Growthology

President Obama Promotes Entrepreneurship

In case you missed it, here is President Obama in the State of the Union speech last night, underscoring the important role of entrepreneurs:

It means we should support everyone who’s willing to work, and every risk-taker and entrepreneur who aspires to become the next Steve Jobs. After all, innovation is what America has always been about. Most new jobs are created in start-ups and small businesses. So let’s pass an agenda that helps them succeed. Tear down regulations that prevent aspiring entrepreneurs from getting the financing to grow.

This may have been a reference to the Startup Act, versions of which have been introduced in both the House and Senate. Even so, any mention by the president of the vital role that new companies play in economic growth is noteworthy, especially because, as many claim, public celebration of entrepreneurs is an important cultural attribute.

The Ongoing Debate Over Small Business and Job Creation

My Kauffman colleague E.J. Reedy wrote an insightful post at Data Maven on Carl Bialik's somewhat disappointing Numbers Guy column over the weekend about job creation by small business. These come on the heels of Charles Kenny's well-done essay in Bloomberg Businessweek about the various nuances involved in counting job creation by business size and the distortions that often arise.

We continue to do research and analysis on these issues--one of the exciting things about entrepreneurship research is that every time we learn something new, we realize how much there remains to understand. What's clear, and what E.J. underscores, is that we should not be satisfied with aggregate data. They help us penetrate to one level of understanding, but aggregate data also introduce another slew of distortions and obscurities. E.J. pointed out that firm age and local/non-local are two important distinctions. I would also add the sectoral lens--the more time I spend with the numbers the more I'm convinced that sectoral breakdowns explain a significant share of what we see in terms of new and young businesses, small businesses, job creation, and churn. There is still quite a bit of work to do, however, and I'm happy to disprove my own hypothesis.

Why Do We Expect a "Normal" Recovery?

The thrust of all debates over economic policy and government debt these days seems to be that this recovery ought to look like previous recoveries. We are insistent that unemployment fall faster, jobs be created more rapidly, consumption rise quickly, and economic growth pick up steam. All desirable outcomes, unquestionably. But we keep ignoring the factors that made the "Great Recession" of 2007-2009--and, accordingly, also the subsequent recovery--an outlier in terms of recent historical experience.

This is only natural, of course; our only comparative frames of references are other recessions since 1948 and, in terms of personal experience, the recessions of 2001, 1990-1, and the early 1980s. But this recessions was clearly of a different order, for a variety of reasons. For starters, the expansion that preceded it was one of the weakest--if not the weakest--since World War Two, as measured by job creation, per capita income, and the employment-to-population ratio.

Of the growth that did take place, we obviously know now that a significant portion of it was distorted by all things housing bubbled-related: construction, real estate, finance, etc. The plural of anecdote is not data, but I find Paul Kedrosky's parable of the highway ladder debris amusingly illustrative. Looking at Statistics of US Business data from 1998 to 2006 reveals that, of the net increase in the total number of firms of 442,000, fully one-quarter of that growth was in Construction (NAICS two-digit industry code). The only larger share went to the Professional, Scientific, and Technical Services (PSTS) sector, which includes businesses in R&D testing, ad agencies, computer design services, engineering services, law offices, accoutants, payroll services, and so on. Overall, a good sector in which to experience growth; yet, both the Construction and PSTS sectors are comparatively small job creators because average employment per firm is nine and ten, respectively, compared to the all-sector average of about twenty.

We keep wondering why job creation isn't automatically bouncing back to expansionary levels, and blaming sluggish job figures on fleeting factors like discretionary government policy. But because job creation in the prior expansion was low and because the driver of job creation--consumption--was built on sand (i.e., housing bubble), we shouldn't expect it to come roaring back. The employment-to-population ratio barely budged from 2002 to 2007, a historical first. The Federal Reserve of San Francisco, moreover, has calculated that personal consumption took a hit equivalent to about $175 per month per person as a result of the recession and is nowhere near returning to pre-recession levels. This is due, in part, to the completely unsustainable level of consumption the US enjoyed in the last decade. We shouldn't expect a return to that.

