I continue to worry about (and worry) the issue of what the experience of the past generation tells us about the relationship between short-run cyclical economic downturns and long-run enterprise, entrepreneurship, and growth...
From the end of World War II until the beginning of the 1990s, it looked as though the Japanese economy was "converging" to the American economy in living standards and productivity levels--that although Japan started the post-World War II period with a labor force inferior in education, with a lower level of installed technology, and with a capital stock deeply depleted by the fact that Curtis LeMay's bombers had made the rubble of Japan bounce, that eventually Japan's economy would "catch up" to that of the United States.
I have been staring at a very gloomy graph--at the Congressional Budget Office's forecasts of "potential output", of what the economy can produce without starting to "overheat" and putting upward pressure on inflation:
Looking at this graph tells me that:
Noah Smith wrote a post over the weekend where he expresses concerns over what he terms the Entrepreneur Subculture:
Well, in the past few years, I've been reading - and hearing - a lot about the Entrepreneurship Subculture. You all know what this is. It's mostly young people, mostly in urban areas (especially SF and NYC). It's mostly (but not exclusively) made up of entrepreneurs in the fields of technology and media. It includes media outlets like TechCrunch, books like The Lean Startup, "incubators" like YCombinator, forums like Quora, and other outlets like the TED and TEDx talks.
First, I'd like to address this above description Smith offers before I talk about his concerns.
Smith qualifies by using the word "mostly" three times, but this still to me looks like he's talking about the idea that the average entrepreneur is a twenty something, in Silicon Valley, and working on an internet startup.
Even if this is not what Smith intends to convey, this is a common perception. And it is simply not true. As we have covered here before on Growthology, entrepreneurs are not, on average, young, and we've talked about how they are not mostly located in San Francisco and New York City, and do not work only on tech and media (see our Inc. 500 research here). Concerning geography, here is the map of the Inc. 500 firms over time (an interactive version is available at the previous link):
And here is a relevant excerpt with statistics on the industry question (from this paper in the Inc. series):
At the nationwide level, only a quarter of Inc. firms are in conventional high-tech sectors, such as IT and Health and Drugs, and the industrial sector distribution is extremely wide, including Business Services (10.2 percent), Advertising and Marketing (8.6 percent), Government Services (7.3 percent), Construction (3.8 percent), and the rest. At the metropolitan level, we observed regional variations and specializations. Government Services in Washington, D.C., was the best example; other cases include Advertising and Marketing in New York City and Los Angeles, Business Services in Chicago and Atlanta, and Health and Drug firms in Dallas.
I note discussion in another part of Smith's post and in the comments about the relevance of venture capital--we've covered that here too, many times, and it bears repeating, most entrepreneurs never receive venture capital (or angel) investment.
Returning to Smith's main message--he asks if we have an entrepreneurship groupthink problem. Dane has wondered about this previously as well. Does the Entrepreneur Subculture insulate? If policy makers and the media focus on entrepreneurs, and if entrepreneurs are more and more in close collaboration with one another, will the same ideas end up being recirculated and groundbreaking innovations become even more rare? The potential for problems is definitely there.
I think Smith is right on the mark when he advises that entrepreneurs should take breaks from this Subculture experience. I have an illustrative story that squares directly with this idea. I attended the Inc. 500|5000 annual conference in Phoenix earlier this month. One of the presentations was from GoPro (the durable, hi-def, and compact camera) founder Nick Woodman, who came up with the two big innovations for GoPro while pursuing his passions. He came up with the idea for the first camera (not able to record video at first) when he thought about capturing his experiences on a surfing tour vacation--the first GoPro was a camera you strapped to your wrist. Later after the company had developed rudimentary video cameras, he was learning to drive a race car and realized that a camera that could be strapped to your wrist could just as easily be mounted to a roll bar. Take a break; discover big ideas while having fun.
Aside from vacations, there are ways to take quick breaks too. There's a popular concept in computer programming concerning rubber ducks. When troubleshooting code, put a rubber duck next to your keyboard and force yourself to explain the problem to the rubber duck. Talking it out to an uniformed thing is helpful. Entrepreneurs might find rubber ducks helpful too as a quick break. But more generally I'm thinking about real life rubber ducks. Rid yourself of the name dropping, the "do you know/have you heard of __ ?" question banks, and forget all the acronyms by talking and explaining things to non-entrepreneurs (I include myself in this camp), and frequently don't talk about entrepreneurship at all. Talk about e.g. the unfathomably good Homeland.
It will also be up to us--organizations like the Kauffman Foundation and others that support entrepreneurs--to speak up, present research-backed evidence, and provide feedback surrounding policies and practices concerning entrepreneurship. Maybe we should start handing out rubber ducks and be sure to use them in our own work.
Posted by Mindee Forman at 12:21 PM in Blogging, Economic Growth, Entrepreneurs, Global, Human Capital, Immigration, Law and Entrepreneurship, Policy, Practically Friday, Research, U.S. economy | Permalink | Comments (0) | TrackBack (0)
Posted by Mindee Forman at 08:58 AM in Blogging, Economic Growth, Economic Recovery, Entrepreneurs, Global, Human Capital, Immigration, Law and Entrepreneurship, Policy, Practically Friday, Research, U.S. economy | Permalink | Comments (0) | TrackBack (0)
Because of their more limited inequality and more comprehensive social welfare systems, many perceive average welfare to be higher in Scandinavian societies than in the United States. Why then does the United States not adopt Scandinavian-style institutions? …we develop a simple model of economic growth in a world in which all countries benefit and potentially contribute to advances in the world technology frontier. A greater gap of incomes between successful and unsuccessful entrepreneurs (thus greater inequality) increases entrepreneurial effort and hence a country’s contribution to the world technology frontier.
We show that, under plausible assumptions, the world equilibrium is asymmetric: some countries will opt for a type of “cutthroat” capitalism that generates greater inequality and more innovation and will become the technology leaders, while others will free-ride on the cutthroat incentives of the leaders and choose a more “cuddly” form of capitalism. Paradoxically, those with cuddly reward structures, though poorer, may have higher welfare than cutthroat capitalists; but in the world equilibrium, it is not a best response for the cutthroat capitalists to switch to a more cuddly form of capitalism. We also show that domestic constraints from social democratic parties or unions may be beneficial for a country because they prevent cutthroat capitalism domestically, instead inducing other countries to play this role.
This is interesting beyond their [re]framing of inequality and technology frontiers in that they specifically mention entrepreneurs as crucial to the wealth/innovation creation process. The entrepreneur has too long been absent from discussions about development outside of specific circles and it is promising to see entrepreneurs as central to a model not explicitly designed to discuss entrepreneurship. They go on to suggest that investigating ‘institutional specialization’ is an important research direction as it may apply to other institutions like education and labor mobility. Such studies could potentially add insight into the ever difficult question of why there are higher concentrations of entrepreneurial activity and success in different areas.
Finally, the use of the word ‘cuddly’ in an academic paper is both ground-breaking and highly entertaining.
