In Venture Capital, Birds of a Feather Lose Money Together

In Venture Capital, Birds of a Feather Lose Money Together

The more affinity there is between two VCs investing in a firm, the less likely the firm will succeed, according to research by Paul Gompers, Yuhai Xuan and Vladimir Mukharlyamov.

by Carmen Nobel

To illustrate the old adage that birds of a feather flock together, there may be no better example than the venture capital industry.

A recent study finds that venture capitalists have a strong tendency to team up with other VCs whose ethnic and educational backgrounds are similar to their own. Unfortunately, that tendency turns out to be bad for business.

“At the early stage of a company, you want the people around the table to challenge each other.”

In the paper The Cost of Friendship, three Harvard researchers show that the more affinity there is between two VCs who co-invest in a new company, the less likely it is that the company will succeed.

“Much of the homophily literature in business research talks about the positive benefits of working with people who are similar to you—ease of communication, comfort level, and the like,” says Paul Gompers, the Eugene Holman Professor of Business Administration at Harvard Business School, who cowrote the paper with HBS Associate Professor Yuhai Xuan and Vladimir Mukharlyamov, a graduate student in the Economics department at Harvard. “What we show is that, in this context, the effects can be quite negative.”

The team set out to answer a few key questions: What specific characteristics influence individuals’ desire to work together on an investment deal? And given that influence, how does affinity affect investment performance? Do common characteristics lead to better communication, which then leads to better decisions? Or does like-mindedness lead to narrow decision-making, to the detriment of the deal?

Working with people similar to yourself can lead to poor decisions.
Photo: iStockPhoto

The research began with a database of 3,510 individual venture capitalists and their investments in 12,577 companies between 1973 and 2003. Over the course of six years, the research team collected detailed biographical information on each VC, including ethnicity, educational background, and employment history. They then looked at who had invested with whom, and what those co-investors had in common.

Across the board, the researchers found that venture capitalists tended to co-invest in deals with other VCs who possessed similar characteristics. This was true regardless of whether the similarities were ability-based or affinity-based. For example, two VCs who graduated from the same undergraduate school were 34.4 percent more likely to collaborate on a deal than were two VCs from different alma maters. And the probability of collaboration between VCs increased by 39.2 percent if they were members of the same ethnic minority group.

The data held up with what Gompers had observed qualitatively in his two decades of studying the venture capital industry. “There are strong affinity groups with Indian venture capitalists and entrepreneurs and with Chinese venture capitalists and entrepreneurs,” Gompers says. “And there’s sort of a cabal of Jewish entrepreneurs and VCs as well.”

The team then examined how these similarities had affected the outcomes of the portfolio companies in the study. (For the purposes of the paper, a successful outcome was defined as one in which a company eventually filed for an initial public offering.)

They found that the probability of success decreased by 17 percent if two co-investors had previously worked at the same company—even if they hadn’t worked there at the same time. In cases where investors had attended the same undergraduate school, the success rate dropped by 19 percent. And, overall, investors who were members of the same ethnic minority were 20 percent less successful than investors with different ethnic backgrounds.

It dawned on the researchers that affinity might make it easier for one venture capitalist to guilt-trip another into making a bad deal—doing a favor for a friend. “We thought it could be that they only syndicate the deals to their friends that they can’t get anyone else to do,” Xuan says.

To test for that possibility, the team assessed the 12,577 investments according to measures that had proven to be indicators of future success, according to previous research. Such indicators included whether a company’s founder had a history of founding successful companies, the stage of the portfolio company (risky early stage versus less-risky later stage), and how much media attention the company had received at the time of investment.

Controlling for these factors, they found that the quality of the deals was not apparently affected by co-investor affinity. In other words, birds of a feather did not necessarily pick worse investments than birds of different feathers on day one. “It’s not like we invest into a deal that’s bad to start with, and therefore we get a bad outcome in the end,” Xuan says.

Rather, the lack of success among similar investors seemed to lie in the decisions that followed the investment.

In addition to granting cash, venture capitalists are heavily involved in hiring or firing the CEO of the portfolio company, choosing a board of directors, devising an overall strategy, identifying potential partners, and so on. Indeed, the researchers found that the negative affinity effect was strongest in early-stage deals, which generally require more input from investors than do later-stage deals.

“[The] lower likelihood of success of co-investments between venture capitalists that share similar characteristics is triggered by them making inefficient decisions or even mistakes that they would otherwise avoid,” the researchers write in The Cost of Friendship.

They attribute this inefficiency to “groupthink,” the psychological phenomenon in which members of a group make poor decisions because they fail to consider viewpoints other than their own. “When you are really familiar with each other, you tend not to go outside of your circle to get an outside opinion,” Xuan says.

The findings are in line with some organizational behavior studies, which have found that that work groups perform better when members learn from one another’s disparate experiences. “I think this carries over to venture-funded startups, in which having a diversity of venture capitalists around the table is actually critical to their success,” Gompers says. “Take two people who once worked at Google, who went to Harvard Business School, and who are Indian American. They probably look at things in a very similar way and are unlikely to challenge each other. But at the early stage of a company, you want the people around the table to challenge each other.”

Gompers and Xuan make a point of sharing the finds with students in the MBA program at HBS, many of whom pursue careers in the venture capital industry. In fact, people with Harvard MBAs make up 24.4 percent of the professional ranks at venture capital firms in the United States, according to a study by PitchBook. A network that powerful must beware the power of groupthink and collaborate with other networks, the professors advise.

“Students come to HBS because, in addition to having access to great faculty like Yuhai, they get the opportunity to interact with other students who are extremely talented and successful,” Gompers says. “And of course they should continue to tap this network.

“But it’s likely that if you’re an HBS MBA, you think like other HBS MBAs, because you took the same courses from the same professors. And it’s important for students to realize that it might be useful to have a diversity of people around the table when you make investment decisions or you’re working on new ventures. That, at least for me, is an important prescriptive element of the paper.”


