The mysteries of innovation and productivity, and why we need to solve them
— by David Fettig
In 1849, as the story goes, the inventor Walter Hunt was pacing the floor, twisting a piece of brass wire in his hands, and worrying about the impact a $15 debt would have on his family’s meager budget. At one point, he looked down at the wire and had an idea.
That inspiration became the safety pin. Hunt sold the patent for the safety pin, along with other wire pins that he dreamed up, for $400 to the draftsman to whom he owed the $15 debt. Hunt’s safety pin became patent number 6,281 and made a lot of money for people not named Walter Hunt.
Hunt also invented the sewing machine, an innovation he did not patent, which allowed others to appropriate the technology and reap the rewards. He also made important progress in the development of repeating weaponry, which permitted other inventors — including a couple named Smith and Wesson — to improve on the technology and to become wealthy doing so.
Hunt’s hundreds of inventions range from bullets and bicycles to shirt collars and boot heels. Even so, Hunt was often in debt. He lacked the business acumen or the interest to take his inventions to market at a time when manufacturing productivity was taking off. What we now call the Industrial Revolution was in full swing during Hunt’s lifetime, a profound shift that gave birth to an increase in per capita productivity that was sustained for well over 100 years. Fueled by innovation and driven by ever-efficient means of production, succeeding generations of U.S. workers became wealthier while doing more with less.
There are many prolific inventors like Walter Hunt in U.S. business history, and many savvy producers and marketers like Smith and Wesson. But what is it about the Walter Hunts of the world that drives them to deliver game-changing products? And how can we explain advances in productivity, especially when some companies are so good at it and others fail? What is the secret sauce of innovation and productivity that will ensure steady economic growth into the future?
These are the kind of broad questions that motivate the research of Ufuk Akcigit, an assistant professor of economics at the University of Chicago, and Chad Syverson, J. Baum Harris professor of economics at the University of Chicago Booth School of Business. Both economists are contributing important work to the field of industrial organization and economic growth, the focus of a research initiative of the Becker Friedman Institute. And as the following discussion reveals, their work on innovation and productivity often complements each other.
From inventor to firm to market
Innovation and productivity are keys to economic growth, and innovation largely drives efficiencies in production, according to Akcigit, who often uses the example of Walter Hunt in his talks. For a policymaker, the trick is to develop policies that encourage innovation and avoid those that hinder it. To that aim, Akcigit says we must first understand where innovation comes from and how it is dispersed. Accordingly, much of his work has revolved around questions relating to firm behavior, individual inventors, and how inventions are marketed and distributed. Akcigit’s work, like Syverson’s, is often “bottom up,” or focused on micro data that gives rise to macro insights.
Firms. At the national and state level, governments transfer money from taxpayers to firms to encourage more research and development (R&D). Why do we do this? Aren’t there enough incentives already to develop new inventions and reap the rewards? The answer is often “yes,” but like many things, it’s complicated, according to Akcigit. R&D is expensive and is often redundant; that is, multiple firms may spend research dollars on the development of similar products, and only one will win. In the aggregate, this could be inefficient.
Also, positive spillovers from new technologies are often realized years, or generations, after a new invention. Inventors cannot know the long-run value of their products and, thus, cannot adequately price (and profit) from their invention; these intertemporal spillovers could mean that we do not invest enough into R&D. In either case, should government get involved?
That’s where Akcigit’s work comes in. Using models built on large databases of individual firm behavior, the resulting analysis can help determine whether, for example, enough R&D is already occurring in a given industry and region. In such cases, there is likely no need to subsidize. Or perhaps the data reveal the opposite result, in which case a subsidy may make sense.
However, these broad answers are just the beginning of the investigation. For example, suppose the research reveals a shortfall in R&D spending. Does that mean every firm should receive the same amount of subsidy? Recent research has revealed that there are basically two types of entrepreneurs: subsistence and transformative. Subsistence entrepreneurs prefer to keep their businesses small and within the family, for example, and they make up the majority of the total.
Only a small fraction is transformative — eager to push boundaries and create the next big thing. Among those transformative firms, research can also suggest whether new firms are preferable to old, or small to large, and whether certain cities or regions provide better opportunities. Such answers are crucial to getting policy right.
Inventors. When it comes to inventors themselves, Akcigit’s research has shed light on a number of important elements, including the relationship between invention and education, income and happiness. One assumption may be that wealthy families reap the most rewards; that is, wealthy children begin with an advantage that gives them a head start on everyone else. However, research reveals that education — not wealth — is the key to success. This finding has important policy implications, Akcigit says, as it suggests that perhaps the most important way to encourage innovation is to subsidize education.
Regarding income, the data reveal that regions with relatively high rates of invention have greater social mobility. As Akcigit describes it: “The child of an assembly line worker can become the next innovator.” There is also a positive correlation between innovation and happiness.
However, both of these results come with one caveat: these innovative regions can also have higher rates of unemployment. Why? Innovation can push out old jobs even as it ushers in better-paying new jobs. One insight for policymakers is that while R&D subsidies may benefit aggregate economies, they may bring real costs to individuals and might suggest the need for income and/or training programs to aid those who are displaced.
