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Venture Capital's Role in Financing Innovation: What We Know and How Much We Still Need to Learn

Venture capital is associated with some of the most high-growth and influential firms in the world. Academics and practitioners have effectively articulated the strengths of the venture model. At the same time, venture capital financing also has real limitations in its ability to advance substantial technological change. Three issues are particularly concerning to us: 1) the very narrow band of technological innovations that fit the requirements of institutional venture capital investors; 2) the relatively small number of venture capital investors who hold, and shape the direction of, a substantial fraction of capital that is deployed into financing radical technological change; and 3) the relaxation in recent years of the intense emphasis on corporate governance by venture capital firms. While our ability to assess the social welfare impact of venture capital remains nascent, we hope that this article will stimulate discussion of and research into these questions. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Venture capital is associated with some of the most high-growth and influential firms in the world. For example, among publicly traded firms worldwide, seven of the top eight firms by market capitalization in May 2020 had been backed by venture capital prior to their initial public offerings: Alphabet, Apple, Amazon, Facebook, and Microsoft in the United States, and Alibaba and Tencent in China. More generally, although firms backed by venture capital comprise less than 0.5 percent of firms that are born each year in the U.S., they represent nearly half of entrepreneurial companies that graduate to the public marketplace.
Academics and practitioners have effectively articulated the strengths of the venture model. These include its strong emphasis on governance by venture capital investors through staged financing, contractual provisions, and active involvement with their portfolio companies. Indeed, Kenneth Arrow (1995) once opined that "venture capital has done much more, I think, to improve efficiency than anything." In many respects, the venture capital industry certainly appears to be a bright spot in an increasingly troubled global innovation landscape (Bloom et al. 2020). Over the last decade, the amount of capital deployed worldwide by venture capital investors and the number of startups receiving funding have grown substantially. Entirely new financial intermediaries such as accelerators, crowd funding platforms, and "super angels" have emerged at the early stage of new venture finance. Meanwhile, mutual funds, hedge funds, corporations, and sovereign wealth funds have deployed large sums of capital into more mature, but still private, venture capital-backed firms.
In this paper, we acknowledge the power of the venture capital in fomenting innovation. At the same time, despite the optimism articulated by Ken Arrow in the quotation above and by many other academics and practitioners, we argue that venture capital financing also has real limitations in its ability to advance substantial technological change. While our ability to assess the social welfare impact of venture capital remains nascent, we hope that this discussion will stimulate discussion of and research into these questions.
Three issues are particularly concerning to us: 1) the very narrow band of technological innovations that fit the requirements of institutional venture capital investors; 2) the relatively small number of venture capital investors who hold, and shape the direction of, a substantial fraction of capital that is deployed into financing radical technological change; and 3) the relaxation in recent years of the intense emphasis on corporate governance by venture capital firms. We believe these phenomena, rather than being short-run anomalies associated with the ebullient market of recent years, may have ongoing and detrimental effects on the rate and direction of innovation in the broader economy.
We begin this paper by tracing the growth of the venture capital industry over the past forty years, noting how technological and institutional changes have narrowed the focus and concentrated the capital invested by venture capital firms, as well as potentially contributing to a decline in governance. We then turn to some potential adaptations to the venture capital industry model that might enable a broader base of ideas and technologies to receive risk capital. In particular, we will propose some possibilities for altering what seems to be a standard and inflexible contract between venture capital funds and their investors, as well as potential approaches to more effectively manage venture investments in certain industries.
Our focus here will primarily be on the U.S. venture capital industry. But we would be remiss if we did not note that the growth rate of global venture capital has exceeded that of the U.S. The National Venture Capital Association (2020) estimates, for instance, that the U.S. share of world venture capital financing has fallen from about 80 percent in 2006-07 to under 50 percent in 2016-19.

The Origins
Entrepreneurs have sought funds to pursue their risky ideas for centuries before the modern venture capital industry emerged. Indeed, some of the key elements of today's venture capital industry, such as the use of risk-sharing partnerships, can be traced as far back as Genoese merchants in the 15 th century and American whaling voyages in the 19 th century (Astuti 1933;De Roover 1963;Lopez and Raymond 1955;Nicholas 2019).
Most business historians, however, trace the origins of the institutional venture capital industry to 1946, when Harvard Business School professor Georges Doriot formed the American Research & Development Corporation with local Boston civic leaders to invest in young ventures developed during World War II. 1 Doriot articulated and practiced many of the key principles of venture investment that continue to this day. These guideposts include: the intensive scrutiny (and frequent rejection) of business plans prior to financing, the provision of oversight as well as capital, the staged financing of investments, and the ultimate return of capital and profits to the outside investors that provided the original funding. 2 Several of the most prominent venture capital firms of today-such as Sequoia Capital, Kleiner Perkins, and New Enterprise Associates-were formed in the early-to-mid 1970s to invest in what would become the burgeoning semiconductor and computer industries. However, the industry did not take off until the early 1980s, when pension funds began to allocate some of their capital towards this relatively new asset class. Much of this change can be traced back to a clarification of an obscure rule in the Employment Retirement Income Security Act (ERISA). The rule had originally stated that private pension managers had to invest their funds' resources with the care of a "prudent man," which was interpreted as requiring only very low-risk investments. In early 1979, the Department of Labor ruled that pension fund managers could take portfolio diversification into account in determining prudence, which implied that the government would not view allocation of a small fraction of a corporate pension fund portfolio to illiquid funds like venture capital as imprudent, even if a number of companies in the venture capitalist's portfolio failed. While the allocations of corporate pension funds to venture capital in the 1980s were initially very modest, even a small allocation of such a large pool led to very rapid growth of the venture capital sector.
A decade later, U.S. public pension funds also started investing in venture capital firms and were soon followed by pension and sovereign funds from around the globe. Initially, neither private nor public pension funds invested in a dramatically different manner than their predecessors. But their impact was important because of their sheer size, which dwarfed that of the early venture capital investors such as university endowments and insurance companies. In the subsequent forty years, venture capital has come to be established as the dominant source of financing for high-potential startups commercializing risky new ideas and technologies.

Venture Capital's Impact
Exhibit 1 highlights how venture capital is involved in financing startups that ultimately become some of the largest and most successful firms in the economy. We looked at the 4,109 initial public offerings over the 1995-2018 period of nonfinancial firms that were founded in 1980 or later. Exhibit 1 (inspired by Gornall and Strebulaev 2015) shows that 47 percent (or 1,930) were backed by venture capital investors prior to their initial public offering. 1,044 firms of those firms were still publicly traded at the end of 2019. The exhibit compares the 1,044 firms-at the end of 2019based on whether they were originally venture capital-backed (582 firms) vs. not (462 firms). That is, 56 percent of the firms that had initial public offerings from 1995-2018 and were still alive at the end of 2019 were backed by venture capital. Considering that under 0.5 percent of firms in the economy receive venture capital financing (Puri and Zarutskie 2012), Exhibit 1 highlights the disproportionate role firms backed by venture capital play in the economy.
An important question relates to whether these differences arise purely due to venture capital firms selecting high-growth opportunities or whether these investors also play a causal role in improving the growth and performance of new companies. Discerning causality in this setting is tough. Much of the research has consequentially been more descriptive in nature. Chemmanur, Krishnan, and Nandy (2011) and Puri and Zarutskie (2012) examine the universe of firms using the Longitudinal Research Database of the U.S. Census Bureau. They argue that the evidence is consistent with the proposition that venture capital increases firm sales and lowers the likelihood of firm failure.
Other papers have attempted to exploit discontinuities to identify the relationship between venture capital and innovation. Kortum and Lerner (2000) use the 1979 "prudent man" change in pension fund rules that increased venture capital funding as a natural experiment, along with several other approaches, to look for causality. They find that a rise in venture capital causes higher rates of patenting. Bernstein, Giroud, and Townsend (2016) examine the opening up of new airline routes that make it easier for a venture capital firm to visit one of its existing portfolio companies. They find that when it becomes easier for the venture capital firm to monitor, the portfolio firm performs better.
Other research has fleshed out the mechanisms that venture capital investors use. These tools include staged financing (Gompers 1995;Neher 1999), securities that have state-contingent cash flow and control rights (Hellmann 1998;Cornelli and Yosha 2003;Strömberg 2003, 2004), and the active role of venture capital investors on boards of portfolio companies (Hellmann and Puri 2000;2002;Lerner 1995). The authors argue these approaches have an important impact on the success of portfolio companies. For a more thorough review of the extensive literature on venture capital, a useful starting point is Da Rin, Hellmann, and Puri (2013).
Looking back at Exhibit 1, one can see that firms that were backed by venture capital prior to their initial public offering represent a similar share of revenues and profits as their proportion of surviving public firms (about 55 percent). On average, they are less labor intensive, more valuable in terms of market capitalization, and represent 89 percent of the recorded research and development expenditures by these firms in 2019.
The disproportionate share of recorded research and development expenditures by firms that were formerly backed by venture capital stems from two elements. First, 91 percent of public firms originally backed by venture capital recorded expenses related to research and development in 2019, compared to a much smaller 72 percent for firms not originally backed by venture capital. Second, among those that did report research and development expenses, the intensity of research and development, measured as a share of firm revenue, was higher.
The research and development intensity of publicly traded firms that were backed by venture capital relates to venture capital's role in financing repeated waves of technological innovation: the semiconductor revolution and diffusion of mainframe computing in the 1960s; the advent of personal computing in the early 1980s; the biotechnology revolution of the 1980s; and the introduction of the Internet and e-commerce in the 1990s (which as seen from Exhibit 2, led to a sharp expansion in venture capital and venture capital-backed startups between 1995 and 2000). After a significant decline in 2000 and the subsequent "dot com bust," the role of venture capital firms in financing technological revolutions continued in the 2000s, as exemplified by the widespread diffusion of "smart" mobile communications technologies and new businesses enabled by the rise of cloud computing. Consistent with this, Howell et al. (2020) use U.S. patent data over the 1976-2017 period to document that venture capital-backed firms were between two and four times as likely to have filed patents that were in the top percentiles of influence (as measured by citations, originality, generality, and closeness to science).

