Thursday, July 19, 2018

Technologies and their diffusion intensity

Marginal Revolution points to the work of Diego Comin and Marti Mestieri, who document the trends associated with the diffusion of 25 technologies in 139 countries over the past two centuries, and posit an explanation for cross-country differences in income growth over the long-term. They focus on two distinct margins of adoption that are specific each technology and country, the adoption lag and the intensity of use.

They simulate a model to study the effect of technology diffusion process on the productivity growth,
Adoption lags have converged across countries, while the intensity of use has diverged... Our simulations have shown that differences in technology diffusion patterns account for a major part of the evolution of the world income distribution over the last two centuries. In particular, differences in the evolution of adoption margins in Western and non-Western countries account for around 75% of the income per capita divergence observed between 1820 and 2000... First, our findings show that the majority of the divergence in productivity can be accounted for by technology diffusion. Second, the critical dimension of technology diffusion to understand the divergence in productivity is the intensity of use of technology. Third, economy-wide factors such as exogenous TFP not only played a minor role in explaining cross-country productivity dynamics. They also played a minor role in explaining differences in the evolution of technology diffusion across countries...
The average estimated adoption lag is 42 years. The average intensity of adoption in Non-Western countries is half (47%) of the level of Western countries. We document significant dispersion on both margins of adoption across countries and technologies. For example, comparing the 90th to the 10th percentiles of our estimates, we find 10-fold differences in adoption lags and 8-fold differences in the intensity of adoption.
Nice summary from Tyler
The mean adoption lag for spindles, classified as a 1779 technology, was 130 years, or in other words that is how long it took for the technology to move to poorer countries. For ships, listed as a 1788 technology, the mean lag is 110 years. Synthetic fiber is a 1931 technology, with a mean adoption lag of 29 years. For the internet, a 1983 technology (is that right?), the mean adoption lag is only 6 years. But the overall story is not so simple. The more advanced countries use more of these technologies, and use them more effectively (“intensity”), and that gap has been growing over time. Yes, Ghana has the internet, but it is Silicon Valley that is working wonders with it. Some technology use begs more technology use.

Tuesday, July 10, 2018

The challenges with Telangana's farm income transfer experiment

The Telangana state government's decision to implement direct income transfer to all its farmers is surely a landmark in India's agriculture policy space. Its outcome will be very closely scrutinised over the coming years. 

In brief, the State government have decided to transfer Rs 4000 per acre per season for the Rabi and Kharif crop seasons to all the 5.83 millions farmers as part of the Farmers Investment Support Scheme (FISS) or Rythu Bandhu Scheme. The transfers are to all agricultural land owners, irrespective of whether the land is brought under cultivation. This amounts to an annual subsidy outflow of Rs 12000 Cr or 7% of the total government expenditure, and would cover from 10-30% of the cost of cultivation depending on the type of crop. Two good assessments here and here.

Arguably the biggest challenge in achieving the scheme's objective of reaching small and marginal farmers arises from its not covering tenant farmers, a category not legally recognised in the State. Such farmers may cover atleast a third of all farmers.

So we have a pioneering agriculture policy reform being unveiled, perhaps the single largest direct income transfer program to farmers anywhere in the world. As Neelkanth Mishra has very nicely argued, it is almost impossible to make any reliable assessment of the program. And evaluations commissioned by the state government will take years to provide any actionable insight, if at all, whereupon the die would have been cast, either in terms of success or failure of the reform. Other states too would have jumped the bandwagon and emulated Telangana, inclusive of all the program's failings. So what is the best that can be done to ensure that the reform is effectively implemented?

