 That's very nice what he said about the ECB, but it's very modest, I mean, this conference. I think it was a very good initiative, so I really, to you and to Diego, also, have been instrumental. I think it's a very good idea. No, it's not my cup of tea, so it's one of the occasions where I feel uncomfortable. I think it's a very difficult topic to be concrete. It's refreshing, I thought, also to listen to the commissioner, because with all these secular stagnation stories, sort of pessimism, now we have a more positive message. But still, it's very challenging, because what is not addressed in that sort of conference is trying to put together all the elements that make that. Why is it that Italy, for example, productivity start to stop growing already somewhere in the mid 90s already? And there are very interesting studies trying to explain that. But when you try to explain that, you have to combine many, many different things that combine together and lead to that situation. So this session is essentially on advances in measurement of innovation and entrepreneurship. We have three panelists, and I will, I mean, they were very great, because I got their CVs and it was terrible, because it was too much. I would have spent so much time by reading the CVs, so they were very nice to say, do it very simply. Let's gain some time. So we will start with Fred, United Nations University, Merit, and you, by the way, Merit. Yes, and then Christian Kettles from Harvard Business School, you are going to follow. And then finally, Scott Stern from MIT, Sloan School of Management, you will finalize the 10 minutes introductory comments. And then we go into, first maybe exchange, reacting to each other. And then we open the floor to the audience. And so let's start when you are ready. And you are ready? You're ready? OK. So we will start. Most of the words you're about to hear have been spoken by previous presenters from the very beginning until most recently from the commissioner. What you will get in this presentation is a discussion of why we try to measure these things that people have been talking about. So we will ask the question, why broaden the definition of innovation? Perhaps you didn't already know that it was a limited definition, but don't worry about it. The outline, if I can press the right button. Ah. Yes, on the right. Very good. The outline is very simple. The issue here is if statistical measurement, that's what people do at Eurostat, this being Europe, is to support the development of innovation policy, pause, and the monitoring and evaluation of implemented innovation policy. And notice I've just slipped a word in there, which is implemented. Ministers can talk about policy. They like to do this. But the real question is what happens when it is implemented, made to work, or at least made to try to work? Who is going to do the monitoring and evaluation? This is where you get the odd statistician who can be easily dispensed with when it doesn't give the right answer. Then measurement of innovation must, must be made in all economic sectors. And you may think it is now. Well, it isn't. That's the summary of this talk. So measurement of innovation in an economic sector includes measurement of the linkages between the sectors. And we've heard a lot today already about how sectors ought to be linking together, how they ought to be collaborating on innovation and research and development and other things. So how do you measure that? And what does it mean? And the policy implications then of broadening of the definition is what I will end on. So this is a rapid tutorial, which you don't have to take. Down, talking about sectors, down the left hand column is what you will find in the System of National Accounts Manual 2008. Not every one of you may wake up in the morning and read that manual. But it is actually quite interesting in places. Down the right hand side, you get the words that I will use in the course of the presentation. Where we're going to spend some time, perhaps even two minutes, is on systems approach. And as we are dealing with innovation, well, the actors that we're going to talk about are universities, government departments, business enterprise, private non-profit organizations. And they engage in activities. And those activities might be training the workforce to deal with innovation, might be making capital expenditure to support innovation. It could even involve research and development about which we keep hearing as an activity of innovation. These people, institutions, are engaged. And notice I said people. I will get to Eric von Hippel at some point, are engaged in linkages. They connect to one another. And those linkages can go both ways, or just one way. But that's where the material, the energy, the finance, the knowledge, the information flow back and forth and have influences on what the actors do, outcomes. Now, we just heard about jobs and growth being a good thing. Every innovation policy I have ever looked at down at the bottom of it has jobs and growth as a priority. So nothing new there. Leading to long-term impacts, and that might well be well-being if you're lucky. But innovation doesn't always work the way you want it to work. I won't talk about innovation in the financial sector in the United States pre-2008. We'll talk about something else. Innovation for measurement purposes. This is where we are now. This is a little frightening, but it is where we all are now. So humor me for a moment. It is the implementation. And I'm reading to you from the Oslo Manual. This is the manual which governs innovation in the business sector. It's a joint Eurostat OECD manual. This governs your life when you worry about measurement. It's not so big. It's not so big. This is true. It's not so big. It's about to get bigger, where in the process of revising it, it will become quite heavy and will have greater impact when it is dropped on the foot of the minister. So let me get to what it is, a new or significantly improved product, or a new organizational method, business practices, and so forth. What the word that is critical here is implementation, that word again. And a new or improved product is implemented when it is introduced on the market. Business enterprise introduced on the market. And then processes are implemented when they're brought into use in the firm. All of this you can read in the Oslo Manual, which you can download and read at your leisure. So that's where we are now. But where are we going is the question. Now there's too much on this slide to absorb in the time I've got. So the only thing I want you to look at is made available to potential users. Previous slide, we put it on the market. This slide, we're changing the definition a little to say we're going to make the product, which is a good or a service in national accounting language, made available to potential users. That gets rid of the market problem. And we can now be a university or a hospital or government department producing a new good or a service and putting it out there for potential users to use. This liberates us considerably. So I can now talk about firms, public sector institutions, Eric von Hippels, households that make new or significantly change products available to potential users. Now, all this is interesting. And if I were coming out of the business sector, I would say, OK, there's no change. Because the way in which we make product available to potential users is we put it on the market. Not quite. You've all got an I thing or a smart thing in your pocket. And when it's not talking to Langley or GCHQ telling people about you, you will have apps on that thing for which you have paid nothing. You are using email addresses for which you have paid nothing. You've all got a little corner of the cloud for which you have paid nothing. So there are products out there being put out, made available to potential users. That is you, which are quite different from market priced products. So we could end up with two kinds of innovation discussion. So that is worth thinking about. However, if we do that, we're going to have to have more surveys. If there's a statistician in the audience, you'll recognize that surveys cost money. And therefore, if we're going to do any of this, we need a bit more money. Well, that gets us to outcomes. Internationally comparable definitions of innovation for all system of national account sectors, support for policy development in public and the business sector, and for monitoring and evaluation of the word again, implemented policies. So then, stimulus or more analysis, key word, analysis, we don't do enough of it, of innovation and all the sectors and the interactions between them. Now, I won't bore you with non-linearity, not that kind of meeting. We will move on. One of the little problems that we have, and we've just had it, is that nobody really cares about the propensity to innovate of a government department or a firm in country of your choice being 55%. That does not interest our political masters. What interests them is jobs and growth. So, OK, everybody is innovating. That's what the surveys say. What is it doing for the people? The jobs and growth issue? Or sustainable, green, inclusive, pro-poor, take all those words and string them together and you end up with what is called restricted innovation. So it isn't just a case of taking the definition and applying it, getting the answer. You insist that it give rise to the political objective. And that requires subsequent surveys. Some social surveys even, this will frighten some people. We could look at the impact of technologies and practices. And there is artificial intelligence, the cloud, the digital economy. We keep hearing about them. Mutual distributed ledgers. In this room, you will know mutually distributed ledgers by a different name. And somebody will say it at some point if you're in fintech. New materials, hmm? Yes, blockchain. Yes, and that is all over this community. But I will move on because my time is about out. So to measure restricted innovation requires additional surveys, including