PhD Graduate Manasa Gopal & Prof Deepak Hegde - Faculty Insights: Covid-19 and NYC Series
This. Is bhatia recent Feldon I want to welcome everyone, to another session, of our faculty, insights, on covert 19. Today. We. Have a focus. On small, business, and entrepreneurship. And we have with us Manasa. Gopal. From. Our finance, department and Deepak, egg day from. Management and Manasa. Has, been doing some terrific research, on, financing. For small businesses, and Deepak. Of course is running, our endless, frontier labs, which, is a really. Exciting new. Accelerator. For, tech, based startups. And has, been directly, involved. In helping. Startups. In New York through the Berkeley Center where he also is the director. Figure. Out how to navigate this. Situation. The. Coronavirus. Calamity. And so, we have some real expertise. And, it's. Clear that kovat, is directly, impacting. These small businesses, and entrepreneurial. Ventures, so. Manasa, I wonder if you could share your screen, and begin with your presentation. Then we'll turn it to Deepak, and then. Open. It up to questions please. Remember to put your questions, in the Q&A box. It's. Great to beat that but yeah thank you for organizing this, session I. Think, as you mentioned clearly, kovat, has had a huge impact on, small. Businesses, and in. My talk I largely want to focus on the, extent, of damage due, to covered, on small, businesses, and potentially. Talk about how we can aid the small businesses, in getting, through this crisis, and. The. Reason, the focus is on small, businesses, is because, aggregate. Economic, recovery, is going to be very closely tied, to, how small businesses perform. Like, the reason this is is because, small. Businesses, which, are defined as firms that have fewer than 500, employees are. Actually ninety, seven percent of all businesses. In the US and. Nearly. 3/4, of these. Businesses, actually have fewer than 10, employees so. We're talking about, very small. Businesses. That contribute, a huge fraction, of the u.s. economy. Not. Only, are they large in terms of the, number, of firms but actually take, contribute, nearly half, of all of US employment. It's. A basically. Aggregate, employment, is going to be very closely tied to how small business employment, moves, and. This. Is also because. Small, businesses not only contribute. To aggregate, employment. They contribute, towards, new, job growth so. Annually. About, half of the new jobs that are created in the economy come, from small businesses, so, really. All of this just makes the point that if, you want aggregate, economic, recovery. We need to really focus on how small businesses are performing, and. This. Is important. Because, if. You see in the last few months small, businesses, have been largely, affected. By the effect, of code right. So in the. One month after, code. Was declared, a national emergency. Revenue. Of small, businesses, fell, over 45 percent so. We've seen some initial. Recovery in the past month, and a half but. It's nowhere close to, what the, pre covered levels were so the, revenues at small businesses, are now still over, 26, percent below what was the average click over word and. While. Revenues. Have gone down at, small businesses. The. Cost that small businesses, face have, not fallen at the same rate right. So what this means is, that earnings. At small businesses, have taken a big hit so. By. April 15th. Earnings. At small businesses, were 60% below, the, average. Level, in, in. Other years and again. Even though we see some sort of recovery. We're still almost 40, percent below where we were to be texture. As. Revenues. Fall and cost stay the same as earnings. Drop at small businesses. Most. Of this loss, has been transferred. To the, employees, of small businesses. It's. A way. If you look at hourly employment. And small businesses, this is again dropped. Over 60% in, just one month after. Cover was declared an emergency and, still. Is right. Now at, the end of May about 40%, below the levels we would like. Now. The season all of this is a big problem for. Small businesses, is they're, not really equipped, to, handle these large shocks, let's. The small businesses, don't, have much, cash on, hand to be able to accommodate large jobs and revenues, and earnings, nearly. 3/4. Of small businesses, when surveyed, at the end of April, said, they have less than 2 months of cash on hand for, operational, expenses.
And. If. We, expect. That. This. Crisis, will continue, for a few months which, seems like most small businesses. Do so, almost 90 percent of small businesses believe it will take them over, 2 months to. Get, back to normal operations. And for 1/3 of them it's over 6 months to get back to normal operations. We, need to find some way to compensate, small, businesses, for this loss that they're facing and. Typically. Pants. Will firms. Rely on banks, for, access. To financing, but, what we have noticed in the past is that, especially. In recessions. It becomes very hard for, small businesses, to access traditional. Sources of financing, so. If you just look at the, last recession. Small. Business, lending, fell by over 40 percent in after. 2007. And in. The last ten years. As. The economy has grown as overall. Bank. Lending, has grown will past, 2007. Levels the, lending to small businesses, from banks is still, not recovered to the levels they were at brief. Financial, crisis, right, so what we have now are, businesses. With a big, drop in revenue. No, cash on hand to, accommodate, these losses, they. Can access traditional. Sources of the financing, from banks that they typically, might so. The being in some sense attacked. From all directions, right, so we, need some sort of support to ensure that small, businesses, can actually survive, this crisis, and. Obviously. This was something I think policymakers. Understood. Very early on so. In late March when. The, case Act was passed a. Significant. Portion of money so around three hundred and forty nine billion dollars, was. Your marked for small, businesses, under, the paycheck protection, program. These. Were largely. 100%. Federally. Guaranteed loans meant. To. Be provided, to small businesses, to, ensure that they, can maintain payroll. And. Continue operations. So. These. Loans, were. Going. To be dispersed, through, banks and, borrowers. Could borrow up to two-and-a-half, times, their. Monthly, expenses, to cover payroll mortgage. Rent expenses. And utilities, and so on and, these. Loans, had extremely, attractive. Terms so, only 1% interest rates on loans for. Up to two years. Borrowers. Did not have to show, any collateral they didn't have to show prove that they couldn't access other sources, of funding just, to ensure that all small businesses, could tap, into these loans. But. Probably. What made the, Paycheck Protection Program so attractive. Was, that these loans could actually be forgiven, right, so if businesses. Spends the money on payroll and multi-region, rent and utilities, and so on this. Amount would actually be forgiven, by the government. And. Since the focus was. Third maintaining, payroll. Businesses. Were expected, to spend about 75%. Of the money that they received, on maintaining. Employment. So. As I said obviously the great thing about PPP. Was that, it was implemented. Early, on, but. There, were large issues. With, the picture protection, program, that became, obvious pretty, early on right. So one of the big things was the size of the program as.
