From the frequency distribution we can see that in the 2014 General Elections, in 417 constituencies out of a total of 543 the NOTA votes were 1.5% or lower. In addition, there are 25 constituencies in which the percentage of NOTA votes were 2.5% or higher. I decided to look at the characteristics of these constituencies which recorded much higher than average NOTA votes. Table II below shows the top ten constituencies with highest percentage of NOTA votes.

Table II: Top 10 Constituencies which recorded the highest percentage of NOTA Votes in 2014 General Elections 

 

It is quite apparent from the table able that these top ten constituencies are all in the reserved category and 8 out of these 10 are reserved for Scheduled Tribes. In addition, of the top 25 constituencies by highest percentage of NOTA votes, 17 are reserved; 3 for Scheduled Castes and 14 for Scheduled Tribes. And of the top 50, 30 are reserved; 7 for Scheduled Castes and 23 for Scheduled Tribes. One can thus draw a definite conclusion that in the constituencies reserved for Scheduled Tribes, the percentage of NOTA votes have been higher than the norm. It is also noteworthy to point out that the Nilgiris constituency in Tamil Nadu which recorded the second highest proportion of NOTA votes in the country is the home of the Badaga tribe. This tribe has been agitating to be recognized as a Scheduled Tribe for a long time.

I decided to go one step further and analyze the frequency distribution of NOTA Vote % for the reserved and general constituencies. The objective was to evaluate if the distribution of seats with different NOTA Vote percentages is markedly different in reserved seats versus the general category ones. From the distribution (see Chart B), it is quite evident that the NOTA Votes cast in seats reserved for Scheduled Tribes is significantly different than the general seats as well those seats reserved for Scheduled Castes.

Chart B: Frequency distribution of the percentage of NOTA votes in for General and Reserved Constituencies

 

Let’s take for example the constituencies where the percentage of NOTA votes were between 2.0 and 2.5%. As evident from the chart above, in less than 10% of the general constituencies and those reserved for Scheduled Castes, the proportion of NOTA votes were in the range 2.0 to 2.5%. By contrast in constituencies reserved for Scheduled Tribes, slightly more than 25% of them recorded NOTA votes in that range of 2.0 to 2.5%. Next, let us consider those constituencies where the percentage of NOTA votes were 0.5 to 1.0%. In the general constituencies and the ones reserved for Scheduled Castes, more than 35% of the constituencies recorded NOTA votes between 0.5 and 1.0%. By contrast in constituencies reserved for Scheduled Tribes, in only about 5% of the constituencies, the proportion of NOTA votes were in the range 0.5 to 1.0%.

Finally, we look at the proportion of NOTA votes in constituencies reserved for Scheduled Tribes in all the states where there is at least 1 seat reserved for the Scheduled Tribes. We then compare the proportion of NOTA votes in these reserved constituencies to the proportion of NOTA votes in general constituencies and the ones reserved for Scheduled Castes (see Table III below).

Table III: Comparison of NOTA vote % in constituencies reserved for ST versus other constituencies

 

From this table it is evident in every single state where there is more than 1 seat reserved for the Scheduled Tribes, the proportion of NOTA votes has been significantly higher as compared to the other constituencies.

In Gujarati, the elder brother is affectionately referred to as ‘Mota Bhai’. I want to borrow this phrase and make an impassioned plea not to ignore the NOTA votes in the constituencies reserved for the Scheduled Tribes. Even with a low percentage of NOTA votes, the Scheduled Tribes in India are conveying a message. It could be that they are genuinely unhappy with the candidates who are in fray and hence, decide to cast a NOTA vote. But I fear that if they casting a NOTA vote because they feel marginalized in the economy and polity of modern India, then it is unfortunate and is probably leading to an incendiary situation. Mota Bhai, the least we can do is to understand the root cause and try to address it.

The Consumer Centric Behavior of Indian Stock Markets

Gross Domestic Product (GDP) is the sum of Consumption (C), Government Spending (G), Savings (S) and the difference of Exports and Imports (X – M). Mathematically, GDP = C + G + S + X – M. Different countries exhibit different characteristics in GDP and GDP growth. For example, in the United States, the GDP is primarily fueled by consumption. Consumption accounts for about 70% of the total GDP in the United States. On the other hand, in China, savings and exports contribute a significant portion of the country’s GDP. In India, GDP is primarily driven by consumption as seen in Chart A below.

Charts A: GDP and Household Consumption in India (1960 – 2017) Source: World Bank

In 2017, India’s GDP was US $2.66 trillion of which US $1.488 trillion came from household consumption - a contribution of 56%. One could argue from the chart above that over the years, the contribution of consumption to GDP has gone down significantly and the argument is true. In 1990, household consumption accounted for 67% of India’s GDP whereas in 2017, the contribution was 56%, a drop of 11% in 27 years. However, one has to understand that from 1990 to 2017, India’s GDP has increased from US $507 billion to US $2.66 trillion which is more than a 5-fold increase. Consequently, household consumption has also grown significantly from US $38 billion to US $1.488 trillion – a 4.4 times increase which is not insignificant by any means. (Note: All GDP and related figures are in constant 2010 US $ terms to eliminate any effects of foreign exchange translation).

