The next item of business today is topical questions, and question number one is from Liam McArthur. To ask the Scottish Government what action is being taken to reduce the number of near misses that are being recorded by police control rooms. Police Scotland continues to take action to strengthen its approach to call handling. The decision to systematically record notable incidents is a direct response to one of the 30 recommendations contained in HMICS November 2015 assurance review on police call handling. The inspectorate has identified that such a process is crucial to creating a learning environment that improves processes and mitigates against risk. The Scottish Police Authority continued to oversee Police Scotland's process in this regard and to provide assurance around the services' on-going performance in relation to call handling more generally. HMICS has confirmed that it will publish an update report on police call handling in January 2017, and we would expect Police Scotland and the SPA to give careful consideration to any further findings or recommendations arising from that report. I want to take this opportunity to recognise a valuable contribution that is made by police call handlers in responding to more than 2.5 million 101 calls and around half a million emergency calls received by the service each year, often supporting members of the public at times of acute crisis. The notable instance information that was released last week highlights that those occur in only around one in every 22,500 calls. I welcome the fact that action is being taken to understand and respond to instances in which the service to the public has fallen short of what would be expected. Liam McArthur I thank the cabinet secretary for that detailed response. He is right in setting those figures in context, as well as to pay tribute to call handlers and staff involved. I think that looking at the detail of some of those cases registered between April and October, I think that he will agree that a number involves fairly serious issues, the locations of incidents being incorrectly logged, a two-week delay in checking on the welfare of a child due to a misplaced report and in response to one threat to life reported four times. The caller was told that there were no officers available. One of the primary concerns that many had about the closure of local control rooms with calls being answered increasingly closer to the central belt was the loss of local knowledge. Can the cabinet secretary therefore tell me how the loss of staff within some cases, decades of experience and detailed knowledge of their patch has been mitigated? I think that he needs to recognise that, when Police Scotland established, there were some 18 call centres across the country, many with IT systems that did not link into one another and could not record vulnerability. We were not able to share intelligence, so we had a system that was not fit for purpose in moving forward to deliver the services to the public that was necessary. The member will also recognise that in the cases that were logged, where there has been an error that has occurred, where there is an issue about concern as to the impact that it may have had on a member of the public. If it is serious enough, the matter is investigated by Perk in a few of those instances, that is what has happened. However, the purpose behind the recording of notable incidents is to make sure that, where an error has occurred—for example, if it is the wrong details that have been entered into the system by logging in the wrong code or whether they have failed to dispatch officers to a particular incident when it has been received—is to make sure that that information is captured and that they then learn from the lessons that can be gained where that is necessary to ensure that that is minimised in the future. That is about trying to make sure that there is the right environment within our call centres to allow staff to be able to provide information where they think that an error has been made. The member will also be aware of the 30 recommendations—or if he is not, he should be—of the 30 recommendations that were made by HMICS last year. Recommendation 12 was one that specifically asked Police Scotland to review its present staffing model for its call centres in Scotland. That police of work has already been completed and Police Scotland is now implementing that in terms of the staffing of the call centres. There is a significant body of work that has been taken forward over the course of the last year. I have no doubt that Police Scotland will continue to do that and make sure that there is appropriate assurance and review of that process as there is through the Scottish Police Authority and independent assurance that I have directed through HMICS. Liam McArthur I thank the cabinet secretary for that further detailed response and certainly the encouragement offered about the way in which Police Scotland is taking forward the recommendations that he outlined. Of course, those statistics were only released to the BBC after the Scottish Information Commissioner ordered them to be so. Does the cabinet secretary believe that those figures should be routinely published as a matter of course in order to aid both public scrutiny and provide wider reassurance? In the issue of freedom of information requests, it is worth recording in Parliament that the public body in Scotland deals with more freedom of information requests than any other part of the public sector is Police Scotland. One of the pieces of work that they are undertaking at present is looking at what information can they put readily into the public domain that would not require a freedom of information request to be necessary. That is some of the information that they are considering. However, it is also worth keeping in mind that Police Scotland is still developing the notable incident process. It is a system that is going to be reviewed as HMICS has already identified that it will review as part of its on-going assurance review. It is a piece of work that they are still taking forward. I have no doubt once that process is being completed, they will be looking to see what information they can put in the public domain to give continued reassurance about the way in which their call centres are operating. Earlier this year, Chief Superintendent Campbell Thompson, divisional commander of a division, which includes Murray, said that "...there have been a number of challenges relating to the recruitment and retention of police staff controllers. Can the cabinet secretary tell Parliament what action was taken to address this issue? Does the cabinet secretary acknowledge the concerns held by local communities about continued centralisation of the vital function of Police Scotland?" The first thing that I would say is that I am not sure whether the member is suggesting that we retained an old model in which we had 18 call centres that did not have IT systems that could actually cooperate with one another and that were not able to share the right intelligence across them because that was not a system that was fit for purpose. The model that has been taken forward by Police Scotland having been reviewed by HMICS has said that it is an appropriate model for the delivery of the services in Scotland. I know that the member who was not in the previous Parliament should be aware that recommendation 12 within HMICS's assurance review that I directed last year made the recommendation of reviewing the modelling of staff that is being provided within the call centres. That work has now been completed and Police Scotland is implementing its recommendations to ensure that the staffing ratios that they have within the call centres are suitable to meet the needs and the demands of the service. As referred to in his answer to Liam McArthur, can the cabinet secretary provide an update on Police Scotland's progress in implementing the 30 recommendations that are contained in the HMICS assurance review on call handling? The member may be aware that the assurance review took place as a result of the direction that I gave to HMICS. The 30 recommendations that were published last November are areas of work that Police Scotland has now been taking forward. Some of those recommendations go beyond call handling in itself about other aspects of how the Police Service operates with its contact command and control centres. HMICS has confirmed that it will provide an update in January 2017, and that will be laid before Parliament. Members will then be able to see what progress has been made against each of those recommendations and whether there is any further recommendations or pieces of work that HMICS is recommending that Police Scotland take forward. However, I can assure the member that those recommendations are under constant scrutiny by HMICS, by the SPA, Governance and Assurance review group that is also responsible for the piece of work, and external assurance that has been provided by Police Scotland to ensure that it is doing everything possible to implement those recommendations effectively. Although I appreciate that the vast majority of cases were properly dealt with, as Liam MacArthur stated, a number of near misses had serious consequences, and HMICS will be following up last year's report into call handling with a more detailed report into each notable incident, a report that is due next month. When published, will the cabinet secretary commit to coming back to this Parliament to update us and assure Parliament that all possible action has been taken to address any concerns that HMICS and the wider public may still have? I am happy to do so if members would find that useful, because it will allow members to get a full update on where Police Scotland is and to follow those 30 recommendations. It is also worth keeping in mind that it is part of the assurance process. I also directed HMICS to undertake unannounced inspections in the call handling contact and control centres to make sure that there was continued review of the way in which Police Scotland was handling calls and the way in which its centres were operating. That continues to take place, and HMICS is continuing to monitor those matters. However, I have no doubt that, if members would find it useful to have an update once HMICS update report has been provided, I would be more than happy to look at facilitating that for Parliament and for members. To ask the Scottish Government what the expected impact on health will be from the ban on smoking in cars with children present. The overall health of children will be improved by reducing their exposure to the harmful effects of second-hand smoke in cars. Second-hand smoke can have serious negative health impacts on the child, including coughing, wheezing, asthma, middle-year disease and respiratory tract infections such as bronchitis and pneumonia. I thank the minister for that answer and for the steps that this Government is taking to protect children from the harmful effects of second-hand smoke. It sends a clear message that children in Scotland should be growing up in a healthy smoke-free environment. How will the Scottish Government monitor the effectiveness of the legislation and, over the longer term, will it review whether the penalties available are providing a useful deterrent? Before I respond in detail to the supplementary from Marie Todd, I want to note that our Liberal Democrat colleagues in the chamber put on record our thanks to Jim Fulham for his work in the previous Parliament and bringing forward the original member's bill. Before I talk about the way that we will monitor it, I just wanted to highlight the more general approach that we are taking around ways to reduce the harm caused by tobacco. We take it right outside campaign and encourage adults to smoke outdoors, which has helped us to reach our target of reducing children's exposures to second-hand smoke from 11 per cent in 2013 to 6 per cent in 2020. While we have reached that target five years earlier, the legislation that started yesterday demonstrates that our commitment to continuing to push this further. We are also increasing restrictions on the sale and purchase of tobacco and electronic cigarettes by under-18s, limiting the advertising of those products and bringing a mandatory ban on smoking here hospital buildings to further protect people from the harmful effects of second-hand smoke. We are also examining proposals to extend the current ban on smoking in closed public spaces to prisons. Working with partners in environmental health, the NHS and others, we will continue to monitor the effectiveness of our legislation and consider what further steps should or could be taken to ensure that we create a tobacco-free generation by 2034. I was going to go on to state that, given the observation that children growing up with a parent or others who smoke around them are much more likely to become smokers than themselves and that two thirds of adult smokers say that they started smoking as children, we can make a real impact on future health by protecting children from tobacco. I was going to ask you to tell us what wider action the Scottish Government is taking to create a tobacco-free generation in Scotland by 2034, but I think that you may just have answered my question. I am not sure if there is anything more you want to say. I can add to that range of different activities that we are taking to let Marie Todd know that, in addition, smoking cessation advice and support is available also to all pregnant women in Scotland to help to ensure that each child has the healthiest start to life. There are a range of activities that we are taking forward to ensure that we have a generation that is tobacco-free by 2034. I would like to extend my thanks to the minister for her recognition of the work of my good friend Jim Hume and the Liberal Democrats in stewarding the bill through the Scottish Parliament. As Minister for Public Health in the last session, Michael Matheson said, we have no current plans to consult on extending Scotland's smoke-free laws to private cars. Successful implementation of the smoking ban has undoubtedly already reduced exposure to second-hand smoke among children in Scotland, and yet today we have this well-deserved fanfare. There is beautiful SNP infographic claiming credit for it. Does the minister agree that, without the intervention of my good friend Jim Hume, we would not have passed this landmark act and we would not be celebrating today the protection of tens of thousands of Scottish young people? Despite the fact that there was a degree of friendliness at the start of that question, it descended into a bit of chirlishness. When we remember how we came to vote on it, it was voted unanimously by each and every party across the chamber. We are putting on record our thanks to Jim Hume. Of course, he came forward with a member's debate, but we had already had a number of pieces of legislation in place to take forward our ambitions about having a smoke-free generation by 2034. Much of that started by the previous administration, the Labour Government. Across all the parties, we have worked hard to ensure that public health in Scotland can be improved and will continue. I hope, in the spirit of consensus, to make sure that we can make further gains in public health in Scotland.


