Thinking Rationally

Category: New

  • Cry Jamlo Makdam Cry

    In a heartbreaking tragedy, a 12-year-old child labour – Jamlo Makdam died on 20th April after walking for 150 km from her workplace Bhupalpally in Telengana to her native place, Bijapur district in Chattisgarh. She was working in Chilly fields in Kannaiguda village.

    see here

    I have written a poem in her memory.

    Cry not -my beloved country- Cry not

                    Save your tears

                    for Jamlo, the chilly-picker,

    She needs them plenty

    to keep her walking.

    Only a mile afar

     mother waiting to hug her

    quench her thirst -before she moves to a land unknown.

    Running away from coronavirus, with week’s hunger in belly,

    100 rupees tucked in her skirt, bedecked with chilly flakes,

    a mere 150 kilometers to walk,

    no marathoners to accompany

    she is walking, walking, and walking.

    On a lonely road

    Sun blistering above

    With no helpful winds to blow away the heat

    She is walking, walking, and walking.

    Thirsty blood, tearless eyes

    Saliva-less tongue

    Still her dream dies hard

    home, sweet home and mother awaiting – her final resting place.

    Hunger, her best friend, she is not afraid of,

    because she must walk, walk, and walk.

    Stars are shining

    in their AC cooled rooms,

    cutting hubby’s hair short, sweeping floors – a first time in life

    singing paeans to Lockdown, Lockdown and Lockdown

    A 100K like in Instagram -no wonder.

    Leaders are busy in their virtual world

    With Mask on

    Conferring on matters of life and death

    gravitas overflowing

    may be talking about Michelangelo

    and heart beating about Jamlos at large.

    But our Jamlo is not even a footnote.

    Which country owned Toba Tek Singh?

    Gods only know.

    Which state owns Jamlo for her to receive some succor?

    The answer is blowing in the wind

    To her mother’s arm that is the only place on earth she belongs to.  

  • Corona Pandemic- One size does not fit all

    “Blessed are the Meek, for They Will Inherit the Earth” (Matthew 5:5). 

    Corona virus -COVID-19- started its journey in an industrial city of China sometimes in late 2019. Within a short span of 3 to 4 months it has enveloped the entire earth with its foot print, thus qualifying it to be designated as a pandemic attack by a tiny microorganism that can multiply only when it can find a human cell as a host , a springboard for jumping to its next victim. It is said that a virus is agnostic about the socio-economic profiles of its victims; it does not care as to what economic strata as person belongs, to what god a person kneels. At the same time credible evidence is there that age, sex and existing conditions do have a bearing on the survival probability of a corona infected person. For example, a study1 of 6839 corona deaths in New York City shows that 72.3% of them belonged to the age group 65 and above, 75% had underlying conditions like Diabetes, Lung Disease, Cancer, Immunodeficiency, Heart Disease etc. 62% of the victims were males.  In another study of 44,000 cases from China, deaths were at least five times more common among confirmed cases with diabetes, high blood pressure or heart or breathing problems2.

    So, there are factors that create an enabling conditions for COVID-19 to thrive and kill its victims. But rate of incidence of corona cases and consequent deaths also varies between countries.  One Indian internal medicine expert has stated why incidence of corona is relatively low in India. He has identified 3 factors for a virus’ spread — the “agent or the virus itself, the host and the environment”.  According to him India’s relatively higher temperature and humidity slows down the march of the virus3.

    It has also been reported that a US government study has also confirmed the role of ambient temperature and humidity in killing the virus on surfaces and air4.

    Even after controlling all the above noted factors there is cultural a dimension that also determines how the virus would affect a given society. David Kelvin, a Canadian microbiologist has pointed out that the practice of Italians greeting “each other with an embrace and kisses” increases the probability pf passing the virus “on a more dangerous dose of COVID-19.”5

    Religious faith also sometimes determines a society’s willingness to accept scientific approach to handling of any epidemic disease. For example, only 72.2% of children aged 19 to 35 months in the United States were fully vaccinated in 20156.

