Seven failures of economic liberalization

We’re all celebrating 25 years of the 1991 reforms, with good reason, but there are also several areas where our hopes have been belied

We’re all celebrating the 25th anniversary of the economic liberalization of 1991, with good reason. The end of the licence raj and the opening up of the economy to private and foreign capital has been a success story. But there are also several areas where our hopes have been belied. Here are a few of them:

Share of manufacturing in GDP%

One would have expected that the New Industrial Policy, unveiled in 1991, would have been just what the doctor ordered for the manufacturing sector and India would soon take its place among the manufacturing powers of East Asia. But chart 1 shows that in 1989-90, the share of manufacturing in the gross domestic product was 16.4%; in 2015-16, after myriad new manufacturing policies, its share was at 16.2%. True, this doesn’t mean the sector hasn’t grown. But since manufacturing holds out the promise of jobs for the masses and its productivity is also relatively higher, it was hoped that its share in the economy would increase. That hasn’t happened.

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Combined fiscal deficit of centre and states

One underlying reason for the crisis of 1991 was the indiscriminate rise in government borrowing in earlier years. It was only to be expected therefore that after the crisis, the government would do all it could to curb its fiscal deficit and that of the states. Unfortunately, as chart 2 indicates, that didn’t happen. By 2000-01, the combined fiscal deficit of the centre plus the states, as a percentage of GDP, had risen beyond the 1991 level. In 2014-15, the combined fiscal deficit, as a percentage of GDP, was higher than it was in 1995-96.

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Tax to GDP ratio

One reason why government deficits remained high is that, in spite of robust economic growth, tax revenues weren’t buoyant. Widespread tax evasion is probably the reason, along with a plethora of sops given to companies. Chart 3 shows that the central government’s gross tax revenues as a percentage of gross domestic product have remained below the 1991-92 level, in spite of recent efforts.

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Central government expenditure

The disinclination to reduce the fiscal deficit had the effect of raising the central government’s interest burden, as it had to pay out ever-increasing interest on its outsize borrowings. The upshot was deterioration in the quality of the deficit. The government was borrowing to fund, not productive capital expenditure on infrastructure, but unproductive revenue expenses. The chart shows that in 1990-91, capital expenditure accounted for 30% of total central government expenditure. The budget for the current fiscal year puts the share of capex at a mere 12.5%.

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Average employment per non-agricultural establishment

Economic liberalization has failed to provide secure and decent jobs to the mass of the population. Chart 5 shows that in spite of all the reforms, the number of employees per non-agricultural establishment has been coming down steadily. It was an average of 2.39 employees per establishment in the 2013 economic census, compared to 3.01 persons in the 1980 economic census. This means the vast majority of the establishments in India are in the informal sector, with neither the capital nor the technology to improve productivity.

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Distribution of employment according to size of employment

Before the 1991 liberalization, 37.11% of employees used to work in establishments employing 10 or more workers. Instead of increasing, that proportion has been steadily coming down and in 2013, only 21.15% of employees worked in establishments employing 10 or more workers. Workers in small enterprises for the most part eke out a precarious existence in the informal sector with no job security and precious few benefits.

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Mortality rate

And finally, surely economic liberalization should result in better care for our children. Chart 7 shows the country has made considerable progress on that front, with the under-five mortality rate coming down from 125.8 per thousand in 1990 to 47.7 per thousand in 2015. But as the chart shows, neighbouring Bangladesh and Nepal, much poorer than India, have both brought down their under-five mortality rates more than India. The chart suggests you don’t really need to be the world’s fastest-growing major economy to ensure your kids survive.

India can become world’s data science service provider

Can India provide an army of data scientists to the world, like the IT engineers that it provided in the last decade? 

In the last two decades, we have seen a huge impact of information technology (IT) on businesses. Today, almost all business transactions and processes, internal and external, happen on a computer or mobile and by the use of a network, primarily the Internet. The penetration of smartphones has extended this automation to the last mile i.e. to the consumers. Large network-based information systems facilitate various business processes such as sales order, financial transactions, human resource management, customer service management and so on—the Aadhaar project being a splendid example of IT reaching the last mile.

The IT revolution has made businesses much more efficient by allowing transactions to be fast, error-free and trackable. It has not necessarily made them ‘intelligent’ but it has paved the way for mining intelligence by creating a wealth of digitized data. For instance, product manufacturers know what product is sold on a given day, at what time and at which outlet. A lot of transactions happen naturally on the web, through e-commerce.

