by Raji Jayaraman
In the last two decades the topic of inequality has entered the public discourse across a broad spectrum of issues, with an urgency that is astonishing. To name but a few examples, the Occupy movement has called for more income equality, Black Lives Matter protesters have demand racial equality, women’s advocates have rallied behind causes as varied as equal pay and reproductive rights , and environmental activists have advocated for climate justice.
Surprisingly, economists are not front and centre of this discussion. I say “surprisingly” because economists are supposed to be the experts on inequality: they measure and study it. I think the reason why economists have not played a more central role in this discussion is that the protesters in today’s mass demonstrations are not just pointing out the existence of inequality. They are saying: “inequality is unjust”. With a few notable exceptions, however, today’s empirical economists don’t talk about justice. I fear that if economists don’t incorporate justice into their analysis, they risk losing relevance.
Why don’t applied economists who deal with data and policy design, speak of justice in a meaningful way? I think it boils down to four fundamental axioms that will be familiar to every economist. First, allocations must be efficient. Second, evidence must be data-driven. Third, policies should be forward-looking. Fourth, choices are made “at the margin”. As I explain below, I believe that these are very useful axioms. I also think, however, that they make it very hard for empirical economists who study inequality to effectively participate in the current debate on justice. In what follows, I explain why, using the four examples of protest movements to illustrate the crux of the problem.
To understand how the first axiom gets in the way, it is useful to start with a definition. In economics, an allocation is said to be efficient if there is no other allocation in which some other individual is better off and no individual is worse off. To understand what this means, consider a simple micro 101 example. Suppose I have ten dollars that can be allocated between two people, Asha and Madhavi. One possible allocation is that Asha gets four dollars and Madhavi gets five. This allocation is not Pareto efficient because I’ve left money on the table: I could give Asha one more dollar and make her better off without making Madhavi worse off. You can see from this example why insisting on allocative efficiency is important: society as a whole is better off when we don’t leave money on the table. A five-five allocation, which happens to be equal, is Pareto efficient. I have left no money on the table; from here, I can’t re-allocate this money to make one individual better off without making the other one worse off.
Now consider a different allocation, where Asha gets nine dollars and Madhavi gets one dollar. This nine-one allocation is very unequal, but it is also efficient. In other words there is no obvious efficiency rationale for redistribution, and you can see from this the potential tension between redistribution and efficiency.
What does economists’ focus on allocative efficiency mean for the current debate on inequality? We live in which wealth and income are very unequally distributed: the bottom 55% of the world’s population owns roughly 1% of the its wealth, and the top 1% of the population owns just 45%. This seems patently unjust, but because it’s not necessarily inefficient economists can look at this allocation and fail to share the same outrage as, say, the protesters from the Occupy movement.
Economists’ focus on allocative efficiency can make them blind to injustice, and that’s a serious problem. But what they do is still important to understanding inequality. For one thing, they carefully document its existence. The public probably wouldn’t even know that global wealth was so unequally distributed if economists hadn’t done the painstaking work of gathering the data and crunching the numbers.
In fact, thanks to the second axiom of empirical economics, they do even more than that. They use data-driven evidence to understand what drives inequality and figure out how to address it. To illustrate this, consider a second example: the gender pay gap. In most wealthy countries, women earn substantially less than men do. In the U.S., women earn just over eighty cents on each dollar that men make. This pay gap varies from country to country, but it is always there. Consequently, “equal pay for equal work” has served as a rallying cry for the gender equality movement the world over.
Economists rightly point out that this demand is too simple, because its implicit premise is that the only difference between men and women is their sex. That is simply not true. Men and women differ on all sorts of dimensions including (but not limited to) education, occupation, childbearing, and industry. Once you take these types of differences into consideration, at least in rich countries, you can account for most of the gender pay gap.
Suppose, hypothetically, that there is a twenty-cent pay gap and that gender differences in education account for five cents of these twenty cents; occupation for another four cents; and childbearing for the remaining eleven cents. This is a data-driven exercise, which allows one to understand where the gender pay gap is coming from. It’s useful because once you understand where it is coming from, you can go about remedying opportunity gaps.
If, for example, education is one driver of the gender pay gap then a potential policy intervention may be to motivate girls to study science by exposing them to its wonders at an early age or building their confidence in math. If women are choosing less remunerative occupations, you may want to incentivize them to become (say) programmers by investing in their computer skills or having role models in the tech sector. If there seems to be a “childbearing penalty”, you could help mothers balance work and kids by allowing for remote working or subsidizing child care. Economists study the effectiveness of these policies, and myriad others, aimed at fostering equity and reducing inequality.
In this way, by using data and analysis, economists can, and do, help to address inequities that equal pay protesters want remedied. The nuance and rigour that economists bring to bear are valuable, perhaps even indispensable. But, as you may have noticed from my example, there’s a catch. Because empirical economists use data analytics, they focus on remedying inequality along measurable dimensions, such as education, occupations, or parenthood in my example.
The trouble is that not everything that is valuable is measurable. Going back to the gender pay gap example, what empirical economists are poorly equipped to discuss are things like social expectations regarding what women should or shouldn’t do; perceptions regarding what women are or are not capable of doing; or values and the worth of activities of men and women. These things are all important, but because they are hard to measure, they don’t figure in a lot of data-driven economic analyses.
This means that, although economists have important insights regarding how to address gender inequality, protesters demanding gender equality aren’t necessarily impressed. They are asking for something different, something more: they are railing against institutions, which they believe has built a system that has denied them equality and justice for centuries.
