March Madness: Maybe online gambles need some restriction
Oddly, it’s easier to bet on a sports game than a stock in America
There is a rumour going around. That senior economists in India feel that the method of measuring consumption affects the construction of the poverty line. This is the Great Indian Poverty Debate III—that a comparison of the levels of living (and hence derivation of the headcount ratio of poverty, or simply poverty) between India’s two official Household Consumption Expenditure Surveys (HCESs) in 2011-12 and 2022-23 cannot be done. And so one cannot conclude that extreme poverty (based on the purchasing power parity or PPP-linked $1.9 poverty line) in India has been eliminated, as Bhalla-Bhasin have done In the online on 2 March 2024, former acting member and chairman of the National Statistical Commission P.C. Mohanan and retired Indian Economic Service officer K.L. Datta, author of said “Tendulkar’s parameters cannot be applied to the findings of the HCES 2022-23 to arrive at a poverty figure.” Why? “Because the Mixed Reference Period (MRP) methodology of the old HCES, whose findings provided the base for Tendulkar’s poverty cut-offs, was different from the Modified Mixed Reference Period (MMRP) methodology employed during HCES 2022-23”.
Its translation: We cannot arrive at any poverty estimate for 2022-23 comparable to the poverty estimate for 2011-12 because the consumption estimates of the two surveys are not comparable. How valid an objection is that? Never in world-poverty history has anybody asserted that a poverty line (poverty cut-off) is a function of how one measures per capita consumption. A reading of poverty literature in India and abroad for the last 80-plus years would suggest that the Mohanan-Datta view borders on defying logic.
The universally accepted accounting procedure for measuring poverty is to define (even imagine) a cut-off level of per capita expenditure (or income). Those above the cut-off are not-poor; those below are poor. The first poverty line was constructed by a working group of nine experts in the Planning Commission in July 1962. These experts noted that “on the basis of available data on distribution of population according to per capita expenditure, nearly half the Indian population in 1960-61 was below this national minimum level of ₹20 per capita per month,” and the commission called them poor.
In their classic study, Dandekar-Rath defined the poor in terms of an average consumption of 2,250 calories per capita per day, equivalent to ₹15 for rural areas and ₹22.50 for urban areas, both in 1960-61 prices. This became the poverty line for academic studies in India and around the world. At around the same time, in the early 1960s, US president Lyndon Johnson launched a war on poverty in the US. The identification of the poor, for policy purposes, was constructed to be equal to the money equivalent of families of three or more whose food expenditure was more than one-third of their total spending. Using this method, poverty in the US was estimated as 20% in the early 1960s, and then dropped rapidly to 12% by 1968. It has hovered in the low-teens since then.
In the early 1970s, the World Bank entered the poverty arena in a big way. In a paper published in 1979 titled ‘Growth and poverty in developing countries,’ authors Montek Singh Ahluwalia, Nick Carter and Hollis Chenery laid much of the groundwork for the poverty research that followed. Issues pertaining to definition, measurement and forecasts were discussed in detail. The authors explicitly rejected a calorie consumption approach and opted for a monetary poverty line; and lack of consumption-survey data for several developing countries made them reluctantly opt for an income rather than a consumption-derived poverty line. The poverty line chosen under the International Comparison Program (or ICP, later to be named PPP) was $200 per capita per year in 1970 prices. The authors tagged this poverty line to be the income of the 45th percentile of the Indian income distribution for 1975.
The circle was complete. Paraphrasing T.S. Eliot, the profession came back to where it started and knew how to measure poverty for the first time. Again, not an iota of discussion took place on whether the different methods or surveys were comparable. The profession, statisticians, economists and policymakers have not really cared about how the poverty cut-off line is derived, so long as it is known and defined in a recognizable manner. Calculation of the level of poverty, once a poverty line has been agreed upon and consumer expenditure (or income) survey data is available, is no more than a simple accounting exercise. Indeed, until the World Bank prevailed on India’s Planning Commission, the practice in the country was to arrive at a best estimate of survey consumption and then blow up all per-capita consumption by the ratio of mean consumption in national accounts and mean consumption in the survey.