    A major global survey published in June 2019, covering 140,000 people aged 15 and older in more than 140 countries found people in higher-income countries were among the least confident in vaccine safety — particularly in North America and Europe. Meanwhile, vaccine trust was highest in countries where preventable diseases still spread, such as Bangladesh and Rwanda.7

    The above brief review of various plausible determining factors for country wide variations in incidence of corona virus and subsequent death provides a possible direction to further research that would help countries to identify deficiencies in their health infrastructure and attitudinal bottlenecks of the people at large to contain and minimize the effect of a virus like corona , in current time as well as in future. Pending that it may not be irrelevant to look at available data that provides some clues to the factor that are driving the variations in country wise impact of corona virus. Our aim is to carry out a descriptive statistical analysis without trying to build any model for conducting statistical hypothesis. 

    Data and Study Variables: For this article we have used data that are available in public domain and put out by multilateral organizations like World Bank, World Health Organization., Worldometer and Pew Research Centre. Main data on COVID-19 is collected from Worldometer, a reference website.  Pew Research Centre brought out a report in October 2017 analyzing religious change and its impact on societies around the world. Covering 199 countries and territories around the world, the study identified countries which favor a specific religion either as an official government sponsored religion or by according a special status to one specific religion over all other faiths. Income data is taken from World Bank website. Expenditure on health data is taken from WHO website. (the further details are available in a table given at the end).

    Intensity of infection of a virus can be estimated by the number of virus afflicted persons with symptoms. But a corona infected person may not show any symptom for several days, extending up to 14 days. These pre-symptomatic cases cannot be detected unless a country either carries out a random tests of enough size or for all citizen or at least of all persons in selected age groups. It is also possible that many persons with COVID-19 symptoms remain un-documented because many covid-19 infected persons with mild symptoms recover without hospitalization.  So, the number of cases reported by a country may also depend on the number of tests carried out by that country. However, we consider the number of reported cases as the primary variable of study. To account for the effect of population size we have taken normalized variables- that is cases/tests/deaths per million of population. 

    Regarding health infrastructure we have considered the “government expenditure on health as percentage of government expenditure / GDP” as the discriminating variable across countries. To convert this numerical variable to a categorical variable, we have divided countries into 4 groups based on their percentile ranks; 4 groups based on 25 percentile, Median, 75% and maximum amount. The corresponding groups are named as Lower, Lower Middle, Upper Middle and High spenders.

    Regarding “Religious Status” variable, every country is put into one of the three categories- (1) Having official State Religion, (2) Having a preferred religion, (3) No official religion. Countries which have declared atheism as official doctrine, we have designated “Capitalist Communism” as its state religion. China, Vietnam. Incidentally, Russia has a preferred state religion- Christianity.

    Analysis:

    Country Coverage:  This study is based on 123 countries having a total population of 7.2 billion as on 2019. The latest US Census Bureau estimates world population at 7.58 billion as on June 2019, a coverage of 95% of world population8

    Income Group: The total number of cases of these countries was 2,32,37,82 or around 2.3 million. If we had included cases of all countries which have reported COVID-19 cases, this number would have been 2.33 million. So, analysis that follows would be representative of the world scenario.  Top ten countries in terms of number of cases accounted for 1.8 million cases, that is 78.26 percent of total cases covered. The income group wise profile of COVID-19 and its proximate determinants is given in the table below.

    Table 1 here:

    Table 2 here

    The descriptive details of various measures of incidence of COVID-19 across income groups and its covariates given above leads to one conclusion – the richer countries with higher proportion of older people are more likely to fall prey to COVID-19 and once infected most likely to die also. The best possible health infrastructure does not provide any protection against these silent and invisible killer.

    A sharper picture emerges if one looks at the top ten countries in terms of incidence of COVID-19. The following table gives the relevant details.

    Table 3 here            

    One obvious outlier in this group most affected countries is Germany. Despite having a high share of older people and a moderate level of public expenditure on health it could achieve much better performance in containing death rate of affected persons. The fact that Germany conducted tests of relatively larger number of persons may not be a good explanation because Spain and Italy also have tested a similar proportion of its people. S

    Health Infrastructure:

    The quality of health infrastructure of a country is positively correlated with the government allocation of resources for this purpose. Many physical indicators like number of doctors per million people etc. would depend more on government initiative than on private one. To establish the relationship between quality of health infrastructure and other COVID-19 related measures we have converted two numerical indicators of Government health expenditure into qualitative measures based on their percentile ranks. The resulting 4 quality levels are based on quartiles. These 4 levels in ascending order are Low, Lower Middle, Upper Middle, High. The tables below are expected to provide some clues about the importance this factor in determining the intensity of COVIS-19 in different countries.