social surveys, conducted at different times. We've just expanded the time scale. And that's a whole different analytical issue for survey statisticians. So conclusion, innovation happens everywhere. Definitions are not standard outside of the business sector. We're working on that. Work has been done in the public sector and the household sector. You've already heard about, Eric. And the definitions need to be standardized. So that is the message I bring to you. Broadening the definition is a step in this direction. Then we can do policy and impose restrictions and have a better analytical understanding of the system. So that is the issue. Now, if you want more information, not for the partially cited, I can't see it from here, you can have a look at that paper, which you get by clicking on the URL. There you get all the references. And that's it. Thank you. Thank you. Thank you. Thank you. I mean, it's a little bit worrisome because we are nowhere. I mean, I understand the definition, which is quite broad. But how far are we in doing that? So it depends, perhaps, of areas. Can you give us some example or where we could implement that sort of measurement? Well, we have some examples in the Nordic countries which have been studying public sector innovation. The next sector innovation. That's what you mentioned also. That's right. And that's the closest to having its very own manual. So that could come back in the discussion. But we're seeing a little bit concretely because I think the broadening of the definition is quite interesting. I can follow you. But then I say, yes, but can you give me examples where this definition is really useful today? Yes. And I got the impression we are not very advanced yet. I mean, because you are still at the level of defining what you want to measure. And in a definition which is not so easy, I mean, to implement. Yes. And then that's not opening the debate, but just to get a quick answer. And I won't respond at this point. Well, I can give you a very quick response. All this is based on empirical experience. So our Nordic friends are measuring public sector innovation. The definition doesn't quite align with other definitions. That's how we got into this 25 years ago, built on 15 years of experimental surveys, we learned how to do it. Then we codified it. We wrote it down. This is the third edition we continue to learn. Painful though it may be, we continue to learn. And we are now producing the fourth edition. And there will be some reference to this material. So it's worth reading. I mean, I would have a look. Read it before the end of the year because then there will be a new one. Christian, Christian. Well, thank you very much for the invitation. So Fred made the point on your last slide that innovation is happening everywhere. And that's, of course, an optimistic view. We also heard from the discussions earlier today that innovation is very spiky. And I want to talk about two dimensions, I think, in which we hopefully understand now better how the environment in which innovation and entrepreneurship is occurring is actually quite different across the overall universe of the economy. One dimension is geography. So I'll talk a little bit about regions and what we learned about different regions. The other one is about sectors because I think what we've also seen is that innovation and entrepreneurship happens in specific sectors and in fact often at the intersection of related industries and related technology fields. There's been quite an advancement, I would say, in terms of the data that's available. And I'll talk a little bit about that but then also want to drive it towards what are some of the emerging policy implications out of that data that is emerging. Now, if you talk about geographies and you talk about related industries, that's really what cluster is all about. And clusters is not a new idea by any stretch of the imagination. It has been in the literature for hundreds of years. Mike Porter's book came out 26 years ago. But there has been a decisive shift in the discussion. And I think we moved really from these case studies that looked at Frankfurt Finance or Southern German Automotive or of course Boston Biotech and other examples to really trying to look at comprehensive data sets that help us to look at the entire economy. And I think the specific important insight is that we now start not to learn only from the top performers. You know, how did Silicon Valley get to where it is? But we understand much more about the average performers. What are the challenges but also the opportunities that they're facing? How do we get about that? And you know, this is actually a lot of work that Scott Stern and his colleague Mercedes Delgado at MIT have been doing. Well, we first looked at the geographic footprint of industries. You know, this is a little bit the old traded local. But it's actually a little bit more than that. It's about how do you view industries in terms of their geographic distribution? Which are the industries that tend to concentrate versus those that are broadly distributed across space? We then looked among those traded industries. Which are the ones that tend to be connected? And we looked really at the revealed evidence of co-location of input-output locations and also of skill linkages that exist between those. And the third step was to kind of look at what's the interaction between these cluster groups, these groups of related industries. What's emerging at the boundaries? The reason is that this is important is that we see that the competitive dynamics are really very different between the traded and the local. And I think Scott will probably pick up on that. Entrepreneurs in the traded sector have an opportunity to serve a global market. Entrepreneurs in a local industry can also be great, but their growth potential is initially limited by the local market. Many others have looked at linkages between firms. I think what we feel is that looking at the revealed evidence of co-location and the other linkages actually gives you a sense of something that's very irrelevant for companies. Because these are the other types of sectors and industries that they earn acting with. The downside of our data approach, and that is why these grouping clusters are so important, that it has a tendency to be backward looking. Because the geographic footprint is kind of the cumulative effect of all the things that mattered in the past. Now what we want to look at an innovation entrepreneurship is we want to look forward. And so for that, I think we've seen that really understanding cross cluster linkages is quite important. But we wanted to move beyond just stating that industry A and industry B is related. What we instead look at is, you know, where are there already today signs of weak linkages that might be coming something more in the future? Here's an example of digital industry, some work that we've done for the European Commission. Each of these colors is kind of one traditional cluster, so set of related industries. But we see that this group here in digital industries shows evidence of being related to each other. So what we're studying is, you know, whether or not there are new combinations of industries emerging that form the nucleus of new clusters, trying to understand how that's going on. So that's kind of giving us, if you will, a language. It gives us a set to look at the data that exists about national and regional economies. What's the type of data that we now have available? Well, for example, we can look at all of these cluster categories. Here's one example, production technology was a little bit more where Europe is strong and already has an established position. Well, we can see what's the geographic footprint like. And if you are a region within these darker areas, you can figure out who are my peers? Who I'm really competing with? What are the relevant business environment conditions on which I'm competing with another location in Europe? What's the footprint that we see there? You can also look at individual regions. And I picked here one mid-Euland in Denmark, which is right north, somewhat north over the northern to the German border, which is kind of a good example of a region that's doing quite good, but it's not the leader in the country. And I think the picture that we see in these cluster portfolios is not untypical. They have two areas where they're very strong, production technology and livestock processing. So pig farming in Denmark is still alive and kicking. It's a very successful industry. But then they also have some positions in other areas. And so for them, the challenge is really, what do we do out of this mix of some positions that we could develop, some already strong? How do we move forward from here? There is some more data evidence that they can rely on as they move forward. We also can see within the data across the entire European economic geography, what are the hotspots of emerging industries? And what we looked here is really, what are the regions that already have strong positions in these type of industries that have shown strong growth and that are kind of overlapping, that really have linkages? And what I see here is actually a little bit the challenge that we're facing because you see the usual suspects. You see the strong regions already, and so they are just by their structure in the best position also to take advantage of the next opportunities of innovation and digitalization moving forward. If you would look only as at traditional clusters, the map actually looks quite different because we have some regions that are quite good and a number of more traditional clusters, but do not have that broader portfolio that helps them to move forward in the kind of traditional innovation and entrepreneurship space. So what do we do learn from the data? So this was just describing what we see in terms of economic geography. Well, first of all, we looked at what we call the strong cluster. So those are those regions that are in their cluster category within the top 20% of European regions