is that policy shock impulse response functions are sufficient statistics for policy rule counterfactuals in this class of models that I've described so we think this matters for two reasons one it's a method that we can construct counterfactuals for these systematic changes in policy with making weaker structural assumptions in a deep micro founded model without violating the Lucas critique and then I would argue that our paper has a little bit of a flavor of theory ahead of measurement so for our method it's really valuable to think about the whole dynamic profile of the policy response following an identified shock and so when we go out and identify policy shocks it's really useful to be clear on how persistent the policy shock is and the whole dynamic path and having multiple estimates with different shapes that inform us about deviations from different horizons it would be like a really valuable ingredient to add to our our method so thank you very much thank you very much Alistair in particular for compensating for the clock that started to run a bit late so the discussant Daniel Lewis from University College London and then we go to general discussion thank you and I'm really excited to be discussing a paper which I think has real potential for the way that we evaluate policy options going forward so as Alistair told you already I think the main focus of the paper is really to provide a novel approach to overcoming the Lucas critique so as just a basic refresher the idea behind the Lucas critique is that we can't really use historical relationships that we can typically estimate from the data to draw reliable conclusions about the effects of no shock of interest under any policy rule besides the one that happened to hold in the data that we're using for estimation and the real implication here is that the sorts of semi-structural models like local projections and VARs that we're familiar with using aren't going to be that helpful for allowing us to conduct policy analysis because we think that agents behavior would be different under these alternative policies so the sorts of elasticities that we've estimated in the model aren't really going to be valid so as Alistair already told you the existing literature has kind of had two approaches to dealing with this the first of those has kind of been this Lucas program wherein you kind of start from a completely different standpoint you have to kind of start writing down a fully structural micro-founded model and then you're just trying to use the data to essentially match key moments or match key responses the other approach that I think in some ways is more akin to what we find in this paper is the Sims and Tsar approach which is essentially to attempt to impose counterfactual rules in these sorts of semi-structural models that people may prefer to use in these settings but only essentially imposing them using contemporaneous values of say a monetary policy shock essentially ex-posts so you can't really handle agents' expectations and typically this is taking the form of kind of zeroing out so the example that Alistair gave where essentially trying to perfectly eliminate the output gap so the main idea of the paper is essentially to kind of take this a step further I think and allow for the fact that agents are not going to be surprised by a new policy rule indefinitely they're going to adapt their behavior so you need to be able to impose this sort of policy rule ex-ante so the way that they're going to be able to get around that that problem is instead of just using contemporaneous shocks they're going to use what they refer to as essentially a full menu of news shocks so that they can impose the rules in expectations as well so they're not going to use just the contemporaneous values new, new zero T they're going to have this full series of news shocks the idea is that going to use the impulse responses to such shocks to infer what the impulse responses to a non-policy shock would have been under some counterfactual rule of interest so a similar example to kind of to one of the simple examples Alistair gave in his presentation I think is helpful to understand exactly the mechanics of what's going on here and this is just a simple three equation New Keynesian model that I know you've all seen many times before I think the one kind of key deviation here you'll see in the Taylor rule is instead of just having that contemporaneous monetary policy shock you have this full set of news shocks that Alistair's told you about already and then you have this counterfactual policy rule with this different loading on inflation, this fee tilde and we want to try to figure out how we know how the economy would respond to a cost push shock under this counterfactual rule so given the features of this model we actually have only two relevant horizons which are going to give us just a system of two equations into unknowns the two unknowns here going to be the contemporaneous monetary policy shock and the one period ahead news news shock about monetary policy so you can see it we've is constructed on the left side of this equation at the bottom of the slide is going to be the response of the interest rate to a trio of shocks that cost push shock and then these two new tildes and then the right hand side you're going to have the impulse response of inflation to the same trio of shocks and the idea here is we want to impose the monetary policy rule between impulse responses so you're going to find the values of new such that that counterfactual policy rule holds and when you found those values of new when you hold this system of equations you're simply going to be able to read off the counterfactual impulse responses on both the left hand side of the right hand side for those two objects so that was a very simple simple example but of course they go much more speak much more generally in the paper and as Alice has already told you the really two key assumptions here one is the linearity of the DGP which I think given the sorts of structural models and also the sorts of semi structural models people are familiar with work working with this doesn't seem to be too binding of an assumption the one with maybe a little bit more traction is the idea that policies only affecting private behavior through the instrument itself and kind of eliminating some of these possibilities of signal extraction problems as Alice has already told you so the main result in the paper is going to take a very similar form to what you have just shown you in the simple example and essentially you're going to additionally require invertibility to hold both historically and under the counterfactual rule and if that's the case then using the impulse responses that you're observing in the data estimating in the data and this counterfactual rule that you've written down you're going to have this system of equations potentially in you know up to T horizons that you need to solve where these A-tilders are just the loadings under the counterfactual rule on both X which are the observable variables in the economy and Z which are going to be the policy instruments and I think it's best to think about these results even in this general case is really applying to situations where we're interested in perturbations of policy because we're really thinking about you know about you know just using a system of partial derivatives are underlying all of these identification results so we're not thinking about dramatic changes in policy like maybe adding another condition to the mandate you know we've talked about a lot of other things that central banks could focus on besides their dual mandate over the past couple of days that's not what this paper's for because I think that could lead to an equilibrium or a steady state shift where these sorts of conclusions aren't going to be valid and it's also important to note as Alistair mentioned as well that there's not really a scope for asymmetric information here and I'll talk a little bit more about that later so one thing that I think when I was first reading the paper you know I didn't pick it fully internalized that I again later impacted my understanding is that what the demands of this approach at first might seem to be very very high so that first we need news shocks for the policy instrument which is something that's not always available to begin with but then we actually also need to have news shocks that potentially up to T horizons for the policy instrument so this is a pretty big demand but a key point in the paper that I think is kind of in the version I've read at least is buried in a footnote is that in practice the shocks don't actually need to be news shocks we just need to have linearly independent measures of the contemporaneous shock and I think this was clearer in Alistair's slides today and in practice of course we're not ever going to have this T shock series but we just need some approximating subset of those shocks so the first thing that I want to kind of contribute here is really maybe an alternative way to think about some of these results because the language in the paper and I think the language in the presentation as well is very much focused on the idea of a sequence of news shocks for kind of the purpose of theoretical motivation because I think it's very nice and also just the language is one of having an adequate menu a rule but you can also think about this as an exercise in matching impulse response functions so it's completely equivalent to instead just think about finding the linear combination of the baseline impulse response functions that's going to come closest to aligning the impulse responses on each side of the policy rule or this minimization objective that they use for the approximation which I write on the bottom of the slide here with just slightly different notation to what you saw in Alistair's slides so why might it be useful to think about the problem in terms of impulse responses instead of shock since as I've said that's an entirely equivalent representation well that in this in that case you're going to be able to tie in to an emerging literature on regressions in impulse response space and you can find this in a recent paper in the QGE by