Hat tip to Chris Blattman.
Today, we are releasing another Kauffman Sketchbook about Better Capitalism, a book authored by Robert E. Litan and Carl Schramm that was mostly completed while they were both at the Kauffman Foundation. The book is a sequel or follow-up to their widely praised Good Capitalism, Bad Capitalism.
You can see all of our sketchbooks at www.kauffman.org/sketchbook.
Bryan Caplan has posted comments he emailed me on an early draft of my new e-book Human Capitalism. I knew in advance that Bryan was going to be a tough critic: after all, a guy who writes a book arguing that parenting has little impact on how children turn out is unlikely to be receptive to my claim that cultural differences (e.g., differences in parenting) explain much of America’s growing class divide along educational lines.
Bryan’s skeptical comments proved very helpful. In particular, he steered me away from focusing too much on the narrow issue of the heritability of IQ – which, he concedes, is a pretty weak predictor of life outcomes. Instead, he urged me to look instead at the heritability of socioeconomic status generally. There is a strong correlation between parents’ outcomes and those of their kids, and there is a considerable literature in behavioral genetics based on the study of adoptees and twins that finds genes, not shared environment, account for practically all of that correlation.
Thanks to Bryan I dove into that literature and found that it does indeed offer support for the view Bryan has called “parental irrelevantism.” But, as Bryan fails to acknowledge, those findings are subject to serious caveats and, in any event, there are other findings in that same literature which show an important effect of upbringing. In addition, other important lines of evidence that Bryan ignores point to the considerable impact of the upbringing environment. I came away with my initial common-sense verdict undisturbed: nature is important, but so is nurture.
Since Bryan has shared his comments, I thought I would post a couple of them here along with the emailed replies I made at the time. I chose these exchanges because I think they address interesting issues I really didn’t tackle head-on in the book. I’ll put his comments in italics followed by my responses.
7. (chap 6) There may be “no prospect for a return to the more authoritarian morality of yesteryear.” But what about a marginal move in that direction? And if the breakdown is indeed caused by the absence of material scarcity, wouldn’t drastic cuts in the welfare state -- drastic enough to restore labor force drop-outs and unskilled single moms to material scarcity -- revive the morality of yesteryear? Why doesn’t this lead to the very unliberaltarian view that the welfare state is the problem?
I believe the fundamental problem is mass affluence, not the welfare state. Clearly we have to engage in speculation when imagining what life would be like in the absence of government-provided income support -- given that such support has been around in the English-speaking world for over 400 years. But my assumption is that private charity in our rich, liberal, humanitarian, soft-hearted society would provide some decent “social minimum” for poor children and by extension for their parents (can you really imagine an America in which children were allowed to starve? or in which they were routinely taken from their parents because their parents couldn’t support them?) I don’t believe the kind of material scarcity that faced the early 20th century American working class, or that shapes the mentalities of current-day immigrants from poor countries, is ever coming back to this country -- or it is does, it will be because of some catastrophe that causes us to forget entirely about the issues we’re discussing here.
That said, when specific welfare-state policies (e.g., the old AFDC) subsidize idleness rather than work, they ought to be changed. I call for a shift in welfare policies toward greater subsidization of work
One last comment that probably won't be very helpful, but I want to get it off my chest: When I see the hard work and positive attitude of the typical immigrant, I find it very hard to sympathize with the problems of the American working class. The so-called American poor are born with so many advantages, but they squander them through their own bad attitude and irresponsible behavior. Yes, in a welfare state the problems of my countries’ working class are my problem. But that makes me want to *attack* the welfare state, not expand it to help undeserving Americans even more. The people we should be worrying about are immigrants and would-be immigrants who can’t even legally accept a job offer, not Americans who can’t bother showing up to work on time.
On an emotional level, Bryan, I sympathize with you. I grew up as a nerd in the Deep South, where being smart and achievement-oriented in school meant social isolation and hazing. So living through that, my knee jerks in the same direction as yours.
But I don’t really think moral desert has much relevance for public policy, at least not here. If public policy reforms can change conditions and incentives in a way that ensures that a higher percentage of morally blameless infants grow up to be morally praiseworthy adults, then we ought to make those reforms -- even if they soften the blows of their own folly for some morally unpraiseworthy adults.
In that regard, I think the reason immigrants are so praiseworthy in your eyes is due to circumstances outside their control -- i.e., they were raised in poor countries under the lash of material scarcity. Likewise, the reason native-born working-class Americans are so often blameworthy is due to circumstances outside their control -- they were raised in mass affluence without being adequately acculturated with the skills needed to make good decisions. If you stop your analysis at the moralistic level, you miss the underlying factors that are driving differences in moral outlook.
As an undergraduate math major, one of my favorite areas of study was chaos theory. That is, the notion that a small, seemingly inconsequential action in one location can have a major effect in another, very distant location. This concept is often illustrated through what is known as “the butterfly effect,” whereby the beating of a butterfly’s wings is the catalyst for a major hurricane on another part of the planet weeks later. Recently, I was reminded of this notion in the context of entrepreneurship and, in particular, women in entrepreneurship.
The 2011 American Express OPEN report, “State of Women-Owned Businesses,” indicates that the number of women-owned firms is growing steadily. In fact, between 1997 and 2011, when the total number of businesses in the United States increased by 34 percent, the number of women-owned firms increased by 50 percent, a rate 1½ times the national average. While that fact is encouraging, and while sales, too, are increasing for these same women-owned firms, sales growth of women-owned firms at 53 percent lags behind that of the national average at 71 percent. It seems a reasonable goal to help grow women-owned firms, which currently account for 29 percent of all enterprises according to the American Express OPEN report, in an effort to increase their contribution to the workforce and the economy.1
Women’s Entrepreneurship in the Americas (“WEAmericas”), an initiative that leverages public-private partnerships to increase women’s economic participation and address key barriers women confront when starting and growing small and medium enterprises (e.g., access to training/networks, access to markets, and access to finance), is working to bring these concepts to bear. In addition to the U.S. government, WEAmericas founding partners include Cherie Blair Foundation for Women, ExxonMobil Foundation, Goldman Sachs 10,000 Women, Inter-American Development Bank, Thunderbird School of Global Management, Vital Voices, Walmart Foundation, WEConnect International and, proudly, my own organization, Kauffman FastTrac.
In the spirit of strengthening economic partnerships and exchanging ideas among countries in the Americas, next month, during a Walmart Foundation and U.S. Department of State sponsored visit to the United States, approximately 40 female entrepreneurs from several Latin American countries will spend a day with Kauffman FastTrac in Kansas City, Missouri. The experience will be designed to engage the visitors in learning, exploration, and dialogue related to entrepreneurship, with a focus on business growth. The attendees will participate in Kauffman FastTrac’s Listening to Your Business three-year visioning workshop. In particular, the women will examine their businesses today, including strengths, weaknesses, and opportunities; visualize their businesses three years from now; formulate internal planning processes to establish interim goals and strategies; identify resources to assist in reaching business goals; and examine and respond to challenges and transitions.