and we usually use nuts regions as kind of where the data is being collected. And what you get is 3,000 clusters roughly in Europe that kind of are in the top 20% on one of those criteria. So in terms of specialization, size, productivity, and or growth. And so we gave some stars for that, you know, there are different heuristics to do that. The interesting observation is that these clusters account for 50% of all payrolls, so all wages paid within traded industries. So remember these are only 20% of the locations, 50% of the value creation in traded industries in Europe. So we do see this concentration. Now what I'm not showing here is that there's also a lot of churns there. About 10 to 15% of these clusters that over a period of five, six years either move out of the group of leading clusters or move into this group. So there's both legacy effects. If you're in this group, you have a better chance of succeeding, but it doesn't destine you to failure if you're not there. You just have to see both of these effects at play. We can also then relate the presence of these strong clusters to kind of economic performance indicators in which we're interested. And you know, there's a lot of work that Scott and Mercedes have done on US data. We have started to do a little bit more work on that in Europe and we do see there's a positive relationship on many of these indicators that matter. In particular, since we're talking about inter-radiation and innovation here, what we do see is that there seem to be higher rates of entry and higher rates of firm growth of these new businesses as we move forward. And so how this played out in the European data is that we see that about 40% of all the gazelles and we used a little bit wider definition than usually, so it's companies that are five years or less old and that have been growing for at least 10% annually in terms of their employment number. But we see that about 40% of those in Europe are in clusters that are strong. So again, 20% of the locations, 40% of the gazelles in those locations. And interestingly, the gazelles that are in these strong clusters have on average 50% more employees at the end date that we register. So there's at least some indication here that clusters provide an environment not necessarily actually for the new idea to start because that could come from anywhere. But to turn that new idea into a business that can kind of grow and that is sustainable over time. We also know that there are huge differences across regional performance where policymakers at the end are interested in and kind of the strength of the cluster portfolio. And here again, we looked at these emerging industry strength and it's quite striking again how unbalanced this distribution is that kind of the top regions in terms of these indicators are doing so much better, particularly on patents, one of the kind of favorite innovation indicators, but also on some of these others. So understanding better the cluster portfolio and how that relates to regional prosperity I think is an area where we get some more evidence but clearly need to do more work. So towards the end, how does this matter for policy? Well, first of all, we think that clusters in itself and cluster data is not the answer, but it's a part of the intelligence that you need to make the appropriate policy choices in the right type of locations. And that starts with diagnosing the problem. What are the locations that are really behind because they have a poor composition of their economy? They're insufficiently specialized, they kind of have something everywhere versus those that are specialized, but they are weak in those strong sectors and there's kind of a structural problem there. So you can get a much better understanding of what the real problem in your economy is. Then as a policymaker, I think you can become more effective in targeting and challenging your policy interventions. So if you do something, let's say on entrepreneurship in your region, what are the companies that you should work with so that you really get leverage from these type of interventions? Knowing the cluster portfolio in your region is very important. How can you upgrade? I think through this notion of related clusters and development path, you can be more targeted rather than say, no, we need new sectors if we're a region in Greece. You can say, well, where are the areas where you might have a little bit of capacity already to build on so where an extra investment really can make a difference? And I think for Europe or for national governments, for that matter, if you start something in a new area, let's say renewable energy, you can be smarter about what are the locations that actually have some of the assets to turn those type of investments into something that creates real benefits. Now, I think the discussion has shifted quite a bit in terms to clusters at least from a discussion that was a lot about creating clusters. Clusters are good and that's what the data shows to how can we use clusters? How do we deal with those? And there is a broad range of efforts that have been used and I think what we see is that unfortunately some that you see here to your left with the red are things that work very much in the short term, paying subsidies, intervening in the market but have a very poor track record in the long term. Well, the other ones are kind of works more slowly but those are really the things that affect productivity. The big difference is really that effective cluster policies leverages clusters. Clusters emerge naturally through the forces that shape our economies and our economic geography but how you work with them then makes a difference and they can impact how you work with policies. My last slide, what does it mean for entrepreneurship policies? Again, as you run entrepreneurship policies I think becoming smarter about where you do certain things. Entrepreneurship is not sector neutral. There are some things that are effective for all entrepreneurs but how you then do it you always work in a certain industry and with certain partners. Use clusters as an organizing principle. So I'm very saddened to see that so far I think we still have very different communities. We have the cluster folks on one end and they do their stuff and then we have entrepreneurship people sometimes in the same region that do their stuff rather than really think about how can we integrate those and how can we make sure that the great new companies find bodies in existing large mature companies that can provide the bridges to a government. Final point, somebody has to do this and we talked a little bit about the role of cluster. So there's often organizations that need to organize collective action around which clusters emerge and become strong and here I think with the cluster organizations that we especially have in Europe we have around 2,000 or so, maybe too many but we have invested in that. This is an asset that we use and we should use it also for entrepreneurship policy. Thank you. Please stand up. Yes, please. Christian, I was struck by your map about the geography. If you take a country like Italy, we see a country where productivity growth has been very slow, almost stopped, and you have the north and the south basically, I mean you see it very clearly. Have you been able to identify in a comprehensive way of course the factors because they have basically the same institutional environment, legal environment and all this. So what explain these big differences? Because not only history of clusters. Did you go into this or you? So I think we're starting to go much more into using this data. What is very important is that of course clusters are not the only show in town there. There are many other factors that matter. And in some ways clusters are almost more an indicator that there is a combination of mutually reinforcing things. And you see in Italy I think a lot of divergence across different regions as you see in Spain and to a good degree also in Germany and other countries. But I wouldn't claim that we have the answer. But I think we can help with the data I think to look in better places I would say. I mean we will discuss it when we finish the presentations. But that's a key issue. Because I mean how do you interrelate all these factors into policy action and then draw the policy action? I mean Italy is a very interesting case I think. When you look at the diffusion of information technology and you see what are the factors, the institutional factors that slow down. I was struck by the World Economic Forum and the sort of mapping countries where you look what are the hindrances to the diffusion of ICT technology and all this and how you can bring that to your cluster which is a very micro sort of story that you have. And still I don't see the two together yet but you're not yet there. That's what you just said. That's the next stage. So not the entrepreneurship. Okay. So first thank you and thank you for both all the speakers and for this panel. And what I'm going to build very naturally both on the discussion that we've already had as well as very specifically among Christians presentation. That's why I went after you Christian I think. So it's been hinted at already but let's make sure that we understand and I think Peter sort of has already in some sense hinted at what's the policy action. Well I think this is at the end of the day a lot of how people start this conversation I think not in a monetary policy sense but in a regional policy or even national policy sense is they would like to be the next Silicon Valley and this is a picture of Santa Clara Valley in the 1920s and they have a notion that somehow you know that's in the you know there that is that is a long time ago but not infinitely long ago and that is now right that very location is the location for the new Apple headquarters. So you know to get a sense of change and what's the challenge with that and I think Christian already talked about some ineffective policy making and I think Fred also hinted at that our colleague at the Harvard Business School