Venture Capital in the 2010s
Venture capital has boomed over the past decade driven by new investment opportunities and greater availability in the supply of capital for this asset class.
On the demand side, there has been a plethora of attractive investment opportunities. Many venture-backed firms have focused on developing novel ways to apply information technology and the widespread diffusion of mobile communications. One manifestation has been platforms that connect and employ widely dispersed sellers of services and goods (frequently dubbed the "sharing economy," and manifested by companies such as Airbnb and Uber). A second has been firms that substantial improve the efficiency of existing services at much lower price points: for example, the ways in which Salesforce.com and other companies provide "Software as a Service" to businesses, the rise of "fintech" and the plethora of "Mobile Apps" available for consumers. Third, several companies replicated business models successful in the United States in other national markets, with the Chinese companies Alibaba and Tencent being the most dramatic exemplars. An important consequence was the dramatic increase in venture capital investment in Asia over this period (itself a topic worthy of much closer study).
Another demand driver has been the substantially lower cost of starting a new business in the software and services sectors. As documented by Ewens, Nanda, and Rhodes-Kropf (2018), the much lower initial capital needed for new ventures in these sectors made it much cheaper to learn about their potential. This change led early-stage investors to be more willing to fund less proven (but potentially high-return) ideas and entrepreneurial teams in these sectors. One manifestation was an increase in a "spray and pray" investment approach, where financiers provide a small amount of funding and limited governance to a larger number of startups. As seen in Exhibit 2, the number of startups receiving a first round of venture capital financing rose substantially over this period.
Coinciding with the fall in cost of starting businesses and the entry of less-experienced founding teams has been the emergence of complementary institutions that fund and mentor very early-stage entrepreneurs. For example, the substantially smaller quantum of capital required to get a business of the ground has led to more opportunities for angel (or individual) investors. Not only did angel groups grow in size (Kerr, Lerner, and Schoar 2014), but some angel investors (the "Super Angels") even began to raise small funds to finance startups at earlier stages than was typical for institutional venture capital investors. Further, using online platforms such as AngelList, groups of individuals could back a lead investor who aimed to replicate some of the systematic diligence and monitoring functions played by traditional venture groups (Agrawal, Catalini, and Goldfarb 2016). The contemporaneous rise of equity crowdfunding and initial coin offerings has had a more mixed legacy, enabling widespread participation in financing startups by the populace but also raising concerns about fraud (Howell, Niessner and Yermakc 2019;Lin 2017;Zetzsche et al 2018). 3 The evolving early-stage market also created an increasingly important role for business accelerators, which sought to systemize the mentoring and development of the larger number of inexperienced, first-time entrepreneurs receiving financing (Gonzales-Uribe and Leatherbee 2017; Hochberg 2016).
The last decade has also seen substantial changes in the way that venture capital--backed firms grow and achieve exits. One element of this shift is the marked decline in the number of initial public offerings since the "dot com" bust in 2000. Instead, venture capitalists are far more likely to exit investments through acquisitions. Inasmuch as firms are going public, they are doing so at more mature stages in their lifecycle (Ewens and Farre-Mensa 2020).
Understanding the drivers for this shift-and the more general reduction in the number of publicly traded U.S. firms-is challenging. Potential explanations include technological shifts leading to a rise in platform (winner take all) businesses (Gao, Ritter and Zhu 2013), regulations making it harder for small firms to go public (Iliev 2010), changes in securities laws that facilitated the flow of more capital into private markets (Ewens and Farre-Mensa 2020), and monetary policy following the financial crisis.
But whatever the cause, the fact that firms that are more mature when they go public has also meant that they do so at substantially higher valuations. Investors that traditionally focused solely on the public markets saw that they were missing out on the capital gains that companies such as Facebook, LinkedIn, and Salesforce garnered while still private. These investors consequentially sought out opportunities in the private venture capital market.
As a result of this interest, the past decade saw an increase in the number of venture capital funds raising capital. The most conspicuous impact of this flood of capital into venture capital was the rise of "mega-funds" (venture capital funds that are substantially larger than historical averages). The most salient of these was SoftBank's Vision Fund. At the time of its first closing on $93 billion in May 2017 (with an anchor investment of $45 billion from the Saudi Public Investment Fund), it was already 30 times larger than the previous largest venture capital fund raised (New Enterprise Associates' 2015 Fund XV). SoftBank would ultimately go on to raise $100 billion for its fund. This rapid increase in interest in venture capital also triggered traditional venture firms to raise very large funds, such as the $8 billion Sequoia Capital Global Growth Fund III in 2018.
In addition, frustration with the high fees charged by venture capital firms led sovereign wealth funds, hedge funds, mutual funds, and other public market investors to begin making direct investments into firms backed by venture capital (Fang, Ivashina, and Lerner 2015;Lerner et al. 2018). Ewens and Farre-Mensa (2020) estimate that between 2014 and 2016, over three-quarters of the late-stage venture capital funding came from such non-traditional investors. Whether through large funds or direct investments, much of the capital from these later-stage investors has gone to "unicorns," defined as privately held firms with nominal valuations in excess of $1 billion.
This combination of new entrants deploying small amounts of capital at the early stage with the rise of mega-funds is reflected in fund size statistics. These changes are best illustrated by looking "peak to peak," from 2007 to 2019 in Exhibit 3. The size of the median fund raised by venture capital investors has fallen from $133 million to $80 million. Meanwhile, the number of funds with a billion dollars or more of capital rose from 3 in 2007 to 8 in 2019 (NVCA 2020).

Venture Capital's Limitations
The growth of the venture capital market in the past decade should not blind us to its limitations as an engine of innovation. Indeed, the changes delineated in the previous section will likely exacerbate these challenges. We lay out three distinct areas of concern about venture capital and is ability to successfully spur innovations. While the discussion must be inherently more speculative, given the relatively limited work done in this area, we suggest that these questions would well benefit from scholarly attention in the years to come.