I. Mentioned, early, on, 97%. Of the, businesses, in the US are classified. As small so. They could have potentially, been eligible, for loans through, with the PPP and there. Is no way 349, billion dollars would cover two, months of expenses for, this, large number of firms in the US who required the funding right, so we estimated about, 810. Billion would, be needed, to cover operations. Of small, businesses, for eight weeks and. Essentially. When this was implemented, it became clear. Early on that there aren't sufficient funds right, so the three hundred forty nine billion dollars, that were your marked ran, out in less, than two weeks, now. Because of this Congress. Passed an additional three hundred and ten billion dollars for, small businesses, about ten days later but. What, seem to have happened over. Time is. Businesses. Were getting. More and more confused, about what, it is they were getting into so. In the two months after, PPP. Was announced, there, have been 14, sets of different, rules on eligibility. For his loans on eligibility. For loan forgiveness and. Service. By the National. Federation of, Independent Business. Is shown that basically 3/4, of businesses. Actually confused, about whether, their loans will be forgiven and how. The businesses, feel, like they can actually spend the money in eight weeks because. Of shelter. In place and lock down orders, preventing, them from operating, and, all. Of this confusion led. To a drop, in borrower, interest, for these loans and the. Second round of PPP. If he still has about one hundred and thirty billion dollars, left even, though initially it was thought that three, hundred and ten billion dollars would run out in less than a week. Now. Because. Of, this drop in demand and because of all of this confusion at small. Businesses. Just. Last weekend, there were some new rules that were passed to make the, PPP, more attractive, to small businesses, and make sure they actually tap into these funds. So. Instead of having to spend 75. Percent on payroll like before now firms. Need to only spend 60% on payroll and they've, been given 24, weeks to use funds instead, of 8 weeks and the. Same time initially, there was penalties. To, small businesses if they were not, really. Hiring their workers now, exceptions. Have been made to that rule if the employee refuses, to, be behind all. Of this to ensure that. Small. Businesses, do tapped in to the PPP, and to, make sure we can rehire, employees, as was the goal. But. Probably. The, largest issue. With. The PPP, was. That there were no clear rules or guidelines, as, to which. Businesses. Should be prioritised, in the loan program as. It was left to the discretion of, banks, to decide, who, they want to approve, loans for and. Anecdotally. There. Is a lot of evidence that, banks. Prioritized. Their, customers. Especially their. Larger ones and a, lot of small businesses, were left unable to. Says the BBB and. This. Is not very surprising, when, you look at the long academic. Literature that, has argued, that, relationships.
Between Banks, and firms. Is actually very important, for access, to financing, especially, in periods, of distress right. So small, businesses, need to have strong ties to, their banks to be able to access funding. And. Borrowers. Without relationship, who are essentially, left out and, we. Can one, other potential, reason, that complicated. This was, that banks, are being paid fees by the government, for these loan approvals, and the. Fees were in proportion, to the size of the loan that was being made so. This naturally, also biased, banks. To approve larger, loans which meant larger, firms for getting these loans, and. If. We actually look at the data this becomes here, pretty easily, so what we see is a lot, of the small businesses, in say, the Midwest and the southern states were. More likely, to get loans under the peep peep peep even, though potentially. Regions. In the Northeast were affected, more by Corbett. And in fact actually there, is almost, no. Correlation, between, the severity, of kovat. In a state and the. Share of businesses, that received, loans and. One. Potential. Way to. Could. To target these loans could have been to actually, focus on which, businesses. Who, are more affected. By the. Lockdown. And sheltered. In place orders. The. Idea here being that, you. Know when shelter in place was. Implemented. And everyone, had to work remotely some. Forms could continue, operating as per usual but. Some, of them were severely affected because, their operations, could just not be done remotely, so. There is academic, work, to, create indices. On the. Extent of, the. Effect of shelter-in-place orders, on different, industries, so, if we had done that we could potentially have targeted, these loans towards. Businesses, that were most. In need of the loans at this point and. One, of the reasons to do that as we see that at least on the. Surface it doesn't look like, loans. To, smaller. Businesses, through the PPP. Improved. Employment. Rates in these states right. So of course this is very preliminary. Data, so we don't entirely know one. If these gains are actually going to be permanent, or if it's just a temporary gain in employment, so ideally we want to ensure that these workers are retained, in the long run but, we have to see what happens once the PPP funds run out and after.