Bhanashana Masters and also in a working paper that I have joint with Carol Mertens so the idea of a regression impulse response space is instead of observations you're going to have horizons so essentially you're regressing an impulse response path across multiple horizons on another set of another impulse response path or indeed a set of impulse response paths so the objective function that I wrote down on the previous slide is exactly equivalent to essentially an ordinary least squares regression that I've written here why I'm using little h to denote instead of observations the different horizons of impulse responses so here the coefficient vector is going to be this bold s which in the papers talked about as being the weight on the various shocks but here we're thinking about it as the coefficient vector the linear combination of the impulse responses on the right hand side you're using to align with the left hand side so the problem here is very similar to that covered in my working paper with Carol the main difference being that in our paper we're really considering having the same shock on the left hand side and the right hand side so the implication is that the math is going to be a bit different to think about this setting as opposed to the setting that we consider but I think there's several lessons from this kind of analogy to regression in impulse response space that are potentially useful so first the paper really focuses on the idea of external instruments and these empirical shock measures but I think it's actually going to be possible to apply this with recursive identification schemes or internal instruments as well. Second in terms of inference in the paper they take this Bayesian approach which in a lot of ways is natural considering that they're interested in inference on essentially predicted in this regression I just showed you but in our paper we're able to develop entirely identification robust frequentist inference methods as well that I think would actually carry forward carry out apply in this setting too so there might be an alternative kind of inference framework available but because this is now thought about as a regression problem there's also the question of waiting so the subjective is always used in the paper always used as an implicitly an identity waiting matrix across the horizons but since we're viewing this as a regression problem some horizons might be more informative than others and we might be able to get some efficiency gains in estimating these weights. I think one of the most important things though is how we can actually interpret the approximation error because you can see in some of the impulse responses that Alistair showed you it was clear that some responses are fairly close to what you would see under the counterfactual rule but I think in general we need an interpretable way, an interpretable unit measure to really think about whether we're actually able to have the need to learn something meaningful in some of these applications and because it's a regression problem you can then sort of get analogies to something like an R squared. Also when it comes to using horizons in the settings that we've studied certain horizons particularly when you get further out actually weaken the strength of identification as opposed to adding additional information so it may be possible to think in a similar sort of logic about which horizons you want to include. So in terms of useful applications for this approach I think the most obvious cases are developed very nicely in the paper in the case of monetary policy and in a recent NBR discussion by Valerie Raimi that talked a lot more about fiscal policy as well. I think there's actually a potentially very useful particularly in policy circles here and I know some central bankers who are already applying these methods to good use. So I think the set of applications that are ultimately feasible and kind of useful is going to depend on the shock series that are available and how many we really need in practice. I think for monetary policy there's a plethora of shock series available while as Alice to mention there are a few different measures available for fiscal policy that's much more limited than monetary policy but of course to really understand whether we have enough shocks to learn something meaningful we need to really know how linearly dependent the shocks we have available on that's something that I'm not sure there's kind of a deep understanding of right now although we know in some cases there's very low correlations between certain sets of monetary policy as I mentioned already it will be very helpful to have some ability to have a well-scaled measure of this approximation error to help us interpret which applications we're actually able to come close to this true counterfactual implementation. Another point seeing is we're now taking counterfactual rules very seriously when applying the results in this paper as to what extent historical variation in policy rules in our estimation sample actually matters for the results that we're able to obtain. So if the Federal Reserve changed its policy rule many times during our estimation sample does that affect our ability to learn here? So a final point that I want to continue with is also which shock measures do we want to be using so as Alastair alluded to one of the conceptual challenges here well maybe not a challenge it depends on kind of your stance in this debate is whether you know it makes sense to think about having there be many simultaneously valid monetary policy shock series and this is kind of the whole Sims rude bush debate from several years ago. One alternative to sidestep this issue entirely as I think Alastair started to mention with the GSS paper is to think about using internally consistent multi-dimensional shock series and a particularly prominent example is the recent Swanson's set of three monetary policy shocks. But as we've talked about asymmetric information in these signal extraction problems I think we want to be particularly careful not to be using shock series that are actually contaminated by central bank information. In fact we've learned a lot from Peter's recent paper with Merrick Jerozinski about this. So this is going to be an issue with a lot of the shock series that some people like to use in practice for example the Nakamura and Steinsen shock series which are becoming increasingly popular and maybe an issue with some of the shocks like Swanson's as well. So another solution to this can be found in recent work by Merrick Jerozinski and in one of my working papers as well where we're essentially able to go after the same trio of shocks as in the Swanson paper while separately identifying a central bank information shock which then can be purged out. So I still know there's some ambiguity about I guess even if we're able to separate the central bank information shock out and not use that you have central bank information affecting the instrumentation is always still going to be able to apply this technique if the central bank information present in the economy. That's something I'm not entirely clear on but these are certainly issues to be aware of. So overall I think this is going to be a very helpful alternative solution to the Lucas critique without having to use a structural model provided we're just dealing with kind of perturbations of the current policy rule. And the information requirements here quite helpfully and not quite as demanding as there may appear at first glance but we need to do some more work to actually assess the true quality of some of these approximations setting by setting and I think the one step can potentially benefit from this analogy to regression impulse response space and finally as I've just mentioned we need to think carefully about which shocks we want to use in practice but overall I think a very nice paper and one that will have great implications going forward. Thank you very much Daniel and marvellously and on time as well. Thank you so much. So I think we should first give an opportunity to Alistair maybe to respond quickly to some of the points. Well thank you very much for a very good question. I totally agree with everything he said. You know I view our paper as really a theory paper. It looks like it's some econometrics paper or something but it really it's a theory paper and we're trying to say what is it that we need to know to construct a policy counterfactual that's robust to the Lucas critique and exactly how you going to implement this idea there's a lot of choices to make and I think phrasing it in terms of regression and impulse response space probably is a more intuitive way to describe the actual method I think that our challenge in this paper is convincing people that this is okay and so that's really like the main focus that we're trying to communicate and then there's a lot of work to do in terms of exactly what's the best way to implement it so thank you Welcome so we can open the floor why not Partosh at the start and the others who are not so known maybe state your name and affiliation before you speak okay thank you I like the paper a lot I want to ask about the following so you you said that a situation in which your method does not apply is when private agents are solving a signal extraction problem now and I remember from the Simpson's job paper that they actually use this case as one way to motivate their approach they say in most situations in reality private agents or when the central bank announces a new policy rule private agents are not going to be 100% certain that that's the rule that's going to be followed from now onwards they will be solving some kind of a signal extraction problem so they will be observing the path of the policy rate and they will not be sure if it's the coefficient on inflation in the Taylor rule that's changed or if it's an innovation in the old Taylor rule that the central bank has been following so therefore it's okay to look to assume that private agents are that it's actually an innovation in the old Taylor rule we as econometricians are not going to be making a very big mistake when private agents are solving the signal extraction problem so I just wanted to