The hoped-for output of these and other efforts: Economic recovery and growth. As noted by the Kauffman Foundation, it is essential to view women’s entrepreneurship as an economic issue – not as a gender-equity issue. Thus, as chaos theory suggests, small investments in women – to help advance their entrepreneurial aspirations – can result in significant positive global economic implications. Just like the butterfly effect, from chaos will come order, and as women bring their ideas to market, global returns will increase and everyone will benefit.
1 The report bases its analysis on the U.S. Census Bureau’s Survey of Business Owners (1997, 2002, and 2007) with extrapolations into 2011 based on Gross Domestic Product.
Last weekend in The New York Times, business columnist Floyd Norris wrote that new data from the Bureau of Labor Statistics "challenge" the notion that small companies create more jobs over time than large companies. Indeed, according to these numbers, from 1990 to 2011, employment in big firms (defined in the dataset as those with more than 500 employees) increased by 29 percent, while it rose by only 10.5 percent in firms with 49 or fewer employees.
The debate over how job creation breaks down by firm size is one with which the Kauffman Foundation is familiar and we have put out our own papers on this topic as well as worked with those who are knee-deep in the data. It shouldn't be a surprise to anyone that looking at job creation solely through the lens of firm size gives an incomplete picture. Elsewhere, the important distinction between firm age and firm size has been adequately underscored, so we won't dwell on it here. Here are just a few points about the Norris column that reveal some of the nuance under the numbers, while confirming that aggregate data are true--mostly.
First, as Norris points out, lumping all job creation together over a long period of time conceals moves of companies between size categories, whether from growing firms or seasonal variation. Second, these job creation numbers obviously include acquisitions, which will usually be reflected only in additions to large company employment numbers and subtraction from small company employment. Not always, of course, but usually. Third, we have known for a while, and discuss this is a forthcoming paper, that a larger and larger share of employment has been moving to large companies over time. Today, the share of total employment in the largest companies, those with over 10,000 employees, is the largest it has ever been in the United States.
Fourth, aggregate numbers mask all the variation beneath the surface, which is really where the real action of reallocation and productivity and economic growth takes place. Other recent work, for example, demonstrates that job churn--moving from one job to another--represents two-thirds of hiring in any given year. According to the Business Dynamics Statistics series from the Census Bureau, the "excess reallocation rate" has averaged around 30 percent since 1977--this is the gross job creation rate plus the gross job destruction rate, less the net job creation rate, capturing the persistently high level of churn in the U.S. economy. I don't know the breakdown of job-to-job flows in terms of firm size, but my guess would be that it is biased, if slightly, toward big firms. In any case, simply counting job growth by firm employment size over a twenty-year period misses what is really important about job creation and economic activity.
Finally, as with net job creation by firm age, part of the size calculation is a function of the math. There is a definitional limit on the share of job growth that can be accounted for by small and medium-sized companies. They can only account for job growth up to 49 and 499 employees, respectively. In contrast, there is an unlimited size level for job growth in big companies. (Theoretically, at least: if we use actually firm size numbers we might say that job growth in big companies can occur within a band of 500 employees and 1 million employees, roughly the size of Walmart.) Job growth can occur, along the vector of size at least, in two ways: more employees at existing firms, and more firms of certain sizes. Within the first, there is a statistical limit by which small companies can comprise relative job growth.
So, as with any statistic, the data Norris cites are true, but for certain reasons that, once understood, reveal a more nuanced--and far more interesting--picture of economic change.
The interesting tidbit from the article is here (bold is my emphasis):
But Italy’s labor unions have taken the lead in resisting many changes to existing law. Debate has been especially intense over Article 18 of the 1970 Workers Statute, which forbids companies with more that[sic] 15 employees from firing people without just cause. The unions say that line cannot be crossed.
This sounds to me like an awful policy that discourages entrepreneurship and growth. I read the "just cause" provision to terminate employees as a disincentive for any entrepreneur to cross the 15 employee threshold.
I wonder if any research has been conducted on Italian firm size exploiting this law taking into effect. E.g. taking a dataset of Italian firms by age and size before and after 1970 to find out if there are a disproportionate number of 1-15 employee firms after this law takes into effect, and for what age of companies. Then compare to data on firm size and age for other EU nations during that time to try to control for any overall economic trends.
Currently, OECD data show the Italian economy, relative to other EU and OECD countries, is on the very high end of having a smaller firm composition.
My inaugural column for Forbes.com, "Avoiding the Coming Growth Slowdown," is now up. Here's a teaser:
Consider this puzzle. Compare economic performance in two periods: 1973-1990 versus 1990-2007. Both periods are 17 years in length; both begin and end with the last year of an economic expansion. In the earlier period, the U.S. economy weathered oil shocks, stagflation, and a punishing recession in the early ’80s, and growth in labor productivity in the nonfarm business sector limped along at a dismal 1.33 percent a year. In the latter period, prosperity was interrupted only by a pair of brief, mild recessions, and the IT revolution led a dazzling rebound in productivity growth up to 2.33 percent a year. Yet in 1973-1990, real gross domestic product per capita rose at an average annual rate of 1.93 percent – better than the 1.85 percent average annual growth rate during 1990-2007. How could that have happened?
Check out the whole thing.
Courtesy of the McKinsey Global Institute, here is an interesting new contribution to the debate kicked off by Tyler Cowen's The Great Stagnation. This new MGI report -- entitled "Growth and renewal in the United States: Retooling America's economic engine" -- doesn't mention Tyler's book, but it offers evidence that supports his argument -- as well as that of his critics. On the one hand, MGI makes a strong case that we are facing strong headwinds when it comes to prospects for future growth. On the other hand, contrary to Tyler, the report points out that there's plenty we can do about it.
The MGI report singles out demographics as the main obstacle to future growth, and it makes a strong case. Think about per-capita GDP growth as a function of two variables: growth in output per worker-hour (i.e., productivity growth) and growth in total worker-hours per capita. If the latter slows down, the former has to speed up for growth to stay on trend. According to MGI:
Today, however, the contribution from labor is slowing down as baby boomers retire and the female participation rate has plateaued. In the next ten years, the proportion of working-age Americans will decline from 67 percent to 64 percent. By the 2020s, the contribution of labor to US GDP growth rates is expected to decline to just 0.5 percent from a peak of 2.0 percent in the 1970s.
Accordingly, to avoid a dropoff in the long-term growth rate, labor productivity growth needs to compensate for the unfavorable demographic situation. Specifically, the MGI report says that output per worker-hour would need to increase by nearly a quarter to maintain the historical average of 1.7 percent annual growth in real GDP per capita.
Unlike Tyler, though, the folks at MGI don't think the orchard of "low-hanging fruit" is bare. They see plenty of opportunities to boost productivity: diffusion of existing best practices, implementation of the next wave of emerging business innovations, and restructuring of low-productivity and highly regulated sectors (namely, education and health care) all offer promising gains.