Dramatic eyewitness footage showed smoke-filled skies and an intense blaze in the hills and mountains above the Canadian city of West Kelowna on Thursday as wildfires continued to rage in British Columbia. Thousands of British Columbia residents were on high evacuation alert on August 19 after rapidly intensifying wildfires forced the western Canadian province to declare a state of emergency. The Pacific province has seen strong winds in dry lightning in the past 36 hours due to a cold mass of air interacting with hot air built up in the sultry summer. That intensified existing forest fires in the province and ignited new ones.


Robosim is a simulation software developed by the Department of Automation and Production Systems at the University of Zelina. It allows users to simulate serial, parallel, and hybrid kinematic structures, and has been successfully applied to control robotic devices. Two different methods for calculating inverse kinematics are available, allowing for greater flexibility and access to the source code. This article was authored by Uri Uresek, Tibor Galbavi, Vladimir Bulic, and others.


Here's how I start my husband's day off right. I start by writing down three reasons why I love him Then I fill up his water bottle to make sure he's hydrated Next I start on his green protein smoothie to make sure he has good nutrients for the day Can't forget about the aloe vera juice for his gut health The most important part to have good energy would be iced coffee with some almond milk and agave Once I'm finished with all of that I start on the cleaning process because of course who likes to wake up to a dirty kitchen Before I wake him I put on some Christian music and then I gently wake him up with a little hand squeeze If you had 24 hours with me and I couldn't say no, what would we do? All right, here's the paint. Here's your roller. That's always not gonna paint itself. Okay chop chop Damn Who is this fine girl?  Oh my goodness. You got a booty. Look at you When my girlfriend has a dream I cheated on her So I match with this very fine female named Brooke and in her bio it says she's a Scorpio and then she wants to be roasted so You know what I did so because I'm a gentleman I asked for permission that she really wants to be roasted and she told me to give me her best so I Gave her my best So I tell her you're the type of girl that puts her zodiac sign in her bio to seem relatable and down to earth But you really don't believe in it and you want people to roast you because you're not here to actually get to know Someone you're just on this app for the dopamine that you get every time you get a new match And you look for reassurance from an app that you're attractive when you've probably never been treated right because You're always looking for the next big thing and actually you don't trust guys at all based on how you've been treated in the past So you decide to make Tinder as a joke just to see you're capable of matching with And she unmatched me so I think I did I think I won There's this super cute guy at the gym Row what the heck? Hey, excuse me. Yeah, um, I just want to say I think you're really cute and I was wondering if I could get yourself that Excuse me I'm good You just kind of busted looking I go for more like Got it I Thought you were just doing the dishes in the kitchen right now Really that wasn't me my twin sisters here to help us clean. Did you say hi? Yeah, I said hi Now that we're married, shouldn't you sell your car spend a little bit more time with me?  You're starting to sound my ex-wife. What you never told me you were married before me. I wasn't For my husband's lunch today, I'm going to start by placing in a piece of parchment paper For this section I'm going to be making some mini bell peppers with cream cheese and of course the everything but the bagel seasoning Next I'm going to pack in some roasted peanuts along with these new Kodak granola bars Lastly, I'm going to slice up some cucumber and carrots and then pack in some ranch for dipping And now that this is ready to go moving on to the main portion where I'm going to be making some tuna fish sandwiches I keep the tuna salad pretty simple by doing mayo mustard some seasonings and sweet relish And then for the extra kicker I do some sriracha First I lay down some lettuce then the tuna salad mixture and then my tomatoes Lastly, I'm going to cut the sandwiches in half so they fit into the box better And I always like to toast my bread to keep it from going soggy by lunch time Now that the lunch is ready to go I'm packing it all away and of course including a note to tell my husband that I love him Oh, what's up tiktok? So I just want to know Am I the only man out there that their woman don't **** shadow when they say, hey babe, I'm going hunting Explain what kind of wife you are in one video Let's go go go So I came home today to this My wife said I needed a beer and stocked my fridge full of beer And ice Sometimes when you find that keeper you just keep them and say thank you Happy early birthday. What the **** is that? Happy early birthday What do you mean happy birthday? Happy early birthday. He's paid for skull cash. It's done. Cheers. Happy birthday Yeah, **** way Happy birthday um Happy birthday There's a second surprise. I see it Oh no, I dare you. He's got the keys. Hi What the **** I can't even Darren delivered it to me today I bought we bought it on Tuesday. Holy **** I've been in cahoots with your dad for several weeks now I had to like hide the text messages because he and I met up there so he could test drive it and be with me and So I was 24. She was 23 Had nothing built something Lost everything and recovered together She has been with me through thick and thin She has even sold her wedding ring at one point to put food on the table She has been through welfare with me through food stamps with me I only wish that every male Could have a life partner like I did. I promise if you go back and look at our videos You'll agree with me


Welcome everybody to the next COVID-19 ECB webinar. Today we are very happy to have Veronica Garieri from Chicago Booth with us. And actually we have a bit of an unusual setup because she's flanked by her three co-authors. But I'm sure we'll take you to the top questions at the end. So we have Guido Ador and Sony, Ludwig Straub and Ivan Werning. And Veronica will take us through her recent research with them on how supply shocks can also affect the demand because of this pandemic and give us sort of also a general flavor on the topic. And Veronica doesn't need any introduction. She's a leading macroeconomist and we're all following her research. So without further ado, I pass on to Veronica. Hi. So thanks a lot for inviting me to give this talk. So as I look mentioned, this is a work on the recent pandemic and it's joined with with the Lorenzoni, Ludwig Straub and Ivan Werning. So everybody, unfortunately, is aware that the current COVID-19 pandemic is having a very bad and weak effect on the economy all over the world. I mean, last data that I read yesterday on the newspaper is new five millions unemployment claims have been made last week and six millions a week before in the US. And the data are not much better, actually are not any better in Europe, if anything worse because the pandemic is more advanced. All governments and central bankers around the world and I know this well, the ECB but the Fed and all other countries have been realizing that this situation is particularly dramatic and they have been trying to help and to think what they can do to help the economy. And clearly when central bankers and governments say we can do whatever we are willing to do whatever it takes, a natural question that comes about is, is it a pandemic, a situation, a type of shock for the economy that needs stimulus for spending? And so to frame this question in terms of the textbook macro model, one can, the natural question that people have been debating is, should we think of a pandemic like COVID-19 as a shock that is primarily about the aggregate supply of the economy or is it a shock that affect mostly the aggregate demand of the economy? This is very important to then think about policy. In our paper, the way in which we approach the problem is, well, let's think about the pandemic. When we think about it, the direct effect that we can think of a pandemic is something that looks more like a supply shock because either because people, there are some sectors where you know that there is more transmission and so people, consumers and workers, prefer not to be interacting with other people or because of lockdown measures, some sectors of the economy simply shut down. And so there is no production of some goods and services. And so this is a clear supply shock. However, our question is, can this shock that it starts as a supply shock propagate to the economy in the form of a demand shock? And can the demand component become even larger than the supply?  When the demand shock becomes the initial supply one, we are going to say that this is a change of supply. And we are going to use some models to show you that a series of models where we add ingredients to show you that there are two main ingredients that can transform a supply shock in a Keynesian supply shock, so mostly in the demand shock. And these ingredients are, first, we need multiple sectors. And in particular, we need these sectors to be very much complement to each other. And so when we think about different sectors, we think about some sectors have been shut down, like sectors where there is a higher contact among people, like restaurants, hotels, and sectors that may be complement to those are sectors like if you think about hotels, maybe people decide to buy less luggage or less cars to travel because they cannot go into a town. So if you think about restaurants, well, people won't buy fancy clothes to go to the restaurant. So naturally, these are not all goods are complement. And there are goods that are substituted. For example, if you don't go to the restaurant, you may want to do more takeout and so forth. So then we have to evaluate what is the stronger force in the economy. And when complementarities are strong enough, then we're going to have a change. The other ingredient is incomplete market, and we are going to talk about that. We are going to also mention two additional ingredients that can enrich our model and amplify the demand effects of supply shock. First of all, input out to linkages and across sectors. And second of all, we are going to endogenize business exit and show that this can generate cascades that multiply the effect of the original. Then we are going to draw some policy lessons from our theoretical insights. And first of all, the first point is that, well, when a supply shock becomes mostly a demand shock, clearly a stimulus can help. So monetary policy easing and fiscal policy may be desirable. But interestingly, we are going to show that for the special nature of this type of shock, the standard fiscal multiplier is going to be smaller than usual. And then second, we are going to show that in particular, what is going to be very important element of policy, if you want to think about optimal policy, social insurance. So ensure the workers in those sectors or the firms that operate in the sectors that are mostly affected by the shutdowns. And then we are going to also think about incentive that another, I'm going to show you that another important component of policies incentivizing firms to preserve matches, so to do job hoarding rather than break the matches. And this is going to be very important, not only for insurance dimension, but also to think about the longer run when the recovery is coming. So let me summarize our main results through this table. So we are going to consider four variants of building up on the basic one sector, complete from market model. And I'm going to show you when these supply shock that we think as a pandemic can transform into the demand shock. Of course, I'm going to show you that in the standard one sector, complete market model, a supply shock is a supply shock. And then this is a well known result. I'm just going to do it to set the stage for the other results. Then I'm going to introduce incomplete markets.  