get your it seems like something they used in part to motivate their approach you say would rule out using your approach so the let me make it very simple and kind of get rid of the signal extraction issue in the discussion that you kind of referred to so Sims has a view of the relevance of the Lucas critique that is exactly that you described that there's many times when the policy institution would take an action that is sort of a normal FOMC meeting it's not a whole review of the framework it's just this meeting they have to do something next meeting nobody knows exactly what that's going to be and so there's some kind of innovation to policy and and he argues that if we for those purposes using sort of standard reduced form methods would be totally suitable and then the you know the Lucas critique side sergeant and Sims are saying we're talking about a systematic change in policy that's announced everyone knows it and I think you know that's how I would characterize it that I think people are on the same page that for some innovations to policy it is appropriate to treat it more like a shock but for some innovations to policy say the 2020 framework framework review that the Federal Reserve did it was sort of big announced this is a change kind of event um that is not just a normal policy shock and so the sort of structural solutions that we come up with fit more you know in the sort of traditional approach Christiana about Evans type of approach you know those are solving for the framework review type of policy change um and so it's sort of you know the use cases of those methods that we're going to compete with if you will Miquela Denzal I also like about this paper I have two questions the first one is more a clarification so just to make sure that I understood so for your method of work you do need to know at least the current policy rule so the policy rule that it's followed in this moment by the central bank otherwise you cannot write those minimizations no no that fortunately we don't need to know that because there would be no way of summarizing like a policy rule for existing policy institutions what we need to be able to write down is the alternative policy the counterfactual rule because we need to know what we're solving for but you don't need to you don't need to be able to summarize the existing rule in any simple way and thanks and the second one is about the type of shocks that you would ideally choose for this method so is it a requirement that the shock is as an effect on the policy instrument for example if I take the three shocks that Denial was talking about this Gorkinak-Sackens-Wunzon shock which by the way have been also derived for the euro area and they are available in the database on the ECB website so the third shock is a QE shock and this actually meant not to change the short-term interest rate so that shock would not apply I guess for your method so you would only look at the short-term interest rate and the forward guidance shock well I would think that if if QE is relevant to the private sector then it's going to have you know it's part of the policy setting that the private sector cares about and you would need to think about policy is not just interest rate policy but also balance sheet policy and then that shock would be relevant you know in my examples I assumed it was just nominal rates that mattered but you know if the premise I guess of the question is that balance sheet policy also matters and then I think you could potentially expand the definition of the policy instrument to also include measures of balance sheet policy and use that shock too so I think that's the point behind. Morton, Robin. Two questions. One is something that Daniel mentioned as well the extent to which you could use like if there were instances where we knew there was a change in the rule the extent to which you could use those as sex or information the other one okay yeah this just I'm not sure about your method but when you do the counterfactuals they have to be I guess under the under the maintainer assumption of having a unique equilibrium is there any way of checking that like it seemed to me that that might not be so easy to check without knowing the full structural model so I mean I could see this would be very tempting for a policy institution like let's do this alternative it looks great but you know maybe under that alternative many other equilibrium. So on the the first question so if you knew the dates when the policy rule changed then that would be very useful and that would provide extra variation in the data that you could use to learn about the effects of policy if you're not sure of the dates I think that complicates things I think you would have to empirically try to infer these breakpoints so I think in some sense variation in the historical period in the policy rule probably is helpful but does lead to complications on the uniqueness question I think just from writing down you know the assumptions that I've stated it's hard to say exactly when you know your counterfactual rule will lead to uniqueness or not so I think the way I would approach that is I would think about this class of models structural models that I'm contemplating and I would and I would want to think about policy counterfactual rules that I had a high degree of confidence that in many of these models in this class we're going to lead to unique equilibria and that's how I would assess that question. There's another question by Francesco Lippi Francesco Lippi so I'm not sure I got 100% of the paper it looks super interesting so your first example where you were looking for the flat rule and you sort of gave an intuition that was very clear and it kind of suggests you know you have some linear system and you can play around with this thing so so I guess the linearity makes the intuition very clear but also suggests that results are going to be accurate up to like the second order terms so is this like is there a way to think about what you're doing like an expansion for small changes to the policy rule something has to be small for the linearity to remain valid in which dimension exactly is this is this like small perturbation like the discussion was suggesting with respect to the rule parameters so the way I would think about this is we have a good sense from working with structural models of when linearity is going to be an appropriate solution method and when it's going to be less appropriate and I would use that intuition that we have from years of working with structural models to think about when assuming that the structure of the economy is linear is relevant to this method and so for me the way I would sort of summarize that is we have some dynamics of the economy if we're going to make major changes in those dynamics then we're going to probably be getting away from linearity so I wouldn't really think about the coefficients in the rule so much as just the stochastic process that the economy is going to follow under the counterfactual I want to add one thing so that the one area that maybe is relevant to certain applications where we could allow for non-linearity is in non-linear constraints on the policy instrument like a ZLB constraint so in many structural solution methods in solving ZLB problems they're sort of a quasi-perfect foresight element to that where people are not really thinking about risk in the way they think about the future evolution of the economy so if you're willing to sort of take that perspective on the solution method then you can impose a constraint on the policy instrument just in you know I'm solving for these hypothetical news that are making this counterfactual hold we just add to that problem there's a constraint that the counterfactual nominal rate can't go negative and that would work we are close to lunch there's another question I see but I can't resist the temptation to go to you said that you see yourself your contribution is theoretical in the first place but you mentioned already the lower bound now and the non-linearity issue and the strategic reviews that both the FAD and the ECB have conducted recently so I can't resist still the question to ask you to illustrate because one thing is to convince the theorists in the room the methodologists to accept this methodology another is to make the us central bankers apply it to look at you know how shocks propagate after major policy changes like rule changes so and obviously the most obviously are these strategic reviews could you illustrate like what we can learn from what you did for how to look at how the economy behaves after our strategic reviews the FAD one which did a form of average inflation targeting as a result and ours which maybe was a bit more on the side of an asymmetric reaction function with some smoothing and so on so I would just say one thing I think but if you pushed me to say what is the most relevant thing that you can take away here for how to think about policy it's that figure that I showed with the output gap targeting where it wasn't perfect you know using a method like this really encodes what the data say says about how the transmission mechanism works that's really grounded in data and speaks to what policy can and cannot do and structural models will sometimes imply that policy can do things that the data don't actually confirm thank you there was one more I mean we are out of time but I'm willing to take one more is it Peter? was it you? okay there's another one it's a very short question following up on Morton who was saying about equilibrium issues so what would happen if you enter an explosive monetary policy rule there say a Taylor rule with a coefficient of inflation smaller than one I guess you would run in sort of an inevitability issue right would you notice that? well so with these methods what you are going to recover is what sometimes called the minimum state variable solution so encoded in the method is some sense that ultimately we're going back to steady state and then we can work backwards from there so let me give you a very concrete example we can solve the problem of like a zero policy response to the cost per shock we know that in a structural model that's going to lead to indeterminacy