Take Tweaks whether these employees. Are going to be retained and we. Have to also identify whether, these gains, are actually coming through the, PPP, loan acceptance. Or because, a lot, of economies, are now opening, up and loosening. Shelter in place and lock down orders, I. Want. To spend maybe a couple of minutes just contrasting. How the u.s., is responded. To the crisis, compared. To how other, developed. Countries have responded so I think largely, there have been two, strands, one, like the US where, they've opened up unemployment. Insurance benefits. To workers would have traditionally. Not being able to. Tap. Into them so, basically even employees. That are not actively, seeking, employment can, now get unemployment, insurance. The. Other stand. Which has been followed, by most, of the European, nations is actually. To pay, firms to ensure that they retain their workers, right. So countries. Like France where they, were actually made sure that if an employee is furloughed, the government will cover about 84, percent of the wages as long, as the. Firm. Retains, its employees, and pays them benefits, in, Netherlands. Again, 90 percent of the payroll cost for companies would be covered for firms, that saw a small drop in revenue. New, Zealand also similarly, failed employers. A fixed, amount per employee. To. Make sure that they were retained, on their, payrolls, and to. Make sure that a certain level of their, wages work being continuously. Paid. Australia. Squizzle, in Germany, Ireland all of them have followed, similar programs, and. What we actually see, is this has led to two. Very different, responses, right, so the countries, that, spent. More on a, lot of these short-term work, programs, or to fund, employers. Directly to retain their employees, have, seen a much slower. Growth. In unemployment, rate. Compared. To the US where, by, far there's been the largest growth in unemployment rate because.
Because. The funding, was not directed, through employers. To retain employees so. This I think largely leads to a question of what, the goal of such a program should, have been right, so if the goal is to make sure that, workers, are retained, on. Employer. Payrolls, and to make sure that when the economy restarts. These. Businesses. Can restart operations immediately, because you don't spend time rehiring, and Retraining workers then, maybe we could potentially have directed, money to firms, instead, of to employees, through unemployment, insurance, benefits. So. I'm going to hand, it over to Deepak. Now but I'm happy to answer any specific questions, at, the end. Thanks. A lot monster for your presentation, and thank you Bhatia for your introduction. And for, leading, the. Faculty, inside, series, with we're all I've, learnt a lot from the. Series which. Has. Helped, crystallize, all of our thoughts on really important, matters during. A period of unprecedented, uncertainty. So thank. You and very excited, to be contributing, to the conversation today. Monza. Talked about, kovetz, impact, on small businesses. And, I. Will, be focusing, on, cool. Xix, impact, on, new businesses, which. Typically, are also born, small, so. Of. Course there may be differential. Assist but what, I am going to be talking about now, is going, to be Co its impact on a subset, of the companies, that. Manso. Touched, on during her talks. So. Why. Why. Can't about startups, write startups, are well-known. As the engines, of economic growth. Between. 1980. And 2010. Startups. Defined, as businesses, less than a year old generated. 2.9. Million jobs, every, year in the United States this. Was one sixth of the gross jobs generated, by all establishments. And nearly. All, of the, net jobs created, in the US economy, the. Implication, of course is that cohorts, of older firms typically, exhibit, nut. Job declines, and startups. Are essential, to, add jobs, to the economy as, they have done over the past thirty years or so for. Which we have this data. The. Second reason we care about startups, is they, disproportionately. Contribute. To, research. And, innovation. As well as productivity, growth in. The u.s. if. You take many examples such as the airplane, the railroad, the automobile, electric, service telegraph, telephone, computers. Air-conditioning, and so on each. Of these were. Started. Up by innovative. Young, new firms, and. Ended, up fundamentally. Transforming. Consumers. Lives but, also became platforms. For many industries, to. Enhance, productivity. One. Staggering. Statistic, is that in fact, 85%. Of the R&D spending in the u.s. today is. Conducted. By Lisa, vac startups, born between 1974. And 2015. So. Really startups. Moment. Of founding, as well as, through. Years of their growth and, disproportionately. To our the innovation. And productivity, growth. Third. Start-ups. Are known, to enhance. Reallocated. Efficiency, what. That means is that startups, exhibit, an upper of dynamic, innovative, and, successful startups. Grow rapidly and become a mass spring of job and I cannot jumps and economic, growth or. They, can quickly fail and exit, the market hello. In capital, to be put to more productive users so. Startups, really enhance the ability for resources, to, flow freely - mayor - where is most beneficial in, an economy where reallocated. Efficiency, is high more, productive, companies grow why less productive, firms contract. Or possibly, exit, the. Economy a great. Example of startups, and reallocate, efficiency, is actually, the medium that is facilitating. Our conversation. Today, zoom. Was born in 2010, when, get it Eric you are then, the lead of Cisco WebEx group was deeply, dissatisfied with. WebEx, for. Those of you who have used Mac's, you, will know that, the. WebEx, conference, service required. You to sign up and then, identify. The system, that you were signing up from which, really slowed things down and. To many people on the line would have to strain the connection, leading to choppy audio and, video as well and. Obviously the service completely, lacks modern. Features like speed sharing forum violence, nor, so. You unreal, II wanted to improve the product, that Cisco. You. Know the buyback scheme that he was heading but, he was really not prioritized. Within, the company at all and. This left of this starting zoom in 2010, the. Company IPO, in. 2019. April, and today. After co-ed, the, company, enjoys a market, cap of about, fifty. Eight billion dollars, nearly. More than the combined market cap of three of the us's largest, airlines, highlighting. How quickly. Startups. Can seize on opportunities. As well as grow in response. To, what, might turn out be a.
