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Issue 6

India and the World: Looking into 2021

“I firmly believe that 2020 will be known, not as a year of external disruption, but as a year of internal discovery, for our society and for our nation,” 

Prime Minister Narendra Modi wrote these words for an exclusive article in the Manorama Yearbook 2021. While his words were meant to bring hope for India in times of crisis it also raised questions of how the pandemic altered the country’s position in the international community. 

Claims that India will be a superpower by 2020 have been thrown around by academics, economists and patriotic bhakts for over two decades. These claims can be traced back to India 2020: A Vision for the New Millennium by APJ Abdul Kalam. In this book Kalam laid down his prediction of an India that would have eliminated poverty, have a high amount of women in the work force and would be an economic giant by the year 2020. These predictions could now be considered optimistic at best and completely delusional at worst. 

Coming into 2020 it was quite apparent that we hadn’t even touched the surface of becoming a poverty free nation. The World Economic Forum (WEF) released a report in January 2020 claiming that it will take seven generations for Indians born in low income families to even approach the country’s mean income. The 2020 Global Multidimensional Poverty Index (MPI) identified 27.9% of the population as multidimensionally poor,  the number was 36.8% for rural and 9.2% for urban India. Even promises about the increasing involvement of women in the workforce has proved to be quite inaccurate. India’s female labour force participation rate fell to a historic low in 2018.  India is currently the most disadvantaged country for women participation in South Asia. Economic predictions about India becoming a super power also seem like a big joke. Coming into 2020 the country’s 5% inflation-adjusted growth was the lowest since 2013 and the 7.5% nominal rate was the lowest since 1978. The country that once had one of the fastest growing economies, has not seen success over the last few years mainly due to several blunders in national economic policies and actions. 

While the above numbers may just seem like confusing statistics they shed light on a much larger issue the Indian economy needs to counter. Low participation of women in the workforce doesn’t just shed light on the gender disparity that is evidently prevalent in the Indian patriarchal structure, but also showcases wastage of a large chunk of the country’s working population. 

A high poverty rate in the country’s population is a clear result of poor fiscal management on part of the government. The fact that a majority of the country’s workforce is employed in a sector that contributes the least to its GDP should be a clear indication that the Indian economy is in desperate need of a transformation. The record low inflation rates shows that the country is displaying minimal growth. All of these indicators point to one answer – India is nowhere close to being a developed nation.

India stepped into 2020 with an economic slowdown characterised by high poverty rates and increasing unemployment. The country was in turmoil as mass protests broke out in all states surrounding the people’s outrage towards the government’s discriminatory citizenship laws (NRC/CAA). This year was also not free of obstacles for the country, the biggest obstacle obviously being the COVID-19 pandemic. The Indian economy that was already suffering before the year started has taken massive hits, as the country has now officially entered a technical recession. The country is now faced with farmer protests due to the government’s new Farm Bills that potentially threaten the stability of their income. So what does all this mean for India’s position in the world?

The Indian economy took a larger hit than any other major economy. In the April-June quarter, the country’s GDP shrank by 23.9% , the worst contraction in its history. India also entered a technical recession for the first time since 1947. The International Monetary Fund (IMF) calculations showed that the Indian economy had taken a “uniquely” larger hit than most other countries. While their 2020 growth projections showed upward trends for countries like Bangladesh, China and Vietnam, India’s GDP dip due to the pandemic was more than double the global average fall. Infact China’s trade surplus widened to a record, gaining a 21% increase (for the month of November) in exports from a year earlier. 

The Modi government has tried to ensure the public that this fall in the GDP is temporary and promised that the economy will rebound rapidly, calling it a “V shaped recovery”.  In reality though this is quite unlikely. Sabyasachi Kar’s model predicts that it will take up to 2033 for India to get back on the pre-Covid growth path if the country’s GDP grows at a rate of 7% for the next 13 years. Another projection made by scroll.in shows that if India’s GDP grows at a realistic 6.1% instead of Kar’s 7% estimate, it will take almost three decades (upto 2049) for the country’s GDP to get back on a growth path. While the Indian government is planning on introducing policies to ensure growth, the country’s standard growth policies are being ineffective. States across the country are seeing a reduction in their capital expenditures (CAPEX) , this is mostly due to the fall in revenue due to the pandemic. This reduction in revenue and CAPEX basically means that the government isn’t investing close to enough money on roads, energy plants and other necessary infrastructure. An increased investment in infrastructure is peremptory if the country is to get back on its feet, and the current spending capacity of the states is only going to make post covid recovery much harder. 

