Inequity in the face of death

Wealth and health go hand in hand. The phenomenon that health differences are systematically related to income is known as the income health gradient. Although it may strike many as fundamentally unfair, wealthy people live significantly longer than those less affluent.

This is not something recent. During the second half of the eighteenth century the British aristocracy lived more than ten years longer than the rest of the British population. Even the most infamous naval disaster in history provides a sad example: aboard the Titanic, those traveling in first and second class were much more likely to survive than those in third class.

Tom Van Ourti speaks with passion when he explains what distinguishes the research project he and his colleagues conducted from others in the field. “We emphasize that researchers and policymakers aiming at reducing health inequalities should be aware that this involves making normative choices. Our aim was not to show how life expectancy varies according to income, but to show how the underlying factors of health differences, such as smoking, diet and exercise, cause this phenomenon. We want to encourage researchers and policymakers to take a conscious decision with regard to the factors they choose to address when tackling unfairness in health. These factors might not only include income.”

In order to do this, the team adopted the ‘equality of opportunity approach’. The idea is that people can be held responsible for part, but not all, of their health disadvantage. Social concern is then restricted to inequalities that are not the responsibility of the individual. Van Ourti and his colleagues also analyzed why people make certain lifestyle choices. “If someone has a health defect which is genetic, most of us would argue that this person is not to blame for the resulting medical problems. On the other hand, there seems to be a consensus that chain smokers should be held responsible. However, we may come to a different conclusion if we know that the chain smoker was born in a poor family where everybody smoked, as opposed to a rich family where smoking was less common.”

The team had access to a very extensive database from the Dutch office for national statistics (CBS). This made it possible to link tax records to medical data such as mortality records, hospital admissions and the Body Mass Index (which was used as a proxy for diet).

Van Ourti, Bago d’Uva and Garcia-Gomez have been researching various aspects of the relationship between health and income inequality for many years. In most studies, the effects of age and gender are filtered out in a process called standardization. This lowers the extent of health and longevity differences between people that are considered unfair. Standardization is often considered necessary to facilitate comparisons. It puts the spotlight on other factors driving differences in health. However, this implies normative thinking. In particular, it neglects all health differences due to age and gender. Policymakers would do well to take a step back and ask themselves if society really considers biological health differences fair, even when they are unavoidable.

The paper provided a framework that makes it possible to use different normative approaches in a transparent way. In Belgium, the framework is already being used in the health insurance sector. The research project has also led to discussions on the opinion pages of several academic journals. How to compensate for the inequity is up to the policymakers. Van Ourti: “Our goal is to facilitate conscious decision making so that researchers and policymakers are not accidentally misleading or misled.”

Note: This article includes some of the contents of Prof. Van Ourti’s inaugural speech.

The added value of a robot tax

The robot who takes your job should pay taxes, Bill Gates argued recently, sparking a discussion among economists and non-economists alike. Gates is worried that as more jobs are being taken over by technology, tax revenue is going to fall, making it harder to fund public goods such as education and healthcare. He suggests to tax the use of robots to raise additional revenue and to slow down technological disruption in the labor market.

Bill gates is not the only one who is worried about workers being replaced by machines. The European Parliament has recently discussed – and rejected – the idea of a robot tax, while the French presidential candidate Benoît Hamon of the Socialist Party has advocated a tax on robots to fund a universal basic income.

The topic is also hotly debated in Silicon Valley, one of the regions where technological disruption takes place on a large scale. ‘Techno-optimists’ hope that technology will eventually make everyone better off, while sceptics are often dismissed as ‘Neo-Luddites’ who want to slow down progress. Indeed, technological disruption of the labor market dates back at least to the times of the original Luddites; a group of English textile workers who destroyed weaving chairs, fearing for their jobs. Eventually, the weaving chair brought about prosperity and made clothing much more affordable to the common man.

Should we thus just embrace technological change or is this time different? Some economists argue that indeed it is. In the past, machines have primarily substituted for muscle power. These days, technology is used to substitute more and more for routine tasks, both manual and cognitive. Even tasks such as driving a car, which were deemed impossible to be performed by a machine just ten years ago, now seem well in reach.

As routine tasks are often associated with middle income jobs, technological change brings about a polarization of the labor market. Employment in middle-income jobs shrinks, while it grows in low-pay service jobs, as well as at the top of the income distribution. As an effect, the distribution of incomes also polarizes, leading to rising inequality. Furthermore, the speed at which technologies change and are adapted is a lot higher than in the past. While it took a generation until the weaving chair was widely used, the adoption of the smartphone took just a few years, with new models appearing every couple of months.

Might this be the time for a tax on robots?

This is one of the questions I study in my own research. To answer it, I use a model of an economy in which robots are a specific form of capital which substitutes for routine work and complements non-routine work. If firms use more robots, workers in routine occupations see their wages fall relative to non-routine occupations. Income inequality increases and the labor market polarizes. A tax on robots can limit the disruptive effects on the labor market and dampen this polarization. It makes it more expensive for firms to replace routine workers by robots.

As a result, there is less polarization of wages and the distribution of gross incomes becomes more equal. Now imagine that the government wants to reduce net income inequality to a certain level and wants to do this by increasing the income tax for higher incomes. Since the robot tax already made incomes more equal, the government needs to redistribute less with the income tax. Taxing income distorts peoples’ decisions to work, which lowers welfare. Having to tax incomes less is thus welfare improving. However, there is a downside: the robot tax distorts firms’ production choices. Without the robot tax, firms would use more robots and less routine workers in order to produce output more efficiently. The robot tax thus leads to a loss in output. At the optimum, the government balances the benefits and costs of the robot tax.