And then I'm going to show you that what you really need, so an ingredient that is going to change things around is multiple set. If we introduce multiple sector, then we can, even with complete market, then we can have engine supply shocks. And when we add to the multiple sector framework in complete markets, the results are even stronger, meaning that the demand effect of supply shock becomes even possible and the range of parameters for each occasion supply shock that can arise is going to be even larger. So let me just with the one sector model in a one supply shock is going to naturally stay a supply shock in a sense that it's going to naturally create an upward pressure or the natural interest rate. Why? Well because in a sense it's like some positive news about the future.  So this is going to push force towards demand and push up. This result is going to be strong enough that it's going to survive even when you introduce incomplete markets. Because basically what you can do if you are, if you cannot borrow, well at most you just don't borrow anything but you'll never go on the other side of saving. So in the end it's going to be a wash for the people who cannot borrow but these effects if there is some people in the economy that can borrow, there is going to be always a positive upward effect on them. Once we introduce a multi sector we have to think as I mentioned before about our goods complement or substitute. Again if we think about restaurants as a leading example, so restaurants are shutting down, we can think of a different type of sector. Some produce goods that complement to restaurants and some are substitutes, take out are more substitutes for restaurants and maybe are more of a complement. If you think about hotels then cars could be another example of complement goods. So what we are going to show is that when the complementarity force is strong enough actually then supply shut and become Keynesian. And this is because once, because once just some sector shut down if there are goods that are mostly complemented to that then demand for those goods is going to reduce beyond the original level and so there is going to be an additional drop in activity on the top of the sector so they are directly affected by this. Now this with complete market even when people who are working in the affected sector are insured. But if we introduce in complete markets the effects are going to be even stronger because now workers in the shutdown sector lose their income and so they have to cut spending. So let me show you these intuition with a simple, with a graphical representation to make it more concrete. Just imagine think about two sectors, sector one and sector two. Sector one is the sector where that is more where there are more contacts among people and so is the one that is going to be shut down. Sector two is the sector where people can work from home and everything is so it's not going to be shut down after the shutdown. Before the shutdown all the workers sector one sector two get income and they spend both in sector one and sector two and so everything works well. Once we have the shock we're going to represent the shock as the shutdown of sector one. Sector one is completely locked down so workers in sector one don't get any income. However they are insured because we assume here that there are complete markets so they still have some resources that they can spend and so both workers in sector one and sector two are still going to spend in the sector two. The question is how much are they going to spend? Are they going to spend as much as before? So the demand in sector two is going to be the same as before the shutdown more or less and the answer to this question of course depends on how complementary or substituted the sector two is relative to sector one. In particular if sector two is a mostly is complementary now, sector one it may be that the demand in sector two is going to be lower than before because now there is less need for the vice versa if it's mostly substituted it could even be that the other way around that there is a higher demand that offset in part the drop down in the lot. Now let's imagine in let's think about incomplete markets so what happened when we had in complete markets simply workers in sector one are not going to get any income anymore they are not insured so they cannot spend in extreme. So now the demand in sector two is going to drop even more and it's going to drop even more and in particular if we think about the situation of complements that we consider before it's going to drop more but even if goods are a little less complement than before it still may be that the demand component now dominates because of the workers in sector one that don't have any more possibility of spending. Okay so let me move into the model let me start with Veronica. Could you go back to the previous slide before we go to the model just to clarify a question from Michele Lanza. So could we think of the model could we think of these sectors also as countries so especially you think about if you think about EMU if there are input-output relationships for instance between Italy and Germany or even more importantly if the lockdowns are not synchronized across countries could your model also speak to that? Absolutely so yes I was planning to talk about that later but this is a natural extension of our model or another way of interpreting our model is thinking about different countries especially in Europe where countries are so where trade is so integrated you can think about countries that are locking down before than others or they don't and you're going to have similar results. And of course this is an impact on policy and I can go back to that later when I talk about policy. And then there's a second question from Florian Haider. What is the role of uncertainty? I mean you said we can think of this as positive news about tomorrow but right now people are very much worried about tomorrow. Yes so we here we we would abstract we're going to abstract about uncertainty of course if you add uncertainty into the picture you're going to have an even stronger demand component that is going to pop up but in a sense there are many other ingredients in the real world that may add on the demand side for example issues and things like that I can't touch on that but what what we do here is like more we want to abstract from many other reasons for demand shortages and try to see purely the supply water the the pure effect on the demand coming purely on from the supply shock that's why we are going to abstract from uncertainty paper but it's certainly very important. Thanks for clarifying so let's see the model. Yes so um so let me start from a simple complete markets one sector model and this is again these are well known results but it just will set the stage for next versions of the model. So preferences are standard there is one single consumption good there is a fixed endowment of labor and barn and technologies. So how do we introduce a pandemic shock a pandemic is going to be uh we are going to think about a pandemic as an MIT type of shock so it's going to be an unexpected shock the economy is in steady state and then unexpectedly there is a shock that is going to be temporary in our model and it's going to last one period so at time zero we are going to have a temporary reduction in labor supply so instead of n bar the endowment uh goes down to 1 minus phi n bar so phi n bar is the is the size of the shock and then from time one hours we are going to go back to normal to n bar endowment goes back to n bar and we are thinking about a flexible price allocation. Okay so uh the the question is um one way of thinking about is this a demand or a supply shock in the frame in the term in terms of our model is to think about what is the the pressure on natural interest on the natural interest rate. So think about the flexible price economy and so let the interest rate adjust what's going to happen to the interest rate at time zero if you want to keep full employment and then we can simply use the earlier question of the um of the consumers to back up what is the interest the real interest rate um knowing that people are going to be at time zero the um consumption has to be equal to uh production that is 1 minus phi n bar because we are in a representative agent model so we use market clearing here and consumption in period two is going to be back to n bar and so you can see that immediately this tells us that there is going to be a upward pressure on the interest and then um another way of of thinking and so this is the supply shock in that sense the supply shock another way of thinking about it is well let's just add that to the opposite example if interest rate thinks that 1 over beta the interest at the steady state level of interest rate and so in a sense let's add the downward rigid nominal wages and then let's think about if there is excess demand or demand shortages in that case in the in the first period okay so this exercise is useful especially if you want to think about the zero lower bound the kind of of environment what it cannot actually adjust really the interest rate and uh if you look at the same error equation and then you flood in the interest rate 1 over beta you can back up what is the demand for in period zero and the demand in period zero turns out to be equal to n bar like in the second period if the interest rate is the same of the of the steady state 1 over beta so this means clearly that there is an excess demand because we know that production needs to be 1 over phi n bar because there has been a shock and so I can summarize this example so one sector of complete market there one sector of complete market model a negative supply shock is a negative supply shock in a sense that generated an increase in the natural rate or in other words generate an increased excess demand if they interest rate it what's the intuition well intuition is as I mentioned before the idea is that if you have a negative supply shock today it's good news for the for the future at some point maybe not tomorrow there may be uncertain for when it's going to be but at some point we know that we are going to go back up and so what agents want to do if we are in a standard stylized one sector model they want to borrow not say so that's why there's an upward pressure on the enough now can complete market save us and kind of overcome these upward pressure on the interest let's see so we're introducing complete market in the simplest possible way so we're going to use a simple version of the model because we want to emphasize the mechanism and then