    Table 4 here

                 

     It is obvious that, the countries in highest income bracket with high rate of government expenditure on health suffered disproportionately more due to COVID-18 pandemic. This group of countries accounting for 10.7 percent of the world population recorded 65.4% of death due to COVID-19.  Both China and India, two countries that account for near about 40% of world population and both spending relatively much less than their peer countries in their respective income groups account for only 4 % of the share of cases and 3 % of total deaths. In China, a plausible reason for this could be that the government at a early stage could segregate the district where the virus first struck.  In India, demographic profile of the population as well as peoples’ inherent immunity due to their constant exposure to highly un-hygienic living conditions could be one factor.  I believe people intuitively understand this- the fact that migrant workers are risking their lives to go out of their metropolitan workplaces to remote villages without any worthwhile medical facilities only corroborates what our data is showing above. It is the rich who should be more scared of COVID-19 than the poor.

    Age Structure:

    Table 5 here

    Table 6 here

    Table 7 here

    The following chain of hypothesis emerges from the data presented above:

    1. the prosperity results in longer life span of people of high-income countries
    2. better health infrastructure increases survival probabilities of older people with heightened co-morbidities
    3. when a new virus like COVID-19 emerges on the horizon, these are the people who are most likely to succumb to the new killer.
    4. in the low-income countries with rickety health infrastructure expected life span is shorter
    5. high child mortality and un-hygienic environment of living for the poor masses create a built-in capability to survive in a hostile environment.

    Blessed are the poor for whom poverty is an enabling condition that better prepares them to face the vagaries of nature; otherwise they would have died young. Cursed are the rich who are shielded by their wealth from various known morbidities but make them ill-prepared to face an unknown one.

    Societal Culture 

    Wikipedia defines culture as “an umbrella term which encompasses the social behavior and norms found in human societies, as well as the knowledge, beliefs, arts, laws, customs, capabilities, and habits of the individuals in these groups” 9.  As mentioned above forms of greeting a person through hugging vs handshake vs bowing reflects “culture” of a group of persons. Religious beliefs or faiths provide the overarching framework of culture of most of the countries, even in 21st century. Such beliefs do matter in the mundane task combating a pandemic. In many Islamic Societies, women cannot go out without wearing burqa or hijab, a kind of mask.  Wearing mask or covering face with simple clothes has been made mandatory in many countries reeling under COVID-19. So, women are much better protected in a conservative Islamic society. An obvious testable hypothesis would be that women to men infection ratio would be much less in an Islamic country that a non-Islamic one.

    Religion could be another major factor in determining the intensity COVID-19 infection in social groups opposed to vaccination. Many low-income or lower-middle income countries have implemented universal immunization policy. But in many developed countries it is legally permitted by parents to deny vaccination to their children invoking religious sanction against vaccination.  For example, in USA, 45 states and Washington D.C. have allowed religious exemptions for people who have religious objections to immunizations. 15 states now allow philosophical exemptions for those who object to immunizations because of personal, moral or other beliefs. The Wellcome Trust survey cited above found that some of the world’s top anti-vaccine countries are in Europe. In France 1 in 3 persons disagreed that vaccine is safe. Till a few years back many Catholics were opposed to vaccination because “genetic source material made to develop most vaccines come from aborted fetuses”.  It may be noted that more than 80% of Italian citizens were Catholics. In Spain around 68% are roman Catholics.

    Thus, religion can be considered another factor that may affect the progress of COVID-19 in any country. When a state declares a religion as a state religion or a preferred religion, the world view of that religion would guide, direct and probably compel any citizen to be incompliance with the edicts of that religion. The following table may not confirm or reject, prima facie, the role of religion in creating a relatively smooth passage of the onward march of COVID-19 across the globe, but it should ignite a more structured examination of the issue.  We may point out here that countries which have Christianity as an official religion belong to either High or Upper-Middle Income group. The shares of countries in these two income groups among all countries with Christianity as declared religion are respectively 41.4% and 50.3% respectively. So, there is confounding effect between these two factors, namely income status and religious status. It is neither attempted nor possible to disentangle the impact of these two factors on intensity of COVID-19 spread in different countries10, 11.

    Table 8 here

    Note: Capitalist Communism is taken as state religion for China and Vietnam as atheism(or rather no organized religion)  is declared as state policy.