Explaining China’s Crash

Explaining China’s Crash

After a decade of massive growth, China’s stock market began a precipitous summer slide that that hasn’t slowed yet. Dante Roscini explains what’s deflating markets worldwide.

by Christina Pazzanese

After more than a decade of nearly can’t-miss growth, China’s stock market began a precipitous summer slide that has spooked investors worldwide.

In July, the Shanghai composite index dropped 15 percent from June, prompting the People’s Bank of China to devalue the yuan by 1.9 percent in mid-August, the biggest currency adjustment in two decades. But continued trading volatility climaxed on Aug. 23 in what many have called China’s “Black Monday.” Shanghai stocks dropped by 8.5 percent overnight, their steepest single-day decline since 2007. Since June, China’s stock market has fallen 38 percent.

As the world’s second-largest economy, China’s crash ripped through world markets, including Japan, Hong Kong, Europe, and the United States, as uneasy investors instigated historic single-day sell-offs.

Early this week, the Chinese government reportedly arrested nearly 200 people, including corporate executives, government officials, and journalists, for allegedly spreading false rumors online about the market’s stability. And in a turnabout, authorities also announced they will not institute more interventions to rescue the still-shaky economy, as they had pledged.

Dante Roscini (HBS MBA 1988) is a professor of management practice at Harvard Business School. For two decades, he ran equity capital markets for Goldman Sachs, Merrill Lynch, and Morgan Stanley. His casework focuses on international investment, sovereign debt, monetary policy, and central banking. Roscini spoke with the Harvard Gazette about China’s economic woes and how they may affect global markets and investors going forward.

Christina Pazzanese: Why were so many caught off-guard by this crash? Weren’t there warning signs that this might happen?

Dante Roscini: Yes, there were warning signs. Some of the indicators in China’s economy have been slowing for some time. In January, the official data for GDP growth was 7.4 percent, the weakest in 24 years and the first time in a century that growth fell short of the official target, although by only 0.1 percent. There has been continuing softness in data regarding manufacturing activity, exports, and imports. When China made a currency adjustment, market participants took fright, fearing a much bigger slowdown than they expected. The wheels came off an over-exuberant Chinese stock market, which had surged over 150 percent in 12 months and hit a seven-year high. The consequences were felt by financial markets everywhere.

Q: Given how opaque China’s economy is, does anyone accurately know how deep or lasting this slowdown might be?

A: The official numbers must indeed be taken with a grain of salt. There is a debate in the marketplace and among economists as to what the future holds. Are we headed for a “soft landing,” a correction that can be managed so that growth, albeit at a slower pace, will continue to be solid, or are we at an inflection point and we risk a more precipitous deceleration, a “hard landing”?

China has astounded the world for 30 years by growing consistently at 10 percent per year or more, lifting hundreds of millions out of poverty. It has gone from almost nowhere to being the second-biggest economy, contributing 15 percent to the global GDP and 25 percent to its growth.

Exports drove that growth. Over the past two decades, the level of exports to developed markets from China grew on the order of 20 percent per year. And yet, the consumption of goods in those markets was only growing by about 5 percent per year. China was therefore grabbing market share; “Made in China” became ubiquitous. This was driven in large part from massive outsourcing on the part of companies in developed markets. They were moving production to China in droves because labor was cheap, so the economy grew very, very fast.

In the process of becoming the “factory of the world,” the country needed infrastructures: roads, ports, rails, plants, cities for the workers, and so on. Massive investment — rather than consumption — drove the economy. Consumption in China is still only about a third of GDP versus some 70-odd percent in the developed markets. China kept buying all sorts of goods and became the first importer in the world for a number of commodities, in the process benefiting those countries that could supply them.

The issue is that we may be reaching the limits to the outsourcing trend. For example, almost 100 percent of textiles in this country are now outsourced–you can’t go further than that. Between 50 and 60 percent of all manufactured goods in the U.S. are outsourced, and not everything is outsourceable. Furthermore, wage inflation in China has dented its competitiveness and there are other location choices. So, the question is: How much more can this phenomenon continue? Are we at the end of the era of Chinese exceptionalism?

This concept dovetails with the idea that China must change its development model in order to gain long-term economic and social stability. Economists have been saying this for a long time and the Chinese leadership is trying to rebalance growth toward consumption. In other economies where this shift has taken place before — such as the Asian Tigers — it was generally associated with lower growth since relying on endogenous progression of domestic demand is not as powerful as relying on an exogenous inflow of export-driving outsourcing.

Q: Although the U.S. and European markets seem to have stabilized for now, what are the potential ramifications globally of China’s market troubles? Could their problems spill over into other markets?

A: Certainly it was trouble from a stock market perspective. The fall was as bad as we saw here in 2001 after the dot-com bubble. The response by the Chinese authorities was extraordinary. They enacted of series of price-distorting measures that smacked of desperation. They stopped all IPOs; they asked state-owned companies to buy back their shares; they arrested traders and journalists; they banned short selling and channeled pension money into equities, effectively nationalizing a piece of the market.

Fortunately, the stock market is a rather small part of China’s economy. The total market capitalization is less than a third of GDP against the 100 percent or more in developed economies. Also, few people have their money in the stock market. The real money is in the property market; a drop in values of real estate would have more far-reaching consequences.

In terms of global spillovers, the recovery in most developed markets does not depend on exports to China. Of course, if the Chinese deceleration were to lead to a negative shock to global growth, that would be bad news for everyone. I don’t believe this to be the base case unless there is a real hard landing.

Q: Which industries and nations will feel this slowdown most acutely and how are they reacting?

