Summary: A new study examines how the United States has shifted its material consumption patterns since 1900, showing a trend of “relative dematerialization” beginning around 1970. While certain commodities have grown in demand, many others have seen absolute declines due to technological advancements and efficiency improvements. Innovation and globalization have allowed the US economy to extract more value from fewer resources, raising questions about the long-term sustainability of this trend in an increasingly digital and energy-intensive world.

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A new study by Iddo K. Wernick from the Rockefeller University’s Program for the Human Environment titled “Is America Dematerializing? Trends and Tradeoffs in Historic Demand for One Hundred Commodities in the United States” offers a remarkable portrait of how much the United States has changed in terms of material consumption since 1900.

The study examines the usage trends of 100 commodities—including iron ore, chickens, gallium, and titanium—and shows that a nation that started the 20th century with a seemingly bottomless appetite for raw materials pivoted dramatically around 1970. This pivot, which paradoxically coincided with the first Earth Day, marked a moment when the American economy began a decades-long march toward what Wernick calls “relative dematerialization.” In essence, “dematerialization” refers to the gradual uncoupling of resource use from economic growth.

In Superabundance: The Story of Population Growth, Innovation, and Human Flourishing on an Infinitely Bountiful Planet, Gale L. Pooley and I document a parallel phenomenon on the global stage, finding that resources become more abundant over time. Our key insight is that time prices—or the time required to earn the money to buy a specific good—have been falling for almost two centuries for almost all commodities. Although Wernick focuses on physical consumption patterns within the United States, his study corroborates a related idea: Increasing efficiencies allow Americans to produce or obtain more output from fewer inputs, which helps to keep price increases in check.

The Rockefeller paper breaks commodities into three groups based on their trends from 1970 to 2020. The first group consists of only eight commodities—including gallium, titanium, and chicken—for which demand grew faster than gross domestic product (GDP), showing that certain products vital to the modern economy (and the dinner table) can still outpace the broader economy. The use of the second group of 51 commodities, such as petroleum and nitrogen fertilizer, grew more slowly than overall GDP but increased in absolute terms. That relative decoupling translates to lower intensity of use: We consume more resources as our economy expands but less per dollar of economic output.

Finally, the use of the third group—41 commodities, including iron ore, cadmium, asbestos, and even water—experienced declines in both absolute consumption and intensity of use. According to Wernick, some of these, like asbestos, fell out of favor due to safety concerns, while others, like iron ore, lost ground because of new manufacturing technologies, such as electric arc furnaces, which made recycling more economical. Once indispensable commodities saw demand shrink, underlining the fact that most resources need not remain economically essential in the long run.

Wernick’s study also acknowledges the role of globalization in shifting the patterns of resource use: Certain energy-intensive or pollution-heavy production processes have migrated offshore, meaning the United States can appear more material-efficient while importing finished goods that embed resource usage from elsewhere. But that shift is neither absolute nor one way: The United States also exports large quantities of agricultural products, effectively shipping out “embodied” water, fertilizer, and cropland. These exchanges do not cancel each other out, but the global supply chain, which allows resources to flow to where they are most valued, benefits everyone.

Critics of this optimistic narrative often point to the “Jevons paradox,” whereby increased efficiency leads to cheaper commodities and triggers higher total consumption. The evolution of the American economy after 1970 certainly raises intriguing questions. Was relative dematerialization achieved at the cost of higher economic growth, which slowed around the first Earth Day? Is dematerialization a product of market-driven efficiencies or a result of government-imposed environmental laws and regulations?

Looking into the future, what will happen to American resource use as the United States becomes an information powerhouse? Although computing is electricity-intensive, it can create massive value with little use of physical commodities. And what if we are on the cusp of using incredibly dense fuels to generate that electricity, as the deals between tech companies and new nuclear companies might indicate?

The march of technological progress, combined with the deregulation and economic growth drives promised by the second Trump administration, may yet provide answers to those questions.

All told, Wernick’s findings confirm that, while the American economy has never ceased to crave materials—including metals, foods, and newly indispensable high-tech elements—it has grown better at extracting more value from less stuff. Our ingenuity is decoupling growth from sheer material input, though whether that trend can be sustained over the long run remains an open question.

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Summary: The Simon–Ehrlich wager famously demonstrated that population growth does not lead to resource scarcity but instead drives innovation and abundance. Since 1900, the production of five metals featured in the bet has risen dramatically. This bolsters Julian Simon’s argument that human ingenuity and technological progress enable us to produce more resources at lower costs, ensuring greater abundance even as populations grow.

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Hannah Richie at OurWorldinData.org recently published an insightful article on the five metals featured in the Simon–Ehrlich wager. In 1990, Paul Ehrlich lost the 10-year bet and had to write a check to Julian Simon for $576.07. Simon had let Ehrlich pick the five metals in 1980 when the bet started. The payment reflected the inflation-adjusted decline of 36 percent in the average price of the five metals over the decade. This was despite an extraordinary global population increase during the 1980s of 850 million people (19 percent)—the largest growth in human history. Yet, even with this surge, resource prices dropped, reinforcing Simon’s argument that human population growth, coupled with ingenuity and the freedom to innovate, drives resource abundance rather than scarcity.

