Article Review - Economic Metrics
In his 2018 book, The Growth Delusion: Wealth, Poverty and the Well-Being of Nations, David Pilling brings up provocative questions.
- What exactly is ‘growth’?
- What is Gross Domestic Product (GDP)?
- How do we create metrics that provide insight?
- Can a metric exist when there is no data collection standard?
In a world awash in data, metrics and computational methods, we still struggle to make good decisions for even simple problems. Pilling investigates the economic metrics society has built to quantify the world around us, and questions whether our long-held beliefs are leading us astray. The metrics we build and follow must support and uphold our shared values - if they do not, then we must create new guidelines.
Daniel Breslau wrote an article that researched the foundations of economics - Economics Invents the Economy: Mathematics, Statistics, and Models in the Work of Irving Fisher and Wesley Mitchell1, published in 2003 in the journal Theory and Society. The abstract references Irving Fisher and Wesley Mitchell’s crucial work developing statistical tools to add quantitative rigor to economics in the early twentieth century. Both Irving Fisher and Wesley Mitchell are well-known in the economics world, and it looked like it would compliment Pilling’s work. However, to say that I was disappointed with this paper would be an understatement.
The paper is filled with both commonsense filler and incomprehensible abstractions – for example, he references a quote by Marion Fourcade-Gourinchas: ‘social science cannot but be impacted by broad social change, even though it follows a variety of trajectories and timings for which social change itself cannot account’, touching off several paragraphs discussing why it’s important that social science should study society even though society changes. That’s the equivalent of saying that physicists should study physics, even though physics is dynamic. Is there a subject that is not? When you are building a novel invention or trying to discover something new, there are going to be unforeseen changes in our assumptions. Another example of academic meandering in this paper is ‘We can find sufficiently compelling reasons for economists and scientists in general, to engage in struggles to establish specific objects and facts’2. There is a difference between writing on a challenging subject that might be difficult for the reader to follow versus adding sentence after sentence of meaningless, incomprehensible jargon.
Where I took the most exception with the paper is the assessment that economics was simply suffering from ‘physics envy’, so Fisher and Mitchell stole physics equations and applied them to economics. I reject this argument – physics provides a mathematical exactitude to the physical world, based on observation. It’s a testing ground for improving quantitative analysis, just as medicine is an excellent way to observe how biological systems react to stimulus and archival research can uncover insights into cultures long past. Perhaps sometimes interdisciplinary applications are a stretch, such as using physical law to try to model the irrational behavior of financial markets. Disciplines are always looking towards others to find new insights or methods. Quantum physics contains highly complex and dense equations, but the field developed through letters and papers sent back and forth between pre-eminent physicists – Einstein, Heisenberg, Schrodinger, Born, Jordan and others constantly battled out their ideas in correspondence and in meetings in cafes, providing different perspectives on shared problems. The equations largely followed the theories and thought experiments. Breslau’s explanation that Fisher and Mitchell just tried to fit some equations from physics to create economics ignores the sophisticated observation and analysis of the business cycle that Mitchell devoted his life to. Sure, there were missteps, such as Fisher’s assurance that the stock market would continue to flourish right before Black Friday, but that is the nature of development.
Finally, there is a significant section of the paper devoted to class struggle. Mitchell and Irving ‘Possess[ed] a specialized scientific cultural capital, but lacking upper class background, contacts and dispositions that characterized the founders of academic economics, Fisher and Mitchell elaborated new definitions of their discipline’s object of study, and a new type of economic expertise’.3 The segments of the paper devoted to class study are difficult to follow (along with the rest of the paper), but at certain points Breslau tries to differentiate Mitchell and Irving by their lower to middle-class background, as if the story of a ‘commoner’ making an impact is somehow unique. Statistically, most people are either lower or middle class - there is nothing unique there. Other sentences, such as ‘Involving agents with different quantities and types of cultural capital, the struggle concerned the relative valuation of these different types.’ Can the author point to the development of a new field of study where all the ‘agents’ maintain the same amount of ‘cultural capital’?
Overall, Breslau gets in his own way. What could have been a fascinating look at how two pre-eminent economists built a new field of study and applied quantitative rigor to a social enterprise turned into a 35-page slog of incomprehensible filler material wrapped in academic jargon.
By contrast, Pilling’s book uses real world examples to elicit thoughtful discussion. The prime motivation of the book is a trip that Pilling took to Japan. Japan’s growth metrics throughout the 1990s and 2000s show an empire in decline, a ‘lost decade’, in an ‘economic death cycle’. Yet the author saw a vibrant country, filled with engaged students studying hard, thriving businesses, packed restaurants and researchers unlocking loads of technological development. There was life and energy in the country that directly contradicted the metrics. By contrast, Angola was growing at 11.1% throughout the same time (in some years, GDP growth was over 100%) – yet it was largely based on oil and mineral exports, with extreme concentration of wealth, corruption, inflation that led to famine and extreme poverty in 3/4 of the country, and a complete collapse of the economy 15 years later. In a direct comparison, economic metrics show Angola skyrocketing while Japan was dying, yet reality told a different story. Pilling makes his point that economics as a field of study has to be careful that it doesn’t build meaningless metrics (he doesn’t go as far as Breslau’s ‘economics is a theoretical construct’). He acknowledges that measuring growth and development is essential, but brings up compelling counter-points. According to the metric of GDP, millions of Los Angelans sitting in traffic is actually a boon for GDP, as this is pure profit for oil companies. An arsonist that burns down a city-block contributes to GDP when construction companies end up having to rebuild. GDP is not perfect, and some of the other metrics designed to measure sustainable growth have their own downsides (Green GDP), but society must start working to measure the world in a way that directs sustainable and fulfilling growth.