A: China represents between 1 and 3 percent of the exports for the G3 economies [the United States, Germany, and Japan]. But for Australia, Chile, Korea, Singapore, and Peru for example, these numbers are more significant, anywhere from 6 to 17 percent. Some of China’s neighbors are tied to its manufacturing processes; other countries more far afield supply it with oil, gas, metals, and other primary materials. A slowdown in China could impact some of these emerging markets pretty hard. Capital has quickly flown out of them, hitting their currencies and equity markets. Europe is less exposed, though some specific sectors, such as luxury goods, will feel the pinch.

Q: What does it mean for the U.S. economy if this is China’s new normal or things decline even further?

A: The U.S. is growing solidly. This crisis is not going to be too impactful through the trade channel. Exports make up only 13 percent of U.S. GDP and exports to China represent less than 1 percent of U.S. GDP. Some U.S. multinationals might be exposed to a fall in their overseas earnings. GE stock was down 20 percent for a time on Black Monday, though Apple, for example, recently said that business in China continues to be strong. Perhaps the strongest impact would be if, as some people are asking, the [Federal Reserve Bank] were to delay raising U.S. interest rates on the basis that China’s deceleration will induce a global slowdown. That decision would clearly have an effect on this economy.

Q: What are investors most concerned about and what will they look for in the short and medium terms to feel confident again in China’s stability?

A: Investors are prone to panic, as we’ve seen; they tend to rush for the exits. In reality, China is generally in a position to manage the turbulence in its economy. First, it has a service sector that is growing fast and that will be a natural counterbalance to the slowdown in industry. Second, China is in good shape from a fiscal standpoint. They have a budget deficit target of 2.3 percent this year, but are currently in surplus. Third, they still have enormous foreign exchange reserves that will allow them to intervene in the currency market. Finally, the Chinese central bank has room for further monetary stimulus; they can lower the reserve requirement for banks from the current 18 percent of deposits and they can reduce interest rates. For example, the one-year lending rate is at 4.6 percent against practically zero here.

One thing to watch for will be how China ensures the stability of its financial system since total debt has reached 250 percent of GDP, credit has been abundant, and the size of the shadow banking system has exploded.

More, investors will judge how China is going to manage its reforms for the longer term. Are they going to foster the rule of law and give domestic and foreign entrepreneurs more confidence to invest? Are they going to allow private companies to better compete with state-owned ones? Are they going to change the system of residence permits so that people can move more freely? Will they liberalize the capital account and let the currency float? In short, markets will assess how credibly the country’s policies are evolving.

Q: How does China’s political leadership affect their economy and their ability to correctly identify and fix the shortcomings? And have these emergency interventions damaged the market’s credibility?

A: I believe that the bigger question is if the political leadership will have the courage to move from a command economy to something that looks more like a market economy. Their heavy-handed remedial actions against the drop in the stock market have damaged their credibility. This was discouraging for those investors who were hoping that Beijing was making its markets more free. A fake marketplace creates distrust and is counterproductive in the long term.

This interview has been edited for length and clarity.

Christina Pazzanese is a Harvard Staff Writer. This article first appeared in the Harvard Gazette under the title China Syndrome.


How to Predict if a New Business Idea is Any Good

How to Predict if a New Business Idea is Any Good

Professor Pian Shu tackles one of the most difficult questions in the startup world: How can you tell if a new business will succeed?

by Michael Blanding

In 2008, entrepreneur Brian Chesky and his two San Francisco roommates made the rounds of Silicon Valley VC firms with what they thought was a great idea: a website and mobile app that would allow homeowners to open their homes to strangers to sleep on their floor while traveling, in exchange for a nightly fee.

Of course, now we know the idea as Airbnb, a $10 billion business with 1.5 million listings around the world. But back then it must have seemed crazy. The liability issues alone seemed insurmountable—to say nothing of the likelihood that people would be willing to give the keys of their houses to total strangers who may or may not be serial killers.

Five VC firms rejected the nascent company’s pitch outright, and another two didn’t even bother to reply. “Investors must have thought, who would ever do this?” says Assistant Professor Pian Shu, a member of the Technology and Operations Management unit at Harvard Business School. “They didn’t know it would turn out to be a multibillion dollar industry.”

“By definition, when an investor makes an investment, it changes the probability of success”

In a new working paper, Shu asks the fundamental question that cases like Airbnb and other once unlikely, now successful startups (LinkedIn similarly got more than 20 rejections back in 2003) seem to beg: How do you tell a good idea from a bad one?

“With startups, especially high-growth startups, it’s extremely hard to predict the probability of success,” says Shu, who studies innovation and entrepreneurship. When dealing with something truly innovative, it’s difficult to compare it to anything that came before. That uncertainty makes the line between a tremendous success and a phenomenal flop a thin one.

Predicting startup success or failure also turns out to be incredibly difficult to study. When VC companies invest in an idea that later becomes successful, it’s hard to know whether that is because the idea was inherently a good one, or because the investment and mentorship made it good, a self-fulfilling prophecy.

Changing the likelihood of success

In order to come to grips with the question, Shu and co-author Erin Scott, of the National University of Singapore, needed to find a setting in which they could pinpoint the relationship between initial evaluation and future outcomes—that is, one in which experts were evaluating ideas but not funding them or advising them in a way that determined their success.

“By definition, when an investor makes an investment, it changes the probability of success,” says Shu. “You need to find a setting in which you have an evaluation of a startup at an early stage, where the evaluation is not known to the entrepreneurs and doesn’t influence the idea.”

New research explores a fundamental question: How can you
predict whether a business idea will succeed or flop? ©iStock

They found that setting in a place close to home for Shu. As a doctoral student at the Massachusetts Institute of Technology, Shu flirted with entrepreneurship herself, even applying to the MIT Venture Mentoring Service (MIT VMS)—a program that connects budding entrepreneurs to successful businesspeople to develop their ideas. Whenever an entrepreneur applies to the program, a staff member writes up a one-paragraph description of the idea in a uniform format, and then circulates it among a pool of more than 100 possible mentors, who may express interest in the idea.