    The table above clearly points out that high per capita income does not ensure lower risk for a citizen getting infected by COVID-19, even though the country has built the best possible health care infrastructure. One caveat is due here. It has been reported that incidence of COVID-19 among poor African Americans are much higher as compared to US average. More data will be needed to address such intra-country issues like incidence of COVID-19 by race, gender and income group.

    Concluding Observations:

    Governments across the world have reacted to the COVID-19 pandemic in a way that reminds me of what Bertrand Russel famously said-   “Collective fear stimulates herd instinct, and tends to produce ferocity toward those who are not regarded as members of the herd”12.  Only one solution – that is Lockdown and Social Distancing – has been offered by our medical experts and their political bosses without any effort to calibrate its implementation with due regard to social differentiation in terms of prosperity, access to habitable shelter, presence of co-morbidities.  A government which in normal times cannot organize delivery of adequate nutrition to millions of children is taking upon itself to feed hundreds of thousands of migrant wage laborer because they were not allowed to return to their home villages. The irony of such policies is that while migrants would have financed their own journey if they could proceed to their home before imposition of Lockdown, now they will have to be provided with shelter and food at government’s cost.

    This essay has been written to highlight the fact that COVID-19 does not affect all countries and even all social groups within a country equally. Of late, politicians across democracies are taking help of Data Science to understand voter’s behavior   – who is more likely to vote in their favors and who are on fence etc.  The electoral strategy is based on such data analysis. But we are yet to see any country that has used Data Science to calibrate its response to COVID-19. For example, in India there are many large industries which are in a relatively segregated place. Most of its workers are residents in the campus. Irrespective of the goods produced there, it is madness to impose complete Lockdown in such places. Many University campuses are also far away from large habitations. It should be possible to work out modalities of functioning of such campuses with appropriate precautionary measures.  These are only few examples.

    References

    1. https://www.worldometers.info/coronavirus/coronavirus-age-sex-demographics/
    2.  https://www.bbc.com/news/health-51674743.
    3. https://economictimes.indiatimes.com/industry/healthcare/biotech/healthcare/india-did-have-an-innate-natural-shield-against-coronavirus-after-all/articleshow/74453719.cms?from=mdr
    4. https://in.news.yahoo.com/sunlight-heat-above-35-degrees-043448286.html
    5. https://nationalpost.com/news/why-the-covid-19-death-rate-varies-dramatically-from-country-to-country.
    6.   The state of the antivaccine movement in the United States: A focused examination of nonmedical exemptions in states and countries:  by  

    Jacqueline K. Olive, Peter J. Hotez, Ashish Damania, Melissa S. Nolan : https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002578

    7. https://www.vox.com/2019/6/19/18681930/religion-vaccine-refusal

    8. https://worldpopulationreview.com/

    9. https://en.wikipedia.org/wiki/Culture  

       10 https://catholicethics.com/forum/dealing-with-the-coronavirus/ 

    11. https://www.buzzfeednews.com/article/peteraldhous/global-survey-vaccine-safety-measles-outbreaks

    12.http://readingrussell.blogspot.com/2008/04/unpopular-essays-chapter-7-part-3.html

    For all tables see the file from the Google Drive: follow the link below

    https://drive.google.com/open?id=15oP7L_k6PAJhecpjMYUSfdzyK3ylSIqXEO1b9xsd7sA

  • Poor as a Commodity

    This is a blog that I wrote on 21st April 2010 for my earlier site . I am tempted to reproduce it without any revision today in the wake of Prof. Abhijit Banerjee getting his Nobel for his work on poor of the world. Although his work is extremely valuable and revolutionary from methodological point, I am still skeptical about the obsession of social scientists and politicians with poverty , particularly absolute poverty.

    Counting tigers and poor have become a national pastime of India’s leisure class. While the population of tigers we want to protect, we would like to number of poor to decline to zero.  We are failing in both, some would say miserably.

     The practice of counting number of poor in a country goes back to the second half of nineteenth century when Charles Booth carried out a remarkable survey of living conditions in London. Booth wanted to contest the results of an 1885 report that claimed that 25% of Londoners were living in abject poverty.  Booth and his team visited every street of London and estimated that the incidence of poverty at 31% initially and then at 35%.  In the first decade of 21st century and after 62 years of independence we can not claim to be in a better position.