so what the model is going to give you or the method is going to give you is going to say suppose the policy maker announced for this shock we're not doing anything but for any off equilibrium thoughts about explosive inflation we're going to respond strongly that's what you're going to get out we have a long lunch break so I'm willing to take two or three no because I then okay there's one from here okay so we should stop I'm so sorry so thank you very much to both the discussant and presenter for this and we see each other at 2.15 again for the next session where we go from changes in policy to uncertainty and counterfactual to uncertainty and consumption behavior and the lunch for the speakers will be served in our dining area so please join one of my colleagues or myself, Luke Levin or Peter Karadi or Bartosz Makovic one of the organizers those of you who don't know where it is yet to find their way thank you again you had this panelist now okay get on one, two, three hello could you hear me that's the tone we'll go to the stage please my picture is coming one, two, three one, two, three hi you get a good audio signal from me yes, that's great okay, all right we only need someone who can you go to the stage and talk on the stage I'll turn on the speaker yes please one, two, three, five, six, seven Chris do you hear me do you have your boxes loud do you have to make it louder yes, I hear you I hear you too please add the audio one, two one, two one, two, three, four, five six, seven, eight, nine, ten one, two, three, four, five Chris do you hear me thank you welcome back to the second part of our session over lunch today so we had before lunch a paper about what happens to the macroeconomy when policy rules change monetary policy rules for example and how we can think about it in terms of counterfactuals and how the economy evolves and now we will address another aspect of change and uncertainty which is the question of how consumers react to increases in uncertain environment as you can imagine in the context in which we are at present here in Europe but not only in Europe this is an absolutely central question not only for science but also for policy with the events that we all observe observe around us the only issue is that so shortly after lunch I believe it's not our primary problem but okay let's look beyond lunch so I'm joined on the podium by Dimitri Georgarakis from the ECB and Jean-Ran Koumore from Sciences Po in Paris and I would without much further do give the floor to you Dimitri thank you very much Phil and many thanks to the organizers for including the paper I'm going to talk about the effects of macroeconomic uncertainty on household spending this joint work with Oli Koybion, Yuri Goronichenko my ECB colleague Jeff Kehney and Michael Weber and of course the use of disclaimer applies so the idea that high uncertainty induces households to spend less and firms to reduce their investment and employment is a quite intuitive one and is generally present in policy discussions especially during crisis times as for example you can see this quote here from Christina Romer that dates back to the great recession in the US we are recognized of course for revealing volatility at the time and as she stressed the resulting uncertainty has almost surely contributed to a decline in household spending in his review of the literature Nick Bloom has emphasized that the empirical evidence on economic agents behavior is at best suggestive and as Nick highlights more empirical work is very valuable particularly work which can identify clear causal relationships so in case you wonder why it is so challenging to establish a clear causal link that runs from uncertainty to economic agents behavior for these there are at least three factors they are confounding aggregate factors like pandemics, revolutions natural disasters that are typically present during periods of elevated uncertainty this makes hard to identify and isolate the effect of interest if you look at a more micro level there are correlations with time varying household and observables you could think for example like time varying optimism or agents outlook about the economic prospects which makes again very hard to identify credibly the causal effect of interest even if you use panel fixed effects models and in addition separately identifying the effects of expectations about first and second moments is again tricky because generally large uncertainty events are also associated with significant deteriorations in the expected economic outlook so against this background the present paper designs and implements a randomized control trial using a new euro area household serving so via this experimental approach we induce exogenous variation to household expectations their first moment and uncertainty their second moment about future economic growth in the euro area and utilizing this exogenous variation we can estimate the causal effect of uncertainty that is the second moment net of first moment's expectations on household's spending on both as you will see non-durable and durable goods and this is the main focus of interest for the paper but also we take a look on how uncertainty can affect household's propensity to assume a higher financial risk. Given that we use micro level data we are able to also estimate the so-called heterogeneous treatment effects that means we can estimate the effects of uncertainty into subgroups of households that are of interest. Let me give you a quick preview of our findings basically we find that uncertainty reduces net of first moment expectations the spending of households on non-durable and some larger ticket items that higher micro uncertainty also reduce household's propensity to assume financial risk especially by choosing to be less exposed to mutual funds and in addition we have to say something about the possible channels that work so one of your channel via which uncertainty about the macroeconomy can transmit it on household's behavior is via uncertainty about own income expectations. We saw that this is one channel at work but it is not the only one so there are also other channels at work that we cannot tell apart each of them but we consider them so together so for example expectation about taxes real and financial asset prices or even more generally households use about the government quality and as regards heterogeneity we also identify some heterogeneous treatment effects we see that consumption tends to be more responsive in response to macroeconomic uncertainty especially among households working in riskier sectors and also households that have included in their portfolios risky financial assets as they are more exposed to stock market risk. So the data we use come from the new ECB's consumer expectation survey this is an internet panel that started in its pilot phase in January 2020 ran initially across the six largest euro area countries since January 21 the survey has been expanded in five more euro area countries covering basically every month a very large sample of 19,000 households the sample is a mixed probabilistic sample where responses are recruited via random dialing can non probabilistic segment that basically recruitment takes place by existing online panels and sample weight serves there to make the samples representative of the underlying national populations. As the name suggests of the survey we interview house about various expectations not only inflation but also their expectations and perceptions about other macro endiosecratic variables and importantly we also ask houses about their behavior every quarter we collect data on their consumption on a number of non durable items that they bought over the past one month. And the survey features a mixed frequency modular approach where we ask questions at different frequencies to the houses of course a nice feature is its panel dimension where you can link respondents across time. Back in September 2020 we fielded a 10 minute special purpose survey following the regular monthly wave and as you will see also we utilize data from other waves close to September 2020 but in this special purpose we are able to field our randomized control trial and in subsequent waves we can measure also household behaviors and as I said we can link this via the panel structure of the survey. In case you are interested in finding more perhaps you can take a look at this reference also recently we have developed a nice web page where we provide a lot of information and we update every month the information about the survey. So let me walk you through the steps we take in order to field this randomized control trial. First we take the entire sample and we ask respondents questions in order to elicit their first and second expectations about GDP growth in the euro area. Subsequently we randomly split the sample into subsamples one set of groups the so called information treatments they receive information that I will show you in a second about actual numbers referring to the GDP growth while there is also a control group that you can think of this is akin to these placebo groups in medical trials that receives no information. After this information provision stage we get back again to house and we elicit once more their first and second moment expectations as regards to the euro area GDP growth and we see whether the information treatments we provided them with make a difference so move their posterior basically and via the panel structure of the survey subsequent waves we can also track and assess whether there are deviations between the treatment and control group in the actual consumption behavior. So now let me across the steps one by one so initially we ask a relatively simple question to households in order to elicit their first and second moment expectation. So we ask them to give their best guess about the lowest growth rate that is your prediction for the most pessimistic scenario for the euro area growth rate over the next 12 months and the highest growth rate that people expect for their most optimistic predictions. Just based on these two numbers they report you can assume a symmetric triangular distribution that basically attaches progressively lower weight to this reported