Shu and Scott realized that they had the perfect laboratory for judging the success of ideas. By comparing the number of mentors expressing interest in an idea to the eventual success of that idea, they could see how well the amount of interest predicted that success. At the same time, since the entrepreneurs—who determine how much mentoring they’d like to get—had no idea how many mentors expressed interest, and since MIT offered access to the same amount of resources to each startup, that success wouldn’t become a self-fulfilling prophecy.

Uncanny ability to pick winners

Analyzing the data along with MIT VMS’s Roman Lubynsky, the researchers found that overall, in fact, the mentors had an uncanny ability to predict the success of ideas. Compared to an average venture, which attracted interest from six mentors, a venture that attracted twice as much interest was 27 percent more likely to commercialize (which Shu and her colleagues defined as having multiple repeated sales, an Amazon storefront, or a technology licensing, among other measures of success).

When the researchers drilled down into the data, however, they found some marked differences in the ability to forecast success based on the industry of the proposed idea. Expert interest was highly predictive of success in sectors that were R&D intensive, such as energy, hardware, medical devices, and pharmaceuticals. However, in non-R&D-intensive sectors, such as mobile apps and software, the ability to predict success was no better than random.

Perhaps that is because it is easier to evaluate technology that has a well-defined set of potential market needs, Shu hypothesizes. “With an industry like drug development, it’s not like you can just switch from one disease to another disease,” she says.

While R&D-intensive ventures can shift the application of their underlying technology, Shu continues, the fact they are formed around specific “intellectual assets” makes it unlikely that such shifts will be drastic. On the other hand, “mobile apps don’t require much fixed costs, so you can change the business objective more easily.” (The way Airbnb did from focusing on air mattresses in someone’s living room to renting out furnished rooms and apartments.)

Some investors believe that with early-stage companies, the idea doesn’t matter so much as the quality and passion of the entrepreneur who is pushing it; while others invest in the idea and replace the founder with a professional management team when needed. Shu speculates that with R&D-intensive companies, the initial idea plays a larger role in determining entrepreneurial success than with less R&D-intensive companies. “There’s a long-standing debate in venture financing on whether one should bet on the ‘horse’—the idea—or the ‘jockey’—the team. Our results suggest that the answer varies across industry sectors.”

The other interesting finding from the data had to do not with the industry of those being evaluated, but the industry of those doing the evaluating. The researchers found surprisingly that those within a certain industry were no better at predicting success of an idea in that industry than those outside the industry.

“We’re not saying expertise is bad,” Shu hastens to add. “We just aren’t finding any evidence that industry expertise is required for the collective group to effectively assess the commercial potential of an idea.”

Of course, the mentors assessing ideas in the MIT VMS program weren’t random—they did have entrepreneurial acumen. However, Shu contends that having a large group of people with general business experience evaluate an idea could be more effective than having a small group of people who all come from a particular industry. “That’s counter to the way VC works, where there are usually a small number of partners in a group that all specialize in one industry.”

It may be more important for entrepreneurs to quickly develop a prototype for a minimum viable product and get early feedback from a much wider group of people. That goes both for entrepreneurs honing their idea into a viable company, and for investors eager to spot the next living room air mattress company that turns into a $10 billion empire.


The Rise of Personalized Entrepreneurial Finance and Other VC Trends

The Rise of Personalized Entrepreneurial Finance and Other VC Trends

Thanks to tools such as Kickstarter, venture capital is becoming more democratized. Josh Lerner discusses crowd funding, investment trends, and other features of the changing funding landscape.

by Christian Camerota

Over the last ten years, technology has reduced entire catalogues of consumer goods to devices that fit in the palms of our hands. Phones are smarter, networks are faster, and more people have access to more information than ever before.

This democratization of access has affected different industries in different ways. Venture capital, for example, was once mostly reserved for institutional investors backed by endowments and pension funds. Today, it increasingly includes individual investors who are using technological tools and data to steer capital directly into businesses they care about and believe in.

Consider that one of those tools, crowdfunding, is on track to account for more investment money than venture capital itself by 2016, rising from just $880 million in 2010 to an estimated $34 billion by 2015.

To understand the current investment and entrepreneurial landscape, and what venture capital might look like in the future, we asked Josh Lerner, the Jacob H. Schiff Professor of Investment Banking and head of the Entrepreneurial Management unit at Harvard Business School, what trends he’s paying close attention to in the coming year.

Christian Camerota: What areas of entrepreneurship and venture capital are especially exciting right now?

Josh Lerner: One of the big changes in venture capital in the last decade is the rise of “personalized” entrepreneurial finance. That includes crowdfunding platforms like Kickstarter, individuals investing directly in companies through angel groups, and people gaining access through mutual funds, which ordinarily wouldn’t have invested in entrepreneurial companies but are increasingly doing so. At HBS, we’re spending a lot of time looking at the globalization of angel investing, focusing in on what I think is one of the secret sauces for entrepreneurial ecosystems: the creation and the role angels play in funding companies.

Technology-enabled crowdfunding provides entrepreneurs a
wider access to capital. ©iStock/merznatalia

There’s been relatively little work on angels, primarily because these are high net worth individuals who (with a few exceptions, like the Donald Trumps of the world) prefer to fly under the radar, even while investing significant amounts of their own capital in various startups. So it’s been hard to study them, and the work that has been done is through imperfect mechanisms like sending out surveys that get very low response rates. Instead, we’ve been focusing on angel groups that have systematic processes for looking at would-be companies and evaluating them.

In particular, we have a forthcoming working paper looking at 13 groups in 21 countries around the world. It poses the questions of: how do these groups work, what deals do they look at, and ultimately do they make a difference for the companies they fund?

Q: Is crowdfunding a threat to more traditional notions of venture capital?