    The reason for obsessive preoccupation with a precise headcount of poor on the part politicians and economists is not difficult to understand. The Indian government has a huge budget for a variety of poverty alleviation programs. Every state vies for a share of the cake and it depends on the number of poor. There is a turf war between the Ministry of Rural Development (MORD) and the Planning Commission with regard to this counting tussle. A footnote in the Expert Committee Report of the MORD is quite candid about it. It says-

    Which Ministry in GOI has the best control over the district collectors, CEO Zilla Parishads and Panchyats? The obvious answer is the Ministry of Rural Development (MoRD). , because it transfers huge funds to DRDAs and to panchayats, runs NREGA, BRGF and TSC, and ever since their creation panchayats have always regarded MoRD as their mentor.  Hence MoRD is the only Ministry in GOI that can make the field officials and the panchayats take its guidelines seriously. Therefore the task of overseeing preparation of the new BPL lists has been rightly given to the MoRD

    Another very interesting thing that this report brings into focus the practice of fixing number of BPL (below poverty line) families to the limit fixed by the planning commission estimated poverty ratio. Thus BPL certificate becomes a badge of honor like a caste certificate. Only difference is that BPL certificate can become a tradable commodity. In fact Mr. P. Sainath, a member of the expert group has put it succinctly

    • In many regions like the KBK, with millions extremely poor, you will find that most of the BPL cards in a village are with the local moneylender. The poor owe him money and he takes their cards as collateral. You can find one man with 400 cards.

    He also notes that

    Dharavi , the biggest slum in all the world  and with a population of over a million ended up home to just 141 BPL cards. If that’s all the poor there are in that slum, then India is poverty-free.

    The expert group estimates the number of poor in India as close to 50% as compared to 28.3%.  With this order of variation coming from two arms of the same government, what sanctity is there in these numbers?

    Apart from the exegesis of official experts, we have a whole industry of Poverty Research mostly funded by multilateral agencies and grant giving foundations. The route to stardom is well laid out – from JNU / Delhi school to Cambridge on both side of Atlantics or some other ivy league schools and then to the portal of the World bank / UN organizations. India which is estimated to be home of the largest number of poor in the world has also produced the maximum number of researchers on poverty.

    And the debate on what is the best way, statistically speaking, to estimate incidence of poverty some times assumes surrealistic proportion.  One just has to recount how, long back, two highly qualified statisticians and professors engaged themselves in a fierce debate about how to take into account inter-person variation in calories intakes and consequently how to correctly measure the incidence of poverty using a minimum level of calorie intake recommended by nutritionists.

    What is the real purpose of the debate? The real motive is political – which set of policy measures is good for poverty reduction. So if your prior belief is that economic reform is bad for the country then get a suitable measure of poverty index to demonstrate that poverty has increased in the post reform period. If one’s prior belief is opposite then get hold of another measure. It is said in statistics that if you beat some data sufficiently you can always reject a null hypothesis.

    I can not better the opening sentences of Charles Elliott’ book Patterns of Poverty in the Third World in this regard-

    The basic configuration of world poverty is well known. Although the detailed statistics are unreliable, the services of a statistician are not required to establish that the majority of mankind is ill-fed, ill-housed, under-educated, and prey to preventable disease.

    Do we really need to count the number of poor so accurately as if it is gravitational constant on which depends the trajectory of a missile?  Poverty is ugly and de-humanizing. It is ugly more in a relative sense than in an absolute sense. A poor is not treated as a full citizen in any country- developed, under-developed, capitalist or socialist. The greatest suffering a poor has when she is made to feel as a lesser human being, a person deserving only piety from others. The tears of universal humiliation are much more real and enduring than the tears of hunger. It does not matter whether she is a singleton or numerous.

  • Adequacy of Reserve and Economic Capital Framework for RBI

    How much forex reserve should RBI have? How much capital should RBI have?  One simple answer to both these questions is- “it depends’.  The obvious follow-up question is – it depends on what?  And there is the rub.  Is it given for a central bank to “die, to sleep – to sleep, perchance to dream” of a tranquil crisis free state of economy when reserves are a luxury, a framework for economic capital for all contingent situations can be worked out. Politicians always seek simple solutions to complex problems. In today’s world, most of the national economies are highly interconnected and are subject to “butterfly effect”. When flap of wing of a butterfly in Mexico engenders a hurricane in China, we call it a “butterfly effect”. The mathematical discipline, called Chaos Theory that deals with such complex interconnected non-linear systems, is based on the assumption that such systems are inherently unpredictable.   There is thus neither any theoretical nor any empirical basis to expect that a central bank like RBI can  predict with a certain measure of uncertainty the capital required to tide over any severe shock in next one or two year.