we can think about how extent I mean generalizable these results are let me start within complete month so we are going to have agents that have access to a zero net supply one period bond it's going to be a it the budget constraint for agent i and and we are going to assume that the fraction mu of the agents face a border constraint so new agents are going to be constrained one minus mu of the agents are not going to be constrained and the ones that are going to be constrained are going to be handleborrow at all so a it needs to be okay and then the genetic dimension comes also in another dimension that is about the shock how who is going to hit by the shock so each agent as a labor endowment and it that is equal to n bar and when the shock happens so when there is this drop in the labor supply in the economy some agents are going to be affected some agents are not going to be affected so five of the agents are going to be affected and are going to have a labor endowment goes down to zero the others are unaffected so let me first of all let me say that this new help us span the different extreme of the economy so when mu is a zero we have no constraint agents the model boils down to the represent to the complete market version that i've just described when mu is equal to one we have the extreme where everybody's constrained okay um so how we think about the effect of the shock in this economy so we have to think about two sets of agents that is one set small let me one set that is the new five of the agents are going to be the ones that are affected by the shock so that they lose their labor supply but they're also constrained so if they're constrained here because they cannot borrow at all their income go to zero they're going to consume zero okay so they're kind of boring we can kind for the analysis we don't really need that so let's focus instead on the others agents in the economy who are the other agents in the economy well on the one hand there are the other affected agents who are unconstrained so these agents can actually borrow from the other agents who are unaffected and are willing to lend that to them okay and then there are the unaffected agents who are could be face both the constraint or not but the constraint is not going to be relevant for them because they are not at the heat by the shock so all these agents are going to group together and they each of them can be the behavior of each of these agents can be represented by a standard earlier equation and then thanks to omotetic preferences can aggregate these into an aggregate earlier equation that is a seed that is a looks exactly the same of a and then once we have that we are going to think about what's going to be the effect on the interest rate and so we have to plug in what is again the same exercise of before let's think that we are in a flexible economy and then let's let the natural rate unjust and let's see if there is an upward or downward pressure well if we do that and we want to keep the economy full employment c zero needs to be equal to one minus five and bar so this is the endowment at the time of the shock and then in period one what's the demand this is the market steering condition what's the demand for goods well the demand from the unaffected and unconstrained plus new fine and bar this is the demand from the people who are constrained and affected at time zero who are at the zero lower bound and sorry at the zero constraint and so now they're going to spend everything that they get from back from endowment and then this has to be equal to unbar the supply of labor and so from here we can back up what is what is c1 plugged into earlier equation and see that again there is an upward pressure on the interest rate meaning the natural interest rate is going to be higher than one of our beta so to summarize again one sector model even within complete markets a negative supply shock is going to generate a rising in the interest rate or we can do the same exercise as before if we kept the interest rate fixed we're going to have an excess so again why well the reason is basically the same as before as I mentioned at the beginning now there is this negative supply shock again agents that are not affected by the shock there is no problem for them but agents who are affected by the shock they well then they want to borrow and so they're going to who are constrained they cannot borrow but they're not going to save so at the most they're just downpending the effect of the others in fact in the limit where everybody constrained is constrained there is going to be no change in it all right now so we saw that with one sector model we are not going to go very far so with one sector model a supply shock is a supply shock so it doesn't seem the stimulus should be very useful if we think purely about this standard effect less than introducing an ingredient that we think is natural if we think about the COVID that is multiple sector why again we think multiple sectors are natural well because some sector we're you're going to think about lockdowns and you're going to think that some sectors are going to shut down but other sector may still be still be active in the economy and so we want to understand if the effect of the of the original shock is going to limit to the sectors that are shut down or is going to spread over into the other sector so we are going to do that with a simple two period sorry two sector model first and then this can be generalized but oh one thing I didn't mention in terms of generalization the result that I gave you before that with one sector model incomplete market is not going to make it to to generate tension supply shock is very general so can be generalized easily to more general framework of incomplete market okay so we can add this just so the result that one sector model is and the intuition is clear because it's the same as before if you have some constraint I mean at most you're going to kind of reduce the increase in interest rate but you're not going to generate within complete markets and on a force to create our pressure one okay so now two sectors c1 and c2 again this is generalizable to a continuum of sector and I'm going to show you this at the end and how do we model the preferences so we're going to think that there is a constant intertemporal elasticity of substitution both intertemporal and intratemporal across sectors right so one over row is the elasticity of substitution across sectors one over sigma is the intertemporal elasticity of substance technology is linear in both sectors so let's focus on the steady state so consumption in sector one is going to be equal to production in sector one is market clearing and production in sector one is going to be equal to phi and bar so we are going to assume that phi of the total endowment and a shared phi of the total endowment is allocated to sector one and one minus phi of the total endowment is allocated to sector okay this is by assumption and then consumption is equal to production that is equal to phi n bar at one minus phi n bar notice that we picked we chose this phi that's defined as share of endowment of labor in the two sector being the same of the phi that is in the preferences and that is the kind of the weight on the two bundle of goods five to the one one minus five to the wrong and we do that exactly to normalize the the price the relative price of the two sectors to one the p star is going to be equal to one by choice of the normality now how can we think about the pandemic shock in this two sector model we are going to think about that as an asymmetric and so temporary again and so we are going to think that the pandemic is going to completely shut down sector one so again the size of the shock is phi and bar because the size of sector ones okay the sector one is going to shut down so consumption production labor is all equal to zero times zero in sector one now how about the effect on the rest of the economy so we are going to think to think about what is going to be the effect on the interest rate we are going to think about the real interest rate in terms of good too for good too so why is that why we picked to do well because the interest rate for good for good too is a good in our simple version of the in our simple model where there is downward wage rigidity basically it is a good for which there is no inflation so the real interest rate is going to be equal to the natural interest rate so it's interesting to look at that and also a good one is going to be a good that disappears from the economy so the price is not going to be it's going to jump up to infinity so it makes more sense to think of or think in terms of but the result more general and I'm going to go back to that later when we talk about inflation so again here we have multiple sector complete model so we're going to have an a any a a little equation and we are going to for good for good too and we are going to look at this other equation and we're going to plug in what is a consumption at time zero and at time one in sector one in sector two in sector one consumption at time zero is going to be zero by the shock and the consumption sector 2 is going to be C2 star and similarly at time 1 we are going to go back to the flexible price and bar so we are going to go back to the steady state level. And you can see that once this is the case we plugged in this number we obtain the interest rate there can be a approximate downward on the interest rate under some parameters and in particular the result is that when we have a model with multiple sectors and complete markets the negative supply shock becomes occasional supply shock in a sense that generates a downward pressure on a natural rate when 1 over sigma is bigger than 1 over rho so when the elasticity of intertemporal substitution is bigger than the elasticity of substitution across sector and why how can you interpret this this result well and we can think about it in two different ways from two different angles let's first like a fixed sigma and elasticity of intertemporal substitution and think about in terms of complementarity across sectors then the commission tells us if 1 over rho is small enough then the demand effect becomes strong and and this is natural because this means that if the two sectors are complement enough then there is going to be a feedback on demand of sectors 2 coming from the shutdown of sector 1 as I described before restaurants closed then people are not going to buy new clothes so this is going to have an impact on demand for the sectors in the other sector. The other way of thinking about this is well let's fix the role of the complementarity across sectors well when the elasticity of substitution is large enough then we are going to have again demand shock dominate so why is that well one way of thinking about that is that you know that today some goods just disappear so if you can substitute consumption between today and tomorrow really or or we are eager to do that because elasticity of intertemporal substitution is large enough well then you want to substitute that so you want to consume more tomorrow because tomorrow some goods are going to go back into the picture right so these goods that you really would like to consume today that are infinite price today you you can consume right and this is a graphical representation of this condition so you can see that the the pink area is the the shaded pink area is the area of the