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Poster by Rajan Mithra@VCBay

In 1937, Simon Kuznets, an economist at the National Bureau of Economic Research, presented the original formulation of GDP in his report to the U.S. Congress titled “National Income, 1929-35”, and the rest is history. Until the birth of the GDP, there was no real way to measure the economy with a single number that was comparable over time and across nations. GDP has become the defining indicator of the last century and the ultimate measure of an economy’s welfare. But the pandemic combined with the climate crisis and rising levels of inequality has cast a shadow on the usefulness of the measure. So why has GDP lost its relevance? Which measures can replace it? 

Artefact of the Manufacturing Age

 We are in the beginning of a mass extinction, and all you can talk about is money and fairy tales of eternal economic growth. How dare you!

-Climate activist Greta Thunberg at the UN Climate Action Summit in New York in September 2019

Born during the Great Depression and the manufacturing age, GDP’s relevance in the modern era has been waning as the economy continues to become more service orientated.

David Pilling, the author of the Growth Delusion, argues that we wrongly measure the progress of nations by a number that tries to count the production of goods and services in a given period but does not account for sustainability, technological progress, living standards and complicated services. 

Pilling, who’s been with the Financial Times as a journalist for more than 20 years, has covered countries across Africa, Latin America, and Asia. In his experience, he has come to realise that GDP could be a faulty representation of national progress

The veteran journalist goes on to say that we have placed GDP on a pedestal and are ready to sacrifice almost everything for it- from our leisure time to our oceans to our entire planet

Fudging

In March 2019, a research paper titled A forensic examination of China’s national accounts by economists at the Chinese University of Hong Kong and the University of Chicago arrived at a sensational conclusion- You can’t trust China’s official GDP statistics

According to their research, between 2008 and 2016, China’s official GDP statistics were inflated by an average of 1.7 percentage points per year. If those estimates are true, it will imply that the Chinese economy is more than 10% smaller than currently reported by the government.

The country’s national GDP statistics are mainly based on data collected by local statistical agencies, and the promotions of officials at these agencies are partly dependent on how well provinces perform on these metrics. So the officials are under pressure to make their province’s statistics look good.

While the Chinese government has admitted that these incentives sometimes lead to overblown local GDP numbers and has tried to account for this, it stopped doing a good job around 2008 when the economy started slowing down.  

In order to arrive at the estimates, the economists had to rely on publicly available numbers that are harder to fudge. So they examined the growth in revenue from taxes. Given that tax fraud and evasion are difficult in China, and since that difficulty has not changed much over time, tax revenues for a given sector are expected to grow similarly to that sector’s GDP growth. This was true up until 2008 but hasn’t been ever since. So the economists based their calculations on this logic and adjusted GDP to be more in line with this tax growth. They also revealed that the provinces of Inner Mongolia and Liaoning had overestimated their GDP the most, 20% and 17%, respectively.

All the Light that We Cannot See

Can you estimate the GDP growth rate based on the brightness of a country’s nighttime lights? The answer is surprisingly yes. 

According to the Centre for Economic Policy Research, the brightness of a country’s nighttime lights, as seen from satellites, is highly correlated with GDP growth. It’s based on the logic that the more money people have, the more likely they are to have lights on at night. Businesses will also stay open for longer periods of time, resulting in even more light.

In a democratic society, citizens, media and opposition leaders serve as roadblocks to the government’s attempts of inflating GDP figures, but the same does not apply to autocratic societies.  

The University of Chicago political scientist Luis Martinez proposed that if autocratic regimes are fudging GDP figures, then the reported growth in those countries should be higher than nighttime light data would suggest. And Martinez was right. In a recently released working paper, he found that in countries with similar growth in nighttime brightness, the more autocratic regimes reported higher GDP growth.

Martinez did examine whether this phenomenon could be due to other reasons such as differences in satellite data across regions, or maybe autocratic societies grow in a way that doesn’t generate as much light after dark. He looked at these possibilities and more but concluded that the type of governance is the only explanation. Martinez estimates that, on average, autocratic governments inflate their GDP growth by 15-30%.