Nirmala Sitharaman had stated that the COVID-19 pandemic was an “Act of God” which may result in a contraction in India’s growth. But India’s position as a potential superpower has been threatened for the last 6 years, and the pandemic has only acted as a catalyst for an economy that was already crumbling. While we can try to stay optimistic and hope that the government’s plans pay off, it’s almost impossible that the country can get back to the growth it enjoyed in the 1990s and 2000s.

Karantaj Singh finished his undergraduate in History and International Relations. He is now pursuing a minor in Media Studies and Politics during his time at the Ashoka Scholars Programme. He enjoys gaming and comics in his free time.

Picture Credit: “India Map 2 N” by Mark Morgan Trinidad A is licensed under CC BY 2.0

We publish all articles under a Creative Commons Attribution-Noderivatives license. This means any news organisation, blog, website, newspaper or newsletter can republish our pieces for free, provided they attribute the original source (OpenAxis).

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Issue 6

India’s Dominant Family Businesses Need Newer Challengers

The great Indian business family is dead. Long live the next great Indian business family. Like taxes and death, this key pillar of life in this country is ubiquitous. But like much of society around it, there are clear signs it is atomizing. No longer is the son of the rice merchant destined to continue the family tradition. He, and in some rare cases she, is experimenting with newer opportunities being constantly thrown up by a rapidly changing economy. 

That though doesn’t mean the end of the business family’s  dominant role in the Indian environment. Family Business Network, the Lausanne-based federation of business families, estimates their contribution to India’s gross domestic product at a whopping 70%. 

Not that there’s anything particularly aberrant about this. According to consulting firm Ernst and Young, 85% of companies in the Asia-Pacific are family-owned. Similarly, family businesses make up more than 60% of all European companies ranging from sole proprietors to large international enterprises. What’s more these businesses create value for themselves but also for the broader markets. Across the world, including in India, returns generated by family-owned businesses have been consistently higher than those by non-family owned ones.

For this they have been amply rewarded. According to the Billionaires Insights Report 2020 published by UBS and PwC the net worth of India’s billionaires has surged 90% in the 11 years since 2009.

It mirrors a worldwide trend of big businesses getting bigger. Thus, the Wall Street Journal recently advertised for the position of Reporter, Google. It isn’t uncommon for media outlets to assign reporters to cover specific sectors or countries but doing that for selected companies is rare. But so dominant are some global companies and so pervasive their influence that it may be blasphemous but not entirely untrue to say that Google matters more than many countries. As WSJ goes on to say in its job description: “Google’s impact on business and society is vast. Beyond its core search-and-advertising business, it is one of the world’s biggest video distributors through YouTube, the largest smartphone-software supplier thanks to Android, a leader in developing self-driving-car technology through Waymo, and a top contender in the booming cloud-computing industry.”

As it is with Google today, so it has been with others like McDonald’s, WalMart and General Motors in the past. Size leading to market dominance has ensured that some businesses have a disproportionately large influence on the world. It has led to the constant tussle between big business and regulators keen to ensure they don’t squeeze smaller competitors out of the market.

That’s where the biggest danger of business family dominance in India lies. The first two decades following the liberalization of the economy threw up new names in the business landscape of the country. Entrepreneurs like Sunil Mittal in telecom, Uday Kotak in banking, Naresh Goyal and later Rahul Bhatia and Rakesh Gangwal in aviation, rushed to take advantage of the opening up to the private sector of areas that had hitherto been reserved for state-run monopolies. Some like Naresh Goyal came to grief. Others soldiered on and have become the business families of today. At Wipro, the software-to-consumer products conglomerate that was set up by Hasham Premji in 1945, the third generation of Premjis, in the form of new chairman Rishad Premji, is now in charge.

It is the way economies with relatively free markets grow. In fact, crystal ball gazing in the late 1990s led several analysts to predict that in the future Indian business would be driven by companies like Ranbaxy, Samtel, Infosys, ILFS, Kotak Mahindra and Yes Bank, as much as it would by existing powerhouses like Reliance and Tata. 

The future is here and sadly most names in that list of future stars have dropped off with only Kotak and Bharti holding fort. In fact, over the last few years, a disturbing trend has  emerged with a handful of powerful families mopping up businesses across sectors. Despite a surge in entrepreneurship generously funded by private equity and venture capital, there aren’t too many start-ups that look like challenging the incumbents whether it is in existing business areas or even brand new ones like e-commerce, green energy, telecom or retail.  

Worse still, if some recent changes proposed by the country’s central bank are implemented, that dominance may grow to dangerous levels. With capital being the first need of any new venture, RBI’s proposal to allow business groups to set up banks may just add more heft to their existing clout. In a linkedin post two former deputy governors of the RBI, Raghuram Rajan and Urjit Patel warned that allowing corporate entry into banking “will further exacerbate the concentration of economic (and political) power in certain business houses.”  