Josh Lerner wrote a book a number of years ago that was called the Boulevard of Broken Dreams why public efforts to boost entrepreneurship have failed and it's a really good read this I really do recommend it'll keep you up at night if you're in this business and the reason is that he really documents that much of the effort to jump start regional growth and to link to those jobs and growth goals through entrepreneurship initiatives and even to a certain extent through innovation initiatives that are sporadic in nature have not delivered the goods in the kind of macroeconomic way that we'd like and so that really led really kind of frames the challenge that Fiona and myself and other colleagues around MIT I'm addressed a number of years ago and Fiona is going to talk a lot more about this tomorrow but I'm just going to sort of talk about how we ended up thinking about measurement here is essentially what's the plan how can we grow through the acceleration of innovation driven entrepreneurial ecosystems in writing a report beyond a sporadic initiative how can we learn from that pretty long record of failure and actually try to transform that into more systematic program of actually impact that is also potentially measurable that is at the foundation of something that Fiona's going to spend I think a certain amount of time talking about tomorrow the regional entrepreneurship acceleration program I'm not going to talk about that in any long way except to say that one of the things we do in that program is we try to bring together the solution that we've talked about all throughout today stakeholders the stakeholder orientation that Marty Schmidt I sort of started out with but recognize that if you just bring people together and they can't agree on the as is state their ability to come up with solutions and even a diagnosis is going to be limited and so that leads to Fred or to Christian or to others to say we have to have a systemic analysis interestingly that turns out to be key the ability to connect real understanding by stakeholders of what the problem is and the challenges and the opportunities of a region allow you to develop prioritized strategy so far so good we do that in a kind of systematic way with a framework and so on and so forth and develop a strategy but I want to kind of jump all the way to a very specific challenge which is that as the minister made clear innovation and entrepreneurship take time and so when we had our first Reap cohort I was talking to one of the members of one of the stakeholder teams a senior member of that team champion and she asked me she said Scott suppose we do everything that this approach is about suppose we really implement this in our region suppose we really do focus on innovation driven entrepreneurship growth entrepreneurship and really use cluster analysis the whole thing how would I know that it was succeeding even if it was and I said something about jobs and growth and she said I will be dead by that point and that really changed my view it led a building on some of the work that Christian mentioned a few other things earlier today that were in my mind and our minds the question was can we develop meaningful and actionable real time metrics for the assessment of these ecosystems for the purposes of policy, action and assessment and the gentleman on the right here is Jorge Guzman who is a MIT doctoral student actually he just got his doctor Guzman just a few weeks ago and he really pioneered in his dissertation a new way of thinking about this problem so the first insight was that to grow firms they have to register that's probably a pretty obvious point but interestingly the business registration records both in Europe as well as the United States are interestingly disconnected from national statistical agencies by and large okay that's not so true in the Nordic countries but in MIT many the second problem as was already hinted at though is that if you go look through a business register almost every single company is Vlad's Pizza I'm looking at you Vladimiro Bolvich you know is some guy named Vlad who wants to sell some pizza and let me declare I'm sure Vlad could make a nice pizza but these are small local businesses or even businesses of an intermediate variety however those firms that have either the intention or potential to grow do different things right from their founding right so if you look at Jeff Bezos at Amazon he was called himself the world's biggest bookstore he registered in Delaware he had a patent and trademark he did a whole bunch of things right at founding that said he was trying to grow now let me be clear most firms even that are trying to be those growth firms those catalytic firms fail because entrepreneurship is risky but some do succeed and then what you can do is therefore create a mapping and just think about as a prediction you can create a mapping between those firms that ultimately grow onto those digital signatures of their entrepreneurial quality at founding against the full population of startups okay and you can do that in a systematic way you can do that in a systematic way and so just to give you a sense this is based on a data set that's essentially 80% of the US economy over 30 years so just to give you a sense what's the chance that you have an IPO or a big acquisition we've also done this on employment and some other metrics as well but based on some things that you might do right around the time of your founding so if you name the firm after your founder 70% likely less likely to grow so sorry Vlad too you didn't name your successful startup though after yourself so good going okay firms that get trademarks 500% more likely to grow interestingly I mean many of you know Delaware registration is something that the firm can choose to register in Delaware it's more costly it gives you access to basically being open to additional financing firms that both apply for a patent in their first year and register in Delaware are effectively 20,000% more likely to grow there's an incredibly skewed distribution of outcomes that's grounded in the skewed distribution of initial entrepreneurial quality just to give you a sense of that this estimate on the full population or 80% of US firms the top 1% of our distribution accounts for more than 50% of all startup growth outcomes in the United States over the past 30 years and our top 10% is about 75 to 80% of those firms okay why would that be why would that be so because they're trying because those were I would do that I would register that because no it's not costly so these are predicted it says it right there prediction not causal okay so it is not because you register in Delaware it's that it's the firms that are trying to do that are trying to grow do different things at founding so just to be really clear this is just a predictive analytic you can be more fancy in that predictive analytic but it is just a prediction not a causal estimate you're gonna be able to do causal things with that estimate in just a second okay so once you have this estimate you now have the ability to have a prediction at founding of every single firm that's formed including firms that have been recently formed so effectively you can use this for real time analysis of every firm that's starting up within a given system we use that approach to propose three new types of statistics one is essentially a measure we'll call entrepreneurial quality of basically the average of a group of firms we could then sort of say well we don't want to just have one good firm we'd like to have a lot of good firms and so we have quality adjusted quantity we're gonna call that the regional entrepreneurship cohort potential index or RECPI and then going very much to what Fred was saying about we can actually measure do the firms actually succeed that we're supposed to succeed we can actually over time mark ourselves to market in terms of seeing did that ecosystem give you the performance over a longer time frame in an ex post study so let's be clear what kind of things we can do so this is incredibly it turns out to be a fairly fine-grained diagnostic tool so for example this is a map many of you have been to the Bay Area this is the Bay Area this is roughly Silicon Valley if you look over so few things there's no entrepreneurship at the airport excellent okay second if you look at Blob over here that's Stanford but there's students in Stanford and there are few faculty houses and that's where the individual faculty member might have an LLC for consulting but right around Stanford so the nomenclature here is the size of the bubble is the quantity of firms the color of the bubble as it gets darker higher entrepreneurial quality higher potential you see this wall of entrepreneurial quality around Stanford individual street you can see exactly where we see the arrival of particular accelerators registering hundreds of firms in individual locations new insight from this those from an inclusive innovation perspective inclusive entrepreneurship perspective the East Bay has a lot of handymen and plumbers and accountants and pizza shops but not a lot of growth entrepreneurship even at founding and we right so this Marty I think this is the ecosystem just around MIT and what you can see is that there's on the one hand for those of you who are MIT alums you remember Central Square and kind of the endless amount of eating and drinking that can go on in Central Square I see a few people remembering it fondly but then this right here this is the Cambridge Innovation Center and it is in fact the highest single address of entrepreneurial quality in the United States use that to actually give a real time roughly real time metric on a zip code level of the average entrepreneurial quality by location and also quantity and just so you understand this so places like Miami right that just have low registration fees right those are places that have tremendous quantity of entrepreneurs but relatively low entrepreneurial quality at founding on the other hand what comes up you can see the total black just means we don't have