In the coming decade, i.e. the decade of data science, we will analyse these data on a large scale to identify trends, find anomalies and most importantly, predict future trends. But let us pause here to understand what data science is. Suppose you have the transcripts of the pitch of sales people in a company including the ones that have led to a sale. You wish to predict which sales pitches are good and what makes them good. Traditionally, one will probably use a sales coach to understand this.

However, the data science way is remarkably different—it uses unstructured data, i.e. transcripts, and derives features such as the length of the call, counts of courteous expressions like “may I”, “please”; counts of words about product value—“automatic”, “fast” and so on. Using these features and statistics, an algorithm builds a model to predict the success of the pitch. For instance, the algorithm may discover that pitches with a good number of positive words, good number of product value words and with a moderate call length leads to success. A totally new sales pitch can then be checked against such conditions to predict if it is good or not.

How is this revolutionary? We can find out whether a new sales person is ready to be put on the job or needs further training based on his/her pitch quality. This model can be linked to the sales process, where it provides personalized feedback for improvement to each salesperson immediately after a sales call. Eventually, one day, the algorithm will replace the salesperson!

Better algorithms, more processing power and the availability of large data sets have enabled highly accurate models. However, this process of data science itself is hardly automated. Initially, a lot of work is required to convert unstructured data in to useful models and integration of these models into the information systems. The person responsible for all of this is the formidable data scientist.

Can India provide an army of data scientists to the world, like the IT engineers that it provided in the last decade? Can this become the engine of our economic growth in the coming decade? It is not only a huge opportunity, but a challenge, too.

First, we need trained manpower. Data scientists need to be adept in programming skills, database skills and basic statistics. Today, we hardly have people who understand both computer science and statistics. Our undergraduate education needs to take up data science courses in a big way. A year ago, we took a bold step of introducing data science for classes V to VIII. These kids successfully built their own friends’ predictor (www.datasciencekids.org). India should aspire to be a leader in providing data science education early on.

Second, we need to be among the leaders in research and innovation in machine learning. Though India became an IT services powerhouse without any great technology innovation, this will not hold for data science services, for innovation and disruption have gathered rapid pace in recent years.

We need to use the latest technology in our services and also be the innovators. Data science service offering will not only be people driven but also product driven. Unfortunately, there is a huge gap here. Our analysis (ml-india.org) showed that Tsinghua University in China alone produces more machine learning papers in top conferences than all universities in India put together. Similarly, companies in the US have taken a lead in machine learning innovation.

Lastly and most importantly, we need entrepreneurs who can go across the globe and solicit data science business for their companies in India—the new Murthys and Premjis. Let us get ourselves ready to become the world’s data science services powerhouse.

India can become world’s data science service provider

Can India provide an army of data scientists to the world, like the IT engineers that it provided in the last decade? 

In the last two decades, we have seen a huge impact of information technology (IT) on businesses. Today, almost all business transactions and processes, internal and external, happen on a computer or mobile and by the use of a network, primarily the Internet. The penetration of smartphones has extended this automation to the last mile i.e. to the consumers. Large network-based information systems facilitate various business processes such as sales order, financial transactions, human resource management, customer service management and so on—the Aadhaar project being a splendid example of IT reaching the last mile.

The IT revolution has made businesses much more efficient by allowing transactions to be fast, error-free and trackable. It has not necessarily made them ‘intelligent’ but it has paved the way for mining intelligence by creating a wealth of digitized data. For instance, product manufacturers know what product is sold on a given day, at what time and at which outlet. A lot of transactions happen naturally on the web, through e-commerce.

In the coming decade, i.e. the decade of data science, we will analyse these data on a large scale to identify trends, find anomalies and most importantly, predict future trends. But let us pause here to understand what data science is. Suppose you have the transcripts of the pitch of sales people in a company including the ones that have led to a sale. You wish to predict which sales pitches are good and what makes them good. Traditionally, one will probably use a sales coach to understand this.

However, the data science way is remarkably different—it uses unstructured data, i.e. transcripts, and derives features such as the length of the call, counts of courteous expressions like “may I”, “please”; counts of words about product value—“automatic”, “fast” and so on. Using these features and statistics, an algorithm builds a model to predict the success of the pitch. For instance, the algorithm may discover that pitches with a good number of positive words, good number of product value words and with a moderate call length leads to success. A totally new sales pitch can then be checked against such conditions to predict if it is good or not.

How is this revolutionary? We can find out whether a new sales person is ready to be put on the job or needs further training based on his/her pitch quality. This model can be linked to the sales process, where it provides personalized feedback for improvement to each salesperson immediately after a sales call. Eventually, one day, the algorithm will replace the salesperson!