At the very outset, we need to acknowledge that one could not have done an RCT to have evaluated the program before its implementation. Foremost, we do not have the luxury of time and KCR (the Chief Minister of the State) would surely not have had the patience. Public policy reforms rarely ever, if at all, happen in a calculated manner affording the luxury of detailed planning. They invariably happen as mutations. In any case, a small pilot evaluation would not have been able to reveal any of the several general equilibrium effects possible - how much of the money used for consumption, how much for investment, tenant-landowner dynamics and the income sharing, impact on land values, incentive distortion and leaving land fallow, impact on food prices etc. In the circumstances, the best effort would have been a rigorous qualitative assessment. 

Once the policy option is exercised, then the challenge is to ensure its high fidelity execution. This would mean ensuring land ownership details are accurately captured (can remote sensing data and GIS mapping, coupled with a field-survey, help with a one-time clean-up?), payments processed and delivered to the farmers in the most cost-effective and most accessible manner (can technology solutions and digital money help?), some way (short of a regulation or rule) in which tenants can negotiate with landowners to get a share of this money (can nudges help?), the money is withdrawn and utilised in the most productive manner (again nudges, say, to purchase farm inputs?), the float in the distribution channel by way of locked up money due to deaths etc be minimised (can technology help?), discourage farmers who could leave land fallow and just collect the transfers (some information disclosures and structuring of the payments be of use?) etc. 

As can be seen, each of these problems can have unique ways to address them. The government would need to innovate improvise continuously. 

Addressing these execution challenges and ensuring that the reform realises its full value would require action at three levels.

The first would be purely at the level of execution management. Can we have a monitoring system with tight feedback loops that inform decision-makers at District and State levels about bottle-necks, distortions and problems as the implementation proceeds (say, larger and absentee farm owners leaving land fallow to collect the transfers which is higher than the tenancy rent)? Can there be a back-up team which can respond to such emergent concerns and address them swiftly, both at the policy level as well as, more likely, at the level of field implementation? Can we have a strong analytics team that is able to rigorously analyse the data exhaust and offer actionable insights, which can perhaps help iterate and improve the policy over time?

The second would be at the level of policy elements. Can the State government emulate the Giveitup campaign associated with the LPG subsidy program of the Government of India and nudge the richest farmers to voluntarily abstain from taking the subsidy? What would be the most effective way to exercise such moral suasion? Given that 9% of farmers with more than 5 acres each own a third of the land and therefore would claim a third of the subsidy, can the government go one step further and cap the subsidy in an administratively simple manner? Going forward, as the farmer database and transfers distribution channel stabilises, can the government explore options of targeting farmers, crops, regions etc? 

The final level of engagement would have to be at the eco-system. Gradually, after a year or so of the implementation, can the database and monitoring system be used to deliver other types of services? How does this work-flow integrate to the fertiliser subsidy transfer system? Can the foodgrain procurement process be linked up with this database? Can this be linked to the agriculture e-market place, eNAM? Can we use this digital spine to deliver direct cash transfer in return for erecting meters on agriculture power connections? Can we gradually build a robust agriculture information management system and a platform to deliver various kinds of farm services?

It is all too easy for me to write these down as a sort of pre-mortem. In fact, I could dig deeper and get more granular at each level. It is an altogether different task for the State government to just keep its eye on all three levels always, much less translate them into action. The best that can be expected is for the State government to perform reasonably well the limited task of high fidelity execution. That is a two-year agenda.

For now, despite all its flaws, the state government should be applauded for the leap of faith, as is the case with any such reform.

It does not need any great foresight to assess how the program will get implemented, if it is done business as usual by the State government. It is almost unrealistic to expect a state government, even a very high capacity one at that, to execute at all three levels. Even high fidelity execution will be a great achievement. The ebbs and flows of political cycles alone are enough to disrupt any neatly laid down plans at policy and eco-system levels. No point in criticising State government for such failings. We only need to be surprised if that does not happen. 

None of this would prevent opinion makers and academic researchers from sitting judgement five years hence, and with the benefit of hindsight smugly castigating the government for all the distortions and failings (some which cannot even be anticipated now) that would have inevitably crept into the implementation - it was not evidence-based policy making, there was corruption, there was no political commitment, the tenants and therefore the poorest farmers did not benefit, and so on. We told you so! 