A: There have been a lot of challenges associated with crowdfunding, reflected in the huge amount of time the Securities and Exchange Commission (SEC) has spent trying to write the regulations around it. The SEC wants to encourage individuals to make investment decisions, but they don’t want to open the door for scammers. At the same time, entrepreneurs don’t want to be required to divulge all their secrets (for regulatory purposes) because it would destroy their ability to compete. So it’s very hard to figure this out. My sense is that it’ll be a rocky road for crowdfunding, and there are going to be even more challenges for VC groups that are using crowdfunding tools.

Q: What role should the government play in subsidizing or regulating access to capital for startups?

A: I wrote a book about five years ago called Boulevard of Broken Dreams around government efforts to promote venture capital and entrepreneurship. As you can guess from the title, it’s a bit of a mixed bag. Entrepreneurship is an increasing returns activity—the more that people do it, the more likely they are to be successful at it. As such, there is a strong “public good” aspect to it and it’s important for governments to take steps to enable entrepreneurship.

It’s also the case that most government efforts to promote entrepreneurial activities have struggled to date. A lot of times, it’s probably fair to say that there are well-meaning government officials who don’t really understand the intricacies of the process and make poor policy decisions, or else political distortion leads to real issues that limit the success of these programs.

Q: The news site Quartz published a chart showing the fastest-growing areas of startup investment since 2012: Bitcoin, photo sharing, storage, space travel, transportation, hospitality. What does that say about the venture capital industry?

A: There is some ebb and flow in terms of what areas are hot or not. Biotechnology was very hot in the 80s and 90s, and then there was a long profound downturn. In the last 18 months it’s becoming really hot again with bioinformatics, which combines information technology and biotechnology approaches. Another example would be clean tech, which half a dozen years ago was red hot and is now in the doldrums. Fintech (financial technology) has come out of nowhere to be a hot area for investment. This continuous flow is part and parcel of the territory in the land of venture investment.

Q: Why has entrepreneurship become such an in-demand course and pursuit for recent MBAs?

A: I don’t think there’s an easy answer. Things in society tend to be popular or unpopular at different times, and student enrollments tend to reflect that. There was a lot of interest in structuring financial products prior to the financial crisis and then interest dropped off.

It’s also been true there’s been a change in attitudes. If you compare 2015 to 1995, there’s much greater interest on the part of the students in shaping one’s own destiny. Rather than going to work for 30 years for the same company, even if it’s a tremendous company, there’s a sense that today people want to control their own fate by being an entrepreneur.


The Globalization of Angel Investments: Evidence across Countries

The Globalization of Angel Investments: Evidence across Countries

by Josh Lerner, Antoinette Schoar, Stanislav Sokolinksi & Karen Wilson

Executive Summary — Examining a cross-section of 13 angel groups who considered transactions across 21 countries, this study finds that angel investors have a positive impact on the growth of the firms they fund, their performance, and survival, while the selection of firms that apply for angel funding varies across countries.

Author Abstract

This paper examines investments made by 13 angel groups across 21 countries. We compare applicants just above and below the funding cutoff and find that these angel investors have a positive impact on the growth, performance, and survival of firms as well as their follow-on fundraising. The positive impact of angel financing is independent of the level of venture activity and entrepreneur friendliness in the country. But we find that the development stage and maturity of startups that apply for angel funding (and those that are ultimately funded) is inversely correlated with the entrepreneurship friendliness of the country, which may reflect self-censoring by very early stage firms that do not expect to receive funding in these environments.


Pay Now or Pay Later? The Economics within the Private Equity Partnership

Pay Now or Pay Later? The Economics within the Private Equity Partnership

by Victoria Ivashina and Josh Lerner

Executive Summary — Partnerships are essential to the professional service and investment sectors. Yet the partnership structure raises issues including intergenerational continuity. This study of more than 700 private equity partnerships finds 1) the allocation of fund economics is typically weighted toward the founders of the firms, 2) the distributions of carried interest and ownership substantially affect the stability of the partnership, and 3) partners’ departures have a negative effect on private equity groups’ ability to raise additional funds.

Author Abstract

The economics of partnerships have been of enduring interest to economists, but many issues regarding intergenerational conflicts and their impact on the continuity of these organizations remain unclear. We examine 717 private equity partnerships and show that (a) the allocation of fund economics to individual partners is divorced from past success as an investor, being instead critically driven by status as a founder; (b) that the underprovision of carried interest and ownership—and inequality in fund economics more generally—leads to the departures of senior partners; and (c) the departures of senior partners have negative effects on the ability of funds to raise additional capital.


These VC Partners May Make Your Firm Less Innovative

These VC Partners May Make Your Firm Less Innovative

Startups that do business with VCs that also fund competitors may find they get the short end of the attention stick and produce fewer new products, concludes research by Rory McDonald and colleagues.

by Michael Blanding

You don’t know what you don’t know—and almost by definition new entrepreneurial ventures need a helping hand from established partners if they hope to succeed. “Startups suffer from what researchers call ‘liability of newness,’” says Harvard Business School Assistant Professor Rory M. McDonald, “which is a fancy way of referring to all of the things you don’t have as a new company—products, knowledge, connections, resources.”

The most common and effective way to make up for that lack is to find someone who can help you overcome it—most often a venture capital firm that can infuse not only much-needed cash but also expertise and advice.

In a perfect world, everyone benefits. The VC firm takes an equity stake and makes money when the company succeeds, rewarding limited partners who have invested in the VC firm.

But what happens when the interests of the VC and the startup don’t exactly align? For example, when the VC hedges its bet by investing in multiple startups that may be competitors?

A startup whose VC also invests in competitors may produce fewer new
products for market, according to recent research. Source: Kadmy

McDonald explores that question in the paper Exposed: Venture Capital, Competitor Ties, and Entrepreneurial Innovation, published in the October 2015 Academy of Management Journal and co-written with Emily Cox Pahnke and Benjamin Hallen of the University of Washington and Dan Wang of Columbia University.