This leads us to the big blind spot in economic analysis, which is that we don’t have a compelling framework for addressing historical injustice. A major reason for this is the third economic axiom: policies must be forward looking. To illustrate why this is problematic, consider a third example. We live in a world with massive inequality across nations: rich countries have per capita GDPs that are anywhere between fifty to one hundred times higher than that of the poorest countries. The latter tend to be concentrated in Sub-Saharan Africa, but there are some exceptions. One is Haiti.
Why is Haiti so poor compared to its neighbours like Cuba, Jamaica or even the Dominican Republic, which you might expect would be similar to Haiti given that they share the same island? Most economists will say, “Haiti is poor because it has weak institutions”. Haiti and the Dominican Republic may be similar in many respects but, they will say, Haiti has weak institutions that are based on extractive development rather than inclusive growth, whereas the Dominican Republic has much stronger institutions. For economists, the wealth of nations is built on strong institutions. In Haiti’s case this would involve greater political stability and a different set of property rights. This is entirely reasonable: current day institutions are undoubtedly important for economic development.
But there’s another part to Haiti’s economic development story that economists don’t dwell on. Following Haiti’s successful 1791 slave revolt, France demanded that Haiti’s emancipated slaves pay their former enslavers 150 million francs. Economists estimate that over the next century and a half, these reparations ended up costing Haiti billions of dollars. During this time, Haiti went from being the richest country to the poorest country in the Americas.
As a human being this seems terribly unjust. You can’t help thinking, “surely we owe it to Haiti to right this wrong”. This view is not broadly shared among economists because, in economics, policy decisions must be forward-looking. Past sins may explain how we ended up where we are today but, from the economist’s perspective, today’s decisions should be based on today’s payoffs and tomorrow’s payoffs; historical injustice doesn’t matter for what we do next. Economists would look pictures of Black Lives Matter demonstrators dumping a statue of the Bristol slave trader Edward Colston into the harbour and say, “Why are you throwing away a perfectly good piece of bronze?”
This willful ignorance of historical injustice limits economists’ ability to make policy recommendations that resonate with public concerns expressed in many of today’s social justice movements. This also follows from the fourth axiom: economics choices are made at the margin. Consider a final example to illustrate this: climate change. Especially in the last couple of years populations in North America, Europe and Australia have witnessed some dramatic consequences of climate change, including wildfires and heatwaves this past summer. As horrific as these events have been, developing countries are really the ones facing the brunt of climate change. Populations in the global south, which are poor to begin with, are experiencing severe droughts, floods, storms, and rises in sea levels, which pose an existential threat to the lives of hundreds of millions.
Action is urgently needed so it is only fitting that world leaders should congregate at climate summits, year after year, to find some way to keep global temperature rises in check. However, each time they meet they seem to hit a brick wall. Why is that?
Consider CO2, which is a major contributor to global warming. If you look at CO2 emissions today, Europe, the US and Asia, including China and India are the regions adding the most CO2 to the atmosphere. “At the margin”, they are the largest contributors to global warming. Therefore, to combat climate change, Europe and the US must do their part to reduce emissions, but so must China and India. This economic insight is spot on: India and China are major contributors to climate change today and, because their economies are growing, they will be the largest contributors to climate change in the future. If they don’t curb their emissions, the planet is doomed.
The trouble is that (although doing nothing is also untenable), curbing emissions is a costly endeavour. Countries like China and India are quick to point out that climate change is a function of the stock of carbon in the atmosphere, and Europe and the US are responsible for most of this stock. Over the last 200 years, their economies grew at rates that were unprecedented in human history. This growth was fed by fossil fuels, the planet has paid the price, and the Global South has borne the brunt. Is it just to ask the poorest countries to pay the cost of this folly?
That’s what Greta Thunberg means when she says, “We can’t call for climate justice while advocating for policies that exclude aspects of equity and historic emissions.” Her camp is calling for justice that considers the long arch of history while the other camp, guided by economic thinking, wants to focus on how to curb incremental contributions to pollution. Yet again, we find ourselves at an impasse.
It would be remiss of me not to mention that the empirical economists have made incredible contributions to the study of inequality. Whether they recognize it or not, the social justice movements sweeping the world today have relied heavily on economic insights. Thomas Piketty’s work has laid the foundation for the global debate on income inequality. The work of Abijit Banerjee and Esther Duflo has lent texture to the lives of the poor and offered thoughtful solutions to the problems people face in countries like Haiti. Claudia Goldin’s work on the gender equity has forced us to understand the intricacies of women and work. Nick Stern’s work was instrumental in bringing climate change into the public conscience. There are hundreds more. That these people are all economists is not an accident. Economics has an indispensable set of empirical tools that are, and must be, used to understand and address inequality. Social justice activists would do well to take advantage of the types of empirical insights, nuance, and pragmatic solutions that economics has to offer.
A fundamental problem, however, is that applied economics lacks a compelling way to think about justice. This is not to say that they don’t think about the question of distributive justice at all. They do. But dominant methods used to think about it are guided by utilitarianism and its descendants. Alternative ethical frameworks or questions of morality, which lie at the heart of justice, rarely figure in our empirical analyses. Unless that changes…Unless applied economists (like me) find a way to incorporate justice into our otherwise remarkable empirical toolkit, we risk losing our relevance in the eyes of a public hungry for justice.