The tragedy is that going forward the Indian business world could end up looking more like that of the pre 1990s era when a handful of names reigned supreme. Groups like Aditya Birla, Ambani, Mahindra and Mahindra, Vedanta, Bajaj, Jindal, Munjal, RPG, Hinduja, Murugappa, Lalbhai and Adani are a throwback to our past. In the 21st century, they need to be challenged by newer groups. That’s not going to happen if regulation, and regulators, continue to throw their lot with the incumbents. 

Picture Credit: “India Map on Indian Map” by Kush Patel is marked with CC0 1.0

Sundeep Khanna is a columnist, business writer and executive editor at the Mint.

We publish all articles under a Creative Commons Attribution-Noderivatives license. This means any news organisation, blog, website, newspaper or newsletter can republish our pieces for free, provided they attribute the original source (OpenAxis).

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Issue 5

Bidenomics For America and The World

Say all you want about President Donald Trump, one thing you can’t deny is that the US economy soared under his reign – that is before the pandemic…

Prior to the pandemic the American GDP grew in a sound manner, the stock market reached record highs, unemployment rate fell drastically, wages continued to rise and poverty rates were comparatively very low. Donald Trump also successfully challenged the rising Chinese influence over the global economy by calling them out for their intellectual property theft. While Trump did tilt towards protectionist economic policies, it worked in the interest of the American people. His focus on deregulation helped American manufacturing operate at a higher level of economic efficiency. 

President elect Joe Biden seems to have very different views from President Donald Trump on most socio-political issues, and his economic policies seem to be very different as well. So what will Bidenomics mean for America and the world? 

Biden has a history of being a supporter of free trade, he has often described Trump’s protectionist policies as ‘reckless’ and ‘disastrous’. This brings to question whether Biden will get rid of protectionist policies after he has been sworn in. While the shift from protectionist policies to those revolving around free trade seem like the most probable step, there are political and economic restrictions that will not allow Biden to make the move quite so smoothly. The trade war with China was one of Trump’s most significant moves as president, and Biden has been criticised for taking it easy on China. While the trade war has disrupted global trade it is widely supported by the American population, hence pushing Biden to practice protectionist policies. While Biden will probably continue the trade war with China, he will propagate global cooperation with the rest of the international community. Biden claims that forming a coalition with allies and partners is a better strategy instead of the unilateral tariffs imposed by the Trump administration.

Biden’s plan to reverse Trump’s tax cuts on corporations has been championed by the leftists, but how effective is this policy going to be in its implementation?  Biden’s tax policy wants to raise the top income tax rate to 39.6% from 37% and the top corporate income tax rate to 28% from 21%. This move will allow the government to collect a tax revenue of approximately $4 trillion by 2030. While this move sounds good on paper, its effective implementation has several obstacles. Corporates with major accounting teams and an army of lawyers have continued to find safe havens and loopholes in tax laws to legally avoid paying taxes. A tax hike of this rate also increases the probability of tax evasion and tax fraud, which will undoubtedly lead to the creation of a larger shadow economy. Additionally in a post covid world that has witnessed large scale unemployment, increasing taxes on corporations and high bracket earners is gonna push firms to cut costs, thereby creating disincentive for hiring. The increase in taxation may also push firms to switch gears and focus more on international markets such as Hong Kong or Singapore that offer lower corporate tax rates. While progressive taxation is ideally the way to go, the Biden government must ensure that its implementation takes into account all the limitations of the current system.

The Trump administration focused on deregulation in the manufacturing sector to ensure productive and economic efficiency, Biden on the other hand takes a different stand – promising to focus on sustainable development instead. Biden as part of his election campaign has released a 10-year, $1.3 trillion infrastructure plan. The plan aims to move the U.S. to net-zero greenhouse gas emissions. Bidens climate change plan in total will cost the US approximately 2 trillion dollars, and he aims to fund it by reversing Trump’s excess tax cuts on corporations and ending subsidies for fossil fuels. While Trump focused on short term economic efficiency, Biden’s plan is for the future. Switching to sustainable means of manufacturing is going to undoubtedly drive up costs for the American economy, but will also create middle class jobs and ensure environmental conservation. This move towards building sustainable infrastructure also displays that America will be joining the global fight against climate change, after Trump pulled them out of the Paris Accords.