extrema but importantly allow to deduce first and second moments with respect to these expectations on for each household. In addition we ask that allow to fit a more kind of realistic if you like a split triangular distribution about the probabilities for each of these two scenarios. So basically if you see these statistics from using the road date out of these answers as I said what is important is that for each single household we are able to estimate both their first and second moments of large euro area GDP growth. On the left hand side you see the distribution of answers by countries and from the overall sample with the black line that are symmetric around 3-4%. And on the right hand side you can see their uncertainty that is more skewn so you see there are people that some people that perceive high uncertainty as regards euro area GDP growth. As I said an advantage of this design is that you have for each single household both moments so you can graph the one versus the other from the road data so this is scatterplot graphing this association that shows this usate that basically suggests that among those who either expect very high growth or they are very pessimistic about growth prospects those two groups also hold higher levels of uncertainty. So following this pre-treatment stage where we listed households prior we randomly split the sample and we go to each treatment group and we provide the following piece of info. So the first treatment group receives this information so that the average prediction among professionals for a casters is that the euro area economy will grow at a rate of 1% and the qualitative statement in support of this that says that by historical standards this is a strong growth. Instead the second treatment group receives the following issue the following information this profession for a casters are uncertain about economic growth in the euro area in 2021 with the difference between the most optimistic and the most pessimistic predictions being 4.8% points again that by historical standards this is a big problem. So clearly these aims to move more the second than the first expectation moments in expectations and a third treatment group receives information on both. We experimented with the fourth treatment group receiving information about disagreement professionals for a casters about foreign countries growth but this didn't prove to be very influential so we can't use it in the analysis. So following this information provision stage we need to go back to households and ask them again at least it again first and second moment expectations but generally when you design surveys it is prescribed to avoid using exactly the same wording when you ask a specific concept to respondents because otherwise you typically know them a lot. So what we did is again we elicit first and second moments but here using a different question that has been used in the literature where people have to assign probabilities over three scenarios for the prospects of euro area GDP growth. So basically the differences in design between the pre-treatment and this question will be absorbed by the control group. So do people update their first and second moment expectations after receiving information? The answer first is yes. On the left panel you see how they update their average expectations after receiving the treatment so basically comparing priors with posteriors you see that particularly those groups that receive information about the point forecast they update towards the signal they receive so those who hold very high expectations priors initially they reduce their priors about growth while those with very low ones they increase them. As regards uncertainty because there was high initial uncertainty in the sample our treatments for most households reduce the perceived uncertainty but what is really important here is that our different treatments induce different relative changes in the first and second moments. This gives us enough power in order to identify the effect of interest in the same regression so to identify separately the effects of second moments net of the first moments. And as I said in follow up months we are able to measure behavior so for example in October people report with respect to these bundles of goods how much weather and how much they bought over the previous month and this nicely aligns with the time they basically received information just in the previous month. And also we have information back then only on the extensive margin of whether people purchased some bigger ticket items more durable items like car, durable holiday and luxury goods. So this is the main equation we estimate so basically if you think of non-durables these are reduced form consumption regression where we regress log spending on the two endogenous variables of interest so the first and the second moment about your area GDP growth plus some controls to reduce the noise. Of course these two variables are endogenous and we use our instruments to instrument for each of them so via IV we can estimate the effect of both of each of them on consumption. So these are the results from the baseline regression basically you see at the first row and the first column the first two consumption adjustments just one month following our formation treatment so what people report in October and in the second column four months after the information experiment with what people report in January 2021. And you see what really matters is uncertainty and the underlying effects are relatively large so this tells you that one percentile's point decrease in the measure of uncertainty that is roughly about one standard deviation of the sectional distribution post treatment reduces by 3.443 percent the spending on non-durable just in one month later on and the effect seems to be pretty persistent although a bit less precisely estimated four months later and you can see from the F statistics at the bottom first and second states that the instruments were successful in giving us enough power for micro data to identify separately the effect of interest. We have a number of robustness checks in a recently revised version of the paper you can see here some panels with additional set of results for example if you use pre-treatment this more realistic distribution in measure the two moments the effects are if anything even stronger if we use as a first stage log of uncertainty instead of levels the effects again are similar also quantitatively similar and another consideration is to control for skewness because by eliciting this individual specific distribution in principle you can also have a third moment so you can calculate a measure of skewness we do so post-treatment so we control for this measure of skewness by construction this is endogenous we don't have enough instruments to have three endogenous variables estimated simultaneously in the same regression but still our IV approach goes through and clearly suggests that if you include skewness the results are broadly the same basically another thing we are doing for consumption is we look at budget shares or whether people in response to these exogenous changes in their perceived uncertainty they adjust more certain goods than the others generally the adjustment seems to be broad based most categories we find there some small difference for categories that are more discretionary nature like say recreational activities but these broad based results suggest that the primary reason for this adjustment seems to be precautionary saving now we like also to say something more about the underlying channels so how macro uncertainty by which channels transmits to households affects their perceptions and then in turn affects their behaviour so one obvious channel by which this can operate is about households own income uncertainty unfortunately in the survey every month we measure both first and second moments about households perceptions about their future income but other channels could be like expectors about future interest rates or taxes or even more broadly government quality or expectations about real and financial asset prices we cannot tell apart each of them what we can do is we can quantify the importance of personal income growth we do some robustness there that I don't have the time to explain in detail but the main finding is that the effects do not operate solely by expectations of own income growth so income growth and uncertainty about own income growth is indeed a channel by which macro uncertainty can transmit to household spending but it's not the only channel so then we conjecture that a number of other possible channels that I list above are also likely at work another thing we are doing again in examining the effects of uncertainty on household consumption is to look at the extensive margins so whether households bought or not major items larger ticket items that are of more durable nature and every month in the survey we ask indeed whether people bought over the previous month house, durable cars, holiday packages or luxury goods we also know from the data their plans of houses to buy goods over the next 12 months so conditioning for this the effect we estimate is more like a surprise effect of the exogenously moved macro uncertainty on spending and we find especially with regards to the last two categories so holiday packages and luxury goods some economically sizable statistically significant negative effects of higher perceived uncertainty these effects were just estimated next month so the effects tend to fade four months after the treatment so for the durable goods this might be more consistent with some that have this way emphasize this wait and see channel the second margin although it's not the main focus of the paper that we look at regards post treatment behavior in financial investing as we know households are typically quite inert so they very sluggish and generally they don't resupply their portfolios they tend to stay with the same mixture of assets over very long periods in time so it would have been challenging to identify this through the data even if we had to use many panel follow up waves so what we did instead was to ask households after receiving the formation