Different. Set of ideal circumstances. In in, the face of changes. Such as the, pandemic. So. Three main reasons why we need, to care about startups. What, is Cobra Dontrell, startups, so. What what I do as. Much as I possibly did, is peer. Back into. Looking at how, entrepreneurship. The formation, financing. And. Performance. Of new businesses, was, impacted. By, previous. Recessions, primarily. The Great Recession of 2008, 2009 and then. Produce some, very preliminary data, on, coup in 19m. Cap on startups. And. We, will bring these two things together to understand, in what ways Cobin. 19 impact, on startups, compares. Or, contrasts. With, the experience, of startups, during the previous recession, and based. On this will try to quickly. Try. And speculate. About what the future might look like for. Startups. And entrepreneurship, in light of probe 19. So. The. Great Recession of 2008, 2009 saw a 20%. Decline in new firm formation, from, about, 700,000. In. 2007. To, about 560. Thousand. In 2010. This. Was by, all means one. Of the sharpest, declines, seen. In the history of the, United States other than during, the Depression, of the. 1920s. You will also see that, although. There, was a recession, following. The burst of the internet bubble in 2000, 2001, the. Impact, in terms of, new. Businesses. Started. The. Impact was not all that. All. That high relative. To the Great Depression, the, Great Great Recession of 2008 2009. We. Also look. At another measure, of. Activity. Startup, activity which, is venture financing. Venture. Capital, in the United States, accounts. For a, large. Proportion of, the, successful, startups, and. What. We can see here is that during, the. Recession of, 2008-2009. Venture. Financing dropped, from about, forty, five billion dollars, in, 2008. To, thirty, 1 billion dollars, in 2009. At thirty-one percent drop, in one year, interestingly. Deal. Count which. Is generally. Considered as. Indicated. Or, at least correlated. With. Allocations. For. Startups. New allocations, for startups, write, more or less stayed, the same at, about, five thousand eight hundred to five thousand nine hundred. Deals. Per, year what, this meant is that in light of the last recession. Overall. Funding, contracted. But. Deal, activity, measured. By their frequency, remained the same, this, basically, means that the average of, size. Of the the, deal contracted. So. VCS were effectively, writing, smaller checks for startups in light, of the. Contraction, so. That was kind of the primary effect or. The last crisis, we, can also look at another. Measure of startup, financing. Which is. Startup. Financing, and the seed or CD, sage stage generally. Startups. Bring on their first round of institutional. Investors during the seed or the CD SE stage and what, you see here as well is about, a 30%, drop in, seed. Stage financing from. 2008, to 2009. What. We also see however is that the number, of deals seed. Seed and seed Issei as stage deals dropped which, meant that very, likely the. Companies, that were seeking financing, for the first time during. This period were the most yet. Through through the contraction, of, BC finance. So. Obviously. The. The rate of startup, financing. And formation, came down during the last recession. Obviously. We care deeply not, just about the rate of startup formation, but also a lot of the quality, of startups, so. A key question, then is the, start of quality, go up during, recessions. One. Argument for why the. Startup quality might go up is, basically because. During. Slumps, there might be a positive selection, effect right, if, you assume that we cease can somehow.
