The Case For No Econ PhD

It’s the loveliest Twitter thread I discovered in Tyler Cowen’s recent blog post. Melissa Kearney, Economics Professor at the University of Maryland,  argues that 6 year Econ PhDs are terrible, especially for female students. Tyler goes a step further and says Econ PhDs should be abolished. Instead, he suggests three years of graduate economics education and off to job market straight away! I agree when he says economics needs lifelong learning, and feel kind of nice when he reminds us that Smith, Keynes, and Hayek did not study for an Econ Ph.D.

What do you think?

Top reads on Indian microeconomics

I usually don’t do this but I am tempted to share an amazing thread by Prof Chinmay Tumbe of IIM-A on some of the top reads in Indian Microeconomics. Sharing some of his recommendations here:

  1. https://www.ierdse.org

1

2. https://t.co/6bvARGYCaL

Journal of Quantitative Economics, started in 1983 by The Econometric Society of India (TIES); On Springer, volumes available from 2003.

3. https://t.co/xDa98NbJQn

Journal of Income & Wealth (Vol. 40 published in 2018), of the Indian Association for Research in National Income and Wealth. Papers from 2003.

4. https://www.springer.com/economics/journal/41775

1

5. https://www.emerald.com/insight/publication/issn/1753-8254

Indian Growth and Development Review, since 2008.

6. https://t.co/OUKvz7ghH3

South Asian Journal of Macroeconomics and Public Policy, published in association with CSSS Calcutta. Since 2012.

7. http://www.i-scholar.in/index.php/ArthaVij/issue/archive

Artha Vijnana of GIPE Pune since 1959.

 

8. Some classics published in the EW 1949-65 () and since then EPW () – whose other contribution is creating useful a time series statistical database –

9. https://journals.sagepub.com/loi/mar
Margin: The Journal of Applied Economic Research of NCAER, since 2007
Indian Journal of Economics, University of Allahabad, published since 1916
11. Research tool to search topic titles published in Indian Journals is housed at ISID, Delhi (), earlier on CDs and now online here:

18 percent of 50

Wikipedia has been a deeply unequal place and this wasn’t going to change anytime soon. But thanks to the efforts of academics and researchers and gender experts around the world, the gender gap on Wikimedia has narrowed. Check out the figures for every country here.

Since 2015, ‘Women in Red’ project based has been leading efforts to mitigate the biases on the internet, especially the “content gender gap” prevalent on websites like Wikipedia. On Wikipedia, women have been underrepresented and this forms the basis for the ‘Women in Red‘ project to work towards turning the non-existent red links on Wikipedia into blue ones, with women’s biographies, details on their work and career, and other gender issues. Since 2015, the entries about women on Wikimedia were just about 15% of the total entries on the site; four years later, it has touched 18%.

At Rice University, Prof Diane Straussman has been encouraging students to take up wikimedia entries as part of their student projects. An interview with her to learn more about her efforts will be on this blog soon.

While I get back here with the interview, here , here, here and here are some interesting reads on the gender gap and efforts to bridge the gap, highlighting the credit for outstanding work by women that either arrives late or almost never comes!

 

 

Trump’s Crazy Quibble Over Yuan

First, the madness over Huawei (I blogged about this here) and now, the accusation of currency manipulation – US President Donald J Trump has let the world know that the US-China trade war is far from over. But what exactly has happened with Yuan to warrant Trump’s accusation?

The Yuan fell to its 11-year low against the US dollar last week. It happened because China’s central bank set a lower than usual reference rate for its currency Yuan, and when Yuan hit a low, it didn’t intervene. Trump immediately lashed out, calling China a “currency manipulator”.

China’s Shady Past

This label (of currency manipulation) has come back to haunt China after more than two decades when in 1994, it had earned the tag and rightly so. Currency manipulation is essentially an artificially lowering of the value of a country’s currency against the US dollar, usually done to boost exports. Artifical lowering refers to the weakening of currency by policy measures rather than market forces. With weaker currency, goods and services being exported from a country become cheaper in international markets, raising the volume of exports. Such behavior is unwelcome as gains derived from artificially lowered currencies tend to provide an unfair competitive advantage to countries with weakened currencies, in global trade. China’s export-led economy today is a manufacturing hub, but not without concerns being raised over its currency manipulation in the 1990s. China is known to tightly control its exchange rate and in the last two decades, its always been around 7 yuan per dollar.

US Tariffs and Yuan

In the ongoing US-China trade war, negotiations over tariffs haven’t been going well. Last week, just before the fall of Yuan, US-China failed to arrive at a settlement on tariffs. Instead, US announced more tariffs on 300 billion dollars worth of Chinese goods. China retaliated saying it wouldn’t purchase US agricultural products. This development was succeeded by the fall in Yuan, which China said was driven by market forces. However, for a country known for its tight control over the exchange rate, this was unusual. When the Yuan was falling, China’s central bank, like several times earlier, didn’t intervene.

Here is an excellent piece on currency manipulation that I strongly recommend.

Back to the Q: Is China Manipulating Yuan?