Optimized for a Narrow Slice of Technological Innovation
Despite the substantial growth of venture capital in the four decades since the revision of the "prudent man" rule for pension fund investment in 1979, venture capital touches only a tiny share of firms in the American economy. The estimated $450 billion currently under management by U.S. venture capital firms (NVCA 2020) remains small in comparison to the several trillion dollars managed by the broader asset class of all U.S. private equity, not to mention U.S. public equities, estimated at $42.9 trillion at the end of 2018 (SIFMA, 2019). Only a few thousand new firms each year raise institutional venture capital for the first time, as compared to over 600,000 annual business starts in the United States. Even among high-potential firms engaged in innovation, Farre-Mensa, Hegde, and Ljungqvist (2020) found that only 7 percent of firms that filed for a patent went on to raise institutional venture capital. These disparities are likely even more extreme in other nations, where the venture industry is less mature.
One reason for this is structural. Venture capital investors typically raise funds for a specific (usually a ten-year) period. This time frame implies that venture capitalists are naturally drawn to investment opportunities where the ideas can be commercialized and their value realized through an "exit" within a reasonably short period. Sudden downturns, as occurred in 2000, 2008, and 2020, may disrupt plans to exit investments, creating more pressure to sell when market conditions permit, even if earlier than optimal for the firm. These constraints imply that venture capital investors often exit their investments well before growth opportunities are fully realized. As a result, they are often drawn to sectors with large uncertainty about an idea's potential that can nevertheless be resolved quickly.
What leads to variation in the degree to which uncertainty can be reduced quickly? An important element appears to be the nature of uncertainty about demand for the new product or service. Put another way, can uncertainty about the viability of the offering and the market demand can be resolved quickly? Software and service businesses, which are typically based on proven technologies, often have short development times and can benefit from quick market feedback are amenable to this approach. And, as noted above, over the past two decades, technological changes have made it quicker and cheaper to learn about demand for a new software business. By way of contrast, many other sectors like clean energy, new materials, and others are less amenable to such rapid learning. The widespread interest among venture capital investors in the few exceptions, such as biotechnology startups, is tied to the drug approval and reimbursement system that enables investors to accurately project the market value of a new drug if it is successful in passing through clinical trials (Janeway 2018). This suggestion is underscored by computations by Sand Hill Econometrics. This firm creates a series of indexes (described in Hall and Woodward 2004) that seek to capture the gross returns (that is, before management fees and profit-sharing) from investments in all active venture transactions in a given category. Their calculations suggest that an investment in the software deals between December 1991 and September 2019 would have yielded an annualized gross return of 24 percent per annum, far greater than investments in hardware (17 percent), healthcare (13 percent), or clean-tech (2 percent). This index further shows that the divergence in the performance of these categories has been particularly stark in the last decade. These stark differences in economics have unsurprisingly led to shifts in the composition of venture capital portfolios. Examining the portfolio of a single venture group four decades apart demonstrates the extent of this focus and narrowing. 4 Charles River Ventures was founded by three seasoned executives from the operating and investment worlds in 1970. Within its first four years, it had almost completely invested its nearly $6 million first fund into 18 firms. These included classes of technologies that would be comfortably at home in a typical venture capitalist's portfolio today: a startup designing computer systems for hospitals (Health Data Corporation), a software company developing automated credit scoring systems (American Management Systems), and a firm seeking to develop an electric car (Electromotion, which, alas, proved to be a few decades before its time). Other companies, however, were much more unusual by today's venture standards: for instance, startups seeking to provide birth control for dogs (Agrophysics), highstrength fabrics for balloons and other demanding applications (N.F. Doweave), and turnkey systems for pig farming (International Farm Systems). Only eight of the 18 initial portfolio companies-less than half-related to communications, information technology, or human health care.
The portfolio of Charles River Ventures looks very different in December 2019. Of the firms listed as investments, about 90 percent are classified as being related to information technology comprising social networks, applications for consumers, and software and services related to enhancing business productivity. Approximately 5 percent of investments are classified as being related to health care, materials, and energy.
This shift in Charles River's portfolio reflects the patterns of the industry at large, as Exhibit 4 depicts. By way of preface, it should be noted that it is difficult to trace fine-grained industry categories over multiple decades. New categories of firms (such as social networks and digital media) have emerged. Moreover, firms do not always fit neatly into a single classification: for example, Uber is a software firm, a transportation firm, and a consumer service firm. With these caveats duly noted, in Exhibit 4 we categorize firms into four broad classifications that are reasonably comparable over time: computer software, hardware of many types (from energy to instruments to semiconductors), business and consumer products/services, and medical, including biopharmaceuticals.
Hardware dominated the investments made by venture capital in the period from 1985 to 1989, accounting for 42 percent of dollars invested into startups by venture capital. Software and service startups accounted for nearly the same share of investments made in 1985-89, while biopharmaceuticals and medical devices represented most of the remainder. The exhibit also shows the large shift in focus of venture capital firms away from hardware and towards software and service businesses. Biopharmaceutical and medical device startups have received approximately the same share of funding. However, the chart masks the fact that this investment now comes from a smaller share of venture capital firms specializing in this sector, as opposed to from many generalist venture capital firms.
The same concentration of investment on software and related businesses seen in Exhibit 4 is also seen in the patent data. Using data on the patents filed at the United States Patent and Trademark Office over the period 2008 to 2017, we found that the top ten patent classes using the U.S. Cooperative Patent Classification (CPC) system represented 48% of all venture capital patents filed over the 2008-2017 period, as compared to 24% for the top ten patent classes for patents not filed by venture capital-backed firms.
Thus, while venture funding is very efficacious in stimulating a certain kind of innovative business, the scope is increasingly limited. This concentration may indeed be privately optimal from the perspective of the venture funds and those who provide them with capital. It is natural to worry, however, about the social implications of these shifts. For instance, promising startups developing renewable energy technologies and advanced materials, which might have broad societal benefits, may languish unfunded.
The reader might well raise eyebrows at this suggestion. If value-creating entrepreneurial investment opportunities exist, should some other investor step in? Certainly, we have seen corporations in sectors such as energy making investments in young firms. But as we will discuss in the final section, these efforts to date have been far from resounding successes.