In addition, the report helpfully points out that our demographic situation is not unalterable. If the United States could achieve the same labor force participation rates for women and workers 55-64 as Sweden, the same youth unemployment rate as the Netherlands, and the same immigration rate as Australia, it could expect to add a full percentage point to its real GDP growth rate over the next 10 years.
On a critical note, the MGI report is sometimes frustratingly short on specifics. In particular, it's much too vague in addressing what needs to be done to boost the abysmal productivity record of the health and education sectors. Nonetheless, it does frame the issue well -- and points the discussion in a more constructive direction than Tyler's fatalism.
That's the title (sans question mark) of a new e-book by Tyler Cowen, economics professor at George Mason University and blogger extraordinaire at the wonderful Marginal Revolution. The thesis is summarized by the book's fashionably prolix subtitle: "How America Ate All the Low-Hanging Fruit of Modern History, Got Sick, and Will (Eventually) Feel Better."
Tyler argues that, ever since colonial times, the American economy has benefited from "low-hanging fruit" -- i.e., bountiful opportunities for growth. He singles out three in particular: free land, technological breakthroughs, and smart but uneducated kids. "Yet during the last forty years, that low-hanging fruit started disappearing, and we started pretending it was stil there. We have failed to recognize that we are at a technological plateau and the trees are more bare than we would like to think. That's it. That is what has gone wrong." Tyler identifies the exhaustion of easy opportunities for growth as the main culprit behind the slowdown in growth over recent decades, rising inequality, the nastiness of our present-day politics, and even the recent global financial meltdown.
It's a wonderful book: provocative, clever, full of surprises, accessibly written, and mercifully brief. And most of the constituent elements of his argument I wholeheartedly endorse. Indeed, in a weird coincidence, I have a new Kauffman paper in the works that touches on very similar themes. I agree with Tyler that growth has gotten a lot harder since the early '70s. And I agree that a great deal of political mischief has been caused by our collective failure to grasp this important truth.
But, at least for now, I can't buy into the idea of a "Great Stagnation." I just don't think the evidence supports Tyler's sweeping historical narrative that centuries of easy progress are now over. A lot of the force of his argument comes from contrasting the United States' glittering economic performance in the decades following World War II with the decidedly less impressive record in recent decades. But if you zoom out and look at the larger historical record, Tyler's Great Stagnation more or less disappears. And if you zoom in and examine recent trends in detail, the numbers likewise belie the claim that we have hit some "technological plateau."
Tyler correctly points out that median family income rose smartly after World War II only to fall off sharply in the '70s. GDP per capita figures reveal the same trend, albeit a little less dramatically (because of the rise in income inequality). Between 1950and 1973, the average annual growth rate of real GDP per capita was 2.5%; for the period between 1973 and 2007, the corresponding figure was only 1.9%
But look what happens when you put these figures in larger historical context (note: I'm using calculations by Angus Maddison for earlier periods and Census figures for post-WWII periods):
1820 - 1870 1.3%
1870 - 1913 1.8%
1913 - 1950 1.6%
1950 - 1973 2.5%
1973 2007 1.9%
From this broader perspective, what Tyler calls the Great Stagnation looks like a return to normalcy after the "Great Boom" of the post-WWII decades. Indeed, recent growth rates are better than those of all other earlier periods. So yes, growth has cooled down since the postwar "Golden Age," and that fact poses real economic and political challenges. But the Golden Age was the outlier, not our present era; it just doesn't make sense to talk about the present period as stagnant after centuries of easy growth.
Now let's focus on trends in recent decades -- in particular, productivity growth. If we've reached some kind of technological plateau, that should show up most clearly in a fall-off in the growth of output per worker hour. But look at the actual BLS labor productivity figures for the nonfarm business sector:
1947 - 1973 2.8%
1973 - 1995 1.4%
1995 - 2007 2.7%
Once again, there was a big dropoff after the postwar boom. But then look what happened: beginning in the mid-'90s, fueled by the IT revolution, productivity growth came roaring back, nearly equaling the record of the Golden Age. It's hard to look at these figures and conclude, with Tyler, that the trees in the orchard are becoming bare.
Granted, the productivity comeback offers no ground for complacency. The productivity figures look better than the per-capita GDP figures, in large part because the labor force participation rate peaked in the late '90s, fell during the dot-com bust, and only recovered to early '90s levels by 2007 (superior growth in output per worker was thus partially cancelled out by sluggish growth in the number of workers). Meanwhile, the per-capita GDP figures look better than the median income figures cited by Tyler because of the rise in inequality -- that is, because income growth has been concentrated at the top of the socioeconomic spectrum.
These facts point to real challenges for future growth. One reason the labor force participation rate has stalled is the aging of the population -- a trend that is going to cause all kinds of economic and political headaches in coming years. And rising income inequality is due in significant part to slumping human capital formation: we reaped big gains from sending Tyler's "smart but uneducated kids" to high school, college, and grad school, but educational attainment at both the secondary and postsecondary levels has stagnated since the '70s even as the demand for highly skilled workers has continued to climb.
I've focused on criticisms here, but I want to close by reiterating what an interesting, intelligent, and thought-provoking book this is. Growth has gotten harder, and there are mounting obstacles ahead. For pointing out these sobering facts, and doing so in such an engaging manner, The Great Stagnation deserves a wide readership.
This is a terrific article by Timothy Garrett at the University of Utah, published in October: "On the coupled evolution of inflation, wealth, and atmospheric concentrations of carbon dioxide." Garrett devises a thermodynamic model of economic growth and energy use and his article is far deeper than what typically passes for energy economics analysis. Looking for a reason to stay awake at night? Look no further:
What remains is only to rapidly decouple civilization growth from CO2 emitting sources of energy. There is an important caveat however, which is that such decarbonization does not slow accumulation by as much as might be anticipated. Decarbonizing civilization promotes society [sic] wealth by alleviating the rise in atmospheric CO2 levels. But growing wealth is tied to energy consumption rates, and therefore to CO2 emissions themselves. Only a combination of extremely rapid decarbonization and civilization collapse keeps CO2 concentrations below 500 ppmv within this century.
Yesterday I had the privilege of delivering testimony on behalf of Bob Litan in front of the Joint Economic Committee. The subject of the hearing was how the United States could maintain its position on the global frontier of innovation, with a specific focus on universities and federal funding of research and development. Most of the Members of the Committee were in general agreement with the panelists: innovation is key to economic growth, universities are important to R&D and innovation, and the United States needs to make some changes if we are to remain an innovative economy.
On one particular point, however, there was a considerable degree of contention. Congresswoman Carolyn Maloney (D-NY) inquired as to the state of technology commercialization in higher education. Can it be improved? Is everything peachy-keen?