Richie highlights an important trend: The long-term abundance of these metals has increased significantly. Take a look at the staggering growth in their production since the early 1900s:

Between 1900 and 2000, the global population grew by 400 percent, from 1.6 billion to 8 billion. During the same period, the production of the five metals soared: Chromium increased by an astounding 78,082 percent, copper by 4,062 percent, nickel by 26,918 percent, tin by 226 percent, and tungsten by 4,829 percent. On average, production of these metals rose by 22,823 percent.

The relationship between population growth and resource production is captured by the production elasticity of the population. It is the ratio of the percentage change in production divided by the percentage change in population. On average, every 1 percent increase in population corresponded to a 57.06 percent increase in the production of these five metals.

In our book Superabundance, we compared the time prices of these five metals for blue-collar workers from 1900 to 2018 and have since updated the data to 2022.

The charts below detail the growth in abundance for each resource since 1900. Please note that vertical scales differ across the charts. The charts generally show the effects of 9/11, the financial crisis of 2008, and COVID-19 lockdown policies.

This table summarizes our findings.

From 1900 to 2022, the global population increased by 400 percent. Over the same period, the abundance of these five metals increased by an average of 546 percent, demonstrating that abundance has grown 36.5 percent faster than the population.

Some have suggested that Simon was just lucky. This is why looking at a much longer time period reveals underlying trends behind temporary fluctuations.

These data reinforce Simon’s prediction: The more people, the more we produce, and the lower the prices.

Tip of the hat: Max More

This article was published at Gale Winds on 1/14/2025.

The Simon Abundance Index (SAI) quantifies and measures the relationship between resources and population. The SAI converts the relative abundance of 50 basic commodities and the global population into a single value. The index started in 1980 with a base value of 100. In 2023, the SAI stood at 609.4, indicating that resources have become 509.4 percent more abundant over the past 43 years. All 50 commodities were more abundant in 2023 than in 1980.

Figure 1: The Simon Abundance Index: 1980–2023 (1980 = 100)

The SAI is based on the ideas of University of Maryland economist and Cato Institute senior fellow Julian Simon, who pioneered research on and analysis of the relationship between population growth and resource abundance. If resources are finite, Simon’s opponents argued, then an increase in population should lead to higher prices and scarcity. Yet Simon discovered through exhaustive research over many years that the opposite was true. As the global population increased, virtually all resources became more abundant. How is that possible?

Simon recognized that raw materials without the knowledge of how to use them have no economic value. It is knowledge that transforms raw materials into resources, and new knowledge is potentially limitless. Simon also understood that it is only human beings who discover and create knowledge. Therefore, resources can grow infinitely and indefinitely. In fact, human beings are the ultimate resource.

Visualizing the Change

Resource abundance can be measured at both the personal level and the population level. We can use a pizza analogy to understand how that works. Personal-level abundance measures the size of an individual pizza slice. Population-level abundance measures the size of the entire pizza pie. The pizza pie can get larger in two ways: the slices can get larger, or the number of slices can increase. Both can happen at the same time.

Growth in resource abundance can be illustrated by comparing two box charts. Create the first chart, representing the population on the horizontal axis and personal resource abundance on the vertical axis. Draw a yellow square to represent the start year of 1980. Index both population and personal resource abundance to a value of one. Then draw a second chart for the end year of 2023. Use blue to distinguish this second chart. Scale it horizontally for the growth in population and vertically for the growth in personal resource abundance from 1980. Finally, overlay the yellow start-year chart on the blue end-year chart to see the difference in resource abundance between 1980 and 2023.

Figure 2: Visualization of the Relationship between Global Population Growth and Personal Resource Abundance of the 50 Basic Commodities (1980–2023)

Between 1980 and 2023, the average time price of the 50 basic commodities fell by 70.4 percent. For the time required to earn the money to buy one unit of this commodity basket in 1980, you would get 3.38 units in 2023. Consequently, the height of the vertical personal resource abundance axis in the blue box has risen to 3.38. Moreover, during this 43-year period, the world’s population grew by 3.6 billion, from 4.4 billion to over 8 billion, indicating an 80.2 percent increase. As such, the width of the blue box on the horizontal axis has expanded to 1.802. The size of the blue box, therefore, has grown to 3.38 by 1.802, or 6.094 (see the middle box in Figure 2).

As the box on the right shows, personal resource abundance grew by 238 percent; the population grew by 80.2 percent. The yellow start box has a size of 1.0, while the blue end box has a size of 6.094. That represents a 509.4 percent increase in population-level resource abundance. Population-level resource abundance grew at a compound annual rate of 4.3 percent over this 43-year period. Also note that every 1-percentage-point increase in population corresponded to a 6.35-percentage-point increase in population-level resource abundance (509.4 ÷ 80.2 = 6.35).