The Disproportionate Role of a Few Deep-Pocketed Investors
Venture activity is concentrated. Yes, the National Venture Capital Association estimates that there were a little over 1,000 U.S. venture capital funds in 2019. But a small number of large venture capital firms hold the vast majority of capital.
To illustrate this point, we created a list of all institutional venture capital investors that made at least one investment into a U.S.-headquartered startup in 2018. For these investors, we examined the total funds they had raised from 2014 to 2018: approximately $284 billion raised by 985 investors. Looking at the concentration in the capital raised by these investors provides a good proxy for the concentration in assets under management across institutional venture capital investors. The top 50 investors, or about 5 percent of the venture capital firms, raised half of the total capital over this period. 5 The large inflow of capital in the last decade has further concentrated capital in the hands of top funds. The reasons for this are worth further inquiry, but are likely at least in part due to strong persistence in the relative performance of the venture capital funds (Kaplan and Schoar 2005;Harris et al. 2014). 6 A small number of higher-performing venture capital firms have continued to raise ever-larger funds.
Moreover, these deep-pocketed investors can play a disproportionate role in driving where other investors put their money. Investors with smaller sums of capital under management typically focus on investments at the earliest stages of a startup's life, well before the startup is profitable or even has revenue. These early-stage venture capital investors often do not have the capital to continue financing startups across subsequent rounds to the point where they can be sold for an attractive valuation. Thus, they are dependent on their larger peers to step in and to continue financing the firms they initially fund. Consequentially, a major worry for early investor is that an otherwise healthy startup might not be able to raise follow-up capital (Nanda and Rhodes-Kropf 2017). In this way, the preferences of large late-stage investors can shape where early-stage 5 Taking into account non-traditional investors such as SoftBank increases the number of investors under consideration to 1,074. Among this larger set of investors, the top 50 investors accounted for 68 percent of the total capital raised by investors over this period. 6 Related work has examined the drivers of this persistence and the degree to which it might be a consequence of differences in skill across venture capital investors versus other factors such as sorting or preferential access to deal flow that may perpetuate initial differences in performance across investors (Sorensen 2007;Hochberg, Ljungqvist, and Lu 2007;Korteweg and Sorensen 2017;Ewens and Rhodes-Kropf 2015;Nanda, Samila, and Sorenson 2020). investors are willing to invest. Consistent with this suggestion, Howell et al. (2020), when examining recessions over the past half-century, find that early-stage venture capital appears to be particularly sensitive to market conditions.
Concerns about a small number of financiers acting as gatekeepers may be particularly salient when considering the characteristics of these financiers. We highlight three dimensions. First, major venture funds are based in a handful of places. In the United States, National Venture Capital Association statistics suggest that three metropolitan areas-the San Francisco Bay Area, Greater New York, and Greater Boston-account for about two-thirds of the venture capital deployed by firms each year. 7 The same phenomenon also seems to manifest itself globally, though good statistics are hard to find. For instance, a tabulation of PitchBook data between 2015 and 2017 by Florida and Hathaway (2018) concludes that the top 25 urban areas accounted for 75 percent of all disbursements globally. Given this concentration of capital, the startup community has rearranged itself to "follow the money." Why might the resulting geographic concentration be a cause for concern? After all, economists have long pointed out that there are increasing returns to scale in entrepreneurial and innovative activity. Regions like Silicon Valley have an abundance of resources for entrepreneurs, ranging from excellent engineers used to working long hours for risky stock options, knowledgeable patent attorneys, and of course, lots of financiers. As a result, there are real social benefits from geographic concentration of entrepreneurs.
On the other hand, the geographic concentration of venture capital has probably accelerated the "hollowing out" of innovative activities in many other parts of the world. Venture firms based in other cities might have chosen very different firms to invest in, given their perspectives on their local economies. More generally, Glaeser and Hausman (2020) have documented in the United States the growing hubs of innovative activity in places far removed from the areas with the greatest economic need, a phenomenon that the growth of venture capital has accelerated. Second, the background of individual decision-makers at venture firms remains far from representative of general population. Exhibit 5 focuses on the 417 individuals listed as U.S.-based partners of the top 5 percent of venture capital firms noted above. 8 Some firms give "partner" titles to a larger number of individuals than the true decision-makers in the partnership, so we also examine the subset of these individuals who sit on at least one corporate board. This restriction narrows the set of individuals to 265.
Exhibit 5 documents the composition of this group. Eighty percent of partners are male; among the set of partners with at least one board seat, 91 percent are male. Three-quarters of partners with at least one board seat attended either attended an Ivy League school, or one of Caltech, MIT, and Stanford; moreover, nearly 30 percent of these individuals are graduates of just Harvard Business School or Stanford Graduate School of Business. In terms of location, 69 percent are based in the Bay Area alone and over 90 percent based in either the Bay Area, Greater Boston, or New York.
The nonrepresentative nature of the decision makers at these firms is important because of the growing evidence that a lack of diversity among venture capitalists has an impact on what businesses get funded. For example, Gompers and Wang (2017) use the number of daughters of venture capital partners as an instrumental variable and show that it is correlated with a higher proportion of female partners and improved deal and fund performance. Ewens and Townsend (2020) document that male and female investors appear to have gendered preferences (or respond to different signals about potential cash flows) in terms of the companies they back. Understanding whether such frictions are consequential enough to influence the nature of innovations that are backed and the choice of products faced by consumers is an important question that we believe deserves more research.
A final concern, more difficult to document, relates to the criteria that these investors use to make decisions more generally (Gompers et al. 2020). While academics have spent a great deal of time seeking to understand the structure of venture investment agreements and post-deal involvement, the process before the transaction is much less understood. We understand that early-stage investors rely heavily on signals of entrepreneur quality (Bernstein, Korteweg, and Laws 2017), but know very little as to whether the emphasis on these signals is efficient. Recent work by Cao (2019), for example, shows that information frictions from early-stage platforms can lead to systematic downstream effects on firm funding. Given the increasing importance of venture capital for innovation and growth, understanding the way in which these investors acquire and aggregate signals of a venture's potential and the frictions in this process are very important and promising areas of future research.

A Declining Emphasis on Governance?
The third concern we highlight here has to do with the seeming decline in active corporate governance by venture capital funds. Venture capital has traditionally been a tough business, with onerous agreements in which firm founders gave venture capital firms significant stock ownership in exchange for funding (Kaplan and Strömberg 2003). Moreover, this stock ownership was not just "paper rights": frequent turnover of management driven by venture capital was traditionally the rule (Kaplan, Sensoy, and Strömberg 2009;Ewens and Marx 2018). These patterns have changed dramatically in the past decade. Across the board, "founder friendly" terms appear to have replaced the onerous provisions traditionally demanded by venture capitalists.
Several potential explanations can be offered for this change. First, the intense competition between venture capitalists during the 2010s may have led to better terms for corporate founders. Even in less ebullient markets, the most promising entrepreneurs have a lot of discretion from whom they choose to receive funding (Hsu 2006): venture returns are very skewed nature, with a few deals generating the bulk of the returns (Hall and Woodward 2010). This pattern has been especially true in the last few years, given the proliferation of mega-funds and the explosion in capital from non-traditional investors such as SoftBank, sovereign wealth funds, and corporations. In an intensely competitive market, some venture capital firms may be tempted to pitch entrepreneur-friendly contracts to founders in an attempt to get access to the most attractive deals (Eldar, Hochberg, and Litov 2020). Reflecting this competition, venture capital groups may have chosen to outdo each other in the extent of their hospitality toward company founders.
To an economist, however, this explanation raises new puzzles. If the intensive governance provided by venture capitalists is socially beneficial-as generations of academic analyses would suggest-why would groups choose to abandon it? Should not venture firms compete instead by offering entrepreneurs progressively higher valuations (and less dilution of their initial equity stakes), not by abandoning governance provisions? Does this explanation also imply that firm founders may underestimate the need for governance?
Other possible explanations for the decline in governance, however, may suggest deeper structural drivers of this trend. For example, a possible explanation reflects the changing dynamics of earlyand later-stage investing discussed above. It has become far cheaper to start a new business. Perhaps the capital that firms need at the earliest stage is too small to make it worthwhile for venture capital firms to engage in active governance. Indeed, some venture capital firms have adopted the "spray and pray" investment strategy at the seed stage of financing, in which they focus on learning about the potential of a venture before spending time governing it (Ewens, Nanda, and Rhodes-Kropf 2018).
In addition, the massive inflow of venture capital from investors that usually focus on the public market may have changed the focus of contractual rights at later stages. A single fund manager in these entities may hold hundreds of separate firms and have little experience directly governing the firms in their portfolio. These passive investors are unlikely to have the capabilities to provide effective governance to the entrepreneurial ventures. As Chernenko, Lerner, and Zeng (2019) document, mutual funds seem far more concerned about ensuring that there is a path to liquidity, reflecting the short-term nature of the capital that they have raised from investors. The changing composition of the capital sources may have thus also led to a reduced focus on governance.
There is a reason to fear that even among traditional venture capital investors, governance may decline for structural reasons. As firms stay private longer, venture capital investors may end up sitting on a larger number of company boards. Put another way, the classic structure of venture funds may have begun to get overwhelmed by the flow of outside money, new financial intermediaries, and the associated change in practices. As a result, venture capital-backed firms may not be receiving the same degree of governance.
Whatever the causes, there are a number of high-profile examples in recent years in which the charismatic founder of a "unicorn" company has been ousted. The departures of founders and chief executive officers like Travis Kalanick at Uber, Elizabeth Holmes at Theranos, and Adam Neumann at WeWork are quite different in their details. But overall, they illustrate some consequences of allowing entrepreneurs with limited prior management experience to raise enormous sums for new ventures with little formal oversight and governance protections. Understanding why traditional venture capital contractual provisions have faded in importance and their social welfare implications appears to be a promising area of future research for both theorists and empiricists alike.

New Approaches for Venture Capital
Venture capital has been a highly efficacious way to support certain kinds of innovation, as reflected in the importance of venture-backed companies in the stock market and in the economy as a whole. At the same time, the industry has important limitations. We now turn to some ideas that might help the venture capital industry to become more effective, with a recognition that these hypotheses may be of greater interest to those practitioners and academics interested in thinking "outside the box." We highlight two sets of ideas: the first, which owes a heavy debt to Lerner (2012), relates to the organizational and incentive structure of venture capital partnerships; the second, to the way in which venture capital firms focus on managing their investments in more challenging sectors.