In addition, we have to also look at how the population and per capita consumption has increased from 1990 to 2017. In 2018, India’s population was 1.339 billion as compared to 870 million in 1990 (see Chart B below). This accounts for an increase in 54% over 27 years or a population growth of about 1.6% per annum.

Chart B: Population in India (1960-2017) Source: World Bank

During the same period from 1990 to 2017, per capita household consumption in India has increased from US $388 to US $1,111 (see Chart C below). Also, it is interesting that the rate at which per capita household consumption has increased has also accelerated. Between 2000 and 2010, per capital household consumption increased by 47% whereas, the same increase between 1990 and 2000 was 31%. In seven years between 2010 and 2017, per capita household consumption has increased by 49%. At this pace, in 2020 per capita household consumption in India might be 70% more than what it used to be in 2010.

Chart C: Per Capita Household Consumption in India (1960 – 2017) Source: World Bank

 

Based on the analysis thus far, one can safely arrive at two important conclusions:

• In India, household consumption is a major driver of GDP.
• In the coming years, per capita household consumption is expected to increase and could thus provide significant boost to the GDP.

The question then is how has the stock market in India reacted to increasing household consumption. After all, the financial markets are efficient and prices reflect all available information. Therefore, our hypothesis is that the companies in India that cater to household consumer demand should have done well.

In order to validate this hypothesis, we need to classify publicly traded companies. For this purpose, we used the FactSet Revere Business Classification System (RBICS). RBICS is a multi-level industry classification system and we have used the topmost level called ‘RBICS Economy’ for this exercise. Each of the RBICS Economies has been classified into one of the three Economic Sectors – Consumer, Infrastructure and Technology (see Table I below).

Table I: RBICS Economy and classification into Consumer, Infrastructure or Technology

Based on this classification, we then created two stock market indices of publicly traded companies in India - India Consumer Index and India Infrastructure Index. For each of these indexes, we consider companies whose RBICS Economy Code fall in the corresponding economic sectors as outlined in Table I. After all, the best way to assess the performance of a stock market or a segment of the stock market is to create an index and track the performance of the index over time. In financial engineering, this process is called ‘Back-testing’.

The specifications for these indices are as follows:

• Number of constituents: 50
• Currency: Indian Rupee
• Review and Rebalancing Frequency: Quarterly on Mar 31^st, June 30^th, Sep 30^th and Dec 31^st
• Weighting Methodology: Free-float Market Value Weighted
• Eligibility Criteria:
• Average monthly turnover (turnover is monetary value of stocks traded) over last 12 months is at least US $2 million
• Average market capitalization over the last 3 months is at least US $250 million
• Ranking:
• The eligible companies are then ranked by free-float market capitalization and the top 50 are selected in each review period

Free-float Market Capitalization = Free-float Factor * Market Capitalization. Free-float Factor represents the proportion of shares that are tradeable and are not held by entities like government, promoters, holding company, joint venture, sovereign wealth fund, etc. The rationale is that these owners buy and hold the shares for long periods and these shares are not available for trading in the stock markets.

The performance of the India Consumer Index is very impressive. The index was back-tested from Jan 1^st, 2008 to Dec 31^st, 2018 – a span of 11 years. The year 2008 was deliberately selected as the starting point to capture the global economic downturn precipitated by the banking crisis worldwide. Over these 11 years, the cumulative returns of the India Consumer Index is 270% as compared to 77% for Nifty-50 and 78% for BSE Sensex (see Chart D and Tables II & III below).

Chart D: Comparative Performance of India Consumer Index and Nifty-50

 

Table II: Comparative Performance of India Consumer Index and Nifty-50

Table III: Top 20 constituents of India Consumer Index

By comparison, the India Infrastructure Index underperforms significantly. Over the same period Jan 1^st, 2008 to Dec 31^st, 2018, the cumulative returns are 26% and in addition, the volatility is higher than Nifty-50 and BSE Sensex by about 3% (See Chart E and Tables IV & V below).

Chart E: Comparative Performance of India Infrastructure Index and Nifty-50

Table IV: Comparative Performance of India Infrastructure Index and Nifty-50

Table V: Top 20 constituents of India Infrastructure Index

Conclusions:

• In todays’ world, financial markets worldwide are very efficient and they incorporate all available information into the prices of securities and the Indian stock market is not an exception. As is evident from the analysis, the Indian equity markets have obviously reacted to the fact that household consumption is a major driver of the Indian economy and will continue to be so in the future.
• Given the fact that household consumption is becoming such a major driver of the economy, it is worth giving a substantive tax cut to the middle class. That has the potential of driving up household consumption even higher and could spur the economy instantaneously. The skeptics will argue that such a move will result in inflation. The counter argument for that is in recent years in India, inflation has been historically low and this could be the best time to spur economic growth further by boosting household consumption through a substantive tax break.
• Also, the Indian equity markets are not optimistic about the infrastructure sector. The prices in equity markets project future trends and based on such belief, one has to conclude that in the near future, things do not look very bright for companies in the infrastructure sector in India. There could however be potential value in this sector in the long run say, 20-30 years.

Disclaimer: This analysis is neither an endorsement nor a criticism of the economic and monetary policies of the Government of India or the policies followed by the governments in power since 1990. This study is a purely an attempt to understand some of the drivers of the equity markets in India.