that state's data but we have for most of the other states we have 34 in here what you can see is Silicon Valley comes out the area obviously around Boston so on and so forth Austin, Texas so on and so forth interestingly when you use this you actually get new answers to questions that I think macro economists do pay attention to you actually there's a right Mario President Draghi said one of the three planks for pessimism or concern was the declining rate of business dynamism in the US and Europe that's a quantity based measure it turns out that once you adjust for quality in the United States you get a much more cyclical story and one that actually started increasing relative to GDP from the beginning of the crisis okay now lots more work needs to be done we would like to do this as well in Europe it's sort of signature that this might be a little bit different I'm going to get done in just a few minutes on the other hand then you can look at what happens in terms of given their quality what's their performance and here what you see was that really was a golden era in the United States in the late 1990s where that innovation innovation driven entrepreneurial engine kind of worked companies were founded of high quality and then they scaled and they had these transformative impacts and what we see by large in the data is it's not a problem of great entrepreneurs and so this I think goes I think to some of the comments that have been made on the other hand there does seem to be at least in the United States a failure to scale to be clear there is no regional relationship between the quantity of entrepreneurship and economic growth but there is an association between not cause a lot of one to claim but between economic growth and measures of entrepreneurial quality you can also use this for program evaluation you can go into regions that have gotten these various initiatives and look at how has that changed their business environment very often these most initiatives are going to be relatively micro and are unlikely to shift the quantity number very much because the dry cleaners are going to still be opening and closing on the other hand here is an example we were able to look at a targeted intervention in the United States we have done an exploratory analysis as well of Spain this can be done on European data and you can see kind of dynamics over time look at this Peters decided we are going to stay on Spain for a little bit we can in principle you can scale this just to be clear the key is not just to write academic studies around this the key is by agreeing on the as is state agreeing on the opportunities of the driver of policy and acceleration in part because innovation and entrepreneurship are not controlled by any one agency or person they involve the stakeholder approach and that stakeholder approach within an ecosystem can use that shared understanding as a driver of coordinated activity ultimately can we leverage advances in measurement of the kind that we have been talking about to foster innovation and that I will conclude thank you great you want to react to your colleagues here around the table is there anything you disagree or you want to emphasize I think you are quite on the same line I don't know you yeah I would certainly support what Scott just said that everything reduces down to a systems problem you don't understand the problem and the outcomes that may not be quite what he was saying but that's I agree with that good in that case we have a cord almost consensus yeah maybe just to underline one point that's got sad and that I think and sometimes in the discussion gets lost we all want higher quality entrepreneurship but I think the key is not that we agree on that the key is that we I think agree that there are many pathways to get there there is not one industry there is not one policy approach but we really need different kind of context dependent strategies to do so that doesn't mean that the European level has no role to play but it doesn't have the role to play to say okay you know we identify one region that did a good job and now we roll that out throughout Europe I don't think that's going to work success and I think that's really is through differentiation and heterogeneity it is not through kind of benchmarking in one sense can I just build very directly on that just so for example people often look at venture capital as you know and was even mentioned before the deep well of early stage financial markets in the United States and that is associated with 55% of all equity growth outcomes in the most of the big firms you know good you know say and interestingly they are tend to be in a much more diverse range of sectors their roots to growth turn out to be quite different interestingly and this is just a more recent paper we've written it turns out that their growth that the kind of simple choices that we're looking at here their intention to grow turns out to be similar but their sectoral composition and their path to growth are quite different yeah and I think go ahead one, two, three yeah regarding the predictive power of those regressions I mean I can see how not naming after your name the company and doing LLC that doesn't seem like you know naturally with predictors but I would think that there's way more than that and so I wonder what's the R-square of that regression so it's once again think about it that in an out of sample test our top 1% give you 50% of the total outcomes no, no, no that's not the question the question is what's the R-square of the regression I want to focus on the top 1% I want to focus on if I if I if I take a company a random and I try to forecast the evolution of that company based on where they are incorporated the LLC yeah so I can I can send you a whole bunch of papers so it is so taking collectively so it is actually a fairly predictive regression think of it as a center so that is but that are squared on individual companies as you saw in the micro predictions we wouldn't be getting that micro geography unless we were basically predicting fairly well on average and I could I could show you a whole but I feel like maybe for this group we could talk more but the micro geography that we're able to establish is a pretty reasonable way of thinking about the power of the regression so coming out so if you register there it must be some clever entrepreneur you know yeah so it's a sort of proxy for many other things so basically there's roughly so in the United States but as I said in the work we've done in Spain which is a very different system we apply very different you know we find things that are true to that system and run a regression you know run the prediction model there in the United States Delaware registration is a not uncontroversial way to organize yourself if you are interested in becoming a growth firm and the reason is it has a consistent body of corporate governance and law that goes back like a hundred and thirty years that allows it to basically be a good place to do growth startups it would be to register yeah yeah yeah yeah when you choose here very good I'd like to come back to this notion of what you need to have for it in a region and also tie that to this discussion on creative destruction so if regions already strong in one particular area they will have a cluster in that area if they want to grow to new areas that will develop a new cluster so how do the linkages between the clusters actually need to be and what would be a good region that can make these transitions have that creative destruction so that's not just at the cluster level but that's how you aggregate at the regional level this cluster portfolio you are in the same issue you know when you talk about the regions and clusters one may get the wrong impression that everything is there okay and also they grow they develop or they don't but in fact when you think about the city component one hand and you know the cluster at the MIT and Harvard they pull essentially the talent from the whole planet I mean it's like black holes you know they absorb okay and so it's not that only that there is something there but it's because of an initial success it creates a dynamic that the whole world is feeding that initial success so the comparisons are called across regions in that sense are not really you know informative because you know the this initial difference completely skews okay the dynamic of what's going on maybe you answer to the two questions Christian maybe I'll start and then Scott you I think you're entirely right that I think focusing exclusively on Boston and on Silicon Valley can be misleading but I think that's where the new data that's now available really can help us because we can much more look at the entire universe of regions and try to track how are they developing and what we do find both all regions specialize in certain ways and there is a systematic relationship towards performance now to I know this question I think that is indeed I would say kind of the bleeding edge because what we know to do quite well is activate existing clusters and I think that was the kind of the traditional model of cluster policy in Europe you know strengthening strength and that works relatively well what we know what we've learned so far is two things one that this is way more risky so we can't use the same models that we had for the mature industries where it's just kind of incremental investments but the second one which seems to be coming out of the data is that as you move into new sectors it's important to understand what legacy assets you have and so your likelihood of success is higher if this is something like the digitalization of automotive industries or use some of the the competence from engineering that you have that's where something you can happen you know think about wind energy in Denmark and some of the coastal regions they were actually using some of the manufacturing capacity that was still there from the maritime and warfed industry but then that was applied to a totally different field of course a lot of new knowledge was needed