Instead, the challenge is to engage in real time. Can evidence-based policy making ideologues offer the State government something tangible in terms of the aforementioned engagement elements that increases success likelihood as it embarks on this challenging reform path? Anyone up for that challenge?

Sunday, July 8, 2018

The competitive race to offer investment subsidies

Governments, across different levels, compete to attract investments, domestic and foreign, that they believe will create jobs for the locals and boost the local economy. In recent times, as the famous example of US cities competing to attract Amazon's second headquarters show, this competition has escalated into a debilitating arms race to offer the largest amount of subsidies with deeply questionable benefits in return.

Now thanks to watchdog group Good Jobs First, it has now become possible to track the business investment subsidies offered by governments to various corporates in the US. It shows that over the past five years, state and local governments, which are facing an acute fiscal crunch to deliver even basic services, have pledged the US technology giants  at least $9.3 bn in subsidies. Apart from the Amazon second headquarters, the largest recent handout was the $4.8 bn promised to Foxconn for its new plant in Wisconsin.

Sample this,
In the last tax year local governments in Nevada lost more than $105m as a result of state abatement programs. Nevada is home to Tesla’s “Gigafactory” - which received $1.3bn in tax benefits, the largest such subsidy the state has ever awarded... Tesla accounted for $68.7m of last year’s loss. Good Jobs First calculates that Tesla’s tax breaks resulted in one school district, Storey County Schools near Reno, losing $36.7m of revenue.
Local governments frittering away scarce resources on subsidies with questionable benefits on large companies is far from the only issue. Most of these subsidies would involve intense lobbying by businesses and their bespoke nature for each company mean significant exercise of discretion by the political representatives and officials concerned. The attendant opportunities for cronyism and corruption are significant. The several exposes in recent times of local government corruption among state and city level leaders in the US is a manifestation. 

At a conceptual level, this cannot but not be regarded a market failure. Cities and states competing in an open market to attract businesses have to be regarded as a monopsony situation. All the more so since, even in a large country like the US, there are only a handful of the big companies which are likely to consider investment decisions at any point in time. The carefully cultivated hype around such investments, despite all the evidence pointing not only to job creation coming mainly from smaller and younger enterprises and larger ones being net job destroyers, has not shaken the faith in large companies.

This trend is now common across the world. In India, industrial policy is dressed up as fiscal concessions and input subsidies to attract large firms. States compete with each other in offering the most attractive package. In fact, some have even started to offer a share of the salary of the first few employees to lure investments. However, like in the US, there is little to suggest that business investment decisions themselves are influenced by such fiscal offers, and at best, this competitive race among States may marginally influence investment location decisions. 

It is difficult to regulate such decisions. After all sovereign governments are fully empowered to offer such subsidies. A more meaningful attempt to reverse the trend may be to force governments to publicise such information at a very granular level (like the recent US Governmental Accounting Standards Board Statement 77) and also develop a mechanism to hold corporations accountable for the promises made in return for the subsidies. Perhaps a nationally organised attempt to quantify and publicise the social balance sheet of these companies would be useful. In any case, information and civil society action, especially at the local government and provincial levels, may be a more effective response to such policies.

Friday, July 6, 2018

Stabilising agriculture markets

Couple of interesting articles covering agriculture over the past weeks. 

