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Nineteenth Century Inequality Not As Bad As We Think

Blog Post | Wealth & Poverty

Nineteenth Century Inequality Not As Bad As We Think

A proper interpretation of consumption data shows that the 1800s fostered an egalitarian shift in wealth distribution.

When prices change, how that impacts people depends crucially on which prices increase and what goods and services people are consuming. Across the western world, price inflation–the rate at which prices increase–has been relatively slow for over a decade. Central bankers have consistently undershot their inflation targets despite their careful implentation of complex monetary policy. 

The supposed dearth of inflation might seem like small comfort–or a cruel joke–to the Californian hipster paying $15 for a smoothie bowl, the German renter whose rents are increasing at a stunning rate or the London young professional shoveling out £5 for an unimpressive lunch sandwich. The larger the diversity in consumption patterns, the less appropriate it is to aggregate price changes into a general price index such as CPI or PCE statistics.

One reason for the dissonance between official figures and real-world experience is the weight that statisticians place on various items when constructing a consumer price index (e.g. the Bank of England’s CPI; the ECB’s HICP; the Fed’s PCE). For instance, in the price index used by the European Central Bank, housing costs make up only 17% of the index, whereas the Federal Reserve places a 24% weight on housing expenses. That divergence turns a 25% increase in housing costs–with all other prices and consumption patterns held constant–into a 4.25% overall inflation in the Eurozone but a 6% inflation in the U.S.

While policymakers are aware of those data limitations and we have standardized statistical ways to adjust for quality improvements, these problems can still cause headaches. One illustrative example is the impact of iPhone prices on Sweden’s price index; Martin Enlund, FX strategist at Nordea, estimates that the quality adjustment of iPhones alone reduced the reported price increase by 0.1 percentage points every year for the last 5 years.

That minor detail has some implication for our modern world, considering that the Riksbank’s interest rate decisions have turned on such small margins before. Looking at these differences in consumption bundles and quality adjustments over longer historical periods, they quickly become astronomical. In a famous paper, Nobel Laureate William Nordhaus surveyed “lumens”–a unit for light–emitted by various sources throughout the centuries. Nordhaus estimated the price of light, the essential service its originators provide us with, to have fallen by 99.97% between 1800 and 1992.

Over decades or centuries, even small differences can result in very large adjustments when we evaluate past incomes. For instance, how much better is a computer as a calculating tool than an abacus? Is a keyboard and word processor ten, fifty or a hundred times better than quills, ink, and bulky, slowly decaying paper?

A recent study by Vincent Geloso and Peter Lindert makes a big deal out of consumption bundles. By disaggregating purchases by working classes and upper classes, they make a revolutionary discovery: beginning earlier than we used to believe, the poor’s standards of living improved faster than those of the rich. Contrary to the tired claim that capitalism involves the rich getting richer while the poor get poorer, it seems that during the 19th century the opposite was true.

The authors reach this conclusion by using different consumption bundles for two different income segments. People’s standards of living depend on what they themselves consume, not on what they could buy if they had the rich’s consumption patterns:

 “[T]he contrasts that matter are contrasts in individuals’ abilities to buy what they care to buy, or need to buy, and not the (nominal) inequality in their ability to buy the same common bundle as some other class could buy.”

The components that drove this extraordinary reduction in cost of living, argue Geloso and Lindert, were falling prices of grain-based foods and a rise in the relative price of services that the poorer classes supplied (mostly wage rates for common labor).

The American rise in inequality over the nineteenth century, using both top-1% / bottom-99% and top-10% / bottom-40% metrics, is much less pronounced than previously believed. The authors conclude: 

“[T]he ‘nineteenth-century’ period 1815–1914 brought a clearly egalitarian shift in the price structure for all four countries—England, Canada, the USA, and post-1850 Australia. The net change over these 100 years is unmistakable.”

A century before Paul Ehrlich would predict imminent starvation in the entire world (specifically in what he thought was a remarkably backwards India), the world surplus of grains had enriched the poor–even in the “dark Satanic mills” of Britain. The lower relative price of grains mitigated and partly reversed the economic inequality we tend to associate with the nineteenth century.

The exact bundles used to measure consumption matter greatly for understanding prosperity, today as well as in the past.