parameter space where we have one over on the x axis and one over sigma on the y axis where Keynesian supply shocks arise and the other areas where a pandemic is just a simple rider supply and again we can restate the result in terms of the patient access demand if we just now how about incomplete markets so uh if we if we add on top of the multiple sectors in complete markets what happened well let's do again that in a um keep the same structure of incomplete markets model as we did before we have now a fraction mu of the agents who are constrained one minus mu who are not constrained and five of the uh workers are going to be affected and one minus five are not going to be affected so again we can focus on the unaffected and unconstrained workers to think about the effect um on the interest rate and in this case you can see that this is the error equation written in terms of the interest rate at time zero and then you can see that what is c2 zero so c2 zero is the consumption in sector uh uh two at time zero if again that we let the natural rate adjust and to keep the full employment this has to be equal to one minus five and bar which is the total uh employment and production in at time zero and how about consumption in two sectors in uh in time one while the we are going to have one minus five mu times n bar as a total uh income and then five of that is going to go uh two um sector one and one minus five so this is going to be this this can show once we plug this into the error equation that there is going to be a downward pressure of the natural interest rate for a larger for loser conditions than before for a larger set of parameter spaces so when um then then before and you can see that in this graph before in their pink shaded area uh we could we the pandemic shock was occasional supply shock now this area becomes blue becomes blue includes this triangle on the right this is drawn for the things where mu is equal to one so where everybody's constrained if you mute those uh is zero we go back to the pink shaded area so we knew in the middle we are just adding a slice of this fire okay so this means that even in cases where one of a raw um uh bigger than one over sigma you could have so for example here i'm showing you some parameters for which one of a row is bigger than one over sigma and so where in the case of complete markets you have um that a pandemic is a simple supply shock and so you have an output gap that is positive in the non-shocter shock sector then if you introduce enough marketing completeness so if mu the fractional regions were constrained increases enough then this is going to transform in an occasional supply of shock in the sense they all could get in the known in sector two start to be negative and the law and interestingly enough for parameters uh for which the shock is larger so for five larger where you have a bigger boom in the case of complete market you're gonna in sector two you're gonna have a bigger bust once you have enough uh marketing uh i have now uh completed my my table so uh just so some uh and uh complete markets or incomplete markets uh a pandemic is a simple supply shock once we introduce a multiple sector uh then even with complete markets occasions of play shot maybe even so they demand the facts of the supply shock maybe even larger uh when we have uh incomplete markets uh on top of uh multiple so now uh let's think about uh uh Monica before we move to policies there were two questions coming in so one is on the the which and the model is sort of a spillover right it's a kind of uh exogenous technological complementarity the question is whether this could also honestly so specifically Freud and I was saying right now I cannot go to restaurants but that also means I voluntarily avoid other sectors down also makes people not want to go to other sectors could this endogenous reaction been alternative to the more technological complementarity you are considering so yeah sure I mean that that's uh a little bit my next point after I took a policy I thought I talked about that so the complementarity of sectors I'm gonna talk I talked about here I just modeled in a very simplest way as pre as part of the preferences but I agree with Florian you can think about the complementarities in a broader sense and what we are thinking is what Florian mentioned about like endogenous decision about the other I mean the endogenous feedback effect of what happened in one sector to the other but another way of thinking about it is to think also about input output linkages across sectors is another way of thinking about complementarities and I'm gonna go there in a few minutes so I totally agree complementarities you don't want to take that as a simple parameter that you look at in a data standard model but it's something that is broader than that okay and then the second question that came in is by Christoph Camps he's asking whether your paper now reviving the law of markets by Sey so Sey's law which basically was about a fallen supply destroying demand yes absolutely I mean we mentioned that in the paper yeah we mentioned that in the paper I mean we think that we have a different interpretation I mean a different take on that but we mentioned that that there is a link to that okay and then there were two further small questions one is by Luca Dedola whether in the incomplete markets version of the model also the persistence of the shock matters yes here we have a pure temporary shock so it's only a regular shock but if you embed a more shock with persistency for sure that that would be important too okay and then the last question by Philipp Hartmann is whether sort of the distribution if you had more than two sectors right if the distribution of containment policies matters so for instance if all sectors operate only at 20 percent because everybody's working from home with low productivity because it's on a form containment policy would the balance between demand effects relative to supply effects change so you're saying if each sector operates at the lower the some intensity then yeah yeah so if it was more of a uniform thing across sectors sort of a partial lockdown yeah we're gonna I'm gonna show you a more general model at the end if I have time with the continuum of sector and then you can interpret that more broadly as an intensive measure of activity if you want but yes okay perfect thank you how about policy so the first thing like let's just think about a simple policy like government spending or transfer that are sector specific and then it's gonna become our workers workers model that is multiple sector plus in complex model so it's striking that if you if you think about government spending and transfers in this model you can see from our proposition that the fiscal multiplier is one so you lose the multi like the the the the second round of Keynesian cross-operating in a standard model with nominal rigidity is and why is that because of the nature of the shock because if the shock is that you cannot have the feedback effect on the fact that people's the people that government spending is going to increase the income of people the income of people are gonna spend more they cannot spend more in sector one because they're gonna spend more in sector two but that's not really where it's needed it's where it's needed in sector one because it's where the workers are the highest right so fiscal policies are still beneficial because the fiscal multiplier is positive but they're not as strongly beneficial as in a standard model how about optimal policy so we want to I mean this is a stylized version of thinking about optimal policy but one important ingredient that we need to add if we want to think in terms of optimal policy is some else dimension because of course I mean if we could just not shut down the sectors that would be optimal there would be no problem at all so but the reason why we are shutting down some sectors or there may be some some some problem but not as big as if you shut down but why you are you want to shut down sector because you think that that is going to help the health of the economy to improve so we need that dimension to think more broadly about so the way we are going to do it is in a very stylized way we are going to have an additive health component that depends on four things one on side that is the shock shock or no shock is binary and then the health of an individual depends on his own consumption in sector one and his own work in sector one because sector one is the contact intensive sector so if you if you are a both a customer in that sector or a worker in that sector you're exposed to contact and so you're exposed to the virus and so that's why the more you consume there the more you work there the higher the lower is your health the higher is your negative health shock and then so also the total level of production in sector one is going to affect your health and this is a standard delta externality so the more active the more people the more active the more production there is in sector one there are more contacts that are and the more people are there the highest is the chance that you get the virus if you think about restaurants if lots of people at the restaurants that you have a higher chance to get the virus okay and so there are three sources of inefficiency in this economy again we are in the complete market multiple sector version of the economy we have the health externality here as in a paper by Martin Sergio and Trombard we have a lot of issuance that comes from the complete components and then we have maybe we have also involuntary unemployment okay because because working in sector one is is a problematic what you have so what is that let's think about a shock an economy where there is a shock but the there are no lockdown policies so you could potentially work and consume in sector one still and and we're writing about optimal policy in terms of pretty much forced still in this economy where you do not have the lockdown policy maybe the production and output in sector one goes down simply because people in the personal decision optimal personal decision to work or consume there is to reduce their consumption their work there and their labor supply in that sector because of the higher virus free and so you can have involuntary unemployment but now the first remark is well can this is this unemployment inefficient well no this unemployment may actually not be socially inefficient in fact there are two forces that may make that unemployment efficient or inefficient on the one hand you have the Keynesian wedge so that of course tells us that the unemployment is bad because amplify the demand effect for the rest of the economy and so this is of course creates some inefficiency but on the other hand you have the PQP given externality that actually it's good that there is an employment because means that there is less contact in the economy and so less spreading now let's think about remark two okay once we think the shutdown for sector one is optimal and because the PQP an external effect is stronger than the Keynesian wedge effect well then these of course is going to generate the demand effect of the Keynesian supply shocks that we've talked about okay so in that sense there is some desire for stimulus in that dimension but as remark three is well within complete markets the way in which the stimulus that the the best way to provide that stimulus through targeted transfers