but they could be more targeted than just saying you know let's figure out what globally it looks like an interesting industry and let's go all off to that yeah so first let me completely agree with Christian I think you're going to be hearing from Don Chisholm and Lorder's tomorrow who there's a real agenda around how you what does it mean to have new innovation and new entrepreneurship that builds on historical strength what does it actually mean it means that there are many regions that invest in very big shiny programs that are pretty unrelated to anything that anyone in that region does and if any of them get it all successful guess what they do they move to Silicon Valley or to Boston Massachusetts to Cambridge and the challenge is that if you start and build on something that builds on your unique things that are in your region that also are very often in the subtle human capital of the region Raj Chetty the economist at Stanford did this fascinating work on patenting and one of his many results is that even no matter where they live children who grew up in Minnesota which is the historical home of the medical device cluster are today leading medical device innovators independent of whether or not they're still in Minnesota and there is this right because that is the area that they learned from and so part is that building on strength gives people a way of saying what they're about what is the potential competitive advantage of the companies that they form and that will itself reinforce and sort of build that actual revealed comparative advantage of the region and I think that that piece of the puzzle has I think been missing from too many policy discussions at both the regional level and to be honest as well I think as people tried to aggregate this up to the macro economic level Thank you so much I wanted to tie this discussion in with the previous discussion on R&D because it was really very noticeable that it wasn't much mentioned in this discussion and I think most policy makers need a very simple sort of formula of innovation and it continues to be that R&D is the key measurement for most policy makers that they associate with innovation and I think that's very important to understand because if that's what we have that's what they think will get them to innovation they see it as a very linear path and I have set on discussions with Romania or Bulgaria you know where huge focus on R&D you know they necessarily need it and my point is it can also divert the attention I want to give two examples I remember when Nokia started getting into trouble around 2007-2008 and a lot of people in Brussels would say don't worry they are one of the top 10 R&D spenders in the world they'll be okay and of course we know that wasn't the case the other example I want to give is I used to be an innovation advisor to Flanders in a very powerful region and they measured innovation with R&D where they were actually quite good and the numbers of PhDs they produced so the market was flooded with these PhDs and then they said we actually want to turn these people into entrepreneurs so they gave them entrepreneurship training with the result it was completely useless because once you have a PhD you don't really want to become an entrepreneur but it is an example what we strive towards is where we are going and if that doesn't lead us to innovation we have a problem so if you could comment on this a little bit because your models are great but they are way too complex for most politicians so they need very simple formulas and I want to suggest a couple productivity growth business churn internationalization of firms and digitalization where we have very poor metrics on where we are now on digitalization within firms or where we are striving where are we trying to go so I think that would be maybe also quite useful for the discussion thank you let's take fred first and scott by the way I agree with what you said but fred and scott yes between the two of us we will leave you in a different state the first thing I'm going to do is take a document from the European Parliament I've lived in this part of the world long enough to know that the parliament doesn't talk to the commission and we operate in different ways but the role of innovation is to turn research results into new and better services and products in order to remain competitive in the global marketplace so innovation is to pick up the R&D and turn it into something useful now one of the little problems in life if you measure more firms innovate than do research and development and this is particularly true when you get down to SMEs which are all clustering together and doing interesting things in Christians world and we'll hear what they do in scott's world in a moment and the question is how do we formulate policy which helps these firms which don't do R&D because they don't have the capacity they don't have the linkages and within the EU you will find for example which allows them to go along to the local technical college and say I've got this money from the government I've got this problem can we get together and solve it and move on and if we do this then we have a possibility of growing those firms so that they can get to the point where they can build the capacity to do research and development and make the cluster scale up to something enormous this is not easy the difficulty and this is not a criticism if there are any in the room that policy makers have is trying to understand the sound bite description of what we are doing and that you put your finger on that and the only thing I can say is admit that innovation isn't just R&D it requires other things and we should be looking at policy in those areas and that will be the challenge I would throw back we will now see how Scott solves the problem so thank you for your comment so let me make two different points and of course Christian as well should join in so let me make two points so the first point is I actually think that while R&D is an important just to work clear R&D is in fact an important input to innovation as are the accumulation of scientific and engineering professionals and maybe not PhDs but necessarily but you know some measure of the innovation workforce I think that there are tremendous potential to actually building on Fred's definition to actually come up with metrics that really are about what new products there are which is let's be clear different than measured productivity growth you know I think that the innovation in Europe the community innovation survey which gives you a basic metric that you can disaggregate to a reasonable level what share of revenues come from new products that's actually your services that's a pretty good metric now once again I'm a big fan that's dashboards need to be simple so on the innovation side I think there's output oriented metrics as opposed to input oriented metrics and then we can then figure out the relationship in more systematic way there's a large academic literature about that but even in a policy making sense sometimes R&D matters a lot in the pharmaceutical industry R&D matters in the app economy not sure we call that R&D right I think with the kind of work that Marty's been doing some leadership on with the MIT engine what we traditionally called R&D is going to matter a lot because there's big physical investments and big skilled scientific and engineering investment the other part is just on the key part just to be clear once again I have tremendous both respect for agreement with violent agreement with the move towards thinking about young firms rather than small firms in terms of business dynamism and the role of churn but just till we're clear the main secular decline that we see in both Europe certainly in the U.S. this I can tell you in that decline in business dynamism is the decline of mom and pop stores but that probably didn't contribute much to productivity growth anyway there's no relationship between churn and regional economic growth it's just a fact quality adjusted turns out to be a much better predictor of actual jobs and growth so you know what I'm saying so I don't want to overstate that but I do think that it's important to you know that having some measure of different ways that businesses are being organized and the vision of those founders are matters Chris it's okay quick reaction also we have three more questions I know very quick I mean I have a lot of sympathy for the different types of indicators and maybe we can work more on this together but what makes me nervous is that the reaction that I've also seen in southern eastern Europe and in many other regions is that as soon as you have one indicator change becomes one directional and everybody says okay we're all running in the same direction and I find ways to create indicators that focuses on coherence and says you know yes you have the right plan for your region and not you know you're just on one on one line and I must admit that's difficult and I'm not sure we have the solution for that yet but maybe that's worthwhile task to take on thank you I have one question here and then and then here and then and then no later you'll come later one, two, three, four, five my name is Giorgio Sarrakinos from the European Patent Office I have a question for Professors Kettles and Stern it has to do with this Delaware thing connected to the map you showed very interesting map of hotspots if I looked carefully at your map it looks like southern Germany and Switzerland appear to be the hottest spots for innovation in Europe more or less would you say that there is a Delaware relationship there like if a company starts there and they have big ambitions that it's a pretty good predictor that in the Munich area and in Switzerland they will also make it big, thank you yes maybe quick response Delaware registration those firms are located elsewhere that's just a place yeah just yeah yeah so the answer is no I think what we are picking up here is something different we're not measuring patents other patents registered but what we see here is more that these