Biden also aims to tackle student loans and flaws in the health care system through his economic plan, and has extensively criticised Trump’s approach towards the same. Biden aims to insure around 97% of the American people through his healthcare plan, and doesn’t shy away to take credit for the Affordable Care Act  introduced by the Obama government. Biden also wants to cancel a minimum of $10,000 of student debt per person. He proposes forgiving all undergraduate, tuition-related federal student debt for low-income and middle class individuals (earning up to $125,000). Biden plans to fund this through the hike in corporate tax. The healthcare and student loan support by the government has been a campaign promise by almost all democrats including Elizabeth Warren and Bernie Sanders. Biden hence seems to be catering to his key demographic.

While Biden and America seem to be optimistic about these economic policies, it can be a cause for great concern if not implemented with caution. An increase in corporate taxation in the midst of an economic crisis can lead to tragic consequences for the American economy. Biden plans to fund sustainable infrastructure, stimulus packages, healthcare, and student debt through his tax plan, while the plan isn’t as optimistic as “Mexico will pay for it”, it still is somewhat overreaching. Even though some may be doubtful about whether Bidenomics will be successful for America, the reversal of the globalisation backlash that we witnessed in the last few years brings some hope for the international community.

Karantaj Singh finished his undergraduate in History and International Relations. He is now pursuing a minor in Media Studies and Politics during his time at the Ashoka Scholars Programme. He enjoys gaming and comics in his free time.

We publish all articles under a Creative Commons Attribution-Noderivatives license. This means any news organisation, blog, website, newspaper or newsletter can republish our pieces for free, provided they attribute the original source (OpenAxis). 

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Issue 3

How the Economics Nobel Laureates help us Understand the Way the World Works

Image credits: Niklas Elmehed for Nobel Media

When we think about the word “auctions”, we may conjure images of high society bidding for expensive paintings, or banks selling off indebted property. It seems to be a distant phenomenon that doesn’t impact our daily lives. But as it turns out, auctions play crucial roles in our lives – from deciding the price we pay for electricity in our homes, to the limit of carbon emissions allowed to different countries. In a mission to learn more about how auctions work, Paul Milgrom and Robert Wilson studied various auction formats and designed an optimal auction mechanism for governments to sell complex public assets. For this, both won this year’s Nobel Memorial Prize in Economic Sciences.

Officially the ‘Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel’, this prize has been awarded to researchers in economics from 1969 onwards, to 86 individuals so far. The ideas studied in the prize-winning contributions, and the methodology followed to reach certain conclusions, often tell us a great deal about how economics has been practiced in the respective times. 

As explained by The Economist, the initial winners were often those who tried to model the economy into a few neat equations, while winners in the past two decades have tried to pick more specific topics, and conducted empirical research to back their results. In the course of the past half a century, the winners of this prize have made several contributions to help us better understand the way in which the world around us works; whether it’s auctions, the role of psychology in the making of economic decisions, alleviating global poverty, governing common resources, and so on. In this article, we have a look at some of the recent prize winners, and understand the impact their contributions have had on our everyday lives.

2020 – Paul R. Milgrom and Robert B. Wilson “for improvements to auction theory and inventions of new auction formats” 

Milgrom and Wilson studied how different formats for auctions–specifically the bidding process, final prices, information available to bidders about the product as well as other bidders’ prior knowledge–all affect the outcomes of the auction such as the revenue generated for the seller, and the broad societal benefit. Through the theoretical study of auctions, they came to design practical auction formats that have real-world implications. In one such instance, they helped the US government auction interrelated objects simultaneously, like radio frequencies to telecom operators. Their contributions ensure that these public assets are sold in the most efficient manner possible, such that buyers (here, telecom operators) get the optimum allocation of their choice, and society’s benefits are maximised (revenue for governments that can be used to fund other public goods.) This auction format can be useful for India’s 5G spectrum auction that is scheduled for next year.

2019 – Abhijit Banerjee, Esther Duflo and Michael Kremer “for their experimental approach to alleviating global poverty” 

Banerjee, Duflo and Kremer extensively conducted field experiments using Randomised Control Trials (RCTs), to examine causes and effective solutions to address poverty-related issues such as poor education and health, lack of microcredit, and so on. By comparing a particular outcome (for instance, academic scores or morbidity rates) across two groups that have similar average characteristics, and differ only in having received a particular treatment (receiving textbooks or deworming pills), they try to quantify the impact of various poverty alleviation measures. The results of these experiments have significantly contributed to policy creation in developing countries globally. A series of experiments found that “poor people are extremely price-sensitive regarding investments in preventive healthcare.” This can inform government policies for pricing vaccines (COVID-19 and otherwise); a shift from highly subsidised vaccines to free ones to even giving additional incentives like free foodgrains, can vastly increase vaccine take-up.