One final point about inventors that can impact policy: inventors, like most everyone else, respond to tax rates. More specifically, inventors in the top 5 percent of their field as measured by patent citations are willing to move to other regions and countries where top marginal tax rates are lower.
Marketing innovation. As Walter Hunt teaches us, it’s one thing to invent something; it’s another to bring it to market. And today, the market stream has less to do with independent inventors and more to do with the firms that hire them. One hundred years ago, more than 70 percent of inventions came from the Walter Hunts of the world; today that number is about 1 percent. That means that large firms are hiring most of the inventors and putting them to work with the incentive to innovate as much as possible.
In some respects, invention is the easy part. The difficult stage can be transmitting those ideas to the production side of the firm, Akcigit says. Bad communication within large firms can leave many inventions, known as “sleeping patents,” collecting dust on the shelf. Further, inventions by private inventors are often lost in a secondary market that does not match new ideas with producers. For policymakers, this secondary market (the realm of so-called “patent trolls”) is ripe for review and, perhaps, new policies to help get inventions to market, according to Akcigit.
The mystery of productivity
Syverson’s training in macroeconomics and his background as an engineer have influenced his research agenda over the years. As an economist studying productivity in the IO tradition, he is necessarily focused on firm behavior. However, like Akcigit, he doesn’t stop there. Unlike much work in the IO space that remains focused at the firm level, Syverson pulls together data and experiences from a number of firms to make macro observations.
The main factor that separates successful and failing firms, as well as wealthy and poor countries, is productivity, Syverson says. Understanding what drives productivity (a measure of efficiency determined by dividing output by input) is therefore important. The United States is not wealthier than a struggling developing nation, for example, because it has more buildings or machines or other physical capital; rather, it is because the United States is more productive at using its existing resources, Syverson says. However, as important as productivity is to the health and wealth of firms and countries, there is still much to learn.
The mysteries of productivity begin at the firm level. For example, in any given industry — similar firms making similar products — the difference between the best- and least-performing firms is striking, Syverson says. U.S. firms at the 90th percentile of an industry distribution typically produce twice as much input than firms at the 10th percentile, while employing the same inputs. That bears restating: in every industry, with firms producing the same products with the same inputs, some will obtain twice as much output. This result even holds among firms within the same city. (In other countries the dispersion rate is even higher.)
How can this be? A first guess might be that there are better managers and/or management techniques at certain firms. But if so, then why don’t the poor-producing firms employ those superior management systems? Further, why does this 2–1 ratio persist over time? That is, why don’t the poor producers all go out of business — Darwinian style — such that only the best remain in every industry?
In an MBA class on competitive strategies, Syverson presents an airline industry case whereby larger carriers hoped to emulate the success of Southwest Airlines. Noting Southwest’s success serving smaller cities on shorter routes and with smaller planes, the larger carriers decided that they wanted a piece of that action. So they branded new airlines with catchy names that were smaller versions of the original, and they all failed. The lesson for those airlines, Syverson says, and for other industries trying to copy the success of a competitor, is that you can’t just pick a handful of observable traits and expect to mimic another company’s success.
Economists are putting more time and resources into the study of management. Survey databases have grown upwards to 40,000 companies, all with the intent of determining the ingredients of that elusive secret sauce that will lift companies — and nations’ — productivity rates. What have economists learned, and what are the lessons for policymakers? Syverson isn’t ready to publish his recipe for productivity success. “The more we learn, the more we realize what we don’t know,” he says.
In that respect, research has raised more questions about how consumers discover the best producers, about the impact of credit availability for producers, about the positive spillovers from companies located near each other (known as agglomeration effects) and about the effect of labor quantity and quality. Any one, or all, of these issues can impact even the best-run companies and stymie or stimulate growth. In other words, there are plenty of research questions left to pursue.
New recipe needed soon?
These questions about productivity are more than just academic. Since 2004, U.S. non-farm labor productivity has grown just 1.3 percent per year, according to the Bureau of Labor Statistics, less than half the 2.8 percent rate of 1995–2004. Over time, such persistent declines in productivity mean a big drop in wealth, according to Syverson. That decrease in productivity averages about $3 trillion in lost wealth each year, he says, and over 30 years can mean a one-third reduction in wealth for a generation.
Further, recent research has revealed the important role of young firms in the creation of new jobs, yet the rate of new business creation has been declining for 30 years in the United States. In addition, the rate of churn, or mobility from job to job among employees is also on the decline. Both of these facts are signs of declining dynamism in the U.S. economy. A deeper understanding of those facts could lead to effective policies to turn those numbers around.
So the stakes are high for the questions that Syverson and Akcigit are asking. And these questions are just a sampling of the issues that Akcigit and Syverson are exploring, as their work continues to push the boundaries of IO and economic growth research. Akcigit, for example, and his colleagues, have compiled a massive patent database that will shed new light on today’s Walter Hunts and the influence of their inventions. Syverson is working on explanations for possible mis-measurement of productivity, among other issues. Their contributions will not only improve our understanding of innovation and productivity, but may also reveal some new ingredients for that secret sauce of economic growth.