Discriminate. Between really, high potential startups and less high potential, startups then, if they have less money to deploy they're going to go after the best deals, so, basically maybe it's it's going to be the best startups, that are able to survive and thrive during recessions. And if, that is the case you should actually expect, startup quality, to go up but. On the other hand that, is the larger. Sort. Of economic. Environment, that really depresses. The. Demand, makes, it may be hard, to access the sort of talent that might. Because. They fear, uncertainty and, don't, want to take risk are less likely to work for startups, and the. General of freezing of those capital. Markets might also mean that startups. May not be able to raise the funding to invest, in their plan ace, further. Sort, of affecting, their, quality so, basically, it's. Kind of an empirical question and there's not a whole lot of good research on whether, startup. Quality, goes up or down during. Your sessions, many. Obviously. Those. Who are particularly, excited, by startups, suggest. To. The suggestion. Point to the examples, of companies like these Dropbox. Groupon, uber, whatsapp, which were all born during. The last recession to. Suggest that maybe the quality. Of startups, that come out during recessions is going to be particularly hot there, are also other great examples Microsoft. Was born during in 1975. Disney, during 1923. General. Motors during, 1908, and General Electric during, 1890. All, times. Of deep, downturns. So. We. Really don't know so this is kind of one, hypothesis. And. Recently. There was about. Three weeks ago the economists, put out an article. That spoke to this. Particular. Aspect. And. The. Article, suggested, that, almost, 500. Of today's biggest, listed, firms in America, whose origins, date. Back as, far as, 1857. A majority. Of them seemed, to have started their life in expansionary years, than during recessions. So. Basically. Of those hundreds since 1970. More than four-fifths, that, survived on the fortune 500 today were, born during expansionary, times, rather during, it rather than during recessionary, times. This. Then suggests that perhaps the. Folklore, that startups, born during recessions, tend to be of high quality, does. Not hold, up to, a closer scrutiny with, a larger, sample. There. Are some recent evidence also being put together my colleague, in the finance department Sabrina. Havel, which. Looks. At patents. Taken out by startups during, recessions, and. Suggests, that, patents. Taken, out by startups, that are backed by VC's during recessions, tend to be less, important, and less technologically. Impactful. And. Less closely related to fundamental, science also. More. In line of. Economists. Sort, of hypothesis, that there. Is a pullback and startup quality, during. Recessionary, times. So. It seems like overall the weight of evidence, you. Know imperfect, as it is seems to suggest. That startup, quality, actually declines, during discretionary, times, there's. Also a, third, key effect, on startups, which is, the. Direction, of activity. Pursued, by startups, during, recessionary, times and, what. We see is that at, least during the Great Recession of, 8:09. There, was a big, contraction. In startups. That. Were pursuing, information. Technology, ideas, so. Basically, typically. The number of hours around 50%, 50%. Of, the venture financing goes. To IT companies, but during the recession, that number came down to about 35%. In. Howard. Between 34, and 40% okay, and, then gradually, started picking back up as. The economy expanded. So. It seems like at least during the eight or nine recession, there was a pull, back on IT. Investment. Even. As a relative, proportion, of VC. Funding. Now. The. Other sort, of effect is on the. Different the differential, impact of. Recessions. On different, startup ecosystems. The, big ecosystems. In the United States are the, one in orange here which is Silicon Valley the West Coast broadly, the. Second largest ecosystem, right. Now is actually the New York ecosystem, that is indicated, here in blue - and include, the New, York DC, Bell and. Then the. Boston New England ecosystem, now is the third largest in, terms of, overall, venture. Activity, and what. We find here, is that. Interestingly. During. Recessions. At. Least, you. Know there is a pullback in. Activity. That happens, in. Maybe. The Northeast. It, seems, like the Oh 8 2010. Recession, particularly.
Impacted. New. York the New York Region startups, in the New York region as well as in the New England region the, difference being that New, York seems to have recovered, handsomely. In the expansionary, years, whereas. Boston. Seems to have had more of a difficulty, in regaining its place, as effectively. The second largest ecosystem in. The United States so, it. Seems like very. Likely through, the channel, of sectoral. Investments. Recessions. Also, have an impact on the geography of, startups. So. Overall, what we have learnt then from, past recessions, in particular, the, 2008-2009. Recession is, that recessions. Lead. To a decline in start-up funding rates about, a 20 to 30 percent decline, in, the in the past Great Recession a. Decline. In average start-up quality, a. Decline. In IT, start-up investments, and possibly. A decline, in northeast. Start-up, investments. So. Now that we can turn to kind of co-ed and with the little data. We have trying to see whether and, to what extent, the, patterns, we see the data reflect, what happened during the previous recession, so here's, new. Form formation, particularly. This, is new. Form filings, by those who are likely to take employees, on their payrolls, the type of. Startups. That generate jobs and we care, about what, you see here was an, unprecedented. Decline, in, new. Firm filings, from about 30,000. Per. Week, in, beak 9 to. 19,000. Per week in, week, 10 of this year this, was basically the first thing of. March. When. Coronas, effect. Was, kind of really, starting. To kind of kick in and you see kind of the unprecedented, nature of the decline it's, not even anywhere, operable, to the. Declines, even, during 2009, okay, so, there was about a four. To five leaf period, then the declines persisted. Really. Record levels, in. Terms of the, hit to, the startup, activity. And then eventually the. Good news is over the last two to three weeks we have started, to see a pull back where, we are actually seeing, a return to. The numbers as. As. Was. The case during an, expansionary year. 2019. May, so, right, now we are at a point where it seems like we have recovered. The. Second, aspect then is venture, funding, and if you look at venture activity. As well we, see. A decline here, from about, 13. 