This points to the deeper factor underlying the slow recovery: this recession was marked by a financial crisis. And, as Reinhart and Rogoff have convincingly showed, post-financial crisis recoveries are very, very slow. Combine that with deep-seated challenges facing the American economy--geographic asymmetries, skills mismatches--and you can't help feeling that this is going to take a while.

You Should Overreact to the Employment Report

The normal advice from sage, two-handed economists is that people shouldn't overreact to one bit of bad news.  The wise guys on Wall Street snicker at the day traders with lines like, "Two data points make a trend!"  So count on lots of punditry that today's employment situtation isn't as bad as it looks, especially when the Bureau of Labor Statistitcs comments that the uptick in the unemployment rate is statistically insignificant. With friends like these ...

This time, if your instinct is not to overreact, I'd urge you to reconsider.  This month's report on May activity shows that the April report wasn't a fluke. And it confirms that the entire last year of lackluster labor market equilibrium isn't some unique aspect of a unique recovery. It's time for some overreaction.

• The unemployment rate is now 9.1 percent, up from 8.8 percent two months ago.  That's important.  Although research shows the U rate is more reliable than the payroll employment numbers over the long term, it might still suffer from a one month blip due to turnover in the survey sample.  But a second increase in two months all but nails the coffin shut. By that I mean that the U.S. is experiencing if not a double recession then a historically stagnant recovery. 
• The May payroll gains of 54,000 are nothing short of stunning. The U.S. lost 8 million payroll jobs during the recession.  Adding 54,000 a month will get the nation back to normal ... never!  A recovery in the job growth number needs to average 400,000 a month to achieve the simplest recovery in 2.5 years.  As it stands, the BLS commissioner is trying to emphasize the good news that the average payroll growth has been 220,000 for the previous 3 months. Let's be clear: that is not a silver lining, it's an indictment of the current course.
• The long-term unemployed increased in May by 361,000.  Add that to the disturbing uptick in weekly jobless claims, stuck north of 400,000 a month.
• The labor force increased by roughly 1.2 million a year before the recession, peaking at 154.7m in Dec 2008.  Two and half years on, it is 153.7m (a million souls fewer).  Another way to think of this is that the labor force has roughly 4 million in extra-normal slack, people who have officially left/not joined the labor force but will come in as the economy recovers.  This is a recipe for the unemployment rate to rise as things get better, but what we are seeing is the unemployment rising even as conditions slip.

So who is to blame?  It's easy for some to blame the Federal Reserve, but I think that is a foolish debate.  Monetary policy, inceed macro in general, has limits to its effectiveness.  The Fed can only compensate for a broken fiscal policy for so long, and it appears the U.S. has reached that point. Think of money supply as blood supply.  You can pump gallons of fresh blood into a sick lion, and she ain't gonna roar.

Growing Pains

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.

Is American Education Getting Worse?

No, says Kauffman senior fellow Ben Wildavsky in an outstanding essay on Foreign Policy. And forget that myth about the rest of the world leaving us in the dust:

If Americans' ahistorical sense of their global decline prompts educators to come up with innovative new ideas, that's all to the good. But don't expect any of them to bring the country back to its educational golden age -- there wasn't one.

...

In this coming era of globalized education, there is little place for the Sputnik alarms of the Cold War, the Shanghai panic of today, and the inevitable sequels lurking on the horizon. The international education race worth winning is the one to develop the intellectual capacity the United States and everyone else needs to meet the formidable challenges of the 21st century -- and who gets there first won't matter as much as we once feared.

No one would deny that education is America can be vastly improved, but part of Ben's point is that educational inequalities within the United States matter much more than the ostensible gaps between countries. It's hard to avoid the conclusion, noted by Brink a couple of weeks ago, that education is at the root of many of America's economic difficulties. But arguments premised on alarmism are not an answer.

Raising Productivity Growth

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.

How this Recovery Measures Up

Good slide deck from the Economic Cycle Research Institute (ECRI) on comparing the indicators in this recovery to past recoveries. Of particular interest is the "stair-stepping down" of the intensity of expansions over the past fifty years (slide 12).

Job Creation Strategy: Statistics?