Experts say it depends on whether China runs a huge trade surplus today and as facts stand, China hasn’t been burying foreign exchange neither does it have a large current account deficit as it used to have in the 1990s-2000s. Even US Treasury investigations have concluded for many years now that China doesn’t qualify to be a currency manipulator.

What Now

Experts have termed US’ current labeling of China merely symbolic as the tag of currency manipulator may not have huge and direct implications for either of the two parties involved. However, it’s the intent and purpose of the Trump administration in this matter that appears terrifying. Besides countless reports on China over its intellectual property and other trade practices, Trump government hs its fangs out for China with tariffs and more tariffs. This has huge implications for the global economy (I have already discussed this in an earlier post). Economists at Morgan Stanley have predicted that if the US-China trade war continues for another four to six months, the global economy will plunge into a recession in nine months.

Negotiations between China and the US, irrespective of the name-calling and labeling, seems to be the only way out. It appears that the US and China both would still like to negotiate a deal, given that plans are already underway for a Chinese trade delegation to visit the US next month. Only more trade talks will stop this trade war from getting out of hand.

 

Two insightful reads on the subject that I so want to recommend:

https://mises.org/wire/trumps-hypocrisy-currency-manipulation

http://econbrowser.com/archives/2019/08/guest-contribution-rmb-reaches-7-0-us-names-china-a-manipulator

What Machine Learning has to do with Global Trade

Machine Learning (ML) is commonly seen as the scientific study of algorithms and statistical models used by computers to perform specific tasks. Considered a subset of artificial intelligence, ML could have game-changing implications for people of the world struggling with language barriers. As we know, Chinese, Spanish and English are the most spoken languages of the world. What ML can potentially do is to help people translate native languages into other different languages they may need to speak in with the help of artificial intelligence, and when this happens, this could seamlessly unite the world in more ways than one. Just sample Google Translate and you’ll know what I am talking about.

How does this help global trade? If economists are to be believed, language barriers have hurt trade substantially, and precisely why, with ML demolishing the language barriers, world trade could change. According to the “gravity model”, a common language between trading partners could raise trade by almost 50 percent. If trading nations, involving millions of people and corporations, begin dealing in a common language (thanks to ML), imagine the gains from the trade! This could mean people being able to work in countries where they couldn’t earlier as they didn’t know the native language, or communicate easily for work, leisure or fun.

With machine translation becoming more efficient and widely used, speakers of languages other than English, Chinese or Spanish will compete with them and the global market will be full of such people wanting a share of the employment pie. Job markets will no longer discriminate on grounds of language. Machine learning may just be paving the path to the possibilities of great human cooperation by bringing down the language barriers.

Yet, ML’s direct benefits for trade remain a matter of discussion for many scholars. They argue that the progress in ML may be limited to indirect communication and as far as trade ties involving direct communication are concerned, factors such as a preference for local products, trust between trading partners and familiarity with business may undermine the role of a common language. Then, there are linguistic, religious, and legal influences that could play a significant role.

Sources here and here.

 

 

India’s Garbage and Cycle Industries Are Facing The Heat, Thanks To China

Two reports in the last couple of days underline the impact of movements and decisions in global trade. This NYT report focusses on the impact on the $25 billion garbage industry in India. The crash in the industry is the result of China’s surprise cut in garbage imports last year. China buys most of the world’s garbage, and US sells the most. In plain demand and supply logic, China’s action cut the demand for trash globally even as trash supply kept overflowing from the US. This has had a severe impact on India’s garbage industry, which is now dealing with low prices and weak demand. This would also have an impact on the environment, as much of the garbage contains plastic which if not disposed of, will be toxic.

From the report:

The type of trash evolved as more Indians could afford more stuff. Water bottles appeared, along with shopping bags, clothes, cardboard and motorcycle helmets. The latest tech, first piles of cassette tapes, then CDs and DVDs started showing up. And cellphones, smartphones and all their accessories.

As the mountain grew it became more exhausting to reach the peak, where the new stuff was dumped. The 10-minute trek grew to 20 minutes. During the hot, dry summers, when temperatures top 110 degrees, pickers lugged liters of water to stay hydrated. Methane fires sprouted up across the mountain, lighting up the night.

China’s shift in policy, and the drop in prices, had a sharp effect on the slum. Workers are now struggling to avoid plummeting deep below the poverty line.

Another IANS report published by Mint said Punjab’s bicycle industry is struggling as cheaper Chinese imports flood the Indian market. It’s estimated that 200 bicycle factories have closed, unable to battle cheaper Chinese.

An excerpt from the report says:

At the heart of bicycle manufacturers’ grouse is how China has gatecrashed the Indian market through the South Asian Free Trade Area (SAFTA) pact, which came into effect in 2006. The agreement paved the way for the eight member countries to reduce customs duties of all goods traded among them to zero by 2016. China isn’t a party to the pact but is still reaping its benefits.

Much Fuss Over GDP But How Do We Measure Happiness?