The Kauffman Foundation takes the position that all is not well in the land of technology commercialization. There are success stories, to be sure: Gatorade, Vitamin D, Netscape, MRIs and so on. And there are star performing universities--Stanford, WARF (the Wisconsin system), and the University of California system do a phenomenal job of moving innovations out of campus buildings and into new (and existing) companies. But universities, on the whole, appear to be under-performing relative to what they could be contributing to economic growth. The Bayh-Dole Act of 1980 allowed universities to hold the intellectual property rights to innovations and discoveries that result from federally-funded research. The result was a wave of university innovations as well as a wave of attempts to move university innovations into the marketplace. Most universities receiving federal R&D dollars established technology licensing or transfer offices (TLOs or TTOs) to manage the intellectual property and serve as the liaison for faculty members seeking to commercialize their innovation. As noted, many universities have managed to successfully commercialize new technologies.
As with anything, however, the structure that was set up in response to Bayh-Dole has now run into problems. The productivity of federally-funded research at universities has been declining for a number of years. Technology transfer offices are typically understaffed and unable to manage their university's stream of innovations--innovations, moreover, that often span a wide diversity of disciplines. At the same time, however, bureaucracy has grown up around the process of technology commercialization and dramatically slowed, if not stalled, the process in many places. Anecdotal evidence abounds of faculty members running headlong into bureaucratic drywall at their licensing office. Furthermore, as a result of the outstanding success of a handful of universities with a handful of innovations, many TTOs and TLOs have implicitly or explicitly adopted a home-run mentality, chasing the next big hit at the expense of many smaller innovations.
Finally, many universities have latched onto the most easily measured outputs of R&D, patents and licenses. But, there is little correlation between federal research funding and the returns (in patents and licenses) on that funding. Maybe we shouldn't expect there to be such a correlation, of course, but the race by universities in the wake of Bayh-Dole to establish commercialization offices and the drift of research spending toward a more political rather than scientific distribution have raised the implicit promise that there is such a correlation. The wonderful historian Roger Geiger has documented such drift: at one time, the distribution of university innovations and federal R&D money to universities both followed a Pareto distribution, with a handful of institutions far outdistancing everyone else in terms of inputs and outputs. Over time, however, while the distribution of innovative outputs remains skewed, the distribution of research dollars has gradually gotten flatter. We expect proportional output in terms of innovations but don't receive it.
There is no magic solution to these bottlenecks, but my colleagues Lesa Mitchell and Bob Litan have come up with a fantastically simple and novel idea: open up technology transfer to market competition. That is, allow a professor from University X with a potentially breakthrough innovation to go outside his or her university's TLO and use that of University Y, if University Y happens to be more skilled at commercialization in this particular discipline. University X would not be required to relinquish IP rights, and of course the professor is not required to do anything. The idea is simply to bring more openness and competition into a process that has become muddled and distorted. Where else in society do we tolerate such artificial monopolies with public research dollars at stake? This idea, in fact, perfectly carries forward and extends one of the primary motivations behind Bayh-Dole--to smooth the commercialization process. Bayh-Dole was enacted in part to construct a platform upon which faculty and professors could more easily interact with companies (new and existing). Allowing universities to hold IP rights was meant to remove one of the legal entanglements in this process.
Who could oppose such openness? Who could oppose competition when competition has been shown repeatedly to be the best avenue toward maximizing innovation and social welfare? Not to sound trite, but follow the money. Most universities and TTOs and TLOs vehemently oppose this idea. In fact, you can scroll through the webcast of yesterday's hearing to the very last question and witness the animation with which Dr. Samuel Stanley opposes the mere mention of this idea. Basically, the opposing arguments boil down to these: (a) there is no evidence that the current licensing process is dysfunctional; (b) allowing such "free agency" would give rise to all the legal problems that predated Bayh-Dole and were put to bed by that legislation; (c) no professor and no university wants to do this; (d) technology commercialization is a delicate art that cannot be commoditized; and (e) the current system is working fine as it is--as proof, look at all the great innovations universities have given us.
Unfortunately, I did not get a chance for a counter-rebuttal, so I offer it here. First, Dr. Stanley (and others) confuses an absence of evidence with evidence of absence. The absence of overt dysfunctionality does not imply the corollary, that things are hunky-dory. In fact, the arguments I've mentioned above regarding research productivity and returns to patents and licenses would seem to indicate something is amiss, as would the growing stock of anecdotes from frustrated professors and companies. It is of course nearly impossible to prove that something like a university is not living up to its perceived potential in terms of commercializing innovations, but the inability to prove that there is room for improvement is not an argument against opening up the process. That, in fact, is the nub of the free agency proposal--just open it up. No one would be forced to operate as a free agent or to contract with a free agent, as Dr. Stanley seems to think we are suggesting. This is entirely optional, as is any competitive market. It could even be optional at the level of the department or school of any particular university, with one department perhaps choosing to work with ABC agent while another chooses XYZ agent.
Dr. Stanley also predicts that such openness would instigate a return to those dark days before Bayh-Dole when legal machinations corrupted every attempt at commercialization--contract disputes, broken agreements, etc. Oddly, however, technology commercialization at universities is still plagued by these problems--Bayh-Dole did not banish legal disputes, and I'm not sure how Dr. Stanley manages to pull off such cognitive dissonance.
By opening up the technology commercialization process, we would likely see the development of completely new organizational forms to facilitate the process. No one can predict what will happen--and that is exactly the point. Maybe free agency will flop; maybe it won't. But there is no (or shouldn't be) single model when it comes to technology commercialization: free agency would encourage experimentation as a way to lower transaction costs, which was precisely the idea behind Bayh-Dole. In fact, many professors are already finding their way around the TLOs and TTOs, doing "end-runs" around the bureaucracy and finding their own commercialization routes. Rather than see this perversion as a defense of the status quo we should encourage free agency as a way to promote the development of more such alternate pathways. In their promotional materials and commencement speeches, university administrators consistently trumpet the glories of diversity and self-actualization and intellectual experimentation--except, it seems, when it comes to their own operations.
That seems to be a running theme of opposition: technology commercialization is special and cannot be subject to the rules of the market that govern the rest of the economy. Dr. Stanley is far from alone in asserting that each particular innovation is unique and must be granted its own customized commercialization process that can only be run through a TLO. Undoubtedly, there is some truth to this. Just as clearly, however, there is plenty of room to lower transaction costs by standardizing some portions of the commercialization process. This is precisely what UNC-Chapel Hill has done with the Carolina Express License Agreement; we will keep you posted as to whether or not the world ends as a result of this dangerous experimentation with technology commercialization.
Finally, we come to the tried and true defense that everything is fine. Universities have, after all, contributed enormously to economic growth and human welfare. Why mess with success? The real message, however, is: don't mess with us! This is the completely predictable and understandable response of any institution when its monopoly is threatened and should, in fact, serve as a reason to promote more experimentation. Just because universities have contributed much in the past does not mean they are performing optimally today (research is only one of many fronts on which we could have this discussion) and does not guarantee that they will continue to do so in the future. If bureaucracy keeps building up around the discovery and innovation process, it is almost guaranteed that they will not.