13 and a half billion dollars to. 11. Billion dollars in, April, so, it. Seems like much of the activity was, felt in April, not in March obviously, because startups. Get into conversations, early and it takes about a month given the due diligence etc. For activities, too close so likely. Yeah. You know the. The reason why you don't see an impact in March numbers, for, VC funding is that most of these deals were, essentially, kind of, closed. During previous, months or. At least committed, during previous months you see a sharp decline in April. But, then a very handsome pullback in May. Okay, and this data is basically hot off the press. So. It is current. O n May and we see we are seeing a very good recovery there, is however a, decline, in the number of deals which. Very, likely means, that, you. Know. VCS, are effectively, writing, bigger, checks, for. Existing. Companies, and are. Probably, not investing. In new. Deals at, least relative. To what generally, happens during, expansionary. Periods. Or normal times this, is confirmed when you look at funding. Numbers or seed. Stage companies. There. You see a sharp decline in new. Deals from. 343. You. Know in the month of March to 223. In the month of April, holding. Steady in the month of May in spa so, it seems like there's a contraction, in. In. In. In new, foreign financing seed financing that, doesn't, seem to have really, recovered, even in the month of May although there also you see a slight, sort. Of up taking the overall figures, if not as a deal numbers. In. Terms of the, sectoral, allocations. What. You see here is kind, of rather, remarkable. And stands. In contrast to. The effect of the previous recession. Where IT investments, were, among the first to be hit you, can see here that I be starting. On startups. That. Are pursuing IT based ideas have, actually. Maintained. The relative. Share and even grew the relative, share when, the contraction, happened massively overall, contraction, of VC funding happened massively, April. Growing. Their share forty eight percent which. Is really kind of remarkable. Main. Numbers, it, seems like ID investments, have kind of decreased, but, usually there's some sort. Of you. Know reallocations. In, refining, that gets done by pitchfork. Likely. Value of the many. Of the companies that are being categorized as, B to C here our tech enabled and are likely to end up as ID investments, here but at least when the decline was the sharpest, in April you see that IT grew it's also, share of Finance. Likewise. May. Be related, to the fortunes, of IT, Silicon. Valley seems to have grown and strength covered 19 relative, strengths or 19, seems, to have increased the proportion of investments, that silicon valley-based startups, seem to have enjoyed and obviously. There, seems to be a halting. Of the march the. Constant, upward trajectory that, new york-based.
Startups, Were sort. Of on, since. Covert 19 and you see a pull back in New. York numbers. Here. So it seems like, you. Know for a variety of reasons. Silicon. Valley startups, seem to thrive, even in the face of :. So. A summary, then, of. Kovat unprecedented. Decline in new firm formation, in March and, with a sharp rebound in May venture. Funding, declined, sharply, in. April, but, also seems to have rebounded back in May in terms of the overall numbers, if not in terms of the number of deals. IT. Startups, seem to have increased their raft of share of venture financing during. The downsizing. Certain. Valley startups, also seem to have increased their share of metro financing. During, those downsizing. What. May not have been evident, in. The bar charts that I showed, because the overall share of finance, related, startups. Tends to be relatively, lower is a, sharp pullback, in venture financing for, financial, service. Startups, you, know going, down from a high of about, 6 to 8 percent of all venture investments, to 1, to 2 percent of all, venture capital investments, during. April so that seems to be a huge, pull back as well, so overall. Where we stand it. Seems. To me that. Looking. Ahead we. Are right now facing. A fork in the road and, I. Think two, scenarios. Are. Equally, plausible, and, can play out the. First, scenario is, the. More drastic one, where, there. Is a wave - of the pandemic, with, some. Of the. You. Know. Numbers, in terms of job losses and. We're. Still that's, kind. Of return to what we were seeing in late, March and, if that happens, very likely, the, rebound that we saw in the data is likely to be short-lived and you will see an unprecedented, decline, in start-up formation, what. You saw in early March was absolutely. Kind of staggering. And if we have a, few, months of that type of. Contraction. I think we, are looking at losing, an. Entire generation, of startups. Here in the United States, very. Likely if, the, patterns from the last recession hole. Under. This drastic, scenario, you will also see a lower average quality, of startups you. Will see tremendous bargaining. Hands. In the hands of, power. In the hands of investors, who are willing to deploy, their dry powder and you will see the. Return of investor. Friendly turns and. You. Will see obviously, a decrease in valuation. Numbers. For the startups as well I think. Relatively. About shielded will be IT startups, and, if you think about id technology, what it does really, write the, pandemic has been unprecedented, in, terms of either completely. Reducing. Or. Or, definitely. You. Know, having an impact on our. Ability to communicate and. And. What, information, technology, does is really reduces. The. Communication, cost if you will and that's. Why it's been such, a powerful, substitute. In. In, these times and we, can expect, the. Relative, strength of IT to hold and. I. Feel, possibly. Given. Given. Silicon, Valley's dominance, as the. Place where new. Information. Technologies get. Generated as well as, the. Likely, effect on the financial sector New, York City's growth as, probably. The fastest, growing. Startup. Hub may, be halted, and. But. On the other hand the, recent numbers look good and if we continue on our present trajectory.