2017 – Richard H. Thaler “for his contributions to behavioural economics”

Thaler’s work incorporates insights from psychology into economic models, to create a more realistic understanding of human decision-making. For instance, the lack of self-control that occurs when one’s long-term goals are defeated by short-term actions, such as difficulty in making healthier lifestyle choices, and saving for the future. To incorporate this finding into useful policy measures, Thaler and his colleagues suggested that governments try and nudge citizens in the right direction (provided they are not misled or coerced.) This has been used extensively to improve pension savings, organ donation and even handwashing. His research has also shed light on common marketing practices that take advantage of human irrationality; this includes “overexposing the rare winners and covering up the multitude of losers” in lotteries, to inflate people’s expectations of winning. Such insights from Thaler’s work can thus help us self-evaluate how we interpret information and guide us to make better decisions. 

2015 – Angus Deaton “for his analysis of consumption, poverty, and welfare”

Deaton’s work delved into understanding how individuals distribute their spending across different goods and how they choose to save. This is important because until the 1980s, work in development economics was largely theoretical, or limited to aggregate data from national accounts. Deaton’s work paved the way for linking individuals’ choices to understanding aggregate outcomes in an economy. For instance, his analysis of household consumption data in India showed that during adverse periods, there are lesser resources allocated to female children compared to males. This helps us quantify the extent of gender discrimination in an individual household as well as across a country, thus helping us design apt policies to adequately address it. It also informs governments about the importance of frequent and accurate data collection, to track and analyse the micro-level causes for macro-level economic outcomes. 

2009 – Elinor Ostrom “for her analysis of economic governance, especially the commons” 

Ostrom’s work challenged the traditional economic thought of “tragedy of the commons”, which suggested that common property be privatised or regulated by central authorities to prevent mismanagement. Ostrom studied various common resources from fisheries to groundwater basins, and found that its exploitation could be avoided by collective local action. Her work delved into understanding the sophisticated methods followed by people to ensure the sustainable and non-exploitative usage of common property. She also explored the diversity and complexity of the combined social and ecological world, and stressed the importance of different approaches to problem-solving rather than a one-size-fits-all institutional approach. This has largely contributed to contemporary discussions around issues like climate change.

Through these contributions by economists, Laureates and otherwise, we find important ways in which we can understand the world around us. What started out as a means to model the working of our economy, has now shifted to understanding how humans interact with the world around them, and the search continues for more efficient and equitable ways to do so. This shift towards making economics more human, beneficial and practical is a hopeful and welcome change in the fate of the ‘dismal science’.

Samyukta is a student of Economics, Finance and Media Studies at Ashoka University. In her free time, she enjoys discovering interesting long-form reads and exploring new board games.

We publish all articles under a Creative Commons Attribution-Noderivatives license. This means any news organisation, blog, website, newspaper or newsletter can republish our pieces for free, provided they attribute the original source (OpenAxis). 

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Issue 3

Forget the Rhetoric: India cannot be the next China!

Image credits:  bmnnetwork

You have to be living under a rock if you haven’t noticed the global backlash against China.

China holds a position of producing a majority of the world’s products and probably will continue to do so in the near future. The industrial giant grew in a rapid and very unsustainable manner over the last few decades becoming a hub for outsourced manufacturing – from making toys and clothes to medical equipment and electronics. China’s aggressive economic growth and unfair trade practices coupled with diplomatic tensions (surrounding the pandemic and border disputes) have given life to the Quadrilateral Security Dialogue – a multilateral group comprising India, Japan and USA and Australia. The four nations resumed dialogue after November 2017 in an attempt to temper Chinese dominance in the Indo-pacific region. The dialogue has raised many questions, the most crucial being – who will now take the role of the ‘world factory’?  

Can India be the next China?

No. At least not in the near future…

While we have heard rhetoric that  often revolves around  how India has a young workforce while China has an ageing population or how the aggressive attributes of China are going to lead to its downfall and create room for new hubs of manufacturing . I beg you to open your mind past the rhetoric and consider some evident issues that won’t allow India to ‘replace’ China in the global market. 

All it takes to break down this rhetoric is a look at employment and GDP statistics through the primary, secondary and tertiary sectors.

I’m not saying that demographic figures aren’t  important, of course they are. But simply basing the fact that India can become the next manufacturing hub simply because of a younger population  is simply absurd. Let’s look at the Indian agricultural industry for example – while over  42% of the country’s man power is employed in the primary sector, it only contributes to approximately 17% of the GDP, making it the most populated and least efficient wing of the Indian economy. So if demographics and economic output was proportional, the Indian primary sector would be the pillar of our economy. 