One by Harish Damodaran draws attention to the recent spurt in agricultural production, something he has described as an "age of surplus". Consider this,
In 2010-11, pulses production, for the first time, crossed not 15 mt, but 18 mt. Even in 2014-15 and 2015-16, both drought years, it stayed within 16-17 mt. And as farmers ramped up plantings in response to the high prices of 2015 and 2016, output soared to 23.13 mt in 2016-17 and 24.51 mt in 2017-18... In the past, sugar production typically took two years to recover from a drought. But 2017-18 will see output rebound to a record 32 mt-plus, from a seven-year-low of 20.26 mt last season. Thus, the old “sugar cycle”, where three bumper years were followed by two lows, is dead. Now, we have only one-in-five bad years. The same goes for vegetables... We have, indeed, entered a regime of “permanent surpluses” in most crops... There is practically no agri-commodity today that isn’t a victim of “permanent surpluses”. 
Another by Ashok Gulati points to the same story in dairying,
The increase in milk production since 2014-2015 has been unprecedented (6.3 per cent per annum between fiscal year FY 2015 and FY 2017; FY 2018 figures are not yet finalised), compared to about 4.2 per cent in the three years preceding that (see graph-1). Moreover, the milk output, instead of falling during the lean (summer) season, registered high growth in 2017-18 vis-à-vis 2016-17... (but) milk prices have fallen by 20 per cent to 30 per cent (by Rs 5 to10 per litre for cow milk) in several milk-surplus states in western and northern India, including Maharashtra, Gujarat, Rajasthan Punjab, Haryana and UP.
What has contributed to this? Harish has this answer,
Better seeds and faster diffusion of technology have made a difference. HD-2967, a blockbuster wheat variety released in 2011, could cover 10 million hectares area in a single season within five years. Along with HD-3086, a newer variety more resistant to yellow rust fungus, it has ensured that the Green Revolution’s yield gains haven’t plateaued yet: The average Punjab wheat farmer harvested 5.12 tonnes per hectare in 2017-18, as against 3.73 tonnes in 1990-91 and 2.24 tonnes in 1970-71. No less impactful has been Co-0238, a cane variety that not only yields more crop per hectare, but also more sugar from every tonne crushed. First planted in 2013-14, it now accounts for well over half of the cane area in North India, while singularly responsible for UP’s sugar output spiralling from 7.5 mt in 2012-13 to 12 mt this season. But the story of yield increases isn’t limited to publicly-bred open-pollinated varieties (OPV). The 50 quintals/acre yields that farmers in Bihar’s Kosi-Seemanchal belt today realise from rabi corn is comparable to Midwest US levels. With planting of hybrids, as opposed to OPVs, paddy yields have gone up from 15 quintals to 25 quintals per acre even in the Adivasi areas of Jharkhand, Chhattisgarh and Odisha. Kolar farmers, likewise, grow three crops of tomato annually, while Maharashtra’s Jalgaon district would be the world’s seventh largest banana producer, were it a country. The technologies in all these — be it hybrid seeds, high-density cultivation using tissue-cultured plants, or drip irrigation — have been supplied by the likes of DuPont, Monsanto, Bayer, Syngenta and Jain Irrigation.
Note that both public policies and markets have played a role in this. The biggest disappointment has been in the weak government investments in irrigation, especially minor irrigation (the field channels that delivery water to the farmers), and on market's tepid investments in linkages like cold storages. While the failings on irrigation can be attributed to state capacity weaknesses, the market failure in responding with investments in the likes of cold storage, private extension services etc is a matter for reflection. After all vegetable and fruit retailing by retail chains is growing and has enormous potential, and even a small proportion of the market is big. 

Harish's article also has more on the vagaries of price fluctuations, maybe the central social problem with agricultural markets,
Last year, after drought in Karnataka drove up onion prices from July — they went past Rs 30 per kg in Maharashtra’s Lasalgaon market by October — farmers sowed aggressively during the rabi winter season. The result: Average rates crashed to Rs 6-7 this April-May. Farmers did something similar when tomatoes scaled Rs 60-80/kg levels in Kolar (Karnataka) and Madanapalle (Andhra Pradesh) last July. Prices again plunged, to Rs 3-5/kg towards February, and haven’t really looked up even in peak summer this time... Two years ago, garlic fetched an average Rs 60 per kg rate in Rajasthan’s Kota mandi. Enthused by it, farmers in the Hadoti region planted more area, only to see prices halve last May, thanks to demonetisation. This May, rates at Kota further halved to Rs 14/kg. 
Agriculture is more complex than other markets in that we have two directly conflicting dynamics at play - higher prices for farmers and lower prices for consumers. And farm produce being an essential commodity for everyone and farmers being producers themselves exacerbates the challenge. Therefore, public policy and markets have two roles - enhance productivity (and thereby production) and stabilise markets (and thereby increase farm incomes and de-risk agriculture).