The paper finds that far from being a supporting hand for startups, some partnerships can be a hand holding a company down, making it less productive than it otherwise would have been.


Investing in multiple companies in the same sector and product category may not seem so nefarious from the standpoint of the VC. “Venture capital is a hit-driven business,” says McDonald. VC firms spread their wealth around to dozens of startups, hoping to hit that one jackpot that might be the next Facebook or Google.

The problem comes when they have to choose between supporting one company over another.

Such a case caught McDonald’s attention in 2009 when VC firm Mohr Davidow made an investment in Navigenics, a direct competitor to personal genomics company 23andMe, a startup it had invested in previously. A year later, a similar case occurred when Andreesen Horowitz cut its investments in photo-sharing company Instagram after doubling down on competitor Picplz (a poor bet, as was proven by history).

In both these cases, the startups stood to benefit not only from the monetary investment, but also from the knowledge the VCs obtained in advising their direct competitor.

As it happened, McDonald and his co-authors had firsthand experience of that kind of “information leakage” in a different venue: As doctoral students at Stanford, they had the same advisor.

“Each of us knew what the others were working on before we ever talked to each other about our projects,” he says. While that indirect information sharing may be benign in the case of students, the researchers surmised it may dampen innovation among competitive companies.

To test that hypothesis, McDonald, Pahnke, Hallen and Wang looked at close to 200 medical device startups that developed products for minimally invasive surgery from 1986 to 2007. Using regulatory codes developed by the Food and Drug Administration (FDA), they were able to tell which companies were competitors in the same patient application areas (such as cardiology, oncology, or urology) and product classes.

Then, using commercial investor databases, they determined which companies were funded by the same VCs. Finally, they determined how “innovative” each company was, based on the number of new products they introduced that were approved by the FDA (averaging one product every two years).

The data showed that companies tied to a competitor by at least one VC firm in common were indeed less innovative than those unencumbered by such ties; in fact, they were 30 percent less likely to introduce a new product in any given year.

The magnitude of the effect took the researchers by surprise. “We thought it might happen, but we didn’t expect the size to be as big as it was,” McDonald says.


Drilling down further into the data, they analyzed which factors determine which companies were most likely to be helped or hurt by such ties. First off, McDonald and his co-authors hypothesized that the biggest beneficiary would be the most recent company to be funded, since it would be able to benefit from the experience of earlier competitors, while those that were first to be funded would pay the price. In the case of Mohr Davidow, for example, “it’s pretty clear Navigenics is going to be the one that benefits, perhaps at the expense of 23andMe,” says McDonald. In fact, they found exactly that: Companies that were first among their competitors to be funded were even less innovative, being 34 percent less likely to introduce a product in any given year.

Two additional factors proved to be even more crucial. The first was the level of “commitment” a VC had to a particular company, judged by the amount and frequency of funding. The same way a teacher may lavish more attention on a favorite student, the researchers found that VC firms also tended to pick favorites, which did better overall; their competitors were 55 percent less likely to introduce a product.

Equally important was a hometown advantage. Companies based closer to funders tended to do better overall; those that were farther away from a shared investor were 56 percent less likely to introduce a new product.

Finally, McDonald, Pahnke, Hallen and Wang looked at firm reputation, surmising that more respected VC firms would be less likely to redirect information between competing startups. They found just the opposite.

Companies tied to VCs in the top 25 percent of reputation indexes were significantly less likely to introduce new products in any given year. Reputable VCs weren’t more likely to invest in competing startups, but when they did, innovation outcomes were greatly diminished. In an effort to explain such a surprising finding, the researchers speculate that perhaps some of these higher-reputation firms may be using their golden image as cover to get away with more flagrant breaches of information sharing.

“We thought there might be a subset of these higher-reputation firms that are taking advantage of their prior successes to do this occasionally and perhaps opportunistically,” McDonald says.


What should startups to do to inoculate themselves from the effects of these competitive ties?

For starters, companies might benefit from looking beyond the traditional VC world to consider the wide range of funding options available—including super angel investors, micro VCs, accelerators, and incubators.

In cases where a startup does decide to go with a VC, it pays to do homework. Through social media and publicly available sources, there is more information than ever on what firms are investing in which companies, making the reputational risks for VCs investing in multiple competitors higher than it once was, and startups better able to find funders without such conflicts of interest.

At the same time, it’s not just about whether to sign with a venture capital firm or not. Says McDonald, “It’s also about what kind of VC I’m going to get—someone with a history of backing these competing firms, or someone who is going to be more focused on me.”


Venture Investors Prefer Funding Handsome Men

Venture Investors Prefer Funding Handsome Men

Studies by Alison Wood Brooks and colleagues reveal that investors prefer pitches from male entrepreneurs over those from female entrepreneurs, even when the content of the pitches is identical. And handsome men fare best of all.

by Carmen Nobel

If you’re in search of startup funding, it pays to be a good-looking guy.

A series of three studies reveals that investors prefer pitches from male entrepreneurs over those from female entrepreneurs, even when the content of the pitches is identical. Attractive men are the most persuasive pitchers of all, the studies show.

The findings are detailed in the paper Investors Prefer Entrepreneurial Ventures Pitched by Attractive Men, published in the March 2014 Proceedings of the National Academy of Sciences.

“Our paper provides concrete proof that gender discrimination exists in the context of entrepreneurial pitching,” says Alison Wood Brooks, an assistant professor at Harvard Business School who coauthored the paper with Laura Huang, an assistant professor at the Wharton School of the University of Pennsylvania; Sarah Wood Kearney, a visiting scholar at the MIT Sloan School of Management; and Fiona E. Murray, associate dean of innovation at Sloan and Kearney’s thesis adviser.