Unlike most economic giants, India skipped industrialisation trying to build an economy that was driven by the tertiary sector, heavily reliant on a digital infrastructure and not a physical one. It’s hard to deny that the focus on the tertiary sector was a success looking at how it has formed the backbone of the Indian economy. While it only employs 32% of the country’s population it contributes to over 54% of the GDP. But a country that has a literacy rate of less than 78% and an inefficient primary sector, cannot simply rely on one wing of the economy. India needs to increase investment in manufacturing.

What can India do now?

Increasing investment and innovation would be an ideal first step…

Dynamic efficiency, a term any high school Economics student would know (and a concept China mastered) holds the key to India’s reign over global manufacturing. The term in this context would translate to high investment in innovation and technology in the short run that would allow industries to manufacture products at an efficient and economical manner in the long run. Chinese growth was and continues to be driven by some of the world’s highest investment rates, which has allowed the creation of the manufacturing muscle China proudly owns. While India only invests about 30% of its GDP into infrastructure, China has consistently invested 50%. 

China is continuing to innovate and invest, increasing the use of Artificial Intelligence (AI) in manufacturing. The Chinese State Council introduced an Artificial Intelligence Development Plan aiming to build a $150 billion national AI industry in the near future. Part of this plan involves  integrating AI technology in China’s factories . The application of AI in Chinese factories aims to target production R&D as well as the production process including: manufacturing, product development, logistics, monitoring and environmental safety. Companies like Shanghai STEP have created industrial robots along with control systems and software for industries that have effectively transformed welding, packaging, construction, and machining. Even logistics technologies are being powered by AI, to bring productive efficiency in Chinese factories to a whole new level. The use of  AI in Chinese factors holds great potential, taking away the threat posed by the country’s ageing population. While the Indian economy is still taking baby steps towards an industrial economy, the Chinese manufacturing sector is already evolving to suit the needs of the future. It is peremptory that India dedicate their efforts to increasing infrastructure if they are to compete in the global manufacturing market. 

What role do politics play?

An important one for sure…

While the Indian democratic system has its many positives, it also has its own limitations, especially when it comes to economic reform. When working on infrastructural projects such as construction of power plants, the Chinese government can simply acquire land and compensate the affected people. Taking on similar projects in India would have several barriers because of the limitations of central control on states, political procedure and legal disputes. For example if a decision to contract a high speed railway line passes in the Lok Sabha, the process maybe delayed and blocked by the Rajya Sabha. Let’s assume that the project is approved in both houses, issues such as raising government revenue or displacement of minorities more often than not hinders the process. The Indian democracy hence has to fight many battles (one at a time) as part of this infrastructure politics.

‘It is impossible to make one generation better off without making any other generation worse off.’

This is a basic rule for an economy that needs to achieve dynamic efficiency. It is going to take a lot of planning, spending and sacrifice if India is going to even be a contender for becoming the world’s factory. While political and economic reform of such extent is too much to ask for, it is the need of the hour. The country has abundant raw material and a mammoth working population, but falls short on investments and planning. India will have to completely shift its economic structure, which will have repercussions that the Indian society and economy may not be prepared to handle.

Karantaj Singh finished his undergraduate in History and International Relations. He is now pursuing a minor in Media Studies and Politics during his time at the Ashoka Scholars Programme. He enjoys gaming and comics in his free time.

We publish all articles under a Creative Commons Attribution-Noderivatives license. This means any news organisation, blog, website, newspaper or newsletter can republish our pieces for free, provided they attribute the original source (OpenAxis). 

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Uncategorized

Targeted ads: Is there an ethical, economically-viable alternative?

By Samyukta Prabhu

Online platforms like Facebook and Instagram have been widely discussed for reasons ranging from increased user data collection to rising misinformation and election manipulation. At the same time, rising internet penetration globally has improved access to information and opportunities like never before. While assessing the current state of the internet, therefore, there is an urgent need to address its limitations, while ensuring that its strengths are not curtailed.

One way to do so is to address the common thread that ties together the above-mentioned pitfalls of online platforms – targeted advertising. However, the contention surrounding targeted advertising is that it is the primary business model of such platforms, thus being viewed as a necessary evil.

To better understand the nuances of this issue, it is helpful to explore how the business model of targeted ads works. This can help us assess the ramifications of potential regulations to the model – both economically as well as ethically. 

