Economics has been called the “dismal science,” a description inspired in part by the 18th-century English economist Thomas Malthus’ gloomy prediction that population will always grow faster than the food supply, dooming mankind to unending poverty and hardship.

However, other economists, such as Adam Smith, painted a more positive picture for mankind through specialization of tasks at the individual and, later, national level in increasing productivity and staving off “unending” poverty.

The current climate crisis debate has illustrated that not all future events can be predicted by economists and that they often get things wrong. Is this a fair judgment for a social science that has also had its fair share of breakthroughs in explaining government and individual economic behavior?

Public approval is often fickle, and the reputation of economists has been a casualty of the seemingly avoidable global financial crisis, making many question whether economists are of any use.

One of the major criticisms concerns economic forecasts given with confidence, whether stock market levels or the future price of oil.

Economic systems however, like human reactions, are typically dynamic and non-linear, with final outcomes likely to be sensitive to even the smallest changes in the underlying basic assumptions leading to fundamental outcomes to the original forecast.

But it is not only economists who are ridiculed for unrealistic assumptions and modeling that holds everything constant while changing one factor or another to assess which are the more dominant determining factors.

Economists have also been accused of being envious of those in the natural sciences, especially physics and mathematics, and hence the new breed of mathematical economists who are more confident in predicting economic events compared with their multidisciplinary economist colleagues.

Interpretation of multifaceted empirical data is at the heart of economic analysis to develop the broad nature of policy options and their consequences. Some key economic models are used for predicting financial market performance, the most famous being the efficient market hypothesis and capital asset pricing model.

But the 2008 global financial crisis and meltdown in stock market prices seemed to lay bare both models, as they proclaimed stability where there was an impending crisis, and, above all, a market efficiency when there was gross asset mispricing for junk bond leveraged assets.

Policymakers took note of such deficiencies and have adopted so-called “pragmatic” policies, not based on economic theory, but with the central dilemma for policymakers being budgetary austerity or fiscal stimulus, an echo of the left vs. right political debate of the 1930s and the more recent government stimulus packages in the COVID-19 pandemic era.

But despite such missteps, economists are not easily giving up as they strive for a comprehensive and universal description of the true state of the economic world, and firmly believe that this will be achieved through consistency and rigor from a deductive approach which draws conclusions from a group of axioms and seem to be applied in computer games, giving it the mark of science.

However, many economists still base their decisions on inductive reasoning by finding patterns in data, such as whether the current or next recession is V-shaped, L-shaped or double dipped W-shaped? Does this also make economic models such as efficient maker hypothesis invalid?

The hypothesis is not a universal truth, and information of bonds, markets, and companies is reflected in their prices, but not necessarily accurately or completely, and efficiency of data becomes important.

Efficient marker hypothesis also assumes that most profit opportunities in business or in stocks have been taken, but in reality it is the search for new profit opportunities that have not been taken that drives most capitalist business forward, as also noted by the Austrian economist Joseph Schumpeter’s famous thesis on the workings of destructive capitalism and the reinventing of product and process innovation by which new units replace  outdated ones, and in essence there is no market equilibrium.

Today’s constant adaptation to new AI technology testifies to this state of affairs. But while economists look to the sciences for guidance, other scientists also look to economists to solve some pressing environment-related issues.

Researchers at the University of Queensland in Australia used modern portfolio theory, a mathematical framework developed by the Nobel prize-winning economist Harry Markowitz in the 1950s, to help risk-averse investors maximize returns, and to identify the 50 reefs or coral sanctuaries around the world that are most likely to survive the climate crisis and be able to repopulate other reefs.

Modern portfolio theory is a framework that aims to reduce risk while maximizing returns for investors. It is now treating conservation as a type of investment opportunity.

The Australian team then used the theory to quantify threats and identify the reefs offering the best options for conservation, while allowing for the uncertainty over future risks from climate change.

In conclusion, perhaps economics is not a dismal science after all? Pragmatic thinking, a dose of realism, and employing many tools may be the only way of understanding economic phenomena and economists’ way of thinking.

  • Dr. Mohamed Ramady is a former senior banker and professor of finance and economics at King Fahd University of Petroleum and Minerals in Dhahran.