regions in southern Germany and you know also northern Italy and some other parts are actually diversified regions that have strong positions in a number of these strong clusters and that is what this indicator is picking up so they have a lot of opportunities at the intersection of different industries well many other regions are kind of might be good at this or that but you know that they have kind of limited opportunities from those islands so we can talk a little bit more how that is related to patents offline later on yeah thank you my name is Oliver Stahl I'm a serial entrepreneur now in the filter for botics and alumni at the MIT Sloan Fellows Program I'm from Munich I think you call this a five-star region still we have challenges to you know to innovate in the area of policies and regulation it takes months, years and you know setting up a company still takes two months sometimes if you think back to the economic power they are today they implemented special economic zones mostly along the coastline mostly around ports is that something you could consider as a kind of cluster think about the special economic zone we had established in Europe maybe around technology clusters but you know where setting up a company is just maybe a matter of weeks venture capitalists and business agents like to go because they have special tax policies and regulations you know we have seen and considered this special economic zone so call it the special tax zone I think you get the point thank you you know I'm very skeptical about that I think we're at a level of economic development when we need these reforms we have to reforms for the entire economy in fact also that it's easier for the pizza parlor to kind of set up those businesses you know for emerging economies I think it's a whole different discussion but I don't think it's a solution for for us who is that you know both being economists but also the chief economist the world bank has spent the better part of a decade trying to implement exactly that solution I think to not tremendous success he is otherwise you know we wish him well at the bank and whatever but that particular piece of his agenda fundamentally you have to get cities are real things you live in Munich for a reason okay okay okay okay okay yep absolutely absolutely I don't want to yeah in addition let's continue let's thank you yeah this is Enrique I'm with MIT the measure entrepreneurial quality seems to kind of hint to being skewed towards the 1% of you know in certain specific zip codes within the United States for example what does that available in a country and is that a natural distribution could it be like 10% not just 1% is it a Pareto principle applying there so we have I can send you a different paper our estimates of entrepreneurial quality are incredibly skewed they follow an accelerated power distribution that if you had asked me that before we did this research I've participated that and it really gets to you know something I think that MIT and the innovation initiative and Marty and his team have really dealt with which is a very small number of new companies end up being the carriers of a lot of the innovation impact and seeding that pool is extremely important once again there are many ways to grow it could be more diversified we could really think of an inclusive but it is also nonetheless true that when we conflate apples and oranges and we hope to do better by quantity that those efforts I think have had a less robust success metric hello good afternoon my name is Jose Potho I'm the tech director of Epic the European photonic industry consortium I was very excited about the model presented by Professor Stern but my question is to Professor Kettles so imagine a fantastic model from Professor Stern with the with the improved version of Fang Medler and we identify some regions like for example the region of Eindhoven that is going to create the next generation of devices for the for the next generation of data centers or Dresden who is focusing now on the on the rapid manufacturing and laser based manufacturing of Copenhagen or Grenoble or Switzerland and we identify those regions and you had in one of your slides cluster initiatives in the long term taking the using the fact that we have in front of you people from the European Commission like and Medler people this is what could you say to them what should be the things that we can do to support cluster initiatives and foster entrepreneurship in those clusters well I mean there is a big policy agenda that the commission has been using for for quite a number of years now and I think these cluster organizations itself it has focused on data like the cluster mapping that we talked about it has focused on the excellence of these organizations and I think that's exactly the direction to go I think it can maybe do more in helping EU member countries and regions to think about how they can deploy these type of initiatives in the right way I think the critical issue here is that we need to move away from a model where we try from top down to see you know what are the best places in Europe and we channel money to them for photonics or something else what we need to realize is really what Scott said that you know it comes down to you know the strategy the people and then of course you know the assets that are underlying these type of regions but that you get in a process where you maybe have competitions which some countries used to really get the combinations of assets and willingness to do something to happen much more at the national level rather than at the at the EU level to kind of have the connection to what what the real local issues are to move things forward okay we have one question there thank you my name is Wolfgang Unger also an alumni from MIT from a long time back it seems I do have one question not being part of the policy world of entrepreneurship and innovation but as an outside spectator reading about innovation and robotics in particular it seems a lot of the success of new companies that have grown successfully and dramatically has been in the computer world and artificial intelligence is of course becoming more important Amazon has launched its echo which sort of brings artificial intelligence to the normal consumer and all the sudden eyes are opening about what this technology can do and there's a study I think in 2015 of Oxford University about the reverse employment impact of some of the innovation that we are now talking about as being generally positive which is good and there's a book by Martin Ford Rise of Robots which I guess is quite worth reading about some of the implications and there are some worries about how many jobs are created and what does this growth in a particular sector mean for the macro economics and the regions actually now bring those two perspectives together the positives of growth and of course the destructiveness of potential impacts of those successful firms and how is that being quantified or measured at this point who wants to answer I have an answer they might want to also no you do you do it okay well you know you know so let me say two things one I think you divide your comments into two parts one is the software eating the world hypothesis that just really this is all about IT and I will say that well the IT is an important sector and I think Ryan Hilda's earlier presentation sort of spoke to a bunch of that interestingly the gentleman from BMW earlier today I think said it extremely well right when you buy a nice car a lot of software but you're buying a lot of software to make a cargo did you show what I'm saying so software in that sense is the large scale impact of software eating the world has been to make real things the real the physical world more effective obviously there's also digital world and that's you know social media and things like that so there's a mix of that and some of those and Christian hinted at that the shipping industry and you're really good at shipping that's a different strategy than either trying just to build more boats or trying to be an economy do you see what I'm saying the second on robotics I mean clearly there are many people here from MIT who can speak to that far more than I I think a very one of the real advantages I think of MIT at least that I've been able to absorb is that there are you know which has a leading role in this area has been the ability to really start bridging some of the gaps between the economists and social scientists and the engineers so having you know sea sail actually talk to the economics department and the business school and we had a group that tried to do that for a few years and what I took away from that group is that at some point well after we can do cognition and I don't know when that will occur that will be some other breakthrough but what we're talking about now and the learning that's once that happens that would you know fundamental scientific advance like that that's unrelated to today's efforts that's a different thing but except for that basically you're in a situation where prediction models what we're calling artificial intelligence are very good at doing prediction and what that means is that human skills are very important and guess what as best as I can tell it's not like we're really close to the optimal level of human judgment currently in this world and either a down home level or at a macroeconomic level and so I think we have a pretty long way to go and we can talk maybe a bit offline but thinking about how much more human judgment can be applied when prediction is made more clear is I think a very important area for thinking about prevention so I'm Jonas and I'm from the UN so I have two questions and one comment my comment is is it possible for Harvard to issue a retraction on the cluster thinking as a whole every time that we go out and we sit with politicians and city officials they tell us we are there to help them come up with some sustainable innovation they want to have a cluster they want to have not one cluster they want to have this for ICT they want to be the