As explained in a report by the United States’ Federal Trade Commission (FTC), the basic model of targeted advertising involves three players – consumers, websites and firms. Websites provide consumers with ‘free’ online services (news articles, search features) into which targeted ads are embedded. Firms pay the websites (through ad networks) for publishing their ads, and specify the attributes of their target audience. To target these ads, websites use consumers’ personal data (browsing habits, purchase history, demographic data, behavioural patterns) and provide analysed metrics to firms; this is used to improve the precision of future targeted ads. Firms are incentivised to improve targeting of their ads since they earn money when users buy the advertised products. This model improves over time, with increased user engagement, since the algorithms running the websites analyse collected data contemporaneously to optimise users’ news feeds. It thus follows that lax data privacy laws and user behavioural manipulation (to increase user engagement) greatly supplement the business model of targeted ads. Phenomena such as engaging with and spreading controversial content, as well as rewarding the highest paying ad firm with millions of users’ attention, are then some of the obvious consequences of such a business model.

Over recent years, a few governments and regulatory bodies have taken select measures to address some concerns stemming from the targeted ad model. However, there often seem to be gaps in these regulations that are easily exploitable. For instance, the European Union’s General Data Protection Regulation (GDPR), a data protection and privacy law for the EU region, prohibits processing personal data of users without their consent, unless explicitly permitted by the law. However, loopholes in Member States’ laws, such as the Spanish law, for instance, allows political parties to obtain and analyse user data from publicly available sources. In 2016, a ProPublica report found that Facebook allowed advertisers to exclude people from viewing housing ads, based on factors such as race. Facebook’s response to remedy the situation was to limit targeting categories for advertisers offering housing, employment and credit opportunities, and barring advertisers from using metrics such as zip codes (proxy for race) as targeting filters. However, this is a temporary fix for a larger structural problem as there exist multiple proxies for race and gender that can be used for targeting. We thus see that despite efforts to target specific concerns (such as data processing, or algorithmic accountability) of online platforms, there exist legal loopholes that allow tech firms to override these regulations. Moreover, with rising billion-dollar revenues and tech innovations that far outpace legal reforms, there is increasing incentive for Big Tech firms to exploit targeted ad systems and maximise profits before the law finally catches up. 

As we can see, niche regulations to the targeted ad system are thus unlikely to adequately address the rising concerns of online platforms. That leads us to a seemingly radical alternative: abandoning the targeted ad system altogether, and exploring other models of online advertising. Such models would neutralise incentives for firms to collect and analyse user data since revenues would no longer be dependent on them. The FTC’s report suggests two such models: first, an “ad-supported business model without targeted ads” – similar to the advertising model in newspapers. Websites would use macro-level indicators to target broad audiences, but would not collect user data for micro-targeting or behavioural manipulation. Second, a “payment-supported business model without ads” – similar to Netflix, which charges the user with a subscription fee. Some platforms (such as Spotify) currently work on a mixture of the two models – free to use with generic ads, or subscription-based without ads. The potential economic shortcomings for such a model include “increased search cost” for firms to find potential buyers of their product, and “decreased match quality” for consumers who might see unwanted generic ads. However, this model has been successful for several music streaming and OTT platforms (including Spotify, Netflix) and ensures useful, customised services without the associated perils of targeted advertising. 

There exist a few other measures that continue to work within the purview of the targeted ad system, but use established regulatory frameworks to skew incentives of data collection and processing. One such measure that gained traction since Lina Khan’s seminal essay in 2017, Amazon’s Antitrust Paradox, is for anti-monopoly regulations as well as public utility regulations to be applied to Big Tech firms. Since these platforms effectively capture the majority of the market share for their respective products, they could be subject to anti-monopoly regulations including breaking up of the firm and separation of subsequent divisions, to prevent data collection and processing across platforms (for instance, separating Facebook from its acquired platforms Instagram and WhatsApp.) A more direct measure to limit data collection is to subject tech firms to data taxes. Another measure, that of public utility regulations, has been in play throughout history to limit the harms of private control over shared public infrastructure, including electricity and water. They stipulate “fair treatment, common carriage, and non-discrimination as well as limits on extractive pricing and constraints on utility business models.” Since the internet (and its ‘synonymous’ platforms like Google and Facebook) is an essential resource in the 21st century, being a principal source of information for the public, it can be argued that it is a public utility, thus requiring it to be subject to the appropriate regulations. With the current state of the internet requiring user surveillance and behavioural manipulation, it easily violates the fundamental public utility regulation of “fair treatment”. Making a case for these online platforms to be public utilities ensures that they do not exploit the technological shortcomings of the law, and ensures fairer access for its users. 