Individual Commodity Changes: 1980–2023

As noted, the average time price of the 50 basic commodities fell by 70.4 percent between 1980 and 2023. As such, the 50 commodities became 238.1 percent more abundant (on average). Lamb grew most abundant (675.1 percent), while the abundance of coal grew the least (30.7 percent).

Figure 3: Individual Commodities, Percentage Change in Time Price and Percentage Change in Abundance: 1980–2023

Individual Commodity Changes: 2022–2023

The SAI increased from a value of 520.1 in 2022 to 609.4 in 2023, indicating a 17.1 percent increase. Over those 12 months, 37 of the 50 commodities in the data set increased in abundance, while 13 decreased in abundance. Abundance ranged from a 220.8 percent increase for natural gas in Europe to a 38.9 percent decrease for oranges.

Figure 4: Individual Commodities, Percentage Change in Abundance: 2022–2023

Conclusion

After a sharp downturn between 2021 and 2022, which was caused by the COVID-19 pandemic, government lockdowns and accompanying monetary expansion, and the Russian invasion of Ukraine, the SAI is making a strong recovery. As noted, since 1980 resource abundance has been increasing at a much faster rate than population. We call that relationship superabundance. We explore this topic in our book Superabundance: The Story of Population Growth, Innovation, and Human Flourishing on an Infinitely Bountiful Planet.

Appendix A: Alternative Figure 1 with a Regression Line, Equation, R-Square, and Population

Appendix B: The Basic 50 Commodities Analysis: 1980–2023

Appendix C: Why Time Is Better Than Money for Measuring Resource Abundance

To better understand changes in our standard of living, we must move from thinking in quantities to thinking in prices. While the quantities of a resource are important, economists think in prices. This is because prices contain more information than quantities. Prices indicate if a product is becoming more or less abundant.

But prices can be distorted by inflation. Economists attempt to adjust for inflation by converting a current or nominal price into a real or constant price. This process can be subjective and contentious, however. To overcome such problems, we use time prices. What is most important to consider is how much time it takes to earn the money to buy a product. A time price is simply the nominal money price divided by the nominal hourly income. Money prices are expressed in dollars and cents, while time prices are expressed in hours and minutes. There are six reasons time is a better way than money to measure prices.

First, time prices contain more information than money prices do. Since innovation lowers prices and increases wages, time prices more fully capture the benefits of valuable new knowledge and the growth in human capital. To just look at prices without also looking at wages tells only half the story. Time prices make it easier to see the whole picture.

Second, time prices transcend the complications associated with converting nominal prices to real prices. Time prices avoid subjective and disputed adjustments such as the Consumer Price Index (CPI), the GDP Deflator or Implicit Price Deflator (IPD), the Personal Consumption Expenditures price index (PCE), and the Purchasing Power Parity (PPP). Time prices use the nominal price and the nominal hourly income at each point in time, so inflation adjustments are not necessary.

Third, time prices can be calculated on any product with any currency at any time and in any place. This means you can compare the time price of bread in France in 1850 to the time price of bread in New York in 2023. Analysts are also free to select from a variety of hourly income rates to use as the denominator when calculating time prices.

Fourth, time is an objective and universal constant. As the American economist George Gilder has noted, the International System of Units (SI) has established seven key metrics, of which six are bounded in one way or another by the passage of time. As the only irreversible element in the universe, with directionality imparted by thermodynamic entropy, time is the ultimate frame of reference for almost all measured values.

Fifth, time cannot be inflated or counterfeited. It is both fixed and continuous.

Sixth, we have perfect equality of time with exactly 24 hours in a day. As such, we should be comparing time inequality, not income inequality. When we measure differences in time inequality instead of income inequality, we get an even more positive view of the global standards of living.

These six reasons make using time prices superior to using money prices for measuring resource abundance. Time prices are elegant, intuitive, and simple. They are the true prices we pay for the things we buy.

The World Bank and the International Monetary Fund (IMF) track and report nominal prices on a wide variety of basic commodities. Analysts can use any hourly wage rate series as the denominator to calculate the time price. For the SAI, we created a proxy for global hourly income by using data from the World Bank and the Conference Board to calculate nominal GDP per hour worked.

With this data, we calculated the time prices for all 50 of the basic commodities for each year and then compared the change in time prices over time. If time prices are decreasing, personal resource abundance is increasing. For example, if a resource’s time price decreases by 50 percent, then for the same amount of time you get twice as much, or 100 percent more. The abundance of that resource has doubled. Or, to use the pizza analogy, an individual slice is twice as large. If the population increases by 25 percent over the same period, there will be 25 percent more slices. The pizza pie will thus be 150 percent larger [(2.0 x 1.25) – 1].