It is the latter that is an interesting area since the policies that have been found to be relatively better (albeit with distortions) in realising this objective are not the ones that economists would advocate - public procurements, minimum support prices, direct income transfers, fertiliser and farm power subsidies, and perhaps even loan waivers. Indeed Ashok Gulati proposes public procurement and development of a buffer stock of Skimmed Milk Power (SMP) by the National Dairy Development Board (NDDB) to stabilise price fluctuations in milk. He also makes several other practical suggestions. 

One possible approach to address the price stabilisation problem would be to undertake high intensity public awareness campaigns before each harvest. The campaign should be informed by the best possible assessment of market trends and offer guidance to farmers on crop choices. Remote sensing data and market information (futures, global trade trends etc) can help make good choices. Instead of top-down directions that restrict government's agricultural programs to those not complying (which are unlikely to be actionable given the political realities ex-post), it may be more effective to articulate these concerns (and even threats) in the discussions with farmers groups and other important collective stakeholders at local levels. The success of Andhra Pradesh government with dissuading farmers from planting cotton this year in anticipation of glut and lower prices is an example. The problem though is with carrying out a campaign with high fidelity, which demands both state capacity and high quality leadership (either at bureaucratic or political levels). 

Another area of work is to engage more intensely on refining the electronic market place for agriculture products, eNAM. As I blogged here, this may involve a mission-mode effort involving committed and stable leadership for a sustained period of time to iron out the several loopholes and deficiencies and establish eNAM as a credible and accessible trading platform.  

Yet another option is the choice between crop insurance and direct income transfers. But evidence from everywhere shows that even in the best case scenario, crop insurance is almost 80-90%, if not more, public subsidy. This makes direct income transfer more efficient (less transaction costs) than crop insurance. In fact, it may also be politically more salient (and therefore acceptable) to do direct income transfers. The recent Telangana experiment is a step in the right direction, though the risks of its poor implementation (and resultant disrepute to the approach) is very high.

Though such saliences has its costs (demands to increase transfers, for example), this would have to be traded off with the pain of validation and payouts (and attendant inordinate delays) that weak state capacity and greedy insurers would make inevitable with crop insurance schemes. It is for all these reasons that direct income transfers are the most common farm support mechanism across US and Europe. Crop insurance is therefore yet another example of evidence-free policy prescriptions that international development institutions advocate for developing countries.

It may perhaps be necessary to apply all the three ideas, alongside the buffer stock procurement, to have any significant impact on the market stabilisation challenge in agriculture. 