treatments to think that they have received a windfall of 10k in this case how they would invest in several financial asset categories so we ask them to allocate across this 10k across the these categories that you see on the slide and there we can see whether they indeed are willing to assume more financial risk after receiving this information treatment and these are the budget shares that would allocate out of this 10k windfall on different assets conditioning on their actual share of investments that we had already asked one month before fielding our formation treatment that was basically in August 2020 and you see that we find sizeable effects especially as regards the effect of uncertainty or reducing exposure in mutual funds which is a kind of standard way via which households hold stocks an indirect way holding stocks and the last piece of evidence regards the heterogeneity that we like to look at more closely across various groups of interests so one first split we try is we we split house across those working in high risk sectors that were affected by the pandemic low risk sectors that were less affected and retired that are typically worry less about their future streams of income and when we do this you see results in the first three columns we see that the effect of uncertainty mainly operates among households that work in risky in high risk sectors another split we are doing is to split houses between those that hold only safe assets in their portfolios and those that include at least some risky financial assets so they are more exposed to stock market risk and when we do this it's the last two columns you see in column 4 those houses that do hold they do have some exposure to stock market risk the effect of uncertainty on reducing spending operates mainly through this for this group of households so let me conclude as you saw we used a randomized control trial an approach that becomes increasingly popular in microeconomic research using recent advancements in household and firm services to address empirical challenges in identifying the causal effect of macro uncertainty on household behavior we find that elevated macro uncertainty strongly reduces consumer spending both on non-durables but also selected durable goods and the effect seems also in some specifications to persist over time at the same time it looks like it reduces houses from capacity to invest in risky financial assets and as I said an advantage of using micro data is that you can really look closer into certain groups of interest so we find some plausible heterogeneous effects by sector of employment and portfolios riskiness and this is my last slide in fighting with repercussions of the great depression President Roosevelt had famously said that the only thing we have to fear is fear itself. Recessions are characterized by increased macro uncertainty and thus an economic recovery may require as we partly argue in the paper management of expectations assurances by policy makers pretty much like the assurances that President Roosevelt gave at the time a provision of stronger safety nets and policies targeting the more vulnerable groups like groups in sectors that have been greatly affected during the pandemic as we showed. Thank you very much and I'm looking forward to the discussion. Indeed Jean Coman is a discussant and needless to say as you realize Dimitri is a very very prolific researcher in this field with randomized controlled trials and the exploitation of these surveys for highly significant questions for central banks are really a powerhouse with his co-authors of research in this field but we will hear more from Jean. Yes so thanks a lot for the organizers to ask me to discuss this paper it's a great paper so the main question it's a very straightforward paper with one main question that throughout the paper they go after and this main question is how does the uncertainty about future income in the case future macroeconomic uncertainty affect people's consumption so they mainly frame it in terms of literature about the effect of macro uncertainty and so evolution of maybe saving over time along the business cycle I think the result are so as this is such an important question that the authors result could also speak to other literatures and just trying to measure uncertainty at the macro level but also household finance literature is a precautionary saving some paper looking about the phenomenon saving on a rainy day so when the world is very bad you actually keep saving why and one suggestion is exactly this effect of uncertainty because the correlation between the first moment so average GDP is really low but also lots of uncertainties so people do save even though it is a rainy day and so the results would validate at least qualitatively this channel switch again we lack causal evidence of that in the household finance literature as well so overall I think it's a very important question so paper is really straightforward and the point that you're trying to make is very clear and they've got these methodologies that is really we are looking for causal relationships so let's do an RCT and let's try to establish this causal relationship so what they do more precisely is build this RCT in which they expose some respondents to different pieces of information about professional forecast of growth in the Euro area over the next 12 months and they do that in September 2020 the information they give is a mean professional professional forecast and the maximum differences between the forecasters from this in the surveys also elicit people's distribution of growth in the Euro area and they show that this treatment so giving people information actually do affect their own perception of the first and second order effect on the distribution individual level distribution of growth in the Euro area so the treatment does work in the sense that it does change people's prediction of growth in the Euro area and so they've got an exhaustion variation that they can use to estimate the effect of the first and second order moment of the distribution of expected growth in the Euro area on people's spending what do they find that a one point decrease in uncertainty about growth in the Euro area over the next 12 months raises monthly non durable spending by 3% in some other specification they find up to 5% it's more so among people in the sectors that were more exposed to COVID the uncertainty also affects the composition of spending with some goods being more prominent in the consumption basket and a decrease in uncertainty raises spending on durables and investment in mutual funds and crypto so it's a pretty consistent story that and that's why I find the paper great now I'm going to make a few comments these are more just things I would like to see maybe discussed a bit more in the paper but I find the paper very clear and very important so the first thing is what is uncertainty you've got this number going from 0 to 15 but so uncertainty is a one standard deviation in this individual level distribution of expected growth in the Euro area in the next 12 months and I computed that for instance to have an uncertainty of one if so these distributions are based on the people reporting the lowest and highest forecast of possible growth in the Euro area and if people have sort of symmetric symmetric distribution and uncertainty of one would mean a 5% difference between the lowest and the highest and uncertainty of four would mean a 10% difference between the lowest worst case scenario and the highest possible growth that you expect so I think maybe giving a bit more content to this number could be interesting and then my point is that on this channel you see that the implied mean actually very you see very large number here so it goes from minus 20 20 minus 15 minus 10 and above 15, 20, 10 and so one question that I want to raise and you see that uncertainty is really high above 2.5 but for those people with more extreme predictions about the growth rate in the Euro area so would that be possible that people with very large uncertainty actually have no real idea what the growth rate has been what would be a normal number to give for the growth rate and so before the prior uncertainty is really large because they have a bit no idea what it could be and then you treat them so you give them some sort of anchoring or reference point and then their uncertainty changes because they didn't know before what could be growth in the Euro what would be a normal number for that and this could explain possibly why you know you find that when you form people so the authors find that when they form people even about the average growth which would be I think 5.6% these changes people's prediction about the uncertainty and this is based from lowest highest etc so probably even by giving them just a number so an average nothing about the uncertainty the disagreement between forecaster is still going to change people uncertainty their own forecast so this could be the case if the mechanism is that you sort of give people a reference point it could also explain why you find this strange but small effect that decreasing the mean expected growth actually comes with an increasing consumption holding uncertainty constant and this would be the case if again the main treatment is to sort of reassure people that things are not going to be crazy it's probably not going to be minus 20% it's probably not going to be 30% so by giving this sort of reassuring message people at the same time raise their consumption and also get towards more normal expectations of growth rate or closer to what the professional forecaster have the second question is about the comment choice of the instrument so I think the usefulness of the instrument is to remove any correlation between consumption and uncertainty that would be coming from characteristics affecting both consumption and uncertainty so if I write it in this very very simple way C here stands for consumption U for uncertainty C would be a linear function of uncertainty plus some demographics then and uncertainty would be like some random variable C here plus the effect of demographics and you see that if you just regress uncertainty of a consumption they