Rethinking Venture Capital Partnerships
Since its early days, venture capital funds have been eight to ten years in length, with provisions for one or more one-to two-year extensions. Venture capitalists typically have five years in which to invest the capital, and then are expected to use the remaining period to harvest their investments.
The uniformity of these rules is puzzling. Funds differ tremendously in their investment foci: from quick-hit social media businesses to long-gestating biotechnology projects. In periods when the public markets are enthusiastic, venture capitalists may be able to exit still-immature firms that have yet to show profits and, in some cases, before they even have revenues. But as discussed above, there is tremendous variation in the maturation of firms in different industries. Certainly, within corporate research laboratories, great diversity across industries exists in terms of the typical project length. What explains the constancy of the venture fund lives?
One possible explanation is that a reasonably short fund life seems to have been the norm in limited partnerships of all types. For example, many of the other arenas where limited partnerships were employed in the 20th century, such as real estate, oil-and-gas exploration, and maritime shipping, all were reasonably short-lived. In the formative days of venture partnerships, the lawyers drafting the agreements may have gravitated to the relatively short fund lives that were common in other contexts. With the passage of time, such arrangements have then been taken as gospel by limited and general partners alike.
Another factor behind the persistence of the ten-year agreement has been resistance of limited partners-that is, the investors in the venture capital funds-to longer fund lives. These investors may fear that if they give the funds to a sub-standard venture group for a longer period, they will be stuck paying fees until the end of time for very limited returns. This reluctance may tell us more about the outsized nature of the fees that venture funds receive than about the inherent desirability of a longer-lived fund.
Indeed, the manner in which venture capitalists are compensated has changed little, even as the funds have grown much larger. Venture groups typically receive a share of the capital gains they generate (typically 20 percent, but sometimes as high as 30 percent) and then an annual management fee (often between 1.5 percent and 2.5 percent of capital under management, though it often scales down in later years). Such fees are quite modest for a fund of only a few million dollars in size: it is likely to cover only a very modest salary for the partners once the costs of an office, travel, and support staff are factored in.
But this compensation structure has remained largely unchanged as funds have become substantially larger. Moreover, as venture capital groups begin managing hundreds of millions or billions of dollars, substantial "economies of scale" appear: put another way, as a group becomes ten times larger, expenses increase much less than tenfold. As a result, management fees themselves become a profit center for the firm. These steady profits may create incentives of their own which may not be very appealing to investors. For instance, there will be an incentive to raise a larger fund at the expense of lower returns, which in turn may be tied to the greater concentration of capital held by a few investors; an incentive to put funds to work quickly and with a subpar amount of vetting, so that a new fund can be raised sooner; and an incentive to focus on excessively safe investments that will not have as much upside, but pose less risk of a franchise-damaging visible failure.
Just how large a temptation the venture capital compensation scheme can pose is illustrated in the work of Metrick and Yasuda (2010), who show that of every $100 invested by the limited partners, over $23 end up in the pockets of the venture investors. These sums might not be disturbing if the very substantial payouts to each partner reflected even larger returns being made by the limited partners in the fund. But profit-sharing is not the most important source of compensation. Instead, almost two-thirds of the income (in time-adjusted dollars) is coming from the venture capital management fees, which remain fixed whether the fund does well or poorly. These incentives clearly may motivate groups to add capital in excess of the growth of partners, even if performance suffers somewhat.
Interestingly, an alternative model already exists: the way that venture capital groups used to operate. Early venture capital groups, beginning with the pioneering partnership of Draper, Gaither & Anderson, negotiated budgets annually with their investors. The venture capitalists would lay out the projected expenses and salaries and reach a mutual agreement with the limited partners about these costs. The fees would be intended to cover these costs, but no more. (A few "old school" groups such as Greylock still use such an arrangement.) Such negotiated fees greatly reduce the temptation to grow at the expense of performance and are likely to lead ultimately to more successful and innovative startups.
What explains the traditional reluctance of the limited partners who invest in venture capital funds to push to change these compensation arrangements? Staff members may not really understand the economics of the funds, or they may fear that rocking the boat would limit their own ability to get a high-paying position at a fund or an intermediary in the future. Alternatively, the officers may worry that developing a reputation as an activist would jeopardize their organization's ability to access the funds with the highest returns. The last concern is a reasonable one. After the giant California Public Employees' Retirement System led a consortium of pension funds who pushed for an overhaul of private equity compensation in the mid-1990s, they were shunned by venture and buyout funds alike. In recent years, we have seen more collective discussion of these issues by limited partners in meetings of Institutional Limited Partners Association. But many of their proposals have been modest half-measures, without addressing the more fundamental issues.
Yet another question is why are such innovations not adopted by newer venture firms as a way to differentiate themselves? It might be thought that such "LP-friendly" terms might attract new investors. While examples along these lines have occurred, anecdotal evidence suggests that many groups who have tried such an approach have found it "tough sledding." In part, limited partners may interpret such concessions as an adverse signal, indicative of a lack of confidence on the part of the new fund managers in their ability to raise a fund. Additionally, even if the group responsible for private equity investments at the pension fund understands the advantages of the proposed alternative arrangement, the investment committee that ultimately makes the decisions at the pension may not. These information problems may lead to the persistence of a socially suboptimal fund structure.

New Approaches to Managing Investments
Venture capital firms face huge uncertainty about the ultimate potential of startup firms. Indeed, over half the investments of even the most successful venture capital investors fail, while the vast majority of returns are generated by a few extremely successful investments that are hard to predict upfront.
As noted before, venture capital investors are drawn to sectors in which this uncertainty can be reduced quickly. Staged financing is therefore not only valuable to venture capital investors as a governance tool, but also as a method of learning about the startup's potential through a sequence of investments over time. This approach to evaluating and governing ventures in software industries has been outlined in practitioner guides such as The Lean Startup (Reis 2011).
But the ability to learn quickly about the promise of new ventures is harder if there is substantial regulatory, technology, and market risk, which we suggest explains the poor performance and declining share of venture investment outside of software. For example, forecasting the unit costs associated with energy storage at scale using a new battery material can be extremely difficult, even if the technology works in a controlled laboratory environment. Since uncertainty about market demand is tied to firms' ability to produce at a certain price point, forecasting demand in this setting is hard.
One promising response to these challenges is to rethink the organizational model for incubating and financing "tough tech" ventures. The venture approach entails entrepreneurs coming to venture capital firms to pitch them new ideas and the firms deciding whether to fund them. This approach has the benefit of enabling the investors to maintain an arm's-length relationship from the entrepreneurial team, reducing the entrenchment that is sometimes associated with corporate research and development and internal capital markets.
An alternative approach that has begun to be used by some venture capital investors specializing in biopharmaceuticals (such as Third Rock Ventures and Flagship Pioneering): to incubate and finance ideas in-house. This process has the benefit of reducing asymmetric information because much of the staff for the team of entrepreneurs comes from within the fund. It also enables the venture capital firm to fund what it might believe is the most promising idea or approach, as opposed to selecting among the ideas that walked in the door. A related approach is illustrated by Breakthrough Energy Ventures, which has a team of in-house scientists who jointly make investment decisions with traditional investment partners. Such new approaches may hold promise for widening the scope of venture capital investment. Understanding the tradeoffs associated with bringing incubation inside the venture capital firm and organizing new ventures more like corporate research and development seems to be a promising area of academic research.
It is also natural to wonder whether collaboration with other parties-governments, non-profits, and corporations-might alleviate some of the barriers to financing new ventures in more difficult technologies. Of course, this suggestion is not new! Governments have been involved with the promotion of venture capital at least since 1946, when a consortium of the Bank of England and leading British banks combined to create the British firm 3i as a vehicle to make long-term investments in smaller firms. Corporations have been collaborating with venture capitalists since the 1960s. Universities and other non-profits have been incubating, mentoring, and directly financing new ventures for much of the last half-century.
But the track record of these collaborative efforts has been quite mixed. There have been successes, such as the Israeli government's jump-starting of its venture industry through the Yozma program that leveraged public money to attract private investment, or the success of many pharmaceutical firms in responding to the biotechnology revolution through their venturing initiatives. At the same time, anecdotes abound of naïve officials making poor decisions. For instance, the leadership of Boston University of put one-third of the university endowment into a single faculty-founded biotechnology company, Seragen, an investment that was ultimately sold for pennies on the dollar. 9 The statistical evidence, while limited, does not seem inspiring. For instance, the Thomson Reuters (now Refinitiv) database suggests that between 1993 and 2013, corporate venture funds lost 4 percent per annum, at a time when U.S. venture funds had annual returns of nearly 30 percent (for a more optimistic view, see Ma 2020).
We believe that these collaborations can be beneficial, but only if they are executed correctly. This caveat is an important one. As an example, we will highlight the role of U.S. government in the venture market. The primary mechanism through which government policy interacts directly with new ventures is through the Small Business Innovation Research (SBIR) program. A striking study by Howell (2017) suggests that the initial Phase I awards under this program have very positive effects on new technology ventures, doubling the probability that a firm receives venture capital and boosting patenting and revenue. But these Phase I awards made up only 20 percent of total of the $2.8 billion spent on the program (U.S. Small Business Administration 2018). The bulk of the funding goes to larger Phase II awards, which Howell argues have no positive impacts. Similarly, both Howell (2017) and Lerner (1999) document that a relatively small number of companies capture a disproportionate number of awards. These "SBIR mills" commercialize far fewer projects than those firms that receive just one or a handful of SBIR grants, but the repeat winners often have active staffs of lobbyists in Washington scouring for award opportunities. Yet despite these well-understood issues, the design of the program looks virtually identical to its initial manifestation in 1977. There has been almost no serious discussion in Washington regarding the idea of shifting more SBIR resources to Phase I grants or curtailing grants to "mills." The experience of the SBIR program underscores the need for careful initial design, painstaking evaluation, and a willing to redesign initiatives.
One promising area of recent growth has been the interest among philanthropic organizations in financing early-stage, high-risk research and development. The hope is that once sufficient development of the idea has taken place, private venture capitalists will be willing to step in. Such activities have been most visible of late in the early-stage financing of vaccines, including for COVID -19. Beyond healthcare, efforts are also emerging to finance initial investments in sectors that have substantial potential societal benefits but large risks. Illustrations include the Prime Coalition's funding of companies that combat climate change yet are sufficiently risky to deter traditional investors and the Ford and Rockefeller Foundations' initiative to seed venture funds investing in regions that have traditionally not attracted such capital. 10 While these efforts are likely to face substantial challenges, they also have real potential.