Where The pandemic spread is. Relatively. About controlled, then we are likely to see a quick rebound and recovery in start-up formation, we are already seeing it in the data and. The. Missing generation, of startups and ideas we, suggested. Will. Kind, of likely. Eliminate, to the ones that, really. Have to exit the market so optimally, because of about. A month of sharp contraction. Eide. Startups, will still, continue to. Right perhaps. Because. Of social distancing. In all other measures that will likely how to be in place effective, affecting. Communication, cost and New. York City might be able to pull back and. Regain, its. Prominence. As the fastest. Emerging. Hub for startups, so. That's. What we haven't very much hoping for leave. To while, not. Necessarily expected. Thank. You both so much for, such, a you, know such really. Thoughtful, and insightful. Ideas. And, and data with respect to both, small business, and entrepreneurial. Firms I, wanted. To just. To kind of start out I'm wondering. About some, I'd like to pose some questions one. Of the things that both, of you highlighted. Is how. Dependent. These startups, are on financing. And, well. Startups, and small firms are on financing. And manasseh. Really. Highlighted. The. Fragility. Of these. Small, firms and, at. The same time. Highlighted. The, fact that, so much of our employment, is dependent. On these small firms and I, guess I'm wondering what. Are you, know so, Warren Buffett said when. The tide goes out you find out who's who was swimming naked it. Does Cove it kind of helped us to understand, a level. Of fragility. Among. Our smaller. Firms, and perhaps among, our newer firms, that, is unhealthy. Or, is. This, actually, a good thing in, terms of the, you. Know that in fact we expect this sector, to be, more, agile, to have this reallocated. Of efficiency. That Deepak, highlighted. So. I guess, the first, question is, is is there, a level of fragility that, is not. Appropriate. Especially go. Manasa. Highlighted. The need to, have relationships. With banks so. It simply sounds like it's not just what you know but who you know not just how good you are but you know their faith in you so, so. What, what should we be thinking about, should, there be. Policy. Changes. Should there be. Should. We be doing things, differently, in terms of recognizing, that we're dependent, on these smaller firms and newer firms especially, for, employment and yet they seem so fragile. How. Do you wanna go first or. Okay. So I guess, one. Thing potentially is I mean even in normal times I think we see it that small businesses, younger businesses, fail very often, and of course I think at one, level that's a good thing you know one resources, allocated, to inefficient. Businesses, I think about. 10%. Of businesses, fail in their first year right, so there is a large reallocation. Even in normal times I think the question, is if a lot of this largely, depends, on say something like the relationships, that you have which, take a while to form then it is not, evident, that these are worse, businesses. But. Potentially, just businesses, that don't have the right connections, yet because, it takes a while for bands, to start initiating. Real. Credit relationships, with smaller businesses. Peer. In terms of you know giving, credit lines having accounts, having normal term loans, banks. Tend to do that for firms that have existed, for a while because they like knowing, that these businesses, will stick around so, you need to have sufficient history. Of good cash flows to, be able to access financing, and, how. A good firm you are it takes a while to establish that, history. Great. So. -. I said but, here your question of whether. Can have the fragility that we are seeing in the data particularly, with respect of the u.s. is a good or up - I. Think. It's a great question and, really. In, my, view at least depends. On the reasons for the, downturn, I think. We. See job losses you. Know you pterence. It is natural, it's the process of creative destruction but. If the. Many. Of the downturns, are precisely, brought, about because of inefficiencies, in. The system and. Basically. The, doctrines, that play, the, role. Of. You. Know reaching the market back to, a new better equilibrium. And. If, you take the, downturn, of. 2001. Right, 2000, 2001, that. Was on. The back of a massive. Inflation, in. Values, of software, startups, even, while there was no pathway, for them to be creating, the type of value, that was being suggested by the. Stock market. Valuations, of these companies, we, saw a downturn we, saw a reallocation, of capital, and arguably. That was a good, likewise. During.
2008-2009. There, were some excesses on the financial, side, and that there were other inefficiencies as, well. Which. Got connected. Immediately. Arguably. Yet. You know at least in the long run, and. Probably. Then the, fragility in, fact led, to the creation of a more robust system, I think. Cohen 19 has been. Fundamentally. Different, in the sense that what, has been brought on us upon. Us has, not been due to any fundamental, in, inefficiency, economic, inefficiency but. It's a hot shot and. So. It is less clear than that. The. Policies, that at, least keep this fragility, or or, or at. Least do not do anything to address. It will, have the same benefits, as might have happened during other recessions. And. I'll leave it at that yeah. That's very helpful, let. Me pose two questions, that came from my partner virile, and. So, those two questions are. Should. We be thinking about the decline, that you highlighted, Deepak, in these, startups. The. The kovat related, decline as just, mothballing. Is it possible, that some of this is really a permanent, loss and. And. You kind of highlighted, these two different, directions, where. It seemed like you were suggesting that, what happens, in the next couple of months is going. To is going to determine those two so that's kind of the first question, and then the second, one is, is. It not just about financing. But also kovat. Related, disruptions. In productivity. And, I. Feel, like that one we could actually see, that being just, as relevant to, small. Businesses. And maybe, some of the ones that are failing. Might. Be in industries. Where it is you, know for example more, hospitality. More. More. Restaurants. Etc in, industries, where it's going to be really, hard to become. Productive. Back. Again, and. And. So, what. Are those two different effects maybe the first question, Deepak, you might start out with the second question well. Some might start out with okay. Great, so. Thanks. A lot for all the, question about whether what