and targeted transfers can help obtain the first best because they keep the three birds at the same time with one stone which is one they provide insurance solving the incomplete market problem two they help raising the natural rate helping if we are at the zero lower bound and three they may make the health policy more desirable because you can directly address the issue generated the the issue generated by the policy and that made it desirable to reduce the spreading of the do more more lockdown policies and reduce the spreading of the now um so socially is necessary and targeted transfer social insurance is key to obtain first best so how now of course this opens a big debate about how to implement the social insurance and how can we think about who who for example should we reinforce policies like unemployment insurance or should we reinforce incentive for firms to keep their work and so in the in the paper we also have an extension where we consider the importance of job matters so if we are in a business that has some workers well at that and your lockdown at that point you can keep your worker attached to your firm by paying the wage this is of course a cost but on the other hand once the the sector reopens your your workers that is valuable for you because maybe you invested in human capital because these are skills that have been developed in your firm and so forth then you have this valuable worker tomorrow on so v1 is the value of the worker that is the wages you have to pay today on the other hand of course you may just you may decide that the cost of paying the wage is too high and shut down and destroy the match so what is your choice what is what is that effect of your choice while the interest rate is important in affecting your choice because it determines how much more you you put value you put on the future rather than paying the cost today and and the interesting thing is that labor hardening provide perfect insurance at the same time is a way of providing insurance because it exactly gives the keep alive the wage for those workers who are in the lockdown sector so it kind of reduce the demand and adverse effect of the lockdown policy so we we make the claim that labor hardening is positive also if we think a longer around the consideration because in the longer run when the economy reopens at that point you are going to have your valuable matches back into the picture and so both because it provides perfect insurance today and before long run considerations of efficiency and avoiding job destruction labor hardening seems optimal so seems could incentivize labor hardening and monetary policy in general of course expansionary monetary policy is going to help in in that direction because by lowering the interest rate that help firms optimally choose to retain their workers now of course there are liquidity issues of firms and so on so when we think about expansionary monetary policy in that dimension for labor hardening consideration we want to think more broadly about the monetary stand and so think about providing liquidity and the all these type of measures to banks and so forth it's all these type of measures are going to help in terms of give the incentive to the firm and then give the liquidity to the firm so to keep the liquidity in the system alive so that the firms may have access to liquidity to keep their workers now i'm going on time i'm doing bad on timing right we have 10 minutes it's it's okay thanks okay so you tell me when i have to stop i'm gonna go for so one more one more issue is that i want to touch upon briefly in terms of policies well when we want to think about inflation of course you have ECB so i don't have a i need a slide on inflation and i want to say our model is very stylized in terms of inflation because we have like stark downward wage of nominal rigidity and of course so we have actually no deflation for example but the main message of the model if you think about generalization of the model we can easily generalize the model in a more general standard setting and the main message of the model in terms of inflation is that demand efficiency means no inflationary pressure so when the supply shock is a shocker than i have no inflationary infinity deflationary pressure pressure and to think about the one way of thinking about the the mechanism i just came before is to think through prices and i think he's useful to take his time so when you think about sector one what about prices in sector one we said sector one is price is essentially the integrity so if you could price the value of going to the restaurant with no risk of getting infected so it's like there is a spike in price in the price level in the shadow price level for sector one and so this means that actually if anything there is going to be a deflationary pressure because tomorrow these prices are going to go back to China so a different way to and this is you prefer to wait and consume more tomorrow okay so this is a different way of thinking about that but the main message is that when Keynesian supply shock arises deflationary pressure may be in the in the picture so effect on the real rate is also deflationary this complementarity among sectors that this seems important for the for our key results and as i briefly mentioned before one thing that i want to highlight is that input output linkages are an important way to think about this complementarity stronger so think about again about our rest accounting services and these account and then suddenly they stop demanding these accounting services the demand for account immediate inputs producing non-affected sectors actually there there is going to be even stronger demand the thing is that the supply chains in our that the the supply make demand the personal demand are supply chains okay not to so typically people think a supply chain in the other way from upstream to downstream so thinking about affected sectors that produce intermediate good for unaffected sectors that are not important but we want to emphasize this this dimension so how do we introduce that into the picture i don't have much time but the idea is that sector one who uses some intermediate goods that are producing sectors when now clearly the upward pressure the natural interest rate is going to be even higher because once you don't have any more the demand in sector two from coming from the demand for the intermediate inputs from sector one you're going to need even more to generate even also to kind of compensate for that so the effect of the demand effect is going to be so the last thing that i want to mention is that and i mentioned that before briefly so first of all these two sectors can be generalized to a continuum of sector you can potentially generalize it introducing an intensive measure if somebody has mentioned before the the one dimension that i want to highlight is that if you have a continuum of sectors okay and you have some monopolistic competition that generates profits and you assume that each variety is produced by a separate worker from so extending our model well then basically the results are exactly the same as in our model within complete markets and two sectors but then if you add an indigenous exit decision things becomes the demand effect becomes even stronger so if you now add a fixed cost a random fixed cost of businesses have to have to cover a fixed cost to stay active now it can be that when some fraction of sector shuts down there is going to be a fixed effect on another sector because this is going to reduce demand in other sectors but in these other sectors businesses suddenly may exit because the demand is not going to be enough to cover the fixed cost and so then this exit is going to fit back in demand from other sectors and so on generating a cascade of exit that amplifying the shutdown the endogenous shutdown in the economy i don't have much time and let me show you this figure this shows that the on the x-axis is the active firms and businesses and on the y-axis there is employment at time zero and you can see that the the business exit lock of the intersection between these firms is the effective active businesses so you can see that in the first here is before the shot the intersection is at one minus five at equal to one means all businesses are active in steady state suddenly if you have a you take out one minus five sector from the economy because there is shutdown then the firm exit lock shifts to the left but then you can see that the intersection between the red and the blue line is going to be at a point that is one minus five meaning that the active firms are going to be much lower than the one minus five in the economy so there is more on the top of the of the five firms that are shut down there is going to be an extra number of businesses that are going to exit endogenously and this is going to okay so let me conclude the conclude with the same slide table that I showed you at the beginning to re-emphasize our main results first a single sector we cannot the supply shock a pandemic is a simple supply shock so stimulus is not but if we introduce multiple sector and in particular if you introduce multiple sector we'd incomplete market and we'd enough complementarities among sectors which again can be interpreted in a loose way especially considering input output linkages well then it's a dependent so having demand side demand the effect that are stronger than the original and let me mention again the point the first question somebody asked again now that you have the model in mind I think it's natural to think about how about international like context like Europe and think about different sectors at different countries and this is a natural is an interesting avenue for thought and I think that this of course could call for a coordinated policy across countries thank you many thanks Veronica um one question that came in from Sebastian Schmidt is whether in the context of your model the type of policies we've seen in Germany it's called the Kurzarbeit where the government pays part of a worker's wage without them going to work from the kind of label hoarding perspective is that a good policy in the model yeah I would say so and this I think it's something similar to Casa Integrazione in Italy where the government kind of pay for the workers to stay attached to the firm I think that exactly this type of policy in this context seems positive I don't know if my quarters have anything to add on that dimension and the second question I guess that's sort of the last question I mean there's a lot I think your papers prompting a lot of thinking here in Europe in terms of more targeted policies targeting certain sectors of course primarily in terms of fiscal policy so as we interact a lot with these policy makers what's sort of the the main message coming from the model I mean you can also kind of step outside of the model like what what sectors to target is it sectors with strong complementarities so so first of all I want to say that this is a question that is particularly important so when we are at the top of the health emergency like in some countries like in Italy for example where all the sectors are shut down of course then the mechanism that we highlight and then the help of the sector is much more difficult to implement at that point the policy that you want to think are relief type of policy and so forth but as probably we are going to get out from the extreme lockdown measure