Final Thoughts
The growth of venture capital in the past decade, both in the United States and worldwide, is an important validation of the underlying model. At the same time, the period has brought into sharp relief the structural challenges facing the industry.
Over the past decades, academics and practitioners alike have highlighted the strengths of venture capital. Understanding and articulating its limitations, as well as how institutional innovations can address them, is an important challenge to both groups going forward. We first restrict investment professionals in these firms to titles that are one of Managing General Partner, Managing Partner, Founding Partner, General Partner, Senior Partner or Partner and further restrict them to individuals based in the U.S. In column 2, we examine a subset of these individuals who also sit on at least one board seat, as some of the firms in our sample have a larger number of individuals with a "Partner" title than those who make investment decisions or are actively involved in governing startups.


Determinants of Small-Scale Irrigation Use and Its Effect on Household Food Security in Debay Tilatgin Woreda, East Gojjam zone, Ethiopia

In Ethiopia, agriculture is the primary determinant of economic growth and reducing level of food insecurity. But in the country in general and study area in particular, agriculture is dominated by small-scale rain-fed production. As a result, the current yield level by rural smallholder farmers in the study area has not been able to fulfill the minimum food requirements. To this end, this research aims to identify determinants of SSI use and its effect on household food security status in Dibay Tilatgin, Amhara regional state, Ethiopia. Multistage sampling technique and Kothari formula was employed to identify the final sample respondents; accordingly the final sample size was 168 (38.7% irrigation users and 61.3% non-users). Both quantitative and qualitative data from primary and secondary sources were collected through interview schedule. Descriptive, inferential statistics and binary logistic model were used to analyze the collected data. The finding of the study revealed that sex, education, household labor size, cultivable land size, frequency of extension contact, training and credit use had significant positive influence whereas farm distance from water source had significant negative influence on SSI use. Out of the total sample households, 72 (42.9%) were food secure and 96 (57.1%) were food insecure. The study result also reported, SSI had significant and positive influence on HFSS at 1% level. Therefore, it is important to address factors affecting SSI use includes sex, education level, household labor size, cultivable land size, farm distance from water sources, training and also priority should be given to SSI development in planning and executing of policies and programs by all stakeholders.

Introduction
Majority of Ethiopia's farmers have been using traditional way of agricultural practices which is mostly rain fed. This has contributed for low productivity of the agricultural sector. To solve these problems, governmental and non-governmental bodies have made restless efforts to bring about change in agricultural production system. They have introduced improved agricultural technologies like use of fertilizers, high yielding varieties of seeds, pesticides and improved farm implements. However, the country has faced is low quantity and quality of irrigation based agriculture. This indicates that there are different factors directly or indirectly influencing the quality and quantity of agricultural production (Yishak, 2005).
Similarly, in the study area the delayed beginning of rainy seasons, early withdrawal and mal-distribution of rain were challenges from which great lessons should be drawn to seriously look into expansion of small, medium and large scale irrigation in perspective. Dependence of most farmers on rain fed agricultural production system, poor agricultural water management at the irrigation scheme and household food insecurity especially in limited and erratic rainfall seasons are another problems the study area has been faced.
In other way, the soaring nature of household food insecurity in the study area has been reason to generate the need for this research. Hence, among different interventions undertaken by government to mitigate food insecurity in the area, irrigation farming is the one that is meant to cover for production inadequacies from the short and unpredictable rainy season.
More importantly, the study area lacks of knowledge and empirical information regarding the major determinants of SSI use and whether food security of irrigation users is better off than those who depend on rain fall. Therefore, this study initiated to choose the study area and will reveal the seriousness of the problem and fill the gaps by analyzing the determinant of rural household's participation in small-scale irrigation and the contribution of small-scale irrigation on household food security status.

Objectives of the study 1.2.1. General objective
The overall objective of this study focused on identifying the determinants of SSI use and its effect on household food security status in the study area.

The specific objectives of the study were:
a) To assess the status of small-scale irrigation in the study area. b) To identify factors affecting Small-scale Irrigation use in the study area. c) To examine the effect of Small-scale Irrigation use on household food security in the area.

Methodology 2.1. Descriptions of study area
Dibay Tilatgin Woreda is one of the extra productive Woreda of East Gojjam adminstration zone in Amhara regional state, Ethiopia. There are twenty three kebeles in Dibay Tilatgin Woreda. The agriculture production system in the study area is a subsistence type of crop production system. A major type of crops grown in the area includes: barely, wheat, maize, Teff, sorghum, and small extent oil crops. In this watershed, some farmers also practice traditional irrigation development activities from Perennial River and springs. Moreover, recently Kulkual-Arajo (is installed to irrigate 163ha, but irrigated only 52 ha) and Wodeb-eyesus (is installed to irrigate 270ha, but it irrigate only 110ha), generally, small and medium scale irrigation development project with a command area of 433ha is under operation in the watershed (but only 162 ha are irrigated).