The debate over India’s GDP numbers (economists are still locking horns over the truth and objectivity in these figures) was back into currency with this Arvind Subramanian piece published in June this year. He said that India may have overstated its GDP figures by 2.5 percentage points every year since 2011. Another insightful piece said the figures may have been overstated by 1-1.5 percentage points. This is significant, and while there may be a difference in figures quoted, inaccurate reporting of GDP is now an elephant in the room, too big to ignore.

GDP is an important economic tool. It measures the production of all goods and services bought and sold in an economy each year, by this very fact, has been of utmost importance to economists trying to measure economic growth. But of late, there have been concerns that GDP my not be a perfect tool to measure growth. Jacinda Ardern, New Zealand PM took it a step further when she said her government is going to look at fresh ways to measure happiness and wellbeing of the people of her country.

So, what are we going to do when we fix our GDP numbers back home? May be, join the global efforts on finding means to measure happiness, because number-driven GDP is already being punched for being an ineffective tool.

Courtney Goldsmith, in this piece, argues why GDP as a measure of economic growth may not be effective:

In an independent review of the UK’s economic statistics published in 2016, Sir Charles Bean wrote that GDP is often viewed as a “summary statistic” for the health of the economy. This means it is frequently conflated with wealth or welfare, though it only measures income. “Importantly, GDP… does not reflect economic inequality or sustainability (environmental, financial or [otherwise]),” Bean wrote. What’s more, GDP is not the precise and flawless figure that many believe it to be – it is merely an estimate. “This uncertainty surrounding official measures of GDP is inadequately recognised in public discourse, with commentators frequently attributing spurious precision to the estimates,” Bean continued.

Sarah Arnold, Senior Economist at the New Economics Foundation (NEF), told World Finance that GDP as a measure of economic activity is simply a means to an end: “It has become so synonymous with national success that the rationale for pursuing economic growth in the first place seems to have been long forgotten.”

Putting the flaws highlighted by Bean and Arnold aside, GDP is still an inaccurate measure of prosperity, as it fails to convey much of the value created in the modern world. GDP was developed during the manufacturing age and, as David Pilling, Africa Editor of the Financial Times, wrote in his book The Growth Delusion: Wealth, Poverty and the Wellbeing of Nations: “[GDP] is not bad at accounting for production of bricks, steel bars and bicycles.” Where it struggles, though, is with the service economy, a segment that accounts for a growing proportion of high-income countries’ economies. “[Try GDP] out on haircuts, psychoanalysis sessions or music downloads and it becomes distinctly fuzzy,” Pilling wrote.

GDP’s preference for tangible goods also means it is insufficient at capturing the value of technology.

Of course, the number-focussed measure of GDP may not be equipped to assess job quality, wellbeing, carbon emissions, inequality, and physical health, key indicators of happiness and wellbeing that development economists have been focussing on.

Goldsmith, in her piece, further argues:

For GDP, which does not distinguish between good and bad production, bigger is always better. …Wars and natural disasters, too, can be a boon to GDP as a result of the associated increase in spending. Comprehensive wealth, on the other hand, accounts for all of a country’s assets, including: produced capital, such as factories and machinery; natural capital, like forests and fossil fuels; human capital, including the value of future earnings for the labour force; and net foreign assets.

GDP’s neglect of natural capital in particular has received more attention in recent years. Natural assets, such as forests, fisheries and the atmosphere, are often regarded as self-sustaining, fixed assets. In actual fact, all of these resources can be – and are being – depleted by humans. Since the 1990s, economists have looked into the possibility of putting a price tag on natural resources to ensure their value is taken seriously. Ecological economist Robert Costanza published a paper entitled ‘The Value of the World’s Ecosystem Services and Natural Capital in Nature’ in 1997 that valued the whole of the natural world at $33trn. While Costanza’s research was highly controversial, the idea of accounting for natural depletion within the landscape of economic growth is becoming more common.

This McKinsey report says:

GDP as a unit of measure has not kept pace with the changing nature of economic activity. Designed to measure the physical production of goods in the market economy, GDP is not well suited to accounting for private- and public-sector services with no output that can be measured easily by counting the number of units produced. Nor does GDP lend itself to assessing improvements in the quality and diversity of goods and services or to estimating the depletion of resources or the degradation of the environment associated with production. Transformative change in technology is not easy to measure using GDP because so much of the benefit accrues to consumers.

World Bank too has touched upon the subject with its own concept of “comprehensive wealth“, covering in its sweep all produced capital such as factories and roads; natural capital like forests and water; human capital, which leads to earnings; and net foreign assets, to project a fuller picture of economic wellbeing and growth. Experts today are also working out ways to measure intangible qualities of happiness and knowledge but we have a long way to go.

There are interesting cues here, in this Econlife piece published today, which questions if money could indeed buy happiness, by comparing GDP, social support, life expectancy et al of the top 10 happiest countries (according to the UN Happiness Report) in the world.

I think happiness couldn’t ever be measured except in smiles and those trying to chase happiness are the unhappiest lot. Think of this at a national level and tell me: is it possible to make everyone happy? I like it when they say, happiness is a state of mind. Of course, this is because this happiness question weighs heavy on my soul so escapist statements best resolve the moral dilemma. However, honestly, GDP and happiness do not always go together, that’s very much true.