Consider this. The World Bank estimates poverty for over 100 countries across 60 years for the same and different poverty lines. None of these calculations involves the method of measurement or number of questions asked, or the methods of collecting data (one visit or ‘n’ number of visits to a household).
In each country, the method of collection of data on per capita consumption has varied from one survey to another. More items are included and some are dropped. Think of consumer durables like typewriters, gramophones, tape decks, etc. The list is endless.
Note that this is a mix of several methods of measurement, all geared to arrive at a best estimate of consumption. Like the Invisible Hand, the Mohanan-Datta model of estimation is nowhere to be seen. How does one interpret their supposed findings and those who agree with their conclusion that the HCES surveys of 2011-12 and 2022-23 are not comparable? It is political, let’s face it.
Like many Americans, I love March Madness. I still consider the night of 22 March 1990, when my local college team won one of the greatest victories in NCAA basketball tournament history, one of the most exciting moments of my life. Of course, a strong emotional attachment to a particular team isn’t the only reason why people love March Madness: The money they have on the line adds an extra thrill. Part of the annual tradition is the office bracket pool—in the age of remote work, it’s one of the few things that brings colleagues together.
Now, that gambling has taken a dark turn. Since the US Supreme Court’s 2018 decision ending the prohibition on sports gambling in most states, March Madness betting has become easier and more accessible. As a result, more people are betting not against their co-workers, but through online gambling sites. In fact, per capita wagers on the NCAA tournament are expected to be larger than the Super Bowl this year.
Add it all up, and the outcome is clear: Americans have an unhealthy relationship with risk.
My libertarian impulses are too strong to oppose the legalization of sports gambling. But I am not sure it should be quite so easy to do, either. This gambling boom has been made possible by technology—specifically, the apps on our phones. Not to mention the betting parlours in many professional sports arenas. Now even many universities themselves are promoting gambling on their campuses.
The amount of money Americans spend gambling has exploded in recent years. Much of it is sports gambling, as casino revenues have not grown nearly as much. Mobile apps and websites account for a large share of the boom; 30 states now allow sports betting on mobile sites. It is a $320 billion business.
It’s extraordinary that regulators have allowed gambling to become so accessible. For some people, gambling may be harmless fun, but many others are developing a serious problem—and younger people are a fast-growing segment of problem gamblers. There are also concerns that there could be more match-fixing.
This lax regulatory attitude is all the more surprising considering the many rules and laws preventing people from taking healthy and productive risks.
Americans face many barriers to taking risk in their lives. Big decisions such as moving, starting a business and even changing jobs are all hamstrung by a mess of regulations on things like occupational licensing, construction and employerprovided health care. The result of all this? Stagnating wages and an inability for many Americans to get ahead.
And then there are cultural forces, such as a fetishization of safetyism that makes even low-stakes social interactions feel risky. In almost every realm of business and society, Americans are taking less risk, and being encouraged to do so.
Taking healthy risks—like starting a business or moving cities—can create value on both a personal and macroeconomic level. Even investing in the market is productive, because it provides capital to businesses and can pay off handsomely for the investor.
In general, the US has a regulatory structure that deprives Americans of agency and makes it harder for them to take risks that enhance their lives. There is one glaring exception: sports gambling, where the bets are zero-sum and the house usually wins. In a healthy society, it should be easier to invest in the stock market than to bet a fortune on a basketball game.
Odds are that more regulations are coming to sports betting. So far, they mostly relate to advertising, though one idea is to ban gambling apps and allow gambling only in physical locations (it seems to be working in Delaware). But as long as states are enjoying the tax revenue that gambling brings, they probably won’t do anything very dramatic. Another approach might be for both the states and the federal government to engage in more systemic reform and foster more productive risk-taking.
Sports gambling is as old as civilization, and in small doses, it can be enjoyable and improve social cohesion—like that annual office bracket pool. But as with so much else, technology is pushing people to the most extreme outcome. As sports gambling has become too big and too easy, more healthy risk-taking has become too rare and too difficult.
Sports gambling is threatening to ruin one of my sweetest memories and one of my favourite things about March Madness. Now when I watch someone hit a buzzerbeating shot, I feel a little less joyous, because I cannot help thinking about all those people who just lost far more money than they can afford.