    It is even debatable whether the concept of economic capital is applicable to a central bank. The economic capital of a firm is the amount of capital that would be required by the firm to remain solvent. The capital adequacy norm for a bank is a regulatory requirement towards that effect. The central banks, however, are not banks in ordinary sense. Although a central bank does function like a bank for government and banks, it is also an integral part of sovereign so far as it has unlimited power to issue risk free liabilities in its own currency. This prerogative of a central bank enables it to become the lender of last resort. Since, theoretically, a central bank can work with even negative capital, it is difficult to work out a threshold level of minimum capital that a central bank would require to remain solvent. Some recent evidences prove this point.

    In January 2015, the Swiss National Bank abandoned its pegged currency regime and allowed Swiss franc to float. Resulting appreciation in EUR/CHF rate led to a massive loss in SNB’s foreign currency portfolio. The bank’s estimated loss of CHF41 billion in the following 3 months period till March 2015 came to be about 6.5% of Swiss GDP.

    Another example of a technically insolvent central bank is the Czech National Bank (CNB).  CNB was operating, at the end of 2007, with an accumulated loss of CZK200 billion, which formed 57% of the central bank currency in circulation and 6.7% of the country’s nominal GDP. The bank’s own negative capital stood at CZK 176 billion.

    The following graph shows even for emerging countries, some central banks continued to function even after registering negative capital for extended periods.

    Even the Federal Reserve of USA registered a steep dip in its capital-to asset ratio – 0.77% at the end of 2013 from 3.54% at the end of 2006, the year preceding the onset of global financial crisis. It is nobody’s argument that the capital requirement of Fed can be a benchmark for any other central bank, as US dollar is the primary reserve currency of the world. However, the fact remains that even for Fed, resolution of a crisis is much more important than maintaining any debatable target capital adequacy ratio of a central bank.

    Since the main component of RBI’s capital is its reserve, search for an optimal capital adequacy ratio for RBI would boil down to a search for adequacy of its reserve. To a large extent the asset counterpart of RBI’s reserve (on the liability side) is its Foreign Exchange Reserve. In my earlier blog post I have provided the relevant numbers for RBI (here) . In this post I want to dwell on the IMF framework for assessment of FOREX reserve of a central bank.

    While building the framework, IMF’s main emphasis has been on the “key distinguishing characteristic of reserves- their availability and liquidity for potential balance of payment needs” (emphasis original). The global financial crisis has woken up all central banks, including those of advanced countries, to the critical role that availability of reserve plays in maintaining financial stability of a country. The IMF study has noted that most emerging market countries have “ accumulated more reserves in recent years than suggested by standard rules of thumb, with the median coverage ratio among EMs being around six months of imports, 200 percent of short-term debt, and 30 percent of broad money in 2009”. Analyzing the costs and benefits of reserves under macro-economic scenarios, IMF has worked out a new metric to assess adequacy of reserve. The metric for emerging market economies comprises four components- export income, broad money, short-term debt and other liabilities.  Computed reserve adequacy, based on this metric, for selected countries including India shows that India is not an outlier in terms of forex reserve it is currently holding.

    Finally, we hope that search for an optimal capital adequacy framework for a RBI would not turn out to be an exercise in futility. Let it not be : tale / Told by an idiot, full of sound and fury, /Signifying nothing.