Using simulations in which the government likes equality, I find that if income taxes can also be set optimally, the added value of a robot tax might be small. However, its value increases if governments cannot easily reform income taxation. Still, the practical implementation of a robot tax could be challenging. According to my definition, a computer might also be a robot. I wonder how Bill Gates thinks about that.

Political violence does not scare all multinationals

In the period from 2003-2012 multinationals invested over 12 trillion dollar in new subsidiaries in conflict countries. This is 13% of all greenfield investments flowing to developing countries: nearly 5% even went to countries experiencing a war. Examples of such investments include Coca Cola’s 26 million investment in Afghanistan in 2006, Shell’s investment in oilfields in Iraq in 2008 and Michelin’s investment in a car tire manufacturing plant in Columbia in 2005.

Most economists agree that, on average, political violence deters Foreign Direct Investment (FDI). After all, there is a high probability of losses of human and physical capital, disruptions on the supply chain and a reduction in local demand. Yet, our research, forthcoming in the Journal of International Business Studies, reveals that the relationship between political violence and greenfield FDI is considerably more nuanced.

Our study shows that violent political conflict has indeed a negative effect on the total amount of greenfield FDI inflows. However, contrary to common beliefs, we find no evidence that either terrorism, political terror or assassinations influence investments. The notion that political violence deters investment hence only applies to one specific type of violence. Moreover, the sector in which the multinational is active and the type of company matter. Only firms that are active in the manufacturing or service industry and that are present in only a small number of countries reduced their investments when conflict erupts or intensifies. Firms active in over 26 countries even seem to increase their investments in the case of a political conflict.

Another interesting finding is that multinationals active in the resource sector do not reduce their investments in the face of political conflict. Investments even seem to increase when the regime represses its citizens. A separate analysis for the oil and gas sector shows that multinationals’ willingness to invest subsidiaries in conflict countries can be explained by the high economic rents obtainable by extraction and the limited number of locations where extraction is possible. During periods of low resource prices and increased resource reserves, due to for example the extraction of shale oil and gas, the willingness of multinationals in the oil and gas sector to invest in conflict countries comes close to that of firms active on the manufacturing and service industry. This shows that the insensitivity of firms in the resource sector to political conflict can be largely explained by fundamental economic mechanisms.

This article is based on the publication “Dodging Bullets: The Heterogeneous Effect of Political Violence on Greenfield FDI” by Caroline Witte, Martijn Burger, Elena Ianchovichina and Enrico Pennings in the Journal of International Business.

The lab, the truth and the real world

Does the lab tell the truth about behavior in the real world? That is a question that concerns economists ever since the lab is used as tool to understand human behavior. The first properly designed experiments were conducted by Vernon Smith, who later was rewarded the Nobel Prize for it.

These experiments, using students as subjects, tested behavior in an artificially constructed market game. It turned out that laws of supply and demand held pretty well in the lab, and so the lab proved to be a fruitful area to test economic theories. Critics argued that it is hard to transfer quantitative outcomes of the lab to the real world. After all, the lab is different from the real world in so many dimensions (such as its population: student subjects). Lab enthusiasts replied by pointing out that qualitative predictions should suffice. Why would general laws of behavior differ in the lab and field? Why would the laboratory not tell the truth?

Well, one area in which the laboratory may be off in its predictions is when it comes to measuring pro-social behavior. Consider the Dictator Game. In this game, a subject receives 10 euros and can choose to share anything with an anonymous receiver. Classical economic theory, assuming everyone cares only about him or herself, predicts that no money is given by the dictator. It turns out that about sixty percent of the dictators give something more than zero, and these gifts average roughly 2,50 euros. So, despite all the incentives not to give, subjects (students and non-students alike) do sacrifice some of their earnings for someone else. At first sight, this seems like evidence showing the existence of altruism. However, the “general laws of behavior” may not hold in this case. A fundamental problem in the lab is that the subjects know that their behavior is being watched and recorded by a scientist. Could this explain why gifts in the Dictator Game are so high?

The researcher designs a set of very similar experiments that start in the lab with student subjects, changing one aspect a time, to end in the field with “real people”, unaware of the experimenter. This method is new, so the literature offers only a few of these studies. One study has found that students donate as much money to charity in the lab as they do in a real life setup of a charity event. In another study, subjects in the lab could send a thank-you-letter with cash to a volunteer of a university. They returned these as often as subjects who “accidentally” got a similar letter in their mailbox. On the other hand, baseball card dealers who are invited in a lab show to be trustworthy in a game that measures trust. These same dealers, however, rip off customers who rely on their trustworthiness when buying baseball cards.

It is too early to tell if the lab systematically overestimates pro-social behavior, because different settings need to be tested. In the meantime, however, it seems as if the experimenter demand effect is not always of big concern. But, as more field experiments are conducted, other challenges are exposed. For example, a popular topic in economics and psychology is to compare altruism between the rich and poor. Lab findings indicate that the poor are more altruistic. But, a recent field experiment that “accidentally” sent letters with and without cash to members of both social classes, showed the rich returned more. This is not to say that the rich are thus more altruistic. It turned out that the poor suffered from stress that hindered them to return envelopes. Such effects can only play a role when subjects have to plan a real activity, and this is typically absent in the lab. To conclude, the debate on whether the lab tells the truth about the real world continues…