Better algorithms, more processing power and the availability of large data sets have enabled highly accurate models. However, this process of data science itself is hardly automated. Initially, a lot of work is required to convert unstructured data in to useful models and integration of these models into the information systems. The person responsible for all of this is the formidable data scientist.

Can India provide an army of data scientists to the world, like the IT engineers that it provided in the last decade? Can this become the engine of our economic growth in the coming decade? It is not only a huge opportunity, but a challenge, too.

First, we need trained manpower. Data scientists need to be adept in programming skills, database skills and basic statistics. Today, we hardly have people who understand both computer science and statistics. Our undergraduate education needs to take up data science courses in a big way. A year ago, we took a bold step of introducing data science for classes V to VIII. These kids successfully built their own friends’ predictor (www.datasciencekids.org). India should aspire to be a leader in providing data science education early on.

Second, we need to be among the leaders in research and innovation in machine learning. Though India became an IT services powerhouse without any great technology innovation, this will not hold for data science services, for innovation and disruption have gathered rapid pace in recent years.

We need to use the latest technology in our services and also be the innovators. Data science service offering will not only be people driven but also product driven. Unfortunately, there is a huge gap here. Our analysis (ml-india.org) showed that Tsinghua University in China alone produces more machine learning papers in top conferences than all universities in India put together. Similarly, companies in the US have taken a lead in machine learning innovation.

Lastly and most importantly, we need entrepreneurs who can go across the globe and solicit data science business for their companies in India—the new Murthys and Premjis. Let us get ourselves ready to become the world’s data science services powerhouse.

Nasa’s Juno is set to approach Jupiter. What will it find?

After completing a five year journey, Nasa’s solar-powered Juno spacecraft will arrive at Jupiter on Monday, and attempt to join its orbit. On arrival, Jupiter’s gravity will pull in Juno until the spacecraft reaches a speed over 250,000 kmph with respect to Earth—making it one of the fastest human-made objects ever.
On Monday, Juno will attempt to get inserted into the orbit using a 35-minute burn of its main engine to slow the spacecraft by about 542 meters per second so it can be captured by the gas giant’s orbit. Once in Jupiter’s orbit, the spacecraft will orbit it 37 times across 20 months, approaching 5,000 km above the cloud tops. This is the first time a spacecraft will orbit the poles of Jupiter, which would help provide many more answers about the planet’s composition and origin.

The Juno spacecraft was launched aboard an Atlas V551 rocket from Cape Canaveral, Florida, on 5 August, 2011. To accomplish its science objectives, Juno will orbit over Jupiter’s poles and pass very close to the planet which will allow it to make the kind of measurements the mission aims to provide.
“This orbital path carries the spacecraft repeatedly through hazardous radiation belts, while avoiding the most powerful (and hazardous) radiation belts. Jupiter’s radiation belts are analogous to Earth’s Van Allen belts—but far more deadly,” Nasa said in a note about the mission.
During the almost one-and-a-half-year of the mission dedicated to science, the spacecraft will attempt close fly by above the planet’s cloud tops every 14 days. Here is what Juno is out to find:
Origin: There are several theories regarding the origin of Jupiter. By finding out the water present in the planet and the maximum possible mass of the planet’s solid core, scientists can zero in on the right theory.
Interior: To gain a deeper understanding of the planet’s interior structure and how material moves within the planet by locating the gravitational and magnetic fields.
Atmosphere: To assess the atmospheric composition, temperature, and cloud opacity.
Magnetosphere: To further explore the three-dimensional structure of Jupiter’s polar magnetosphere and auroras.

IAS 2016 PRE ADMIT CARD CAN CHECKED HERE

Civil service exam-2016 prelims admit card is out.

IAS 2016 PRE ADMIT CARD CAN CHECKED HERE

http://upsconline.nic.in/eadmitcard/upsc_ac2/admitcard_csp_2016/

• Exam will be held on 7^th August, 2016, Sunday
• Must tick MCQs with Black Ball point pen only.
• Paper-I (General Studies) from 9:30AM to 11:30AM (You’ll not be given entry, if more than 10 minutes late).
• Paper-II (Aptitude) from 2:30PM to 4:30PM.
• If problem, contact e-mail: – web-upsc@nic.in (For Technical Problem) , uscsp-upsc@nic.in (For Applicant Data Problem)

After Mauritius, Cyprus set to ink new tax treaty with India

India will get the right to tax capital gains from sale of shares on investments made by Cyprus-based companies after 1 April 2017 

India and Cyprus are poised to sign a new tax treaty which, like in the case of a similar pact with Mauritius, will shut the doors on investors using loopholes in the bilateral agreement to avoid paying taxes in India.