[Cross-posted from Progressive Fix]
A recent post highlighted the importance of new and young companies to job creation in the U.S., implicitly raising an important question for policy makers: How can we increase the number of startups? Assuming it can be done, such an increase would not solve all of the economic challenges facing this country, but it would certainly help. New companies not only create millions of jobs across all sectors of the economy — they also introduce product and process innovations, boosting overall productivity.
Saying startups are important is one thing, of course; actually designing policies to increase their number is something else entirely. Before making any recommendations, for example, we need to know more about the universe of startups. Are they more prominent in some sectors than others? Does the impact of new companies differ across sectors or geographic regions? Should policy focus on encouraging more new firms, or on enhancing the growth of those already in existence? How would any such policies affect established companies, large and small?
Policymaking around entrepreneurship is evidently not clear-cut as there is still quite a bit we do not understand regarding startups. In the coming weeks we will try to explore these questions and illuminate the world of startups for policymakers. We’ll start with the lowest-hanging fruit of all, though one that may seem like poison to some in Washington: immigration.
It’s commonly accepted that the United States is a nation of immigrants, settled and populated by those fleeing persecution, seeking commercial opportunities in a new land or looking for a fresh start. We have always recognized the important contributions of immigrants to the U.S. economy, from entrepreneurs like Samuel Slater (textile mills) to Andrew Carnegie (steel) to Andy Bechtolsheim (Sun Microsystems) to the laborers and workers who built this country with their hands.
Recently, researchers have begun to paint a broader picture of the economic role of immigrant entrepreneurs. For example, Vivek Wadhwa and his research team have found that, from 1995 to 2006, fully one-quarter of new technology and engineering companies in the U.S. were founded by immigrants. In Silicon Valley, the figure was one-half. These firms constitute only a sliver of all companies, yet contribute an outstanding number of jobs and innovations to the economy.
It makes sense, then, that if we are seeking to increase the number of new companies started each year in the U.S., we might look to immigrants. It turns out that Sens. John Kerry (D-MA) and Richard Lugar (R-IN) are thinking precisely along these lines, introducing the StartUp Visa Act (PDF) in the Senate. This bill would grant a two-year visa to immigrant entrepreneurs who are able to raise $250,000 from an American investor and can create at least five jobs in two years. Without question, such a visa is a good idea and this legislation hopefully paves the way for future actions that would reduce the pecuniary threshold and focus more on job creation.
Quite naturally, however, the promotion of immigrant entrepreneurs arouses suspicion among those on the right who harbor nativist views, and those on the left who perceive progressive immigration policies as a threat to American labor. Such views take the precisely wrong perspective: immigration, as we have seen, is a core American value. Immigrant entrepreneurs, moreover, come to the U.S. to make jobs for Americans, not take them.
Further, many of those who promote immigration as a way to boost economic growth narrowly focus on “high-skilled” entrepreneurs, those who might start technology companies. Clearly, as Wadhwa’s research indicates, such companies are important to American innovation. But we exclude non-technology entrepreneurs at our peril — every new company, including those founded by immigrants, represents pursuit of the American dream. By closing our borders to immigrants in general or welcoming only those with certain skills, we leave out many who will start new firms in other industries. If not in the United States, they will go elsewhere to start their companies and create jobs.
Entrepreneurs are implicit in Emma Lazarus’ poem: “Give me your tired, your poor/Your huddled masses yearning to breathe free.” Entrepreneurs start from nothing and work endlessly to build their companies, expressing their individual freedom through commerce. Why should we want to exclude them from the home of entrepreneurial capitalism?
ADDENDUM: Ben Wildavsky's new book, The Great Brain Race, will be released soon and I highly recommend it to anyone interested in higher education, globalization, and immigration. It is a fantastically written book and, as noted in the title of this post, Ben posits this wonderful notion of "brain circulation." When discussing globalization and immigration and job creation in the very recent past (and, for that matter, still in the present), we have usually spoken in terms like "brain gain" and "brain drain," implying a zero-sum contest between countries and regions. Ben's book makes quite clear that we are moving into a world of brain circulation, wherein people circulate among countries and institutions, starting companies, creating jobs, propagating innovations--adding to the economies of many countries at once.
This is a sequel to last week's post about moving from Paul's drunkard's walk to the accumulation of firms over time. Basically, the message of those two posts is that the internal dynamics of the American economy--lots of new companies founded each year, the exit of firms at all ages, the persistent predominance of young firms as the economy moves through time--make it highly probable that job creation will come from new and young companies rather than older, more established companies. (In these data that we're using, a firm is no longer classified as "young" once it reaches age 6, so the term "older," perhaps imprecisely, includes firms ages 6 and up.) Thus, when we say that new and young firms account for most net job creation in the U.S. economy, we are partly describing the reality of these firm dynamics.
This doesn't diminish the importance of these companies or the jobs they create. After all, the reality of these dynamics is premised on four things: a more or less steady inflow of startups; more or less consistent survival rates from year to year; comparable gross job creation and gross job destruction in older companies; and a higher number of jobs created at young firms (4 versus 1). These are not functions of what might be perceived as mathematical inevitability--they are the reasons behind the mathematical probabilities we are describing. If the level of firm formation were more volatile, if older companies created more jobs than they destroyed, if young firms were somehow suppressed in their hiring (through, perhaps, bailouts of larger, older companies; just speculating here)--if these variables changed, the dynamics of firm age through time, and subsequent job creation, would be different.
But, in recent history, these variables have all held and together they have created a picture that does, in fact, resemble something like mathematical inevitability, but which is probably more accurately described as a likelihood, or something of higher probability. In any given year over the past three decades, young firms (startups [age 0] and firms ages 1-5) have constituted the largest demographic of firms in the United States. Starting an economy at t=0, going out 25 years, the influx of new firms and the survival rates of firms over time generate this outcome. And, we might expect (provided the other variables are true) that the largest demographic sector will create the largest number of new jobs. This says nothing, of course, of innovation or productivity, subjects for another day.
Here, I want to supplement last week's post, which used average figures calculated from the Business Dynamics Statistics data, with the actual numbers from that dataset, which covers 1977-2005. That is, did reality conform to the stylized numbers we used last week? (The charts will not follow precisely the same format because last week's charts extrapolated out beyond 5 years on an annual basis, while the actual data aggregates firms into 5-year age categories after the fifth year: 6-10, 11-15, and so on.) We'll start, first, with the U.S. economy starting de novo in 1977, with only firms that came into existence that year. How, over the next 28 years, did the composition of firms by age change?
Here, startups (age 0, new firms founded each year) are broken out separately while all other firms are combined into 5-year categories. The data generally track the accumulation pattern revealed in last week's post: in any given year, young firms (ages 1-5) will quite naturally comprise the largest sector in terms of firm demographics. Note how few firms in 2005 are included in the 26-28 age category--these firms were founded in 1977-1979. By 2005, 19% of the firms founded in these three years remained. That may be more than expected, but using the survival line for firms founded for 1977 we can trace a slowly declining line of survival out two decades. If we imagine that the line continues on that downward slope for the next two decades, it appears as if very few firms in the economy survive more than four decades. Either those firms we all delight in describing as "dinosaurs" should properly be seen as remarkable achievements, or firm failure (over time) is a much more dominant force in the economy than we perhaps imagined. Probably both, and I'm probably simplifying here.