Monday, July 2, 2018

Stocks market facts of the day

The Economist points to the research of Hendrik Bessembinder who finds that most of the historic stock market gains in the US can be traced to a handful of stocks. He finds,
Of the nearly 26,000 common stocks that have appeared on Centre for Research in Security Prices (CRSP) monthly stock return database from 1926 to 2016, less than half generated a positive lifetime buy-and-hold return (inclusive of reinvested dividends) and only 42.6% have a lifetime buy-and-hold return greater than the one-month Treasury bill over the same time interval... When stated in terms of lifetime dollar wealth creation to shareholders in aggregate, approximately one-third of 1% of the firms that issued common stocks contained in the CRSP database account for half of the net stock market gains, and slightly more than 4% of the firms account for all of the net stock market gains. The other 96% of firms that issued stock collectively matched one-month Treasury bill returns over their lifetimes.
The graphic below shows the cumulative percentage of net US stock market wealth creation in the 1926-2016 period when the 25332 companies in the CRSP database are sorted from largest to smallest wealth creators.
The next graphic looks at the cumulative percentage wealth creation by the 1100 wealth creating companies (the remaining companies lose money).
This draws attention to the importance of portfolio diversification, and in particular of increasing the likelihood of being able to capture atleast some of the likely winners,
The results presented here reaffirm the importance of portfolio diversification, particularly for those investors who view performance in terms of the mean and variance of portfolio returns. In addition to the points made in a typical textbook analysis, the results here focus attention on the possibility that poorly diversified portfolios will underperform because they omit the relatively few stocks that generate large positive returns. Actively managed portfolios tend to be concentrated. For example, Kacperczyk, Sialm, and Zheng (2005) show that actively managed equity mutual funds hold a median of only 65 stocks. The results therefore help to explain why active portfolio strategies most often underperform benchmarks (such as the S&P 500 return) that are constructed as average returns across securities available for investment. Underperformance rates that exceed 50% are often attributed to transaction costs, fees, and/or behavioral biases that amount to a sort of negative skill. The results here show that underperformance can be anticipated more often than not for active managers with poorly diversified portfolios, even in the absence of costs, fees, or systematic behavioral biases.

Saturday, June 30, 2018

The off-balance sheet debt problem in the US

John Mauldin has a series of US debt crisis. The ticking bomb is the unfunded social security and health care unfunded liabilities, which sits atop the $21.2 trillion federal government debt (105% of GDP) and $ 3.1 trillion (15% of GDP) of state and local government debt. Consider this,
These estimates of when the trust funds run out depend on a slew of assumptions. To estimate revenue, they must know how many workers the US has, their wages, and at what rates those wages will be taxed. To estimate expenses, they mustknow how many retirees will be drawing benefits, the amount of those benefits, and how long the retirees will live to receive them. They also have to assume an inflation rate on which thecost-of-living adjustment is based. A small deviation in any of those can have huge long-term consequences. For what it’s worth, then, Social Security says it has a $13.2 trillion unfunded liability over the next 75 years. That’s the benefits they expect to pay minus the revenue they expect to receive. Medicare projections require even more assumptions: what kind of treatments the program will cover, how much treatment senior citizens will need, and what those treatments will cost. Allthese could vary wildly but the “official” assumptions put Medicare’s 75-year unfunded liability at $37 trillion. It could be vastly more or, if we all get healthier and healthcare costs drop, could be less... 
Larry Kotlikoff estimates the unfunded liabilities to be closer to $210 trillion. That’s a far cry from the $50 trillion official estimate. So, at a minimum, we can probably assume Social Security and Medicare are at least another $50 trillion in debt on top of the $21.2 trillion (and growing) on-budget federal debt. And then you come to the scary part. This doesn’t include civil service or military retirement obligations, or federal backing for some private pensions via the Pension Benefit Guaranty Corporation, or open-ended guarantees like FDIC, Fannie Mae, and on and on... CBO numbers show that by 2041, Social Security, health care, and interest expenditures will consume all federal tax revenue. All of it. Everything else the government does (including defense) will require going into more debt.
The article nicely lays down how these are most likely the best case scenario given the uncertainties associated with making such estimations as well as the headwinds that would have to be overcome.

Thursday, June 28, 2018

A few mid-week reading links

1. FT reports of the US decision to suspend Rwanda's access to a preferential trade agreement, African Growth and Opportunity Act (AGOA), in retaliation for that country's decision to restrict the import of used clothes from the US. As a matter of fact, Rwanda's policy on promoting domestic industry follows the much more mercantilist industrial policies adopted by all developed countries during their own growth phases. 