The Kauffman Foundation's E.J. Reedy on how improved data collection can enhance job creation:

As the government and other nonprofits implement more local programs to spur job creation or small business development, data are desperately needed to track local trends in business outcomes and conditions. It’s because of this that politicians tend to be more interested in supporting programs that can help provide independent, meaningful, and timely data on job creation in their regions. The statistical community should recognize this and strengthen their collections before politicians become alienated consumers of private data.

Read more of this insightful piece here.

The Great Stagnation?

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.

State of the Union Word Cloud

 

And, according to the New York Times, President Obama used "innovation" 9 times (compared to two in 2009), and "government" 18 times (compared to seven in 2009).

Some Puzzles about Entrepreneurship and Entrepreneurial Capitalism

The standard narrative about the American economy in the late twentieth century typically runs as follows: after four decades of quasi-statist capitalism (the 1940s through the 1970s) that brought the United States to the brink of economic ruin, the economy experienced an entrepreneurial explosion around 1980. The economy moved from the dull bureaucratic capitalism of the "Organization Man" to the exciting entrepreneurial capitalism of high-technology and, accordingly, more robust growth and productivity. Without questioning the importance of entrepreneurship to economic growth, I'm beginning to wonder about this.

For starters, let's take recent technological history. The information technology revolution that is associated with the 1980s and 1990s was born in the 1950s and 1960s, emerging out of government-funded research performed at universities and large company laboratories. We could probably mark the start of the IT revolution at the founding of Fairchild Semiconductor 1957 or, perhaps, the founding of Intel in 1968; Microsoft and Apple followed in the mid-1970s. Other companies typically associated with this entrepreneurial rebirth include FedEx and Southwest Airlines, which were also started in the late 1960s and early 1970s. Even within the confines of the conventional narrative outlined above, we can trace the roots of entrepreneurial capitalism to the final stages of bureaucratic capitalism, a pattern that aligns with other models of technological revolutions and transitions. In his wonderful book, The Age of Abundance, Brink Lindsey (who is now a Senior Fellow at the Kauffman Foundation), connects the counter-cultural ethos of the 1960s with the subsequent entrepreneurial revolution in business.

The typical narrative of entrepreneurial capitalism is also usually supported by reference to either changing rates of overall entrepreneurship or the high number of initial public offerings (IPOs) in the 1980s and 1990s, as well as the explosion of alternative forms of financing, from junk bonds to venture capital. And, indeed, according to at least one strand of Census Bureau data, the absolute number of new incorporations did increase dramatically from the 1960s to the 1970s and again to the 1980s and 1990s. New company listings, moreover, rose from an average of 156 per year from 1973 to 1979, to 549 per year from 1980 to 2001. From 1980 to 2001, in fact, newly listed firms comprised 10 percent of all listed firms in any given year. Venture capital, too, increased by several factors from the end of the 1970s and despite reverting from its astronomical heights in the late 1990s, VC remains at historically elevated levels.

Over the last several months, however, I happened to come across several pieces of evidence--some new, some older--that would appear to contradict the typical narrative. (I am not claiming any particular insight here, nor do I intend to mean that the U.S. economy was somehow "better" in the 1960 and 1970s than today. I heartily endorse Brink's arguments in "Nostalgianomics" on this point.)

Let's start with the most basic empirical information: the number and rate of new business formation. When the Census data cited above are expressed in per capita terms, the apparent doubling of firm formation disappears: the population doubled, bringing new business creation along with it without a corresponding increase in the rate. Indeed, we have published two papers on the puzzle of relatively steady levels of entrepreneurship in the United States, both across the past thirty years (the purported period of extreme entrepreneurship) and, potentially, across the entire twentieth century. In fact, firm formation fell from the 1980s to the 1990s and then flattened, neither falling nor rising. Per capita rates of new business formation today are actually quite similar--and certainly no higher--to those in the 1940s and 1950s, the ostensible high tide of bureaucratic capitalism.