then you're right that then our about different sectors is going to become important and how to target that insurance is going to become important and the the I mean one way of thinking about it is well of course you want to target you want to help the businesses in those and the and the workers who lose their their job so that you are attached to sectors that are affected from the mostly affected from the lockdown because these are the workers that then are going to spend in other sectors rather than help directly the other sectors that are the ones that have a complementary but of course if anything if you want to add some some help to other sectors that are active then you want to I mean the model would would would call for more action in those sectors that are somehow more linked to the sectors that are shut down in particular sectors that produce intermediate input for for sorry sectors that are producing yes intermediate inputs for those sectors that are shut down so that temporarily have a particular shortage in demand beyond what what would arise if the other sectors were not shut down thank you my quarters want to add something on that all right I don't hear anything so uh oh who's that yeah I yeah I just this is Guido yes Guido go ahead all right yeah no on the on the asymmetry between sectors I think that is I mean I totally agree with everything that Veronica said and yeah I think the idea is that when all the sectors are shut down like where we are in a really total lockdown then we're not saying that uh social insurance is not important but I guess at that point policy is essentially doing like disaster relief you're just helping people that get hurt but you don't worry at all about restarting activity because it just cannot be done and so in a sense like all our messages that the moment some sectors can be active then the question as are these sectors at the right level of activity or are they going to be too depressed and so we want to help them out and so I think is is when you start having some asymmetry when you have to start to have some sectors that could be operating like some manufacturing sector where you can do things without compromising the health of the workers then the question is like is activity in those sectors too too low that's what where we would want it to be and what kind of interventions can help so the asymmetry is very important thank you Guido so I'll surely be thinking about these issues and working with the input output tables and etc um if unfortunately time is up so I wanted to just end by thanking Veronica in a big way for preparing this very interesting presentation for us so on behalf of the whole ECB there were several our board members on the call as well thank you very much for doing this Veronica thank you please stay healthy all the best and I'm gonna close here for now thank you very much everybody bye bye now


My name is Isaac Hulun from St. Paul, Minnesota. You're watching Trucker Josh Vlogs on YouTube, channel TJV, and he's with this co-pilot diesel, the Weasel. Good morning, everybody. Start the day with a beautiful Chevrolet. Passing me there, look at that. Very nice, very nice, how much? Too much for me. Highway near Fergus Falls, Minnesota, headed west on I-94. Gonna go up to I-29, turn north, and not gonna stop until we hit Canada. It's birthdays in a few days, and I gotta be home. I wanna be home for her birthday. So many years now, I think since we've been together, I've missed every one of her birthdays, the actual birthday. We celebrate her birthday, but I haven't actually been home on her birthday, I don't think. Even this year, we're celebrating her birthday tomorrow, and her birthday's in a couple of days. She's gotta work on her birthday this time. But at least I wanna be there. Yeah, make her breakfast or something. Make her day a little easier. So I should be home five hours or so. We'll be home this afternoon. I should be at the house. Proud, probably end up being around supper time. She's got her cousin over right now, but they're newborn baby. So she's pretty preoccupied right now. Me, the last six hours, they're gonna drag out, they're gonna feel like forever, because I wish I was at home already. It's time to get into the pickup, buddy.  Gonna go home? I'm excited too, probably contain myself. Hey, so let's just quickly throw everything in our bag. Diesel, where are we going, man? We're in the pickup, we can only be going one place. No, not the vet. We're not the park. Though you could maybe call it a park, a small park, our own park. We're headed home, buddy. I'm not too sure how long I'll be home. It'll be a few days now. I'm filming this on, what is it today, Tuesday? I think it's Tuesday today, isn't it? Getting home Tuesday night, when's it? End of the week at least. We'll see. Not gonna think about that right now, let's just think about getting home. Got a bit of a hike there yet. Out of the semi and into the pickup isn't the end of the journey home. Just the beginning of it. Well, I wasn't gone for that long and the canola fields are already ripening. Look at this, they're all turning bright yellow. Before you know it, they're gonna be harvesting that stuff. You ever wonder where your canola comes from? The one on the left is a little more yellow than the one on the right, but it's these fields that turn bright yellow. That's canola. We grow a lot of it out here in Western Canada. It's really beautiful when it's in full bloom and it's just big, bright fields everywhere. When people from other areas come here and they see these fields for the first time, they're like, wow, what is it? It's like neon yellow, if that's a color. It's like bright, bright yellow. I grew up here, so that's pretty normal, but it's still pretty special every year when you see it. But like everything in summertime, I just wish it lasted a little longer. There's some more on the right there. Lots of food. Lots of it was making me hungry. Home sweet home. Right, Weasel? You're good to be home. What? What? It's just me. It's just me, guys. You forget who I was already? I know who you are, dad. You're my favorite dad in the whole world. You're my favorite Chevy. I like you even more than my Chevy truck. And that's a lot. So that's the day. Hope you join us. I'm gonna be home for a few days now. I'm not gonna be filming for a couple of days. I got a lot of work to do around here. Just gotta focus on that. And we'll see you when we're headed out on the road again. I believe I'm headed towards Alberta on my next trip. We shall see, but thanks for tuning in, everybody. It's been fun. Time to go enjoy some summertime weather. Where's Chevy? What are you doing? What are you doing? Why don't you always do that?    Is that your favorite? Is that your favorite? I'm with the belly scratches. Those two, those two. Not as good, but pretty good. Yeah?  Good boy. And we got this all here. We just gotta paint this up and we'll be ready. Had a tree that we had to take down in the backyard because it was getting ready to come down on its own. So I'll figure I'd take it down in my own terms before it took me out on its way down. Gotta clean that up sometime soon. And that's that. Bye, Chevy. We'll see you later.


Hey, I'm Andy Robinson. I'm the potato extension agronomist for North Dakota State University and the University of Minnesota. And we're really happy to have you here for Field Day, although it's a little bit different this year because of the world pandemic, we're still glad to be able to bring you some information and some insights from the researchers this year that are working really hard on potatoes in North Dakota, Minnesota. So as far as my program goes, we have two research staff specialists, Eric Brandvik and Peter Eyrie, they're helping make sure all our projects get done and also have two graduate students. We have Jed Groh, who's working on a chip selection trial. We're looking at some advanced chip selections that Suzy Thompson is working on or has bred and he's looking at spacing and nitrogen rates on those up in Hoopal, North Dakota. And Inise, she's working on a project where we're looking at different nitrogen sources, including turkey compost for russet potato production. So as far as my research goes this summer, we have research located in Perum, Minnesota, Oaks, North Dakota, Inkster, North Dakota, as well as Hoopal, North Dakota. We're looking at fertilizers. We have slow release nitrogen trials, slow release ammonium sulfate trials we're doing. We're looking at different placement of these fertilizers in the potatoes. We also have herbicide work we're doing. We're looking at weed control with products such as saunalan from Galwan. And we also have projects where we're looking at herbicide injury from some of the plant growth regulator chemistries, such as clopyrilid and aminopyrilid and the carryover that that can have in seed potatoes. And then when we get up north into Hoopal, we have our variety trials there where we have 20 different red advanced selections or varieties and 30 yellow selections or varieties. And these will be harvested, graded, and we'll have the yield data for that. And then we'll also put those into storage as well to look at pressure flattening as well as sprouting and storage. And so typically we like to show those on field day, but we're not going to this year. But what we'll do is we're going to get creative this winter. We'll have another Tater Talk field day this winter. Hopefully we'll be able to allow growers to come and look at those varieties in person. And if not, we'll provide pitchers and information for you to be able to see those so you can make your decisions for future potato production needs. So that's kind of what it's going on in my research world. As far as the extension goes this summer, we've had a really good season so far. We had good planting. We've had good heat, good growth and development and good rainstorms, especially in the valley. It seems like the potatoes are basically grown under irrigation because we're getting weekly rainfalls and yields are looking good and qualities looking pretty good. The heat has caused some problems with the quality. We've been having a lot of issues in late July, early August with second growth on potatoes. We've been seeing a lot of growth cracks, sprouting of some of the less dormant varieties and even tuber malformations going on. And so that's probably something growers are going to see this fall as they get into harvest. And also with the extra moisture we've had this year, it's been ideal for late blight. Our spore traps have been catching spores. We have not identified late blight to this point that this is being recorded, but certainly conditions are very favorable. Even today, this day, it's very humid and muggy and we'll probably continue to see spores show up in the spore traps, but continue to be diligent in your field so we don't have storage issues with late blight. And also with that extra moisture too, we've been seeing quite a bit of soft rod as well. And so don't be surprised if you're seeing more soft rod as we go to dig and get things into storage. But we hope that everyone will have a great finish of the season and a good crop and be able to store it well and be able to keep continuing to feed the world. Appreciate your patience with everything going on this year and the ways we're doing things, but let us know. If you have any questions or if you have ideas, please reach out to me.