The article also points to the strongly patronising reaction in the UK to Rwanda's decision to promote its tourism potential,
There is a parallel in the harsh reaction Rwanda got when it announced last month it was spending £30m on sponsoring the shirts of Arsenal football club. The Daily Mail, a populist UK tabloid, blustered that what it called a Rwandan dictator was blowing the cash of his impoverished people on a vanity project. Never mind that the sponsorship deal was part of a joined-up strategy to turn Rwanda into a convention and tourism destination. Rwanda has gorillas, a game park with the big five animals, good air links and an impressive new convention centre in Kigali, the well-functioning capital. But, thundered the Mail, it got £62m in British aid and should not be spending its money this way. That message is essentially the same as Washington’s. If we give you any aid or encouragement, we expect to set your policies and your priorities. If you try to lift your country out of poverty, then we will cut you off.
This has resonance with the "evidence-based" belief in international development circles questioning the efficacy that investments in rural roads and rural electrification. 

2. We live in the age of superstar CEOs. Apart from the Wall Street titans, there are the founders of the various technology and other startups who have been endowed with extraordinary abilities and feted by the media and opinion makers. This is despite a very rich body of evidence that disputes this conventional wisdom. So, conditional on the basic entrepreneurial attributes (and smartness, intelligence et al), quite how much of the success of startup CEOs is plain good luck of being at the right place at the right time? I am inclined to think most of it!

FT has this to write about Elon Musk's latest series of outbursts,
The performance has stoked long-simmering questions about whether Tesla has adequate checks and balances to control a chief executive who thrives on shattering convention. One analyst who covers Tesla for a large bank says many observers believe Tesla lacks “grown ups” to rein in Mr Musk’s outbursts, particularly on Twitter, where he goads journalists and promises to “burn” speculators who short the company’s shares. “For a while it was endearing, but he [Mr Musk] has gone full Trump. The pressure, the need for attention — it’s weird, his mental state is deteriorating,” says the analyst, who asked to remain anonymous. An industry executive who knows Mr Musk adds: “If any other CEO on earth exhibited the behaviour he is doing they would be out in an instant.”
As the examples of Travis Kalanick and Mark Zuckerberg shows, much of these reputations vest on plain good fortune.

3. If we are talking of risk appetite and thinking super-big, SoftBank's Masayoshi Son, with his $100 bn Vision Fund, would beat the likes of Elon Musk hands down. Consider this,
SoftBank is shifting the relationship between the tech sector and capital markets. At a time when start-ups are minded to stay private for as long as possible, SoftBank allows its portfolio companies to pursue growth without worrying about burning cash. Some venture capitalists even quip that “SoftBank has replaced the IPO”. Stephen Schwarzman, the billionaire co-founder of private equity firm Blackstone, says Mr Son is redefining technology investing. “No one has ever done that before at this kind of scale,” he says. “It’s unprecedented but it’s meeting a market demand.”

At the least, Son has the $145 bn worth stake in Alibaba from a 2000 investment to show for. More than what can be said about many superstar VC managers from Silicon Valley. 

4. As LIC assumes a controlling stake in IDBI Bank, Bloomberg Quint raises concerns about what it means for LIC's shareholders. Consider this,
LIC currently holds 11 percent in IDBI Bank. Hypothetically, if it were to buy another 40 percent stake to get to 51 percent shareholding, it would cost the insurer Rs 9,600 crore at current market value... India Ratings estimates that IDBI Bank’s total stressed portfolio (including non-fund based faclities) is 35.9 percent of total loans... This means that... in 2018-19, IDBI Bank will need more than the Rs 10,000 crore that it received from the government last fiscal. Even if you take a conservative estimate of Rs 10,000 crore in capital needed, that takes LIC’s immediate capital commitment to IDBI Bank to over Rs 20,000 crore. Is that money well spent by LIC? It’s tough to argue in favor of that given that the bank has reported losses for six consecutive quarters now... Note that no private investor has shown an interest in IDBI Bank even though the government has been wanting to sell equity for over two years now.
And the systemic risk consequences posed by LIC's growing exposure to the banking sector,
As part of its investment activities, LIC has been an active investor in public sector banks. This was particularly true in 2015 and 2016, when LIC bought into preferential share issues of a number of government run banks to cover for the shortage of capital. As a result, LIC’s shareholding in these banks has risen. Shareholding data from stock exchanges shows that LIC holds more than 10 percent in at least six government banks. Apart from holding equity in banks, LIC invested in debt securities issued by banks, including additional tier-1 bonds. As such, its connectedness to the banking system is already significant.
5. Livemint has a two past series on traffic congestion in Indian cities that draws on anonymised Uber data from 2016. It shows that Indians have among the longest commute times and this has been worsening in recent years. As a measure of the congestion, commute times almost doubles during the peak times when compared to off-peak hours. 
6. Paul Krugman has this assessment of the consequences of a global trade war. He estimates tariffs to rise buy 32-60 percentage points (he approximates to 40 percentage points), a 70 per cent decline in global trade, and a permanent reduction in world GDP by 2-3 per cent. In simple terms, the world economy would be back to 1950s in terms of trade.