get a bias because you're going to get the effect and just a correlation between people's characteristics when you've got an exogenous treatment it's a really nice thing is that now you get an exogenous variation, treat here and so if you look at the effect of this treatment on consumption if the treatment does affect uncertainty correctly captures the alpha without the bias now what I was surprised when I read your paper but maybe there's a very good way to do that is that your instrument is not just a treatment but the treatment interacted with the prior and my belief is that maybe the prior capture a bit some demographic characteristics people with a very high prior may have different level of education, different jobs and other people and if that's the case because you're doing this type of instrumentation maybe you know it's coming back by the window this effect of demographics and maybe you're capturing in part a covariance between the reason why people spend more in September 2022 which is due to the demographics and the fact that they respond a lot to the treatment which is due to the demographics so you do control when you do this regression it's not just directly the effect of uncertainty on consumption with the treatment you also control linearly for then so this would partly disappear unless that affects consumption non-linearly in which case I think the bias would come back like it could be there and so trying to think about the situation in which this might be a problem is that if people who have high prior uncertainty also have a high spending in September because a high prior uncertainty in what the artist find associated with also a high effect of the treatment like those with a really high prior uncertainty are those who reduced their uncertainty following the treatment and I was thinking maybe a test with that would be to do a placebo look at the effect of if we see exactly the same procedure look at spending in August 2020 and if you don't find any effect it's good and you're sure that your treatment with which creates the response on that so it's a bit of a related comment you find that the positive effect of prior uncertainty on spending so this is really great I think because what the artist find is that the exogenous part of uncertainty so when that is actually coming from the treatment it does affect spending negatively while the prior uncertainty affects spending positively so this validates the choice of an exogenous variation we do need an exogenous variation because otherwise you're going to get the two go opposite way so you do need your instrument so I think you can emphasize a bit that maybe more but also like this is a bit consistent with this comment that people who have a high uncertainty also save more the last comment is that so that's the timing of the take-up so I try to educate myself a bit about this survey and what I understood is that the treatment is added to the survey and apparently but maybe I'm not a you're the expert here there's a window that is opened for them to take the survey from the first Thursday of the month until some point later on and then they can take up the survey at any point during this window and so it might be that in what apparently 70% of the responses are usually completed within the first 10 days of the data collection period in September 2020 the window started on September on the 3rd of September this means that 70% of the people were treated between the 13th and the 30th but also that 30% of the people were treated quite late so they're looking at the effect of the treatment on the whole spending of September while half of the 30% of the people were only actually could have changed the spending because of the treatment only after half of the month so maybe you could use this sort of margin of when people were treated exactly during the month of September to check whether the effect is stronger for those who took the survey on their own which should be the case because they could adjust the spending a little more to their reduced uncertainty so that's these are my comments, thanks a lot for having me discuss the paper it's a great paper Thank you, John take following usual practice you have any answers to or you want to answer a little bit Thanks a lot John, indeed very thoughtful discussion paying attention in many details we need also to take probably again a look this is a longer project we have tried several things, several robustness so some of the things you have may seem to have tried but probably forgot to include in this version as robustness one thing I would like to be absolutely clear is how do we measure uncertainty so it is prescribed by Czakmanski to when you measure in expectation service not just to ask about only 0.4 because people have different underlying distributions so just reporting that I expect inflation to be 2% and you report the same this can be quite different due to underlying distributions and we need to measure this and these questions we use are particularly designed for this so when we measure uncertainty we need to apply formula where for each of these type of questions we calculate an individual specific measure of uncertainty and then we assume not to understand the deviation of this but a unit change of this to see the effect of interest it's not the standard deviation that we vary there so so as regards possible outliers we know there's a lot of noise in this data often you need to filter out to have tried also Hubert robust regressions that's lower weight to outliers so the negative effect we find in the first baseline regression about the first baseline is despite being significant 10% we also comment on its quantitative importance it's really trivial so we think it's more noise yes we need to explain a bit more the IV strategy because indeed we interact with priors but note that the priors are orthogonal to the rudimentization so to the experiment so this is not a priori but what you can do in order also to be statistically say waterproof is to to report and have done this and there the evidence is clear over over ideas so you can test for over ID and you see that we clearly fail to reject the now there because there you can use the as instruments only the dummies of the treatments which are of course you of course you trust but also great suggestion about running a kind of backward looking placebo actually we did it because in August we don't collect data on construction we collect in July though and we did that of course we didn't report that great suggestion now for late respondents yes we can look a bit more to make but generally late respondents are always late respondents also we do some other filtering for people are speeders so take the survey in a very fast manner so we also check this but thank you very much again for all these points well taken okay now we open the floor so if you have any questions before I take the first question I just want to ask to my colleagues in the back I have a question on Slido but it is from 5 to 3 so I'm precious from the last session so I won't take it until you tell me that that is actually for this session from last session okay good so floor is open for questions if you want to structure your thoughts I can ask my first own first question if you need some time for the heavy lunch so I wanted to follow up where Jan actually started a little bit maybe for those of us who are not actively researching in this literature you could juxtapose your result about the size of the fact the economic significance of the fact with the macro or other literatures that may use different approaches to measuring uncertainty and to identifying the effect of uncertainty on consumption maybe put your number of these 3-4 percentage points into perspective with that literature that will be very helpful I think for some of us yeah that's a very good point thanks so generally you know for those working with micro data this is a very big effect but also if you kind of aggregate it it's a kind of huge effect because it affects non durable spending you know just the one month afterwards of course you know this effect is conditional on what kind of change you assume in the underlying uncertainty so this is straightforward to read if you assume one percentage point assumed increase in uncertainty that corresponds to as I said roughly one standard deviation of the cross section distribution post treatment but if you go to the raw data and you see actually after receiving our formation treatments how much people on average change their level of uncertainty and you apply these which is exactly what raw data tell you you find an adjustment in the following month of non durable spending of the order of about 0.7 to 0.8 which again because it's monthly so it's again a very sizable effect so there seems to be a very sizable effect on non durable spending that it looks also that persists sometime until consumption in December that is reported in January 2021 and also in some of the durable goods with extensive margin again by the standards of the literature these are very sizable effects in the in a recently revised version we have done also some back to the envelope calculation to contrast versus macro figures this comes with many assumptions but it is broadly consistent with what you get also from the macro literature thank you don't be shy here we go Morten I have a hard time formulating this question in my head I'm thinking at the point when you ask about actual consumption that of course people are also hit by actual shocks in between so I'm wondering whether the lack of the impact of the mean that's because that matters less than the actual shock you are hit with because I'm not hit with an actual shock on certainties that may have a bigger impact thanks so indeed in between you can have many shocks that people face right and of course the longer the horizon over which you look at the more likely this is to happen but what is really crucial here for the validity of the experiment is the and allocation across control and treatment groups this tells you this ensures you actually that the shocks that people will receive they have equal probability to receive them either being in any of the treatment groups or