“Our paper provides concrete proof that gender discrimination exists in the context of entrepreneurial pitching”

As a behavioral psychologist, Brooks studies the situational variables that influence personal persuasion. Kearney, her twin sister, is an entrepreneur and scholar whose research is fueled by both a frustration with and curiosity about the dearth of venture capital for women. (In the first half of 2013, companies with at least one female founder secured some 13 percent of total venture funding, up from 4 percent in 2004, according to data from PitchBook.) Murray is Kearney’s thesis adviser. Huang, whom Brooks met in the initial stages of their research, studies the role of “gut feel” in investment decisions.

The Guys Have It

In their first study, the research team examined video recordings of 90 randomly selected pitches from three real-life entrepreneurial pitch competitions, held in various United States locations over a three-year period. In each case, a panel of angel investors had judged the pitches and awarded startup capital to the winners.

Click on image to enlarge
Click to enlarge image.

The researchers recruited a separate panel of 60 seasoned angel investors to watch the videos and code them across several measures, including physical attractiveness—rating the entrepreneurs on a scale of 1 (very unattractive) to 7 (very attractive). The coders were blind to the actual competition results.

The analysis showed a significant relationship between an entrepreneur’s gender and whether a pitch had been successful. Male entrepreneurs were 60 percent likelier to receive a funding prize than were female entrepreneurs. Among those male entrepreneurs, investor-deemed attractiveness led to a 36 percent increase in pitch success. But for female entrepreneurs, their looks had no apparent effect on the success of their pitches.

The second study was an experiment designed to isolate the effect of gender on pitch persuasiveness. The researchers used 521 participants to watch two entrepreneurial pitch videos online. In each case, one of the pitches had won funding in real life. Participants in the experiment, roughly half of whom were women, were tasked with guessing the actual winner, with the incentive of a monetary reward for a correct guess.

The pitches included still images and a voiceover narration by the entrepreneur. This format enabled the researchers to assign a gender to the entrepreneur—dubbing in a male voice for some videos and a female voice for others, while the content of the narrations remained identical.

All else being equal, 68.33 percent of participants favored ventures pitched by male voices, while only 31.67 percent chose female-voiced pitches. Importantly, the gender effect held steady regardless of the “investor’s” gender.

“We saw the same discriminatory effects between male and female participants,” Brooks says.

In the third study, 194 participants each watched only one pitch video. As in the previous study, the researchers manipulated the gender of the voiceover each time. Additionally, they accompanied each video with a photo, which varied according to a scientific scale of physical attractiveness. “We manipulated attractiveness using four faces: one high-attractiveness and one low-attractiveness female face, and one high-attractiveness and one low-attractiveness male face,” Brooks explains. “We used photos that had been used in previous research and validated as highly attractive or unattractive, and we also ran our own pilot study to ensure that the faces uniquely manipulated attractiveness.”

Each participant rated the investment potential of the venture on a scale of one to seven. As with the previous studies, participants awarded higher ratings to pitches with male voices—deeming the male pitches more “persuasive,” “fact-based,” and “logical” than otherwise identical female pitches. Additionally, the participants preferred pitches from the “high-attractiveness” male entrepreneurs over those from “low-attractiveness” men. But looks had no significant effect on whether female-voiced entrepreneurs fared well.

Next Steps And Lessons Learned

In the secondary stages of their exploration, the researchers plan to dive deeper into gender dynamics. Among the questions they are pursuing: What happens when the female entrepreneur is perceived as stereotypically masculine vs. feminine? Is a female entrepreneur more likely to be funded if her business targets female customers? Will a successful track record increase a woman’s chances of securing capital?

Brooks is hardly shocked by the results of the studies thus far. “I was surprised to find the effects consistently across both field and lab settings,” she says. “But, in general, I find our results to be more sad than surprising.”

Still, she’s hopeful that the research provides a wake-up call to the venture capital industry.

“Awareness is a critical first step,” Brooks says. “Though gender in entrepreneurship has become a hot topic (Sheryl Sandberg’s wonderful Lean In and Ban Bossy campaigns, for example), we haven’t seen much concrete data on the topic until now. We hope this research leads investors and entrepreneurs to become more supportive of male and female entrepreneurs alike.”


Is Greed Ruining Private Equity Firms?

Is Greed Ruining Private Equity Firms?

In a first-ever look at the internal economics driving private equity partnerships, Victoria Ivashina and Josh Lerner find that founding partners who take an unequal share of the pie can ruin their firms.

by Dina Gerdeman

In a first-ever look at the internal economics driving private equity partnerships, Harvard Business School researchers have found that many of these funds can be torn apart by greed among founding partners who take home a much bigger share of profits than other senior partners, even when their performance doesn’t merit higher rewards.

This creates a ripple effect, where other senior partners become resentful, disenchanted, and leave their jobs, causing instability that spooks potential investors and could lead to a firm’s collapse.

“Short-term greediness is affecting the long-term stability and continuity of the firm”

This pattern of unequal pay was much more extensive than anticipated among the 717 private equity partnerships studied by HBS finance professor Victoria Ivashina and Josh Lerner, the Jacob H. Schiff Professor of Investment Banking.

These rifts, far from being uncommon, are the average experience in PE partnerships, Ivashina says.

In their working paper released in March, Pay Now or Pay Later? The Economics within the Private Equity Partnership, she and Lerner found that a partner’s pay was often tied more to the person’s status than to performance. Previous success as an investor seemed to have little bearing on how much the partner earned. Founders in particular gobbled up a much bigger piece of the pie.

Senior partners who believe they aren’t compensated fairly are significantly more likely to leave a firm. These departures can give limited partners the impression that a private equity firm is unstable. That perception creates a wariness to invest, which means a PE firm often struggles in its attempts to raise the next fund.

So in essence, founding partners are damaging their own firms, in some cases beyond repair, by being greedy.