Don't know whether they have been factored into the studies mentioned by Krugman, there are two important collateral damages likely. Consumers in developed economies will be hurt by the imported inflation arising from higher tariffs. And exporters in developing countries would be hit by costlier imports of intermediate goods which would end up increasing the final prices of their finished products.

7. Businessline has a good article that puts India's low tax base in perspective. Contrary to conventional wisdom it does not find tax compliance to be a major problem. Sample this,
The latest Labour Bureau’s Annual Employment-Unemployment Survey in FY16 covered 1.5 lakh households. It found that over 87 per cent of the households earned less than ₹20,000 a month (₹2.4 lakh a year). This included full-time workers, part-time ones, casual workers, as well as the self-employed. This effectively means that only 13 per cent of the 25 crore Indian households (about 3.2 crore households), may be earning enough to pay income tax. If income tax collections are held back by low income levels, corporate tax collections in India seem to be afflicted by the poor scale and low profits reported by the vast majority of businesses. In India, business is dominated by the 6.3 crore unincorporated enterprises that are mostly run from home. Registered companies number just 17 lakh. Of the registered companies, only about 11 lakh are active and about 7 lakh companies filed their I-T returns in FY17. But again, as many as 5.3 lakh of those companies reported an annual income of less than ₹2.5 lakh! The above data also explain why, as the taxman has trained his guns on evaders in the last three years — tracking down non-filers and issuing a flurry of notices — he has mostly netted only small fish. Between FY14 and FY18, India saw the number of I-T return filers expand by 80 per cent from 3.79 crore to 6.84 crore. But the direct tax kitty grew by a far lower 55 per cent. Nearly a fourth of the current return filers fall in the zero-tax bracket.
This was the central message of Can India Grow?

8. Amidst the uncertainties surrounding debates on peak oil, the oil market is going through the latest cycle of investment contraction. Consider this
In the second half of this decade total capital expenditure by the large oil and gas groups is projected to fall by almost 50 per cent to $443.5bn from $875.1bn between 2010-15, according to Norwegian consultancy Rystad Energy. Although partly offset by a fall in oilfield development costs, the drop also coincides with the big groups ploughing more capital into shorter-term projects, which pay off quickly, as well as renewable energy.
This comes even as prices are experiencing downward pressure due to the convergence of renewables and the falling cost of production itself due to technological advances. 
The article points to oil majors preferring renewables and short-cycle shale projects rather than long-gestation conventional projects.

9. Finally, the Times points to the flattening yield curve in the US, a portend for recession. The flattening yield curve sets the stage for its inversion, wherein the long-term rates fall lower than the short-term ones. All but one of the nine recessions since 1955 have been preceded by an inversion of the yield curve.
In normal times, markets expect long terms rates to be higher than short-term ones, a reflection of the inflation expectations over the longer term. However, an inverted curve points to market expectations about weaker economic growth prospects and consequent lower rates.