global leaders for medicals and everything else and it all has its fundamental roots basically in Porter's popularity of the term cluster thinking and when you ask these politicians if they can mention one cluster that they would like to copy they all fall back to Silicon Valley or Cambridge basically so that's for you the other one is basically one issue in Europe and the US 2% of the population start companies out of them only 9% are women is that something that can be measured and if so how are you considering entering that into to the work you're doing right now and finally disruptive on the map that Scott showed us we see employment how that intensifies in growth companies how can we measure disruption I mean if we look at Google they were not the first search engine if we look at Facebook that was not the first social network service so the disruptors were the first entries and they are normally not successful so how do you support that and how do you measure it thank you last one please well so believe me I've thought a lot about this particular problem because I feel that we have often the wrong friends as well as the wrong enemies indeed I think the perception sometimes of Porter's work and you know I mean he doesn't sit here but it has been too often that okay clusters are good you know let's create a cluster that's not what's in his book 25 years ago and that's certainly not what we're advocating or what our work is about with different governments but I accept that we need to do a better job and communicating on you know how does this inform more effective policies and so watch that space hopefully we can do it's easy now I'm asking him if we do the there is an opinion poll so I ask is it easy to do because there's in my notes you want to answer on the other on gender on gender I think the gender thing the gender thing is extremely important in the third world and I also come from a UN organization and spend a lot of time in Africa and the education of women changes things considerably and technology also has an impact on how they are empowered and I will offer you telephone banking not necessarily impesa which allows you to move money around but full telephone banking which you find in South Africa even the illiterate people are able to memorize patterns on the cell phone keyboard and they can access their accounts and they can turn their little garden into something that produces value and they can bank the money avoiding the husband taking the money and going down to the pub and consuming it a good example yes it is technology which changes people's lives so if we had more examples like that maybe we could persuade countries from asking for a cluster from Harvard or using that literature and broadening their interest in empowering the people but this is something that could go on for a long time so I will stop there still it's nice to hear I'll be short because we're over your question was roughly when Fiona and I all sat down to design the regional entrepreneurship acceleration program what we and you know right that was the question that we had in mind was how do we go with the slogan and sort of oh we need a cluster to really undertaking that in a more systematic way Fiona is going to talk about the work you know that our work in that and her work in that and I think that the that that has been a model that I think we've both learned from about how to try to work with stakeholder teams to move beyond that kind of overly quick model so there is here in my notes I should announce now an audience poll the Mentimeter you did it before okay so you know how it works so I can give you the question yeah you have it there well I didn't write it but it's the how important is it for Europe to enable creative destruction well depends on I didn't write it but and then I will I will conclude after that yes very important no well it's going up it's going up oh somewhat important somewhat important important very important not important I mean it's not so yeah I didn't write the question I said it take the incumbents yeah that are around today and have startups take it over yeah competition through innovation yeah no maybe maybe in line was your 20th well not important did you push the bottom now two no let me I mean there's no conclusion I mean the first point I think it was a great initiative I learned I learned that I don't know much about these things my my view was the question of diffusion of technology basically diffusion question so I'm more what I did in the past much more and usually rankings of countries about you know I mentioned the World Economic Forum or the World Bank sort of indicators trying to spot you know what are the weaknesses across countries and the reinforcing aspects you know of the institutional environment because that's what is interesting in in these studies is a little bit in the cluster spirit is all these things that act together and not piece by piece that you consider them so I thought I thought for example if I was in a past fascinated by some of the studies on on Italy for example Zingales was one of the the persons that I thought was quite interesting to try to explain you know why productivity growth stopped in Italy by the mid 90s already and trying to link you know many different things together in the results for example there are many tiny firms I mean the pizza company which can also innovate a lot by the way because the definition that you use I think is the marketing for example how you pay for the product how you deliver the products and many of these things and not so much also the question of robots you know and all that the other discussion on inventions or close to inventions I think so the diffusion is probably the main thing has to do with and it's relatively easy to spot you know the major weaknesses when you go and I like it also this approach when you go into regions because the regions are quite interesting because environment and to some extent to some extent the same more or less cultural environment well language is not the only thing I know but I thought it fascinating why in I mentioned Italy but there are many other cases why in the North Italy you have a lot of innovation you have a lot of the diffusion of technology is real why in other parts of the country with the same sort of laws the high taxes and why you have a totally different picture look at figures like R&D and all that and I think that's misses the point I mean it's always important to have money for research and development but that's not the key issue as you rightly said and I thought it fascinating for example in a study on Italy that the fact that you had you know a number of thresholds in terms of I would say labor protection but I'm not criticizing you know these law per se but they were thresholds you know the bigger you are the more the pressure you have in terms of you know having a conseil d'entreprise or bedrève serrate of you know this and that you see in Italy you have this huge amount proportionally of very tiny firms and there is a threshold but you don't really grow beyond that and that then you link it to family enterprises and why are these family enterprise not innovating very much introducing information technologies which would be relatively easy theoretically there's a lot of things due to the fixed cost that you have to the education you know in these things and why are they there there's a lot of barriers to entry also in different they're very difficult to explain because the competitive environment a priori the institutional environment is more or less the same the legal environment I say it's the same so I think if there is a comment on this you're welcome but it's very interesting to go what I was a bit worried about your presentation is that it signaled I mean that we have very far from understanding and having a a good system when we can bring solution rapidly because I don't think the voters are going to wait so long before we can redress a little bit the productivity challenge that we have and so I was a bit worried about these presentations and of course there are the other questions about the implications of the diffusion of technology on the labor force on labor in general and the distribution aspect but that's for another conference in short I think it was a very good initiative refreshing we have been as you know in central bankers quite innovative and very often criticized because we have been innovative but we have been challenged by the lack of classical instruments where our rates went to zero so we had to innovate and we could do that in that institution we tend to think very successfully but I mean that's not always what people say but we think we have been you want to comment on my question that Italy would be important for Chris please very quickly say where in 2015 did you 7% more and then see Italy 4.5% North or South No but I'm just saying that because of the regional dimension of Christian also I thought it quite interesting when you have you can control for the the formal institutional environment formal of course not the informal institutional environment why because then you control for one aspect like taxes and things like this and I thought it interesting to within a sort of formal institutional environment the same one the differences you have and so well thank you it's not the conference not finished for me but it's quite good let me step in just with a few logistic issues first thanking the panel thanking Peter for sharing his report we move to the dinner the dinner is now following seamlessly directly so just follow let's see the people leading you will be gathering from here taking elevators and then going to other part of the building I'm told to advise or to encourage you to bring your codes so that you don't have to come back here later because it might be closed whatever some people could not come in or had to come in later because they don't have a valid ID it's not enough driver license you have to bring either your passport or national ID with all that thank you very much and let's continue dinner