What about IPOs? Using historical data from Gompers and Lerner and more recent data from Fama and French, here are the average annual IPOs for various time periods back to 1935 (the groupings are dependent on the authors' work, not my own manipulations): 

1935-1949:    11

1950-1959:    45

1960-1972:    233

1973-1979:    37

1980-1989:    328

1990-2001:    413

The averages obviously mask variability, but it is generally true that after 1980 the United States saw sustained levels of historically high numbers of IPOs. But it is certainly not true that the era of bureaucratic capitalism was without entrepreneurial excitement. From 1959 to 1962, the average number of IPOs per year was 224. From 1968 to 1972 it was 388, a number much closer to the supposedly go-go 1990s than even the 1980s.

At the same time, the IPO explosion after 1980 brought its own issues. Fama and French found that the "decline in the cost of equity capital for new lists" meant that weaker firms could now go public. In particular, in the 1980s and 1990s the distribution of revenue growth across newly-listed firms skews to the right, meaning higher growth. Meanwhile, the distribution of profitability skewed left, meaning lower rates of profitability. Survival rates of newly listed firms also fell over this time period. As they stated: "Basically, the evidence says that weaker firms and firms whose expected payoffs are further in the future become viable candidates for public equity financing." This echoes other research finding, since the late 1970s, a dramatic rise in growth rate volatility among publicly-traded companies but a fall in the volatility of privately-held firms--nearly to the point of convergence, in fact. It is true as well that volatility among our largest companies, the Fortune 500, has risen and not quite one-fifth of today's Fortune 500 companies have been founded since 1980. But this is more an indication of turnover among existing companies, including mergers and acquisitions, rather than new firm entry. And even if more companies fall off the list, it doesn't mean they fail; it just as likely reflects the relative rise of other companies.

(Some of this also calls into question the role of high-growth firms. As the above comments indicate, rapid revenue growth does not necessarily mean profitability. This corroborates other work that examines the Inc. lists of fast-growing companies. I am a huge fan of the Inc. data and I think much more can be done with it, but we shouldn't imagine that high growth in revenues tells us anything about economic impact or long-term success. Presumably it should, but it apparently does not. I have written elsewhere that high-growth firms are neither as interesting nor important as they are typically thought to be. If the underlying dynamics of firm formation and competition are reasonably healthy, we should expect to see high-growth firms as epiphenomena of those, not necessarily drivers in themselves.)

In any case, what does any of this mean? Let's review. During the period of entrepreneurial capitalism, we have seen no increase (yet no significant decrease either) in levels of firm formation, but a larger number of IPOs and greater volatility among publicly-traded firms, indicated particularly by dispersed growth rates and profitability. This dimension in the public markets is, in part, an effect of greater availability of financing. Is what we call entrepreneurial capitalism really just a reflection of public-market volatility, itself a reflection of the rising role of finance in the American economy over the past thirty years? 

I should point out, again, that none of this is meant to imply that the last thirty years were somehow worse than the middle part of the twentieth century. Nor is it meant to exclude the dramatic changes in technology over the past three decades. Indeed, high-tech companies likely account for much of the public-market volatility. At the broader level of aggregate firm formation, sectors such as food service, administrative services, health care, and professional services (in particular lawyers) tend to predominate, particularly among high-growth firms. My points here are not a value judgment on the types of companies that are formed. But it appears that there is still quite a bit about entrepreneurship--its trends, its composition, its impact--that we do not understand. And, should we be on the cusp of an entrepreneurship boom--whether because of technology, changing economic factors, demographic factors, whatever--it remains to be seen whether, in the context of existing structural factors, this will shift us to a different neutral state. And, again, we have not even touched the impact of new companies yet; a much more extensive treatment than I have given here will also layer on technological change. So much goes on beneath the surface of aggregate entrepreneurship levels, of IPO activity, of growth and profitability, that it is difficult to make blanket claims about capitalist typology.

I could, of course, be wrong.

The Budget Deficit isn't a Math Problem

I'm as encouraged as the next Serious Person to talk about the intricacies of budgetary math.  What do you non-economists think we do on Friday nights, anyway.  So the report of President Obama's budget commission is the perfect Thanksgiving feast.  For an abbreviated summary, I recommend Kevin Hassett, Felix Salmon, and the pointers provided by the ever reliable Mark Thoma.  For fun, I'll provide snippets from each of the three, and challenge you to guess whose is whose:

A ... On the other hand, bold ideas in terms of new taxes — carbon taxes, wealth taxes, Tobin taxes, consumption taxes, you name it — are nowhere to be seen: as Jonathan Chait says, this is “a plan that’s tilted, overwhelmingly, toward Republican priorities”. Which means a large dash of wishful thinking, a bunch of tax cuts (!), and even a cap on the amount of tax revenues that the government can bring in. How that’s meant to help reduce the deficit I have no idea.