The advantage of using the real data from BDS is that we can include the "left censored" firms in our calculations, those companies founded prior to 1977 but for which we don't have age information. In 1977, then, these firms could be anywhere from age 1 to age 100. But we can track their survival after 1977 against all firms founded after that year. How long do these companies persist?
I included a brief explanation within the chart itself, but you can clearly see how these pre-1977 firms gradually decline in number over time, while new and young firms in any given year gradually get bigger in comparison. By 1988 (the circle), the pre-1977 firm group has shrunk such that it is now smaller each subsequent year compared to cohorts of new and young companies. By 2005, these firms still number 1.5 million, accounting for about one-fifth of all firms in the economy. This is a lot, but is an aggregate of every year before 1977, so there are probably a good number from the 1970s, a proportionately smaller number from the 1960s, and so on.
Now, we can include these pre-1977 firms in our overall chart of firm demographics over time and compare firms of all ages:
This is actually an incredibly interesting chart, as the text insert fleshes out, but I'll repeat it here so you don't have to open the image itself. It shows two different ways in which firm composition changes and in which new and young firms consistently account for the bulk of firms in the economy. In 1977, the t=0 moment here, the economy is composed of a class of startups (age 0) and all other firms existing that were founded before 1977. As the economy moves through time, you see four things happen. First, age 0 firms and age 1-5 firms account for a steady slice. Second, the overall number of firms accumulates. Third, the pre-1977 firms gradually decline in number. Fourth, post-1977 firms that age through time also diminish in terms of their numbers as fewer survive in subsequent years. So new and young firms dominate the economy (numerically) by two mechanisms: gradual disappearance of older firms and gradual disappearance of firms as they age. Same thing, different pathways (on this time scale).
Finally, we'll move to the percentage shares of each firm demographic (excluding pre-1977 firms here):
Once we get to a point where we have firms older than age 6 (and remember, the pre-1977 firms account for the missing shares here) in 1983, new and young companies account for between 30 and 40 percent of all firms in the economy. This percentage naturally falls over time, albeit slowly, as the overall number of firms grows, but this demographic of firms nonetheless comprises the largest demographic slice--a plurality, if you will--in each year, and this would persist over time.
So what, if anything, does this all mean? It means that new and young companies account for most new jobs in the economy in part because they are the largest demographic category of companies. It also means that job creation may actually be a secondary story here because this reality is a reflection of underlying dynamics that have been remarkably persistent over the past three decades. The United States has enjoyed a more or less steady level (and rate) of firm formation and survival rates for those firms have also been rather steady. Older companies, moreover, experience roughly equal levels of gross job creation and destruction, meaning their net job creation approaches zero.
It is entirely possible that these are transitory phenomena. As far as I can tell from the desultory data and research on firm formation prior to the 1970s, entrepreneurship (and subsequent survival rates) across the entire twentieth century have been remarkably consistent (I mention this, with an accompanying citation, in a forthcoming paper, so I'm not simply making this up). According to some Census data, for example, the number of new business created each year doubled from the 1940s to the 1990s--yet the country's population also doubled so the per capita rate of firm formation remained steady. Over the past thirty years, moreover, entrepreneurship rates have been remarkably steady, not declining as some have alleged.
Yet we surely can't assume that the dynamics beneath such factors are immutable. The preponderance of research concerning firm demographics in many European countries, for example, holds that firm exit is a much smaller factor and that, consequently, unproductive firms simply continue to exist and new firms are dissuaded from entering. Large companies enjoy favorable policy and so the above charts might look quite different for other countries and clearly indicate that the dynamics can change. Even if part of what the above charts do is describe a mathematical reality, it could be considered progress if policymakers in Washington and elsewhere spoke in terms of this reality rather than giving undue attention to the largest companies in the economy (which, incidentally, often seek regulation as a means of protection from competition from startups). What this all means is that startups and young companies are no less important than we thought before--they are a robust and enduring dimension of the U.S. economy. It would be foolish, however, to assume that this is somehow a natural or permanent state of affairs--policy could easily be made to alter these dynamics for the worse.
In describing how human knowledge advances, Donald Campbell devised the BVSR model to explain the evolutionary way in which knowledge accumulates. BVSR stands for Blind Variation and Selective Retention and is more or less natural selection applied to creativity and epistemology. Others have explored Campbell's with great insight and how it applies to fields such as organization science.
Evolutionary economics moves in and out of fashion but for the most part remains on the fringes of economic thought. Prompted in part by Paul's post earlier today, I'm wondering today about startup firms in a BVSR model of economic dynamics. It's no surprise (and, I don't think, controversial) that free market competition works through an evolutionary process of selection. Individuals and companies try various things (new products, services, processes) and their fate hinges on whether or not the market "selects" them vis-a-vis competing ideas. These new products and services are the variations in BVSR, whether radically new innovations or incremental improvements on something that already exists. We throw lots of spaghetti against the wall to see what sticks. Economic variation, of course, is not completely random since firms often seek to satisfy a previously identified market need or solve a heretofore unsolved problem. Variation is, however, blind in Campbell's sense, in that we do not know beforehand what will or will not succeed. "Blind" refers to our knowledge (more specifically, our lack of knowledge) about the consequences of any particular variation.
So we continuously introduce new variations into the market. The manner in which they are winnowed and propagated is "selective retention." Selection is clear: a new market variation either succeeds or it doesn't. Or, more precisely, it either survives (is selected) or doesn't survive (is not selected or selected against), with survival not always a proxy for subjective superiority. Here, it seems like the BVSR model advances somewhat beyond the standard view of the free-market-as-natural-selection (in addition to the explicit recognition that variations are blind). Once a variation is selected, what happens to it? It is retained, meaning it somehow propagates through the population. A variation doesn't merely survive--it grows and spreads.
How would you increase economic growth or increase innovation through the BVSR model? Let's say each element is multiplied by the others, so growth or innovation is the result of V x S x R, all divided by B. Increasing any one element in the numerator should theoretically increase the product. (It's not clear that this should be true, by the way. I haven't convinced myself that multiplication is correct here. I suppose it's conceivable that it could or should be, for example, "+" R. This isn't a research paper and I'm just following an idea here, so please feel free to take issue with this. At this point, it's of de minimis concern.) According to this, then, you could increase growth or innovation by increasing variation (the introduction of new products and services), improving the selection process (so only "good" or "right" variations are selected), and improving retention, to the properly selected variations quickly achieve rapid scale and propagation, disseminating their benefits to everyone.