    Table: Actual Forex Reserve maintained as percentage of required           

    Year RUSSIA BRAZIL INDIA INDONESIA KOREA CHINA
    2010 179% 129% 175% 94% 118% 197%
    2011 174% 156% 159% 144% 117% 175%
    2012 163% 159% 143% 90% 112% 160%
    2013 151% 159% 144% 123% 114% 155%
    2014 225% 155% 151% 126% 118% 137%
    2015 264% 192% 156% 122% 124% 120%
    2016 248% 165% 155% 128% 121% 106%
    2017 265% 162% 159% 128% 106% 97%

    Source:            http://www.imf.org/external/datamapper/ARA/index.html

    Table: Balance Sheet of Federal Reserve of USA

    Source: Carpenter, Seth et. Al; The Federal Bank’s Balance Sheet and Earnings: A Primer and Projections, International Journal of Central Banking March 2015

    IMF:  Assessing Reserve Adequacy February 2011

  • Trillion Dollar Economy – no magic required

    Reaching $ 5 trillion GDP benchmark is being projected as a landmark milestone for the Indian economy by many in the Government. The latest estimate puts the size of Indian economy, measured as GDP at current market prices, at $2.4 trillion. Does reaching $5 trillion mark reflect a significant achievement or is it really an implicit admission of incipient sluggishness in growth of Indian economy? Let the data speak.
    Indian economy registered an average annual growth of 12.8% in GDP (at current market prices) during 17 years – from 2000-01 to 2016-17. During the same period, only in 2 years, the growth rate fell below 8%, the minimum being 7.6%. The 25 percentile growth rate was above two digits at 10.4% and the median rate was 13%.
    Given this nominal growth scenario of recent past, dollar value 5 trillion appears to be too modest a goal to be set by the current government. Table 1 gives the projected value of Indian economy till 2035 under various growth rate scenarios. Even if Indian economy grows at the lowest rate achieved during last 17 years, the size of the economy would reach at least 4 trillion US dollar by 2025. If rupee depreciates in mean time the growth in dollar terms would be lower. At 70 rupees per dollar, the size would become only 3.9 trillion dollar by the end of 2025.
    A nominal yearly growth rate of 7.6 percent would imply, given 4 % target growth rate notified by the government of India (GOI), a real growth rate of only 3.6 percent. A 10.4 % growth rate would thus imply real growth rate of only 6.4%. Thus if projections of $5 trillion is in nominal terms, then no big achievement is being claimed.
    Suppose, all the projections are being made under the assumption of constant prices of 2016-17, then the target average growth for next eight years should be 9%. India has achieved a double digit real growth rate in the last 66 years only once. Even in the last 25 years India clocked a real GDP growth rate greater than 8% only 6 times. So the probability of clocking a real growth rate of more than 8% is as low as 25%. Achieving 9% uniform real growth rate till 2025 with stable rupee-dollar rate might be a chimera. If rupee depreciates to 70 rupees by 2025, we would need an average year over year real growth rate of 11%. It could be a dream worth pursuing but there is no evidence in terms of accelerated investment or growth in productivity that could make the dream a reality.
    In summary, reaching 5 trillion USD by 2025 in nominal terms is no big deal – a lower than achievement would be considered a highly disappointing performance. Achieving the same target in real terms could be an enormous challenge- heralding a real structural break in the Indian economy with productivity led growth and not merely by adding more capital and labour.

    Table 1: Projected USD Size of Indian Economy under various growth rate scenarios and with constant exchange rate of 63.5                      ($Trillion)

     Distribution Measures based on data from 2000-01 Compound Growth Rate of GDP at current market prices 2025 2030 2035
    Minimum 7.6 4.2 6.1 8.9
    1st quartile 10.4 5.2 8.6 14.1
    Average 12.8 6.2 11.4 20.9
    Median 13 6.3 11.7 21.5
    Note: Only first decimal value without rounding up has been reported. Projections are based on CSO’s preliminary estimate of GDP at current market prices for year 2016-17.

    Note: Only first decimal value without rounding up has been reported. Projections are based on CSO’s preliminary estimate of GDP at current market prices for year 2016-17.

  • Corporatization of Nations

    Reliance Jio Infocomm Ltd, the telecom arm of India’s largest company by market cap (NSE:RELIANCE), plans to create its own cryptocurrency called JioCoin. Supply chain management logistics and loyalty payment with JioCoin are amongst the envisaged uses of JioCoin. Worldwide, many large corporates have already started launching their own private cryptocurrency.  KFC, Burger King and Kodak are the few well-known names that have hitched onto the bandwagon of this currency of the Internet.