B ... Beginning a tax overhaul by closing loopholes is a strategy that should appeal to those on the political left, the ones that so far are voicing the loudest criticism of the Bowles-Simpson plan. A chart released with the plan shows that eliminating all tax breaks, other than the refundable credits targeted toward the poor, would reduce the after-tax income of those in the top 1 percent of the income distribution by almost 14 percent, those in the middle quintile by about 4 percent, and those at the bottom by only about 1 percent.

C ... One third of of the deficit reduction under Bowles-Simpson is from revenue increases, and two thirds is from spending cuts. The above is about tax cuts, but the spending cuts will, in the end, likely hit lower income households harder and end up being regressive as well.

My take is that the deficit commission is fine economics. I do think capping the amount of federal tax revenue is key, so I like that aspect greatly.  Such a guarantee is a minimum to get a serious political conversation.  Capping federal spending, which the report also endorses, is also essential.  But I think the whole of the entrepreneurial community won't like treating capital gains as income.  The public might understand this better if we just described cap gains as startup gains.  Or maybe growth gains.  As Uncle Miltie says, you tax more of something, you get less of it.  Do we really want fewer startups?

That said, I tend to view the process skeptically.  A good friend on Capitol Hill laughs every time a commission is announced.  There's simply no better way to play political dodgeball than to assemble a blue ribbon commission, which kicks the issue down the road a year or more.  My own skepticism is rooted in one of the Kane mantras:

The Budge Deficit isn't a Math Problem.

I once had a dream that I would come to Washington, DC and share my great ideas with the wise men and women in Congress.  "Eureka!" they would reply.  "Here is a Good Idea!"  Time has solved that idealistic illusion.  Congress knows the math.  They can appreciate the many ways that 1 + 1 =/= 14,750,200,000,000 (the current U.S. GDP).  If it were just a math problem, legislators would have solved it years ago.  No, the addiction to a budget deficits is a Rules Problem.  To solve it, the nation has to change the rules.

Loyal readers know that I believe the optimal rule change will be the national adoption of Constitutional amendments. Balanced budget. Max Tax. Spending Limits.  Any one will do, but all three would be even better. But maybe other rule changes would work better, even faster. Some believe that statutory rules like Pay-Go (I recall Nancy Pelosi committing the House to that one) or Gramm-Rudman or shaking up the Committee assignments (HT Chris Edwards). Edwards also argues that a spending cap could be instituted legislatively. Maybe.  But I don't trust the long-term viability of anything not carved in Constitutional stone, not with stakes this high.

Remember, the Constitution is not a living document.  The Constituion is a written document, and those words have eternal meaning.  I haven't lost that idealistic faith just yet.

No Way Out (of the recession)

Once upon a time, Kevin Costner made great movies.  Like "No Way Out" the 1987 Pentagon thriller that co-starred the always superb Gene Hackman.  The title resonates with the lingering pessimism people are feeling about the U.S. 

The Friday jobs numbers confirm that the jobless recovery is a harsh reality.  History will tell (along with some robust econometrics, no doubt) whether the policy responses were effective, counterproductive, or just plain irrelevant.  But the theme at this moment is surely a sense that nothing is working.  The U.S. economy is stuck in a pattern of high unemployment and there is no way out. 

A microcosm of the macro predicament is the state of the venture economy.  Once upon a time, young startups planned on building valuable companies bound for a public offering.  But somehow or another, the outlet for new offerings shriveled.  Some argue the cause was the ill-conceived Sarbanes-Oxley law.  Others say the previous IPO market was a bubble.  Regardless, the new normal is a business world where startups have, essentially, no way out. 

A new survey of tech executives and venture capitalists confirms the sentiment.