The new agreement will enable Indian authorities to tax capital gains on investments routed through Cyprus; it will also lead to the removal of the Mediterranean island nation from an Indian government blacklist on which it was placed for not providing financial information sought by India.
The renegotiated tax treaties are part of an effort by the National Democratic Alliance (NDA) government to curb treaty abuse, tax evasion and round-tripping of funds—the practice of money stashed overseas by Indians returning home through tax havens such as Mauritius in the garb of foreign capital.
India will get the right to tax capital gains from sale of shares on investments made by Cyprus-based companies after 1 April 2017.
But this will be effective prospectively. Consequently, all investments made earlier have been protected, similar to the provision made in the India-Mauritius treaty.
“On June 29th, 2016, the negotiation on the Double Taxation Agreement for the Avoidance of Double Taxation and the Prevention of Fiscal Evasion with respect to taxes on income between Cyprus and India has been successfully completed, in New Delhi. The completion of the negotiation and the agreement reached on all pending issues will pave the way for the removal of Cyprus from the list of notified jurisdictional areas place in November 2013,” said a statement put up on the Cypriot finance ministry’s website late on Thursday.
Also Read: Cyprus team to negotiate revisions in tax treaty with India
India declared Cyprus a notified jurisdiction in November 2013, putting it on a blacklist, saying the nation had failed to share adequate information on tax evaders. As a result, business transaction with entities based in Cyprus came under increased scrutiny of the income-tax department.
The notification makes it difficult for taxpayers to claim deductions on transactions with entities based in Cyprus. It also subjects a taxpayer to enhanced reporting requirements and higher tax outgo.
The statement didn’t say whether investors would be offered a transitionary period like the one provided by the India-Mauritius treaty, under which only half the capital gains tax rate will be applicable between 2017 and 2019.
A statement from the Indian finance ministry said an in-principle agreement had been reached on all contentious issues and the signing of the final, revised treaty will be subject to approval by the Union cabinet.
“It was agreed to provide for source-based taxation of capital gains on transfer of shares. However, a grandfathering clause would be provided for investments made prior to 1 April 2017, in respect of which capital gains would be taxed in the country of which taxpayer is a resident,” the statement said.
A grandfathering clause provides for an old rule to apply to existing cases and a new rule to future ones.
Cyprus was one of the key destinations through which companies based in Europe and the US invested in India, benefiting from the treaty between both countries. In 2015-16, Cyprus ranked eighth in terms of foreign direct investment into India at $3.3 billion.
The existing treaty provides for capital gains tax exemption and a low withholding tax rate of 10% on interest payments made to entities based in Cyprus.
The completion of tax treaty negotiations with both Mauritius and Cyprus, on which talks have been under way for years, will be considered a victory by the NDA in its fight against black money.
Other pacts that will see similar changes in the coming months include India’s tax treaties with Singapore and the Netherlands.
Although it will increase the tax outgo for investors, it will also end uncertainty for investors routing their investments from these countries.
“The development on the India-Cyprus tax treaty is another welcome step towards providing certainty in tax. The intent to grandfather existing investments, which is in line with a similar change proposed in the tax treaty with Mauritius, should provide comfort to existing investors,” said Gautam Mehra, leader (tax) at PricewaterhouseCoopers India.
Cyprus will be removed from the Indian blacklist retrospectively with effect from 1 November 2013. Mint had reported on 9 June that Cyprus was willing to allow India the right to tax capital gains in exchange for removal from the list of notified jurisdictions.
Amit Singhania, a partner at law firm Shardul Amarchand Mangaldas and Co., said that retrospectively rescinding the classification will have significant repercussions for many entities that have deducted tax while making payments to Cyprus entities.
“It needs to be seen how the Indian government will provide for refund for those transactions and also provide for revision of withholding tax return,” he said.
At present, any payment to a Cypriot entity attracts a withholding tax of 30%. No deduction in respect of any other expenditure or allowance arising from a transaction with a person in Cyprus, or a payment made to a financial institution, is allowed unless the assessee provides the required documents.
If an assessee enters into a transaction with an entity in Cyprus, it is treated as an associate enterprise and the deal as an international transaction attracting transfer pricing regulations.
Transfer pricing is the practice of arm’s length pricing for transactions between group companies based in different countries to ensure that a fair price—one that would have been charged to an unrelated party—is levied.
“If the assessment of Indian entities who have transacted with Cyprus entity in past has entailed an addition in their income under transfer pricing, then how will the CBDT (Central Board of Direct Taxes) provide for revision of return/assessment order to nullify the effect of Cyprus notification retrospectively? In substance, nullifying the effect of Cyprus notification seems to be difficult,” said Singhania.