Autor: Bill Snyder
Three Stanford scholars explore how we measure innovation, how innovation drives productivity, and how productivity affects inequality.
In 1500, China’s economy was the strongest in the world. But by the 19th century, the U.S., Western Europe, and Japan had leapfrogged over China by churning out goods and services in vast quantities while the former superpower stalled.
Why? Some economists argue that China’s lack of free markets and unencumbered innovation in the West led to the shift. But what is the relationship between innovation and markets, productivity, and inequality?
The answer to that puzzle and others were explored during a recent forum on the relationship of innovation to economic growth at the Hoover Institution. Three Stanford professors, all Hoover fellows — Stephen Haber, Edward Lazear, and Amit Seru — spoke on a panel moderated by Jonathan Levin, dean of Stanford Graduate School of Business.
The panelists offered thoughts on how innovation is measured, the role of markets, and what types of firms are likely to innovate. They examined how productivity affects wages, skills, and social inequality, and considered what kind of policies might ensure that the pace of innovation remains brisk.
How Do You Measure Innovation?
Like art, everyone knows innovation when they see it, but defining and measuring it, says Amit Seru, “is a holy grail” for researchers. Studying patents might be key to answering that question.
Seru and his colleagues used big data techniques to analyze 9 million U.S. patents filed over two centuries. Although the Silicon Valley ethos holds that startups are the wellspring of innovation, the researchers found that established firms were also very innovative, as measured by high-quality patenting activity. They also concluded that both private and public firms contributed to innovation and that universities and some government entities were also quite innovative.
The first step in that analysis was to construct a measure of high-quality innovation. The researchers did so by comparing the texts of all the patents in the database and tabulating the occurrence of important words. If there was little overlap between the text of a patent and its predecessors, the patent was likely a novel innovation. If words in subsequent patents were similar, the subject patent was likely an important innovation that other patents had built upon. Patents meeting both criteria, i.e., novel and important, were considered “high quality,” says Seru, a Stanford GSB professor of finance. As a check, the researchers compared their list of high-quality patents to those already deemed significant by economic historians. The two lists were quite similar, they found. Using this measure of high-quality innovation, the researchers examined which entities contributed to breakthrough innovations over time and what patterns were consistently associated with these events.
What is consistent is the notion of creative destruction” and the rational reallocation of resources around such events, Seru says. When firms innovate, profits go up, and labor and financing flow to them and away from their competitors, who suffer from this creative destruction. For this to occur, labor and capital markets need to function efficiently. While creative destruction and associated patterns are not a new notion, what is different today is that innovation might occur across different entities — such as government as well as public or private firms — and inventors working across geographic boundaries. Innovation remains brisk, but if markets in the U.S., which have functioned efficiently for centuries, are hindered, innovation could falter, Seru argues.
What Happened to China?
Like Seru, Stephen Haber and his colleagues used big data to analyze economic growth. To build their geographical representation of economically powerful regions, they geocoded every major city in the world and, using a variety of sources, researched the level of economic activity at 100-year intervals. The study took three years.
During the period when China was economically more advanced than the West, it traded goods like spices, silk, and tea for silver. At the time, the West had little else that the Chinese needed, Haber says. But that changed, and by 1800 the West had pulled ahead. Innovation made the difference — modern chemistry, steam power applied to transportation, and interchangeable parts — but not just innovations in technology. Modern economic growth also came from organizational innovations in the military, transportation, and the legal and financial worlds, Haber says.
One major example: the concept of the patent as a tradable property right.
“Places where people were free to experiment, to simultaneously compete and cooperate through a market where no one was in charge of deciding which technologies would be adopted, which would be rejected, and which would be forbidden, flourished,” Haber says.
Historically, China took the opposite approach: The state wielded the power to reject certain technologies. For example, the development of railroads was drastically slowed by China’s emperor because he feared their spread would undo the agrarian society and threaten his rule, Haber says.
That lesson, he says, should not be lost on today’s leaders. “If there is a threat to prosperity, it comes from people who believe they are doing good by using the power of the state to decide which innovations are just and which are unjust.”
How Are Productivity and Inequality Linked?
There are two ways to achieve economic growth: Add population or make people more productive, says Edward Lazear, a professor of economics at Stanford GSB. Economic growth in the 20th century was tremendous. The standard of living doubled every 33 years, but that made a challenging target for the 21st century. Slower population growth and aging of the current population imply that we will need productivity increases to do more of the work in the future.
Productivity feeds into wage growth, but as productivity has slowed in recent years, so have wages, Lazear says. In the late 1990s, productivity grew by about 3% a year; now it’s only about one-third of that. So it’s no surprise that wages have also been flat. But the pain of flat wages is not shared equally throughout the population.
The productivity — and wages — of highly educated workers has soared over the last 30 years. But the opposite is true for less educated segments of the population.
Making matters worse, the industries that have grown are the ones that employ highly educated workers, while the industries that have shrunk are the ones employing people with less education.
However, artificial intelligence and other technologies are not to blame and will not put everyone out of work, Lazear says. As measured by participation in the labor force, jobs as a whole don’t disappear when new technologies change the nature of work. There was never a transformation as radical as the Industrial Revolution, he notes, yet the labor force grew.
“The concern is not that people won’t be working. The concern is that they will work in crummy jobs,” Lazear says. To alleviate the problem, it will be necessary to rethink education and job training. The key, Lazear says, is this: “Lower the skills gap.”