we are seeing is kind of what that mothballing. Versus. Permanent. Loss right, at. Least up until now. You, know he's. Based on my conversations. With the VCS it, very much seems to be more. Along the lines of what you called mothballing, Baba, so BC's are saying. VBR. Appears, to be are still interested, in looking at startups, but. You want to be kind of chatting with them we want to have our read ourselves, we. Will be very cautious. But, we are not closed for business is, what they're saying. Okay. So at. Least on, the whole that, seems to be the case and. Then part of it really kind of you, know goes to. The. Lifecycle of venture firms they're generally, they get money from, limited. Partners, and. Health, funds, that have, turn off about 10 years so. In fact the. At least technically. The amount of dry powder that they have to deploy has, not taken, as much of a hit because. Of Cove in nineteen, so. That. Might explain kind, of why. This might seem more of balling, a fad correctly but at the same time there's also evidence. Of permanent, loss and particularly, even, in the data I highlighted, that the, sharpest contraction. Or pullback has been in terms of funding starts. At. The seed stage seed, stage is kind of the first time they're the, startups, are approaching, the. Institutional. Investors, and I, know for example startups. With maybe. One, or two business. Employees that, they absolutely need. It to be paid, you. Know you. Keep. The startup going right. If. There's not going to happen even as many of these employees, who are running labs for instance, could. Not go into the last and the starts could not afford to play these. Unproductive. Employees even if they were the only person on their team and they, have to basically get rid of them and. And. I think there, are some of those cases, also. Obviously. That, suggests, that there have been permanent losses and, really it's a matter of time I feel the longer this prolongs, and the more likely. Be returned to the drastic world scenario, the more of the permanent, loss of steam you'll see but. Right now by, and large it seems to be evolving. And. So why. Not so maybe you could address the question of do. We think that there are productivity. Losses I know, also. Part, of what, Deepak referred, to is a. Digitalization. We certainly gone through a digitalization. Working. From home remote, work the question is is it more. Or less productive. Obviously. A lot of businesses, can't do work from home. CEOs. Are telling us that work from home is even more they're.
Having Productivity. Gains in work from home I wonder, if you think that these. Kovach related, disruptions. Are, coming. From productivity. Changes. Yes. I think yes I think that's a great question so it was something I alluded to briefly in, the talk which is about you know Cohen has differential. Effects. Across, different, industries different. Firms based on their ability, to remote, work right. So a lot of said tech firms are able to. Continue. Well cannot actually even be more productive working. From home well there are businesses, that just cannot do any of their operations. Remotely, and one. Of the reasons, for like may be differential, targeting, of these business. Loans would have been helpful was, if work. Is continuing as, normal, if earnings and revenues at certain businesses, will, continue. To explain, flat maybe they don't need government. Assistance as much as businesses. That have lost their ability. To continue working because, potentially it's useful, to have airlines, and restaurants, around when we come back from, the crisis, even if they are not particularly, productive at this point because there's just one, drop. In demand and true they're just not able to work when, everything. Is under, lockdown so. I think at some level they need assistance. To, survive this crisis, because at the, end of it we wants them to survive so yeah. I mean but actually people will still take slides after. Yeah. You know kovat has found, a treatment. So. As we're getting to the top of the hour one, last question, that I think really interests, everybody, who's got an NYU Stern, connection. Which is are. There, things that can be done in New York or in the Northeast, in our area, to, help to support, small, businesses, and entrepreneurial. Firms are, there things, that you'd like to see from a policy standpoint, from. From. A financing. Standpoint. Or any, other. Perspective. That, would be that would help to, buffer. New, York sort, of put New York back on the right trajectory. So. I don't know if this is New York specific. But I think we, think that is potentially, being, noticed, is even when the, economy is opening up it's not necessarily. That smaller, businesses, are back to having levels. Of revenue that they had free crisis because, consumer. Demand still needs to go up right, so maybe potentially one, way of helping, small businesses, is to actually redirect. Some, of the demand, towards small. Businesses, and I think at least around NYU there are a lot of them. Yeah. So I think that's the one way to potentially improve. Outcomes, at smaller businesses. Anything. You want to add Deepak as the. Head. Of our endless frontier labs, and therefore, invested. In the future of entrepreneurship. In New York City now. New, York has always been a great, place for. Entrepreneurial. Activity. I think. The. Big, difference between Silicon, Valley and, New York is that, it. Is. Silicon, Valley somehow, has managed, to acquire a repetition, of building.
Startups. That. Seemed. Relatively, well shielded, from economic. Upturns, and downturns, for better or for worse, and. The, role of universities has, always been, very important, you, know because universities generate. Its. Scientific, and technological innovations. That can create. Or improve, productivity, in the long run so, in, fact them, for. New. York to be very much the same up until now it appears much of New York's uptick, in north neural activity has been driven by the markets, here the. Businesses. Rather than the push sort. Sort of strategy, but, for. New York policymakers. To acknowledge. And recognizes, that all universities, are amazing, and. Can equally contribute to entrepreneurship, as they have done in Silicon, Valley would be phenomenal it. Would also make us more, robust I think in the longer run, thank. You both so much for such, a terrific session. It was full, of insight. And and, definitely, gotten, you know it sounds like we need to all be doing more to support our small businesses, and entrepreneurial. Firms thank you very much and we'll see everyone next week, thank. You come on so thank you everyone. You.