How would we approach startups here? Obviously, startups are one type of variation (at the population-level of the economy). They are selected for and against: roughly half of new firms (48%) survive to age five, with the survival curve slowly falling after that. (I've seen some data indicating that one-third of new firms survive to either age 7 or age 10.) Survival, of course, tells you little about success or quality, and selection in the case of firms is an ongoing process. Some research suggests that only the tiniest handful of companies survive for more than a few decades (suggesting that groups such as those companies on the Fortune 500 are both an incredibly small minority and, perhaps, a secondary story--maybe failure is the dominant story of economic selection). Retention could be either the organic growth of young companies or, I suppose, acquisition by larger, more established companies. (Revenue or employment growth or both would here serve as a proxy for another way of looking at retention: spread of a company's product through the market.) With the denominator, "Blind," we might want to reduce the blindness of our variations--that is, wouldn't we want to have a better idea of the prospective fate of new firms? Or, should B be another multiple here? Would increasing blindness be better because it would throw more of the burden onto the competitive process? Perhaps B is neutral here? That is, perhaps it cannot be increased or decreased?
In any case, let's assume, with good reason, that startups are absolutely essential to innovation and economic growth. To increase these, what would we do with startups in the BVSR model? To begin with, could we reduce the blindness of a particular startup's fate, or the fate of all startups together? (It's not clear, moreover, what Blind should refer to here: mere survival to a certain age? Success, however nebulously defined?) Let's say Blind refers to the state of knowledge facing the founders of a new company: they do not know, and can't know, whether or not they will "succeed," however they define that term. (Although, if your objective is to simply work for yourself or the ability to wear flip-flops to work, then merely starting your own company can be considered success.) From a macro perspective, it's not clear that we can either reduce or increase blindness at the startup stage--the figure given above for survival to age five (48%) has been remarkably consistent across time. The survival rate for new firms, that is, doesn't appear to vary much founding year. There is some variance by sector but again, the survival lines within each sector are rather consistent, so it's not clear how we could either raise or lower the survival line. Of course, if survival rates have been consistent for thirty years, then perhaps the Blind element is neutralized: there is a 50-50 chance your firm will still be around five years from now.
Now, to Variation. Here, you would simply want to increase the number of new firms that are founded each year, with the expectation that trying more new variations would lead to more "good" things being selected and retained in the economy. An increase here means an increase there. I am sympathetic to this strategy, but I'm unclear as to how we do it. Firm formation in the United States has been pretty steady for two or three decades and the question of how we increase it is not so simple. Things like awareness and lowering barriers to entry are probably our best bets but these will vary by sector and geography and characteristics of the founder. All of this assumes, of course, that a basic increase in startups (more variation) will result in an increase in innovation and growth. And this assumes that we would see a similar proportion of innovative ideas and potentially successful firms in a larger pool of variations--is that a valid assumption?
Selection of startups occurs through a variety of mechanisms. One, of course, is the market itself: you start a new firm and quickly find out whether or not it will selected in or out. If we increased the number of startups (increased V), then conceivably our selection mechanisms could remain the same, simply working on a larger population of firms. If, however, V remained constant, we might want to intensify S by looking more carefully (somehow) for promising ideas or "sure-thing" innovations. I suppose this is the role played by venture capital firms and accelerators such as Y Combinator. They have many entrepreneurs approach them and apply to them, but only select a few for funding or developing. Those that they do not select still go on to start new companies, so the claim of these particular selection mechanisms is that they are intensifying S so as to increase R: selecting the "best" of V, those with the most potential for retention and propagation by the market. As an overall strategy to enhance Selection, we would look to increase market competition in general, removing protective barriers around certain industries and firms, for example. A perennial complaint about some European economies (and conclusion of numerous McKinsey reports) is that they are not as competitive as the United States--stultified selection suppresses innovation and economic growth. It's also conceivable that simply increasing V would naturally increase S (they are, after all, multiplied by each other)--more firms overall would mean more firms competing.
These notions of Selection, however, presume that any selection process, whether in biological evolution or in free market competition, is an optimizing one--that the "best" organism or population or idea or company always beats out inferior competitors. Adaptive fit, after all, implies such optimization. Yet we know that natural selection is only one way in which genes and organisms are winnowed and propagated. The role of accident and randomness in evolution cannot be forgotten: we like to think of dinosaurs as having met their proper evolutionary fate because they were all slow and dim-witted. But many evolutionary theorists have pointed out that, if a meteor or volcanic explosion did the dinosaurs in, then that isn't necessarily "natural selection" in terms of adaptation and competition. It was an exogenous event and the emerging population of smaller mammals happened to be better suited for survival. So, yes, an exogenous event "selected" out dinosaurs, but it wasn't necessarily the "optimizing" path we like to imagine. The same applies to the selection process in terms of firms and ideas: Silicon Valley bested Boston and Dallas because it had a better ecosystem, the selection process was more optimizing. But what if William Shockley's mother lived in Dallas, not Palo Alto? What if Frederick Terman had not contracted tuberculosis and had ended up returning to MIT? I realize these are entirely speculative and that the obvious riposte is, 'Well, that's just how things happened.' My point is simply that we shouldn't assume that Selection always implies optimizing; human behavior and group dynamics are such that the economic process contains plenty of satisficing behavior. (We also shouldn't forget that an entity such as a firm can become over-adapted to certain circumstances and thus too sessile to change; selection could work too well.)
Finally, how would we enhance Retention? What would this mean? It could entail somehow promoting those firms that are selected--say, those that survive to age six--via certain rewards such as a retroactive tax credit or something like that. Or, it could mean favoring those firms that grow rapidly in their first few years and have rapidly passed through V and S and we want to enhance their retention and propagation. It could mean reducing barriers to "scale," whether in the form of regulations, corporate taxes, whatever. (I continue to maintain, however, that the effect of certain taxes on entrepreneurship is not nearly as straightforward as some might like to believe.) Maybe we think of Retention as going public, in which case perhaps changes need to be made to Sarbanes-Oxley. Over the past few years, around 80% of VC exits have been acquisitions, not IPOs, and many of the companies coming out of accelerators are acquired by companies such as Google.
In any case, I don't know if this has added anything to the general discussion of entrepreneurship and economic growth or not. If we think about startups through the BVSR model, there are probably certain areas in which we can make changes to enhance the economic impact of startups, although some of them steer quite close to "picking winners." In general, as I said, I favor increasing V, but I'm as yet unclear as to how we go about doing this. Importantly, increased Variation should apply to firms of all types, not simply in favored sectors or those sectors we think (or would like to think) represent promising areas of innovation. Firm formation and innovation are compounding phenomena, so increasing the overall level of startups should (emphasize, should) raise our rates of innovation and growth, and this should be true whatever sector of the economy we are discussing. Information technology has been hugely important for American productivity, both in its production and its use in sectors like retail. We needed IT, but we also needed all those new retail outlets and supply chain innovations for the IT to become productive. It's possible that a BVSR-type of analysis in, say, 1995 might have concluded: we need more IT startups and fewer new retail stores. The economy might not have performed as well as it did.