The science lurking in the Arts Building

Though economics firmly has its realm in the Arts Building, do its empirical methodology and lofty ambitions qualify it as a science?

Economics has an unfortunate, and somewhat deserved reputation: many consider the discipline to be little more than pseudo-science, or ‘astrology for men’, and it often lacks the steadfast commitment to empirical evidence found in the natural sciences. Yet the questions asked by economists (How should we end poverty? How should the government allocate its spending? How can we ensure that everyone has a home?) are essential to creating a better society. Fortunately, economics is changing. Over the last two decades, economists have combined insights from psychology and methodology from the natural sciences to produce reliable answers to the most pressing questions of our time.

Let’s start with measurement, the cornerstone of evidence-based science. The nominal goal of most economic theories is to maximise well-being. Currently, the most widely used metric is Gross Domestic Product (GDP), calculated by adding up all the income earned by producing goods and services in the economy. However, GDP has become something of a surrogate for proper measures of well-being and progress. Even worse, it sets the incentives faced by politicians – governments must keep GDP in the green at all costs, lest the opposition accuses them of presiding over a stagnant economy, or even worse, causing a recession.

As a measure of pure economic activity, GDP is invaluable. As a measure of well-being, however, it is woefully incomplete. If I have no option but to work six days a week, 12 hours a day, GDP will increase, but my happiness will surely decrease. If I pick up a new hobby and decide to work fewer hours, the opposite happens. As Teddy Kennedy famously noted in 1968, ‘GDP measures everything except that which makes life worthwhile.” If economists and politicians continue to depend on GDP alone, they will continue to miss the mark when they set public policy.

Economists have tried to solve this issue by quantifying happiness. In 2004, a team of economists and psychologists devised an ingenious technique called the ‘Day Reconstruction Method’. A large population is assembled and are called to regular meetings where they are asked to relive the previous day in detail. They record what they did, who they were with and for how long each episode lasted. The DRM relies on an insight from psychology: when people are asked to relive an experience in vivid detail, they also relive the emotions they felt during the experience. They even exhibit the same physiological states (e.g. an increased heart-rate or pupil dilation) as they displayed during the event.

The data is then analysed and computed into a ‘U-index’. This is the percentage of time, on average, people spend in an unpleasant state throughout their day. If the sample size is large enough, the happiness of an entire population can be measured. For example, if the average U-index of a country falls from 30% to 25%, then the total amount of time people spend feeling unpleasant emotions will fall by a sixth. Even a small drop in a large country’s U-value would equate to millions of hours of avoided suffering.

The U-index allows economists to identify which activities or conditions contribute the most to total unhappiness, thus making the allocation of resources to improve well-being more efficient. For example, researchers have found that the distribution of suffering in society is unequal: most people are reasonably happy, while a minority of people experience great emotional pain, bringing up the average. This might suggest that investment in mental health services would be the most cost-efficient way for governments to bring down their national U-value.

One of the most common and unpleasant activities (at least before Covid-19) was commuting, with a U-index of 29% in some studies. That indicates that increased investment in transport infrastructure would make a real difference to people’s happiness. On a different note, the U-index of sex is 5%, suggesting that the JCR in Trinity Halls is doing society a service by distributing free condoms.

The use of evidence and controlled experiments in economics has also improved in recent years. Since the late 90s, some economists have attempted to move the discipline away from abstract theorising, and towards reliable, evidence-based conclusions with fascinating implications for public policy.

Economics is often invoked in arguments against the minimum wage; classical theory states that when regulation forces the wage up, firms will hire less as labour becomes more expensive. Fewer workers are hired, and unemployment rises, hurting the people the law was supposed to help. Yet when economists David Card and Alan Krueger tested this theory, they found that the opposite happened. In 1992, New Jersey increased its minimum wage from $4.25 to $5.05, while neighbouring Pennsylvania kept its constant at $4.25. The economists collected data on employment in fast-food restaurants in both states. In New Jersey, employment did not fall relative to Pennsylvania – instead, it increased.

While the betterment of society is often a by-product of research in the natural sciences, it is at the heart of why we do economics.

This evidence flew in the face of decades of armchair economics, the kind of baseless theorising which was used to justify the policies of deregulation implemented by Reagan and Thatcher in the 80s. However, in light of Kreuger’s findings, most economists nowadays acknowledge that minimum wages are often desirable. This is especially true under conditions of ‘monopsony’ where firms are able to force wages lower than they would be under fair market conditions.

If those classical models had been tested empirically, would neoliberal economics have become so influential? Unfortunately, these developments have yet to make their way into popular political discourse; especially in America where there exists a deep-rooted opposition among many republicans to any increase in the minimum wage.

Experimental economics has found a place in development economics too. In rural western Kenya, a group of development economists wished to compare the effects on educational outcomes of greater access to textbooks, and free school meals. They couldn’t simply collect data on schools that had more textbooks, and analyse the outcomes; for example, greater access to textbooks often indicates that children from wealthier families attend the school. Wealthy families provide their children with other advantages too, meaning it would be impossible to isolate and measure the effect of the textbooks.

Instead, they used a large sample size of schools, and randomly assigned each school to one of two groups. One would receive free textbooks, and the other would receive free school meals. The fact that the groups are randomly generated ensures that on average, the characteristics of the two groups were the same. Surprisingly, they found that neither more textbooks nor free school meals had any significant impact on educational outcomes, suggesting that investment in such programs is a waste of resources. This kind of research allows NGOs and public bodies to set public policy that will make a real difference to the lives of people on the poverty line.

While the betterment of society is often a by-product of research in the natural sciences, it is at the heart of why we do economics. Economics has the potential to use the rigorous empiricism and experimentation of the natural sciences to solve very human issues.