Research Method
Multi-stage sampling technique was employed to select the final sample respondents. First, Dibay Tilatgin Woreda was selected purposively based on the following reasons; the Woreda has relatively better small-scale irrigation activities that give opportunity to government in developing modern small-scale irrigation schemes, the necessity of irrigation for the area due to high erratic rainfall in high land kebeles, the focus of government to increase agricultural production and productivity to ensure food security and absence of similar studies in the area. In the second stage, simple random sampling technique was used to select three kebeles from irrigation accessible kebeles. There are more ten irrigation accessible kebeles in the Woreda which are found in high land agro ecology. In the third stage, the sampling frame (complete village household lists) was obtained from each Kebele administration office and was stratified in to the two strata (irrigation user and non-user households). Since, each stratum is more homogeneous than the total population, we are able to get more precise estimates for each stratum and this enables to get a better estimate of the whole.
In the fourth stage, systematic random sampling technique was applied to select the sample respondents from each stratum at each kebele. Since, systematic sampling has certain plus points, and it can be taken as an improvement over a simple random sample in as much as the systematic sample spread more evenly over the entire population (Kothari, 2004).
The sample size for this study was determined through Kothari formula which is based on approach of precision rate and confidence level, the researcher has specify the precision that he wants in respect of his estimates concerning the population parameters. This approach is capable of giving the mathematical solution and as such a frequently used technique of determining 'n'. Accordingly, the formula to find out the sample size (n) of finite population is: Where, N = population n= sample size z= the value of standard variation at a given confidence level and to be worked out from table showing area under normal curve p = sample proportion q= 1-p, e = given precision rate or acceptable error (Kothari, 2004). In this study, N = 1716 z= 1.96 p= 0.15 q= 1-0.15= 0.85 e = 0.05 n = 1.96²*0.15*0.85* 1716 / 0.05² (1716-1) + 1.96²*0.15*0.85 = 168 This sample size (168) was redistributed to each kebele via probability proportion to size through the following formula: Where, n i is number of sample HH from each kebele, Ni is the number of households in each kebele and N is the universe or total population. Data were collected through household survey, focus group discussion, and key informant interview and field observation.
After data were collected from both primary and secondary sources, it was entered to statistical software (SPSS-20). Prior to data entry and analysis , the data processing includes, data preparation (coding, editing and checks for errors and biases), counting (frequency of occurrences) and grouping of collected data was carried out. Descriptive, inferential and regression analysis were employed. The econometric model, binary logistic regression model was used to identify factors that affect small scale irrigation use and to realize whether irrigation practice has an influence on household food security status or not.

Result and Discussions 3.1. Status of Irrigation Use in the Study Area
Traditional irrigation particularly, traditional river diversion in the area is one of the irrigation systems and it is simple for farmers to practice by inheriting the knowledge from grandparent. At present time, both traditional and modern small-scale irrigation systems are being practiced in low land parts of the study area. Modern irrigation scheme like canal river diversion are introduced and some farmers have also adopted irrigation technologies like motor pump (MAWANRM, 2019). The same source disclosed that currently, the total irrigation potential of the study area is 22,779 ha. However, from the total irrigation potential 9,893 hectare of land was covered with both traditional and modern irrigation (irrigated).

Sources of Irrigation Water for Irrigation Users
Information gathered from key informants and field observation indicated that major water sources for irrigation in this area include rivers like (Muga, Bora, and Yebert Rivers) .The survey result revealed that most of irrigation user households in the study area 37 (56.9%) and 20(30.8%) depend on rivers . Additional information gathered from FGD reported that, in the area, rivers especially in rainy season are available and accessible source of water for all irrigation users. But during dry season the volume of irrigation water from the rivers decrease and that farm land located far from these sources and downstream communities have less access to use irrigation water when compared with that farm land located nearest to the rivers and upper stream communities."

. Irrigation Water Diversion and Lifting Mechanisms in the Study Area
Farmers in the study area use irrigation water through diverting from rivers and lifting from other sources through different types of water diverting and lifting mechanisms. The survey results show that out of the total irrigation users 41 (63%) divert irrigation water through traditional diversion mechanism mostly through ditches, 18 (27.7%) divert irrigation water by using motorized water pump and the remaining 6(9%) has used canal river diversion mechanism.

Factors Affecting Small-Scale Irrigation Use in the Study Area
Among the thirteen independent variables included in the model, eight variables had statistically significant influence on use of SSI. These variables are sex, education level, household labor size, cultivable land size, farm distance from water source, frequency of extension contact and irrigation and related training and credit use. The interpretation and discussion of each variable are indicated below: Education level of the respondents: Educational level was found to be one of the vital factors that contributed to the use of SSI. Consistently to hypothesis, it had significant positive influence on the use of SSI at 5% significance level. Other factors held constant, the odds ratio in favor of SSI use increases by a factor of 28.44 as the education level of respondent increased by 1 level. Household labor Size: The model result revealed that household size converted to adult equivalent had positive and significant influence on use of SSI at 10% level. Total cultivable land size: Cultivable land size had significant positive influence on use of small-scale irrigation at 5% significance level. All other things being kept constant, the odds ratio in favor of small-scale irrigation use increases by a factor of 144.983 as cultivable land size increased by 1 hectare. Farm distance from water source: Farm distance from water sources had significant negative influence on use of SSI at 1% significance level. The odds ratio disfavors the use of irrigation by a factor of 0 .002 as the farm distance from irrigation water source increased in 1 km. Frequency of extension contact: The number of contact with Development Agents per month had significant positive influence on irrigation use at 5% significance level. Other things held constant, the odds ratio favors the likelihood to use irrigation by a factor of 18.126 as the respondents' number of contact with the Development Agents per month increased by a unit. Therefore, respondents who highly contact with Development Agents per month have more chance to practice small scale irrigation in the area. Attendance on irrigation and related training: Attendance on irrigation and related training had significant positive influence on the use of SSI at 10% significance level. Other things kept constant, the odds ratio in favor of irrigation use increases the likelihood by a factor of 151.389 for the respondents who attended irrigation and related trainings. Table3 .000 -2loglikelihood=29.036, correctly predicted user=96.9%, correctly predicted non-user=99% and Overall prediction = 98.2%. ***, ** and * Significant at 1%, 5% and 10% significant level respectively. Source: Computed from own field survey, 2019.

The Effects of Small-Scale Irrigation on Household Food Security
Out of the 13 explanatory variables 6 were found to have significant effect on household food security. These variables include SSI use, livestock holding, cultivable land size, total household income, farm distance from water source and distance from nearby market. ISSN 2222-1727(Paper) ISSN 2222-2871(Online) Vol.11, No.5, 2020 5 Small scale irrigation use: The model result reported that SSI had significant positive effect on household food security at 1% level, meaning that irrigation plays a major role in enhancing household food security in the area. The study result therefore revealed that, relative to non-users of irrigation, the likelihood to be food secure for irrigation user households increased by a factor of 6.516 all other things kept equal. Livestock holding (TLU): As model result revealed, livestock size had significant positive effect on probability of being food secure at 5% level. The odds ratio indicated that as size of livestock holding increased by one TLU the likelihood of households to be food secure increased by a factor of 1.34. Total cultivable land size: The model result revealed that total cultivable land significantly and positively influences household food security at 10% level. This means those households who had larger cultivated land size are food secure than those having smaller land size. The odds ratio indicated that when the total cultivable land size increased by 1 ha, the likelihood to be food secure households increased by a factor of 1.72. Total household income/Year: The result of model reported that total household income positively and significantly affects households' food security at 1% level. The odds ratio in favor of being food secure is increased by a factor of 1 when the total annual income of household increased by 1 Birr. This result is consistent with the fact that more income improves the purchasing power, let farmers use modern inputs that improve their production and productivity and diversify their production activity. Distance from nearby market: The result of model disclosed that market distance from farm households' house had significant negative effect on household food security at 10% level. The odds ratio revealed when the distance of households' house from nearby market increased by an hour, the likelihood of household to be food secure decreased by a factor of 0.687. .123 -2loglikelihood = 169.512, correctly predicted food secure = 69.4%, correctly predicted food insecure = 84.4% and Overall prediction = 78.0%. ***, ** and * significant at 1%, 5% and 10% respectively. Source: Computed from own field survey, 2019.

Conclusion and Recommendations
For the further development of the small scale irrigation and promotion of household food security status in the study area attention should be given towards the following points: Use of small scale irrigation in the study area is determined by the sex of respondent, education level of respondent, household labor availability, total cultivable land size, farm distance from water source, attendance on irrigation and related training and credit use. Therefore: The government and other development partners working with rural households have to empower females, household labors and non-user male headed HHs to involve in irrigation activities through awareness creation and promoting credit accessibility by strengthening the involvements of MFI in agricultural development.
Education and agricultural sectors should give emphasis on training farmers through strengthening and establishing FTCs, technical and vocational schools to improve farmers' awareness on use of irrigation and adoption of irrigation technologies. Attention should be given in improving the quality of land through improved soil and water management mechanisms, awareness provision for farmers to use farm land in a more productive way.
In the study area also farmers use rivers and lake as source of irrigation water. These sources were not accessible by most of farmers due to distance problem. Therefore, it is better to initiate farmers to develop other alternative sources like ran-off water harvesting technologies, ponds and ground water development. management.