The survey was done by DLA Piper and can be read in its entirety here (when it gets released - growthology comment). ... The most surprising stat: A whopping 72% of respondents said that they no longer viewed an IPO as the optimal exit for a venture-backed company. Let me repeat that: Only one-quarter of the VCs and Valley executives surveyed said their goal when starting or funding a company was to take it public.

Before we shed too many tears for the titans of Silicon Valley and the lower probability of whipping up billion dollar IPOs after a few years of toil, we should remember that the biggest victims of the weak economy are lower-income workers.  Econbrowser's Menzi Chinn compiled a must-see chart:

In researching statistics for our forthcoming book, Lost Decades, Jeff Frieden and I stumbled upon this study by Andrew Sumand Ishwar Khatiwada, with Sheila Palma, of Center for Labor Market Studies at Northeastern University. They characterized the mid-2010 employment situation as "A Truly Great Depression Among the Nation's Low Income Workers Amidst Full Employment Among the Most Affluent".

Americans making less than $20k incomes per year have an average unemployment rate of about 26 percent, which is more like 39 percent when factoring in the underemployed. To me, the implications of this are obvious.  The minimum wage is failing to protect workers as promised.  Don't forget, the Congress raised the minimum wage three times in the teeth of the recession, pricing exactly these lower-income workers out of jobs.  Is there really a mystery here?  Other worker protections, like extending unemployment insurance way beyond the norm, like new mandatory benefits, like promised high tax rates on "rich" entrepreneurs who do all of the job creation, are backfiring.

Although the poisonous political atmosphere of the last decade has fueled the populist policies gumming up economic growth, I remain hopeful tha the looming divided government of 2011+ will be like the 1995-2000 era when Democratic President Bill Clinton worked with Republicans in Congress to truly reform economic policy.  But when I'm not hopeful, I remember the epic line of Lieutenant John J Dunbar (Dances with Wolves), paraphrased here:

Major Fambrough: You wish to see the [production possibilities] frontier?

John Dunbar: Yes sir, before it's gone.

 

Why Not a Market for Advancing Innovations out of Universities?

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.

Kauffman Economic Outlook Q2

Read the Kauffman Economic Outlook Q2 2010: A Quarterly Survey of Leading Economics Bloggers (PDF)  

Here are the first few charts:

 
  

3.2 percent ain't good enough

The advance number for Q1 growth was released today: 3.2 percent (this link is to a WSJ summary of economist opinions).  Three-point-two would be good in normal times, but it's not enough to catch-up to where the U.S. economy "should" be. 

I'm skeptical this is a solid recovery. I'm skeptical there won't be a double dip. Why?  Because interest rates are very low and have to rise sometime soon, because federal spending stimuli are fading, because I believe in a place called California, and because so much of the durable consumption seems driven by cut-rate deals (Toyota in Q1 offered zero-percent financing for the first time in history). Thin ice.

This would be a good time to reread Mankiw's argument that this is a Unit Root recession, not a Trend Stationary recession. A rebound to normalcy would be nice, but we all know better than to believe the housing bubble defined normalcy. It's time to shelve fantasies that a stimulus, any stimulus, can or should get America back to artificial prosperity.

Who Declared War on Entrepreneurs?

Nick Schulz over at the Enterprise Blog draws our attention to an apparent crackdown by the IRS on the flexible employment arrangements used by many independent contractors and small businesses. It's not clear what impact this will have but, anecdotally at least, there have been reports that many new and young businesses in this recession have been turning more and more to freelancers and contractors. And we've seen the average size of new companies shrink over the past few years by about two employees--as noted in the story above, this likely indicates increasing use of such flexible arrangements.

Put this together with the anti-angel provisions in the Dodd bill (which I think may have been slightly diluted recently), and it seems as if someone has declared a war on startups. Which is, in other words, a war on job creation and economic growth.

The Accumulation of Firms and the Predominance of New and Young Companies

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.

More on Friedman

Here is another, albeit similar, take on one particular response to Thomas Friedman's Easter column celebrating startup companies. By the way, while you visit the PPI website, be sure to read Michael Mandel's policy memo on why the jobs crisis may well be an innovation crisis.