Digital Goods

In 2018, Barclays, one of the world’s largest banks, joined the “let’s downplay GDP” bandwagon

Digital goods are significantly different when compared to physical goods. In general, we set the price of a good at the marginal cost to produce it. While digital goods have a fixed cost at the start, they have close to zero marginal costs. Unlike physical goods, their digital counterparts don’t suffer from scarcity issues and are cheap or free to transport across large distances. So it’s difficult to price digital goods, which results in an underestimation of GDP

While the potential underestimation is hard to calculate, Barclays predicts that the gap will keep getting bigger as the digital economy expands.

To Replace or Not to Replace GDP

Many alternatives and improvements to GDP have been proposed over the years. Examples include median income, which is meant to ignore averages as they are massively skewed by extremes, accounting for externalities such as CO2 emissions, and a measure of happiness. Other prominent alternatives/ improvements to GDP include: 

GDP-B: Despite digital goods such as Wikipedia having zero cost, we derive a lot of value from them. So MIT economists developed a new tool to measure the benefits of the digital economyGDP-B, where B stands for benefits

The economists posed a simple question to the survey participants- “how much should we pay you to give up a particular good?” They surveyed hundreds of thousands of people and compared their valuations for goods like Facebook, Twitter, breakfast cereal, jet travel etc., and the results were fascinating. The median person wanted US$ 48 to give up Facebook for one month, a significant value for something that’s essentially free. When these valuations are added up, they range in the billions, and the conventional measure of GDP fails to measure it. GDP-B does not aim to replace the conventional measure of GDP but can instead complement it. 

Healthy Life Expectancy: Healthy life expectancy (HLE) is a promising metric that is easily understood, already in use, and addresses a lot of factors that GDP leaves out. 

Technically richer countries should have higher life expectancies, right? No.

The U.S., with a GDP per capita of US$ 60,000, one of the highest in the world, has a life expectancy of just 78.5 years, while countries with far lesser GDP per capita have higher life expectancies. Portugal’s GDP per capita is 65% less than the U.S. but has a life expectancy of 81.1 years, and South Korea, with 50% less GDP per capita, has a life expectancy of 82.6 years.

One of the factors that HLE addresses is the environmental condition- poor environmental conditions are detrimental to long, healthy lives. HLE also factors in happiness as there is plenty of evidence to suggest that individuals who are happy and fulfilled also tend to live longer and remain healthy for longer. In general, healthy populations support stronger GDP. 

Will targeting the HLE bring about meaningful results?

Yes. Our genetics account for only one-fourth of the factors contributing to how we age. The policies and the environment we live in influence how we age and how long we live. Targeting the HLE could also help address one of the biggest challenges we will face, societal ageing. If healthy longevity is ensured, people could lead longer, more productive lives, thereby reducing the burden on health and pension systems

High-Frequency Data: As the pandemic induced lockdowns became the norm, economic field surveys had to be suspended, making it harder to gauge the effect of COVID-19. But economists soon found a solution, high-frequency data. Even Fed chair Jerome Powell said that they were monitoring quite a lot of high-frequency data. So what is high-frequency data?

High-frequency data can be defined as any kind of data that is available at more frequent intervals than a month. Especially in a time of crisis, data needs to be available more quickly as the economy changes rapidly.  Examples of high-frequency data from the public sector include daily airline travel data and weekly reports on unemployment insurance claims. The private sector was also instrumental in providing high-frequency data; examples include dining traffic data from the restaurant reservation company OpenTable, measures of consumer spending based on credit and debit card transactions, and mobility and foot traffic from the geospatial data company Safegraph. 

The variety of sources and the frequency allowed economists to measure in real-time how the economy is reacting to changes such as a spike in coronavirus cases and stimulus funds. 

You can’t manage what you don’t measure!

GDP has to undoubtedly be replaced or at the very least improved. As the popular saying suggests, you can’t manage what you don’t measure. So if we want to manage the pandemic, climate change, and inequality, we need a measure that addresses these challenges. Dissatisfaction with the conventional GDP isn’t enough; a large reputed transnational body has to agree to an alternative framework. The ideal successor will be easily implementable, compelling, and portray an accurate picture of the economy. While finding and implementing an alternative is a herculean task, it is not impossible. So the question that remains is whether we want to find an alternative. 


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