CNBC | Food Production

Chipotle Tests Automation for Burrito Bowls and Salads

“The Hyphen robot will make burrito bowls and salads for digital orders only. The technology moves the bowls underneath the digital make line to dispense the correct ingredients. Simultaneously, an employee can assemble digital orders for other items, such as tacos, quesadillas and burritos, on the digital make line. When the robot is done making an order, it sends the bowl or salad back up to the surface so employees can properly package the order.”

From CNBC.

The Human Progress Podcast | Ep. 37

Stephen Barrows: The Economic Madness of Malthusianism

The economist Stephen Barrows joins Chelsea Follett to discuss the intellectual history of population economics, the benefits of population growth, and what we can expect from a future of falling fertility.

Blog Post | Air Transport

The Gift of Flying Home for Christmas

The time price of airfares has fallen 38.1 percent in five years.

Airports will be busy again this Christmas. According to Kayak data, domestic flight searches are up 155 percent compared to 2020, though they are still 43 percent lower than in 2019.

Fortunately, we continue to enjoy the gift of decreasing airfares. The Bureau of Labor Statistics reports that since 2016, airfares have decreased in price from an index value of 270.9 to 203.8, or 24.8 percent.

Since we buy things with money but pay for them with time, we prefer to analyze the cost of airfares using time prices. To calculate the time price, we divide the nominal price by the nominal wage. That will give us the number of hours of work required to earn enough money to buy an airplane ticket.

We can calculate the time prices using data from the Bureau of Labor Statistics. They report that the nominal blue-collar hourly wage increased by 21.5 percent from $21.72 in 2016 to $26.40 in 2021.

It took 12.47 hours to earn enough money to buy the average airplane ticket in 2016. Today, it takes just 7.72 hours. That’s a decline of 38.1 percent.

For the same amount of time working, you can get 61.6 percent more airfares today than in 2016. Flying abundance has been growing at a compound annual rate of around 10.7 percent a year. At this rate, we get twice as many flights every 7.22 years.

Excerpt from our forthcoming book, Superabundance.

Blog Post | Scientific Research

The Fastest Learning Curve in History?

Human genome sequencing has become over a million times more abundant since 2003. In the near future, the price may drop another 90 percent from $1,000 to $100.

The Human Genome Project was an international effort to map the entire three-billion-letter human genome. The project launched in 1990 and concluded its work in 2003 – 50 years after James Watson and Francis Crick discovered the double-helix structure of DNA. The U.S. government contributed $3.8 billion toward the project, though the cost of the actual sequencing was lower.

Dr. Eric Green, the director of the National Human Genome Research Institute, recalled that “the first genome cost us about a billion dollars … Now when we sequence a person’s genome, it’s less than $1000, so that’s a million-fold reduction.”

Note that blue-collar worker hourly compensation (wages and benefits) rate increased by 51 percent between 2003 and 2020 (i.e., from $21.54 to $32.54). Consequently, it would have cost that worker 46,425,255 hours of work to earn enough money to buy his or her DNA sequence in 2003, but only 30.73 hours of work to do so in 2020.

The time price of DNA sequencing, in other words, dropped by 99.99993 percent. For the same hours of work required to earn the money to buy one DNA sequence in 2003, a blue-collar worker can get over 1.5 million sequences today. That amounts to over a 150 million percent increase in DNA sequencing abundance.

Now a group of Chinese entrepreneurs at the BGI hope to get the price down to $100 using a robotic arm and a roomful of chemical baths and imaging machines. Rade Drmanac, chief scientific officer of Complete Genomics, a division of BGI, noted that at $100, genetic sequencing could soon be common for every child at birth.

The National Human Genome Research Institute tracks costs associated with DNA sequencing and produced the chart below. Note the logarithmic scale on the vertical (i.e., Y) axis:

Exponential innovation occasionally experiences a double exponent or punctuation as it did in January of 2008 when DNA sequencing transitioned from the Sanger method (i.e., dideoxy chain termination sequencing) to “second generation” or “next-generation” DNA sequencing technologies.

A fall in the cost of DNA sequencing from $1,000,000,000 to $100 over 20 years would imply a compound rate of decline of 6.5 percent a month. (Adjusting for the time price puts the compound rate of decline at 7.13 percent per month.) Moore’s law indicates that prices of computing decline at 2.85 percent a month. So, the cost of DNA sequencing per genome may amount to the fastest price decline in history.

Long live learning curves. The knowledge they create is our true wealth.