Founding partners who shave off what is considered excess
pay for their efforts can destabilize private equity firms. Source: Nic McPhee (CC 2.0)

“Short-term greediness is affecting the long-term stability and continuity of the firm,” Ivashina says. “If you perceive you’re talented and you believe there is an unfairness in terms of compensation, you are likely to move on. It’s an important element that could trump the continuity of the firm.”

It’s interesting, she continues, because you might think that founders would care about legacy and the firm continuing beyond one generation. “But many firms seem to be missing the consequences and longer-term effects.”


Partnerships remain key to the way the professional service and investment sectors are run. Previous research has shown that the partnership structure has many advantages, including encouragement for senior partners to mentor successors.

The divide among partners has played out in the media in recent years.

For example, Weston Presidio reportedly suspended its fund-raising in 2014 after a group of partners left the company to start a new investment firm.

Doughty Hanson fell apart in 2015, according to one investor, because “historically there was an issue with the top guys having all the power and the economics, so there were quite a few spinouts in the past.” Another investor who decided not to invest in the firm’s funds said, “One of the things that we never got comfortable with was the economics between the two founders and the rest of the team, and as far as I’m concerned that did cause [staff] turnover to a large extent.”

Also in 2015, Charterhouse was said to be “a scene of frictions, involving both how its earnings are divided among the staff and how to hand power to a new generation.”


Ivashina and Lerner studied 2,577 senior partners and 1,394 junior partners, as well as 1,032 investment professionals who were classified as founders. They looked at a variety of detailed data on the partners and the funds, including performance information, as well as the split of ownership and carried interest—or profit share.

The average founding partner grabbed a much larger share of the carried interest than the average non-founder: 19.2 percent compared with 11.3 percent. Similarly, a founding partner had an average ownership stake of 30.8 percent, compared with the average non-founder’s stake of only 13.6 percent.

The researchers also took note of partners’ departures, which in general are uncommon. For the average fund, the probability that a given senior partner will depart was 9 percent, and for junior partners, 12 percent. But senior partners were significantly more likely to leave a firm that had higher pay inequality; partners on the shorter end of the profit stick were the ones leaving.

The paper notes that senior partners who stay have much higher carry stakes than those who leave—16 percent versus 9 percent. The difference in ownership stake is even higher: Senior partners who stay until the next fund have 23 percent of the ownership, whereas those who leave have only 13 percent.

Ivashina says that although senior partners’ departures were strongly related to pay inequality, this was not the case with junior partners, who also earn less.

“The junior partners will be paid less, and it doesn’t really matter,” Ivashina says. “The fact that as a junior partner you don’t make as much as a senior partner, that could be justified. The junior partners are willing to endure a lot until they get to that status of a senior partner. But when you become a senior partner, it matters.”

When senior partners walk, it often has very real consequences for the performance of funds. Even when partners are replaced by comparable investors, the team may be viewed as less stable due to the challenges investment professionals often face when working together for the first time. With the stigma that comes with staffing changes, the partnership may struggle to drum up ongoing investments.

Junior partners can come and go without affecting the ability of a PE firm to raise the next fund. But that’s not the case with senior partners: The more senior partners leave, the smaller the next fund is.

That’s because limited partners often take the time to look at the partnership makeup at private equity firms when deciding which ones to invest in.

Limited partners “have a lot of private conversations and collect a lot of information. They look at the partners and how they have performed in the past,” Ivashina says. “If someone left and they believe this person is important, there is likely to be a very serious conversation about that.”


The researchers naturally expected greed to surface at some private equity firms, but found it notable that this pattern of unequal pay played out among so many of the firms they studied.

“There are several firms that do think about this issue very seriously: They think about how to pass senior rights to next generations and make sure there is continuity to the firm. It’s not that there are not good exceptions out there,” Ivashina says. “But the result we observed in a large sample—with [certain] senior partners taking away most of the economics—seems to be the average experience. The average experience is more in line with the stories we hear in the news about unstable firms. People are frustrated.”

The research conducted by Ivashina and Lerner was made possible through collaborating with one of the largest limited partners, which provided what Ivashina calls “unprecedented data” about how people are compensated, with a promise from the researchers that information about individual firms would be kept confidential.

“We are sworn to secrecy,” she says. “Many of these firms are very curious [about the findings]. Private equity firms are quite interested, but there is especially huge interest among limited partners who have a choice about whether to allocate money to firm A or firm B. They may be the agent of change here.”


Financial Regulation in a Quantitative Model of the Modern Banking System

Financial Regulation in a Quantitative Model of the Modern Banking System

by Juliane Begenau and Tim Landvoigt

Executive Summary — This study at the intersection of macroeconomics and banking explores the optimal regulation of banks. Studying and quantifying the effects of capital requirements in a model that features regulated (commercial) and unregulated (shadow) banks, the authors find that a higher capital requirement makes regulated banks safer, but does not affect the riskiness of shadow banks. The net benefit of such a policy would depend on the level of fragility of the unregulated banks.

Author Abstract

How does the shadow banking system respond to changes in the capital regulation of commercial banks? This paper builds a quantitative general equilibrium model with commercial banks and shadow banks to study the unintended consequences of capital requirements. A key feature of our model is defaultable bank liabilities that provide liquidity services to households. The quality of the liquidity services provided by bank liabilities depends on their safety in case of default. Commercial bank debt is fully insured and thus provides full liquidity. However, commercial banks do not internalize the social costs of higher leverage in the form of greater bankruptcy losses (moral hazard) and are subject to a regulatory capital requirement. In contrast, shadow bank liabilities are subject to runs and credit risk and thus typically less liquid compared to commercial banks. Shadow banks endogenously limit their leverage as they internalize the costs. Tightening the commercial banks’ capital requirement from the status quo leads to safer commercial banks and more shadow banking activity in the economy. While the safety of the financial system increases, it provides less liquidity. Calibrating the model to data from the Financial Accounts of the U.S., the optimal capital requirement is around 20%.