The Conundrum of Price Cut

Price decrease is often seen as the default action in a downturn. This was the case in the 2008/2009 financial crisis, and it is happening again right now in the middle of the COVID-19 pandemic 2019/2020. But past experience shows that it is more often than not the best decision to make. Pricing is no magic wand. Price decrease will not necessarily create additional demand, but it will definitely leave a dent on the margin. Especially in the B2B sector, price is usually not the decisive criterion for a purchase decision. If clients are complaining about the price, there is oftentimes something else that they are not happy with, be it product- or service-related. Price cut is obviously not the remedy.

When I put the question to the audience, the majority said No. Why is that? Presumably because I had before unduly framed them by showing them the impact of pricing on the bottom line with the help of the following mental exercise.
Suppose you find yourself in a deteriorating market situation, which of the following two options would you prefer?

What You Will Discover?
CEO: "Sales is declining! What do we do?" VP Sales: "Let's decrease price to recoup some sales!" Does it ring a bell? It is how companies act in reality. Whenever there is a sales crisis, managers feel pressured to decrease price, pretty much as a knee-jerk reaction. This can be a self-destructive form of behavior. When does price cut pay off, when doesn't? Are there better alternatives to price cut in the face of a sales crisis? 1. Cut price by 10% to keep sales volume from declining? 2. Keep price unchanged and accept 10% decline in sales volume? I don't know why a 10% decrease in sales should be more painful than a 10% decrease in price to many companies. They will prefer the second option, i.e., lowering price in favor of the sales volume, without really understanding the consequences. For the sake of simplicity, I set the scene as follows. In the starting situation, we have a product whose price = $10, sales volume = 1 million units, and revenue = $10 million. Assuming cost is equal to $8 million, we make a profit equal to $2 million. Further, we assume all cost is variable, which means cost is perfectly correlated with sales volume. See Fig. 1.
The impact of Option 1 is visualized below in Fig. 2a. In order to protect sales volume, we go down from $10 to $9 in price. What happens then?
Take a look at the green area, which represents the profit. A 10% price reduction would slash profit by half. Would you reconsider your decision? Wait, you have heard about price elasticity. Isn't it logical that we would have more volume coming in, if we decrease price? Fair enough. Let's see how much volume boost we need to make at least as much as profit as before? Check out Fig. 2b.
In a nutshell, it will be almost a mission impossible to be profit-neutral given even the seemingly harmless 10% price decrease. In order to bring in at least $2 million in profits with the reduced price, you would have to double the sales volume. It translates into a price elasticity of −10! Where should the massive increase in volume come from? Would you suddenly double the customer base, because new customers would get so excited about the 10% price cut? Or would existing customers suddenly double their purchase orders? Neither of these scenarios seems realistic. We are also ignoring another possible negative impact, evident when we ask what would happen if competitors follow suit and decrease their prices, too. Unfortunately, a 10% price decrease would bleed you dry without bringing about any benefits.
Price decrease is often seen as the default action in a downturn. This was the case in the 2008/2009 financial crisis, and it is happening again right now in the middle of the COVID-19 pandemic 2019/2020. But past experience The Conundrum of Price Cut shows that it is more often than not the best decision to make. Do not get me wrong. I am not blind to the other forces that urge price decreases such as the need to support clients in trouble and maintain adequate market exposure, the pressure from work unions to keep workers employed, the fear of losing supply chain partners, etc. All in all, I am not against price decreases but encourage managers and business owners to be wary of the possible consequences to and ask themselves three questions before implementing the price cut. These questions are: 1. Will I win new customers? 2. Will existing customers buy more? 3. Will competitors follow suit?
If you don't have clear answers to the questions above, you'd better think them through and refrain from a price decrease till you figure out the answers. A piece of popular wisdom has it that doing nothing is also an option, and sometimes it is the better one. Maintaining price integrity in difficult times, i.e., not hurrying into price reductions, will prove to be a superior tactic in many cases.
So far we have seen what damages price decreases can do to the bottom line. It is only fair to take a moment to look at the flip side. What will happen if we increase the price by 10%? See Fig. 3a.
If we increase price by 10% while losing no sales volume, profit will climb up to $3 million vs. $2 million in the starting situation. How nice is that! Price is the most effective profit lever. Price increase usually pays off, unless you have zero bargaining power against your customers. By the way, if you have to pray the night before you raise prices by 10%, you are in a horrible business, according to Warren Buffet.
Then a valid and sensible question presents itself, which is: How much volume loss should we expect, if we increase the price? So let's do the math to see how resilient the profit potential from price increase is in case of volume loss. See the result in Fig. 3b.
Whenever we increase the price, volume reacts in a negative way (under normal circumstances)-less customers will be buying or existing customers will be buying less, or a combination of the two. All in all, we can afford to lose a third of the total volume if we thereby earn at least as much profit as before. We are looking at a price elasticity of −3.3, a moderate to high price elasticity. If managed well, price elasticity should be less in many industries. I am of the opinion that making a price increase is the safer choice if you are not sure whether to pick price decrease or price increase. The numbers are more revealing than plain speculation. Do the math to be prepared or to be shocked! Now, let's return to the empty parking house case, I believe that offering deep discounts on weekends is most likely not the right answer to improving occupancy. On the contrary, it could make things even worse for the parking house operator. Why is that? Because the drivers who have to park in the parking house on the weekends will definitely be pleased if they have to pay less than they were willing and expecting to pay; on the other hand, the central business district on the weekend is meant to be empty. Pricing is no magic wand. Price decrease will not create additional demand in this case. If I were The Conundrum of Price Cut the operator, I would probably consider increasing the prices on the weekends in the face of constant demand. For those that need to come over to the place on the weekend, the demand curve is extremely inelastic. In simplified words, it does not matter how much you charge, they will come and park on the weekend. It is a different story during the week, where you can use pricing to manage capacity in a more dynamic way. The technological foundation for dynamical pricing is generally in place these days. Nevertheless, common sense about the relation between price and demand is still much needed and valuable. Another possible solution would be a loyalty program which grants frequent parkers free parking hours on the weekend similar to and based on free night awards offered by many hotel chains to guests that come often.
There is a strikingly similar project example where price decrease fails to do what we want it to do. The client of mine, in this example, is a B2B retailer for miscellaneous factory supplies, keeping in stock a large number of items. The market landscape is highly competitive, as the customers usually have two to three competing suppliers in most product categories. At the same time, it is also a business with a very fat long-tail, meaning that the offerings of different suppliers have limited areas of overlap (there are overlaps, though sourcing through different channels could lead to significant price differentials at the end customer) and customers generally have little knowledge concerning prevailing market prices (because there is none in many cases, when it comes to industrial long-tail products).
It is not uncommon for salespeople to be closer to their clients than to their own organization, and they are tempted to give discounts to please their clients. In the meantime, the management also wishfully hopes to boost sales through price promotions. When conversing with the CEO of the B2B retailer for the first time, I told him about my gut feelings on the spot: price decreases are futile, as there will be probably no effect on volume at all. After having made this strong statement, I had to prove it. Among others, the project team looked into the instances of price changes in the last quarter. To my relief, the data proved me right. See Fig. 4.
In the last quarter, there were about the same number of price increases and decreases. As the business was growing fast, we were seeing growth in sales volume regardless of the direction price changes were taking. In the case of price increases, the retail price went up by 7.1% on average; when there were price decreases, the retail price went down by 3.0% on average. Interestingly, we saw a stronger sales increase, where the prices were increased. In the meantime, price decreases failed to boost growth, while destroying margins. In the price decrease cases, profit margins dropped by 5.5 percentage points. Price decrease is guaranteed to be a bad choice when demand is inelastic. For our client in this case, the price elasticity in all product categories is generally low. We also noticed during the project that if clients are complaining about the price, there is oftentimes something else that they are not happy with, be it product-or service-related. Price cut is obviously not the remedy.
The CEO was so convinced of the results of our analysis that he soon hired a dedicated pricing manager as a conclusion of the pricing project. This is why we can proudly say that we are on the sunny side of consulting.

Remember This!
• Price has a huge impact on the bottom line. • Do the math before enacting any price actions, especially when you are about to decrease price. • Before decreasing price, you need to ask yourselves this: -Will I win new customers? -Will existing customers buy more? -Will competitors follow suit?
Don't decrease price unless you have clear answers to the questions above.