From New York, it's theCUBE. Covering Big Data New York City 2016. Brought to you by headline sponsors, Cisco, IBM, NVIDIA, and our ecosystem sponsors. Now, here are your hosts, Dave Vellante and Jeff Frick. Welcome back to New York City, everybody. This is Women in Tech Wednesday here at Big Data NYC. We do Big Data NYC every year, concurrent with O'Reilly, Strata, plus Adoop World. It's Big Data Week in New York. We go all week. We started Monday with an evening on deep learning and AI, co-sponsored by NVIDIA. We had a party that night, last night. We had really an awesome afternoon. We did all day CUBE interviews, and then we did a segment, really focusing on machine learning and applying analytics and cognitive. IBM came on theCUBE prior to their big announcement last night, we'll talk about that in a second. And then we hosted a panel of eight data scientists, rockstar data scientists talking about things like, is there such a thing as a citizen data scientist? How should application development and data science teams work together? What is a data scientist? And then after that, we went over and listened to Bob Picciano and his team, Riddhika Gunna and others at IBM, announced their new platform for cognitive analytics. Really trying to simplify and up-level the complexities of doing big data analytics.  Jeff Frick, my co-host is here with me. We were on the ground interviewing people at the party, data scientists, practitioners, executives. It was good. Good night. Yeah, it was a great night. And we continue to try to innovate Dave and theCUBE and to have that round table, eight people up on the set. I was kind of, it's fun to see all the faces that match the Twitter handles that we see all the time. A lot of big influencers. You know, the only thing we didn't really cover, and I was trying to get you a question in there, is kind of what about, it's still kind of how to lie with statistics, right? You know, you can pretty much always find a number to support your hypothesis. And we really didn't get too much into that. We did get into, you know, if you've got a result that just looks too good to be true, you need to go back and check. But a lot of other things came out of it that I thought were good, especially on Women in Tech Wednesday, we had 25% of the folks on the panel were women. But talking about the softer skills that one of the panelists said you used to never come up in kind of a data science conversation. You need to have softer skills to have a broader kind of experience based in which to build your algorithms and test your algorithms, which I thought was pretty interesting. The other concept that keeps coming up over and over and over again is this concept of a data scientist. Is it a unicorn? And I think it was Craig Brown brought up that really the way to think about it, it's a team sport. It's like nothing else in business. You know, you need people that have different skills that they can bring to the table. So I thought that was a pretty interesting play and I thought the round table worked out pretty well, which we've never done before on theCUBE. Yeah, it worked out great. Afterwards, we were talking to, so it was interesting, there were two out of the eight panel members were women that just happened to be 25%, which was the number I threw out about the percent of chief data officers that happened to be women. I don't know if that's the right number or not, but it was just sort of a coincidence, but we were talking to both the women on the panel, Miriam Fridell, who's with elder research, does some really interesting high-end stuff, and Jennifer Shin, who works for Nielsen. We were talking to them afterwards at the party along with Des Blanchfield and what they were saying to Peter and myself, Peter Burris, is when they go to build models, they assume that the data's not going to be there. So Jennifer right now was doing some stuff with electronic medical records and trying to predict cause and effect of health incidents and likelihood of certain diseases, and so they go into building these models with the assumption that the data's not going to be there because they're real skeptics. And then the other thing, somebody said they had a great line the other day, if you torture data long enough, it'll give you the answer, right? And so one of the aspects of being a data scientist is really not giving up on the data. I keep looking at it from different angles, and so it was quite instructive, I thought, that panel. So today we got a big day today, more wall-to-wall coverage. We did 10, 12, 15 interviews yesterday. And so one of the other big themes is this whole Hadoop ecosystem is really shifting.  And a big discussion yesterday about the cloud guys trying to go sort of create an abstraction layer above their sets of services, and in many respects creating threats to guys like Cloudera, because generally Cloudera and Hortonworks, and we'll explore this today with some of the folks from Hortonworks, do a lot of on-prem stuff. They're betting on hybrid cloud, and pure cloud is going to be an interesting dynamic for those guys to compete specifically with Amazon and Microsoft. I mean, they will participate in those solutions in the marketplaces, but increasingly customers are going to consume those capabilities as services for Amazon and others. The other kind of theme that keeps coming over and over and over is before big data kind of equal to Hadoop. And there were big data shows, and it was Hadoop World and Hadoop Summit, and we're hearing more and more that Hadoop is kind of a generic term now almost for the ecosystem around big data, and I thought what was really interesting, part of Pitchiano's thing last night is he said, you know, IBM is going to innovate at the speed of open source, and we hear over and over and over at DockerCon and all these different open source shows that you just can't compete with an engaged community on speed of innovation. And so for Bob to have called out specifically and then bring up all the open source projects that they're really actively involved with, and I think it came up in one of the interviews yesterday. They're the number one contributor, I might be mixing it up for the Spark project. It really shows a bold move and kind of changing the whole narrative around big data as Hadoop to big data and analytics, and again, building off the NVIDIA panels we had the night before is a much bigger play than just Hadoop. Yeah, I don't know what that actual number, so we heard two different quasi-conflicting stats yesterday. One of the IBM folks that were number two contributed to Spark, and then twice we heard I think from Riddica, and I heard it again yesterday from Bob Pitchiano with an announcement that they were number one, I think IBM is number one in contributions around machine learning or something like that. Number two, maybe overall, who knows, we'll try to unpack that. It really doesn't matter. They're putting a lot of resources into Spark, and it's interesting, Jeff. I mean, Hadoop, we talk about all the time, and Rob Hoef just wrote an excellent article on the Hadoop, big data hasn't lived up to its promises on siliconangle.com. We talk all the time about the complexity and the barriers of absorbing, and you heard some of the guests yesterday say, well, we're not experiencing that, and of course the vendor view versus the practitioner view is sometimes not aligned. Nonetheless, when Spark came to fore, what we saw is a lot of people said, okay, I couldn't deal with Hadoop complexity. I'm gonna replace or supplant a lot of the things that I'm doing with or had intended to do with Hadoop with Spark, because it's more integrated, it's simpler for us to use, and I'm gonna go pure Spark. Now, if people have investment in Hadoop, they've gotta obviously get a return on that asset, so they're gonna continue, and likely they have the skill sets, but there's no question that this bespoke sort of Hadoop movement has spawned a lot of innovation, but it's been a challenge for practitioners to bring all that together and actually deliver value, so that's something that we've been tracking and watching, and I suspect we haven't heard the end of this. Spark is not the end of the road. When you talk to people who come out of Google and other places that are early adopters of sort of big data technologies, they said years ago, oh, MapReduce, long gone, we're not doing that anymore. Hadoop, yeah, do use it a little bit, but we've moved on, and you talk to people now, they say, yeah, in memory, Spark, yeah, we did that, but there's other stuff going on, so you know how it is. When it happens in the hyperscale guys, five years later, it hits the enterprise. Right, and Armand Rees from IBM talked about this project, their data science experience, because there's so much open source going on all the time, there's so much development, and he called it Facebook for data scientists, which was pretty funny.  IBM, again, had made an announcement yesterday, they called it DataWorks, and their whole thrust was, we're going to try to simplify, we are simplifying the complexity of doing analytics, and we're bringing Watson to bear, and they gave a demo, it was actually a pretty good demo of somebody who went on a website, they wanted to go camping, where do you typically go camping, Acadia, family, how many people, blah, blah, blah, I answer a bunch of questions like a wizard, and then it suggested, okay, these are the tents, this is the equipment you need, they brought up an offer, like 10% off this whatever gas stove, or whatever it was, and I was impressed at a couple of things, first of all, they're doing this with a line of code, doing some basic visualization, I think Peter Burris made the comment that the Viz was not totally where it should be, and I would agree with that, I think there's some work to be done in visualization, but I'm assuming that they can integrate with other visualization tools like Tableau and Click and others, but nonetheless, the speed with which they were able to configure that those answers, and present those answers to the consumer, was lightning fast, it looked like it was really simple to code, single line of code, to create functions that used to take hundreds of lines of code, and like I said, lightning fast, I think of those, the wine websites, and they're very rudimentary, and okay, you want red or white, cab or that, and you sort of do these pull downs, and it sort of chunk, chunk, chunk, chunk, and then spits out a bunch of wines, it looks like we're now entering the next generation of consumer sort of friendly assistance in terms of buying, so that's one example, it's a classic retail example, but there potentially are many, many others in healthcare and finance and fraud detection, and the list is endless, so the big question is, can IBM simplify that in software to the extent that you don't have to use expensive IBM services to pull this stuff off, and now that's been IBM's business model for years, is lead with services to minimize the complexity, pay us, we'll do it for you, but that's not a great scale model, and I think IBM is really trying to drive scale through software. Right, and then there's a whole another level that came up in the panel last night, which is why are you doing it all in a drop down menu? Eventually you'll be asking, you'll be asking the computer, the computer like you do now for directions with a natural language, so the whole natural language piece of it still has a long way to go, and then again to build on all these inferences, to build in, I think the example came up, what are my sales looking like this month? What are my sales going to look like next year? And to take that type of a verbal trigger into the compute is going to be, the feature is going to be crazy. So today we'll be having a lot of guests from the big data ecosystem, both the Hadoop and Spark ecosystems, some of the management vendors, we've got some other folks coming on, the technologists are coming on, maybe talking about some of the big picture trends that we've touched on here, the future of big data, the viability of the business. So we're going to have some interesting discussions throughout the day, we're going to be here all day today, Wednesday we'll be here as well, on Thursday we're at 37 pillars on 37th street, I think it's 514, 37th street, it's a John Furrier driver from Javits Center, just up 37th street, stop by, we got signs out, say hello, and Jeff and I and Peter Burris and George Gilbert will be going all day long, so appreciate your attention, appreciate you guys watching, you can tweet us, I'm at D. Volante, at theCUBE, check out theCUBE Gems, check out SiliconANGLE.tv for all the videos, John Furrier is actually down at Splunk.conf this week, he's covering that with John Wall, so we got that event going on, and we'll share with you where theCUBE is going to be next, so really appreciate you guys watching, keep right there, we're back with our next guest right after this short break.