In today’s world, where the internet is intertwined with most parts of one’s life, including politics, entertainment, education and work, it is of utmost importance that its online platforms be recognised as a public resource for all, rather than a quid pro quo for surveillance and behavioural manipulation. An essential part of achieving this recognition is to adequately address the harms of the targeted ad system, in an ethical and economically efficient manner.

Samyukta is a student of Economics, Finance and Media Studies at Ashoka University. In her free time, she enjoys discovering interesting long-form reads and exploring new board games.

We publish all articles under a Creative Commons Attribution-Noderivatives license. This means any news organisation, blog, website, newspaper or newsletter can republish our pieces for free, provided they attribute the original source (OpenAxis). 

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What do stock market fluctuations in 2020 tell us about human behaviour?

By Srijita Ghosh

If I ask you what’s common between choosing the wrong major and not being able to lose the last 5 kgs that you thought you’d lose by summer, most of you would think there isn’t one. But if I ask you the same question for the stock market behaviour during the dot com bubble (most of you were probably not even born by then) and the same stock market behaviour during the recent pandemic, you can probably name a few. However, the common thread amongst all of them is that they are all driven by incorrect beliefs about future events. 

You were so sure that economics was the right major for you, but at the end of the second year, you realize you have gravely underestimated the technical skills required to finish it and now you wish you had chosen something else. It is natural and quite common to have a wrong belief or estimate about a future event since future events are fundamentally uncertain. 

Economists have been aware of incorrect beliefs and their impact on decision making but modelling them formally has started fairly recently. Taking motivation from psychology and neuroscience, economists have started modelling decision-making under the assumption that the agents are cognitively constrained. They can make mistakes while predicting some uncertain events about the future which can have severe consequences on their life and living. 

It’s the same cognitive constraints that drive the seemingly irrational behaviour in the stock market. But the mistakes that people make in the stock market or most economic context are not random. By studying the patterns of mistakes, we can design effective policies to improve welfare. 

In the context of the stock market, recent studies by Bordalo et al (2020) have found that people overreact to good news and overvalue them in the long run. If we overestimate the long-run valuation of stocks, then eventually we will be disappointed since our predicted value will not be materialized. This can lead to perverse behaviour in the market.

For example, during the current pandemic, the stock market remained more optimistic than what would be expected from the condition of the economy per se. It might be driven by the overestimation of the long-run fundamentals of the stock market. The problem, however, is that the pandemic initiates a “regime change”, which means we cannot be sure where the fundamentals of the stocks would lie in the post-pandemic period.

Another cognitive function that severely affects our belief is that of memory. Various puzzles in the stock market can be related to the nature of memory. There are different features of the memory that affect what we believe. The most obvious one would be the temporal nature of memory; we remember things with more clarity that have happened in the recent past than a distant past. This implies that while forming belief we put more weight on the recent phenomenon that is the underlying trend. This can lead to having an overreaction to bad news. 

The other, more complex feature of memory is representativeness, which implies that different cues about the same underlying object can lead to very different beliefs depending on what comes to mind. In a recent study by Wachter and Kahana (2020) has shown that we often associate two events that are temporally related. If one of these events repeats again we remember both the events, as they are contextually related events. This can lead to further distortion in belief and some examples of such behaviour would be under or over-reaction to news, fear being a leading motivator of financial decision-making, and so on. 

However, we should note that this literature is fairly young and researchers all over the world are trying to understand the impact of cognitive functions on beliefs and subsequently on decision-making. So we should proceed with caution when interpreting the results from the early experiments. Just like any other scientific discipline, we can only conclusively make remarks after several studies have reproduced similar results. 

One major problem here is that human behaviour is complex and when combined with the stock market framework the scope of non-standard (from a neoclassical economics perspective) is large. This makes analyzing and predicting behaviour in the stock market particularly difficult. But one way forward would be to understand how humans form beliefs generally and extend that to the stock market scenario. This will also help us become better decision-makers and be more consistent with our own world-view. 

Srijita Ghosh is an Assistant Professor of Economics at Ashoka University and has done her Ph.D at New York University.

Sources:

Expectations of Fundamentals and Stock Market Puzzles by Pedro Bordalo, Nicola Gennaioli, Rafael La Porta, and Andrei Shleifer (2020)

Memory and Representativeness by Bordalo, Pedro, Katherine Coffman, Nicola Gennaioli, Frederik Schwerter, and Andrei Shleifer. 2020

 A Retrieved-Context Theory of Financial Decisions by Jessica A. Wachter and Michael J. Kahana

We publish all articles under a Creative Commons Attribution-Noderivatives license. This means any news organisation, blog, website, newspaper or newsletter can republish our pieces for free, provided they attribute the original source (OpenAxis).