    Fast-food chain KFC has announced that it will accept  virtual currency for paying bills in its outlets in Canada with the launch of Bitcoin Bucket. A customer can buy this bucket with 0.0011564 BTC, equivalent of CAD $20, according to a company statement. Eastman Kodak has announced last week that it is going to launch its own cryptocurrency KodakCoin in partnership with WENN Digital. Burger King has launched its own cryptocurrency in Russia called ‘WhopperCoin. IBM recently partnered with Stellar and klickex to develop a blockchain-based cross-border payments solution. Stellar is a distributed hybrid Blockchain that facilitates cross-asset transfer of value including payments. Similar to Bitcoin, Lumen is the asset of value issued by Stellar.

    This rush by multinational companies to get on board of the cryptocurrency mania camouflages a much larger issue and a potential threat to the current international political order. This threat can be analyzed from various perspectives including political, economic and technological.

    Glenda Sluga, a Professor of International History, has written about  the possible unraveling of the current international order from a historical and political perspective: These days, the pulse of the world’s political health is running fast. The general prognosis is terminal, the end of the international world order, as we know it.(here)  Political headwinds which led to such prognosis are easily discernible- rise of “radical nationalism” in USA, “long the axis of modern international society” and, rise of “heteropolarity” in the international power structure.

    Beyond this haze of political chaos, a much bigger threat to the existing international world order lies in emergence of private cryptocurrency and its adoption by multinationals. There is no gainsaying the fact the comity of nations defines the current world order. A nation state without its own currency is like the staging of Hamlet without the prince of Denmark. The power of a nation state to tax its citizens would stand highly diminished if large corporates can issue their own currency. Let us see how it would play out in reality.

    Alice buys 1000 JioCoins (JC) by paying, say, 20000 Indian rupees. Alice pays 60 JC to Bob for as rent for the apartment she has leased from Bob. Bob buys monthly grocery from the supermarket run by Reliance. Bob uses 250 JC for this purpose.  Bob tops up his Jio mobile with 50 JC. Suppose, Bob works in Reliance Industries and receives 3000 JC every month. Bob pays 750 JC to Reliance Petroleum for purchase of gas for his car. He has purchased his car by taking loan from HSBC by paying EMI of 750 JC every month. This EMI payment is routed through a cryptocurrency exchange run by a Russian bank.  RIL pays IBM India monthly 100 million JC for maintaining its IT infrastructure. IBM may pay RIL is own cryptocurrency for using Jio mobile services in India. Gradually, a complete ecosystem of economic agents can emerge, who will use JC as their preferred currency for all their payment requirements.  It may be seen that the JC to Rupee exchange takes place only when Alice purchased JC. At a certain stage of development JC will acquire its own life, cutting its umbilical record with the fiat currency.

    The above description of evolution of JC to encompass a significant slice of economic transactions in its country of incorporation, i.e. India, does not necessarily imply that JC would pose a threat to the  existence, or at least severely restrict usefulness,  of the sovereign currency INR as a fiat money. Initially, INR can continue to be the unit of account within the boundary of India. But if JC emerges as the people’s preferred medium of transactions and store of value, only raw state power can prevent rupee’s passage to oblivion. Be that as it may, the moot question is whether JC would severely dent the Indian state’s capability to tax the economic activities mediated through JC. Given the ability of a cryptocurrency to mask the identity of transactors, imposition of indirect taxes, like goods and service tax, might be a serious challenge for tax administration. If an Indian resident tax payer earns and spends only in JC, fixation of its tax liability would not be an easy task.

    If all multinationals including RIL, IBM and others can agree on an exchange platform for conversion of their currencies then the nations of the world would find themselves divested of their defining power to tax and earn seigniorage.  The depth and reach of the large multinationals can be gauged from the fact that in 2016 the Fortune 500 companies had revenue of 27.7 trillion USD while the combined GDP of 198 countries was around 76 trillion USD. Using Output to GDP ratio for US economy, the share of Fortune 500 companies in the worlds’ GDP would work to around 21 percent.   So if these large corporates were to sign off from the current international order with their own currencies, their total GDP would be the second highest, next to USA only. They can usher into a new Bretton Wood regime for their private currencies and significantly reduce the cost of managing exchange rate risk.

    Technologically, these large corporates could not but continue to be part of one country or other, at least formally, the emergence of cryptocurrency can unshackle them from this tether of fiat currency and its in-built inflationary bias. If the world economic order get re- arranged on this line, what would happen to the multitude of people who would continue to remain outside the charmed circle of digital economy, can only be a matter of speculation and not an informed guess.