being in the control group as a result whatever deviation systematic deviation you identify in their behavior comes from basically the information provision that you did in this way so the nice feature about this randomized control tries exactly this we know and we are aware that in this data there is a lot of also measurement error right but also by kind of similar arguments measurement error can be dealt with via this because for example people who are more prone this is self reported spending people who are more prone to misreporting spending they are probably likely to be present in each of the treatment and the control group so you always estimate with a control group okay so I understand the answer you gave but if the actual shock if that was big enough I guess that could wash out the effect on the first moment of the expectation no if there was in between a very big so might but you know back then I think actually an advantage of the paper that that we are able to fill the information experiment and then based on a different survey that is just one month after people report their spending and this very nicely aligns because they report their spending with respect to the past 30 days that is exactly they count these days started counting from the time they receive the information so they are actually following this so as far as I recall back in October 2020 there was no kind of major shock of this kind Alistair so there is a very large literature that has a lot of trouble finding effects on expectations of any form and response to shocks obviously using a very different methodology and design to what you are using here but here you are finding effects not just on expectations you are finding these effects that filter through to consumption as well so you is kind of your opinion on this that it is just due to a very different sort of methodology or do you think there is something kind of more fundamentally different kind of besides the methodologies with some of these these existing studies in the literature right so there are indeed you know a lot of papers and both on the micro and micro front on the micro front papers that I am aware of they do find effects on say of consumption are set to a background income risk on spending and this is also a model through state of the art life cycle models in macro there are also papers yes with some conflicting results the thing is that is why we put so prominently there what Nick Bloom has you know summarized out of this literature that precisely by the nature of this question is extremely tricky and challenging to clearly identify and make causal inference both moments in principle are moving we were lucky that our instrument that our treatments not only moved people's posterior to a different extent so this gave us indeed the space we wanted we needed to identify then separately the two effects so it's a completely different approach for sure here but it shows I think also the power of this kind of methods that you know now become they become more popular and we see that by providing information treatments can change indeed people's behavior in many respects it's not only consumption or macro there are also recent studies that look at information that graduate students receive on their majors and this on the salaries of the possible sector they can work for in the future and this changes their choices of a major so you know you find in various fronts and this consistent also with you know limited prior information and knowledge that people have for many of these issues sorry Daniel for misspelling your name sorry for before other questions if not I can take another one from my primitive list of questions so but it's actually the flip side of the previous one so one issue of these randomized control trials is that they always take place in a very peculiar and very specific circumstance and a very specific time which has not the long time dimension so what makes you confident what you measure in terms of the consumption reaction the different goods the composition is not a special covid effect rather than a general consumption effect where we as economists and you know briefing people of policy makers can be confident that they are of a certain general nature how do you go about these issues thanks for this actually question we receive often in seminars we will give this paper because apparently we filled the experiment during covid although it was not exactly you know at the time of a lockdown or say at the same time when the October's when the infections went up again in January was deep into but I mean there were no local restrictions at place etc so again my answer relates a bit to my earlier answer to more than that the beauty of this is via atomization you can make sure that people that are priori sensitive or affected by covid they are equally present in the control and treatment groups so this somehow ensures you know that you don't buy as your effects this way now exposed as we did actually you can split the sample and look at people working in sectors that have been affected more from covid versus those that have been affected less from covid but this is you know totally legitimate in this context is more kind of estimating heterogeneous treatment effects so your baseline effect you can trust it in terms of this causal estimate you identify and then you can split the sample in various ways to see this another piece of fact is that we have much time to go through to talk about was this consumption budget shares where basically we saw that the effects of our information treatments were across the board so it was not the case that we saw concentrated effect of increasing consumption uncertainty on certain goods that was more difficult say to access due to covid there was some bigger effect on recreational activities or on goods that are subject say to supply constraints so it was across the board so this suggests that it was more a kind of precautionary saving response so people wanted but not strictly say a covid a covid effect okay thank you we are at the end of our time and obviously this new survey of the ECB would give tremendous scope for future research so if people are interested in what are the prospects for using this maybe you talk to Dimitris what how this will be gone about and if you have become interested through this little appetizer that would lead me to close this session now and tell you that we break for 15 minutes and then I'm sure you will be all coming back for a fascinating discussion with Paul Krugman and Larry Summers about something they think less often about than US inflation which is your area inflation so I'm very curious what they come up with thank you very much we now come to a absolute highlight of this annual research conference at the ECB a long awaited sequel to the meeting of two giants of our profession we might also call it a clash of the titans Paul Krugman and Larry Summers truly need no introduction we have last seen them at the beginning of this year debating each other on the outlook and the causes of inflation and it was 90% about the US inflation which is of course given where they are based and given the situation in the US as being ahead of Europe at the time absolutely understandable this time in the sequel we will want to dedicate some time, hopefully a lot of time to Europe which is at the center of the present storm the last debate was in January this was pre-Russian invasion this was pre-energy crisis this was even before the up shooting of inflation in the Euro area so we are very curious what you two have to share with us your points of view Paul can I ask you to go first please the floor is yours alright thank you thanks for the invitation so I want to give a just a quick analytic perspective talk a little bit about the US and then talk about Europe about Europe where I have surprisingly confused convictions about where we are right now so okay I think we have a kind of a shared perspective I believe most of us in this field and I think Larry and myself that roughly speaking we think of inflation as being determined by some measure of capacity utilization labor market tightness output gap plus expectations of inflation and then of course with volatile prices so you want to make a distinction between some kind of underlying measure and the headline inflation rate the we have there is in all of this an implication that there is some level of unemployment to use star at which actual inflation matches expected inflation originally the natural rate according to Milton Friedman it got renamed the NARU I think partly because people didn't like the implication that natural sounded like it was good and we didn't want to say that unemployment was good but I think actually in this case natural is better because the NARU involves the implicit assumption that expected inflation reflects recent past inflation and so it's a question of inflation acceleration which does not as I'll explain in a minute does not look like a good description of where we are in the United States the actually let's talk about the US for a second so I have two slides on the US situation they're not updated for this morning's inflation print which was a little upsetting but don't want to make too much of one month so if I could have the first slide for a second if we can get that can we get it if not well I guess not all right let me talk let me just tell you what's on them by the numbers current inflation looks quite a lot like inflation in 1980 which is our nightmare scenario is that we're going to have a replay that we're going to have to go through a a Volcker type period of extremely high unemployment to bring inflation down and headline numbers the inflation numbers per se are very are not very different from what they were in 1980 you have to bear in mind that we've changed the way we calculated inflation but the Bureau of Labor statistics provide numbers that essentially backcast current methods to old data so we have high inflation that is a little bit lower than in 1980 but also the Fed's target for inflation is lower so it looks kind of nasty what's very different best we can tell is the state of expectations current inflation expectations in 1980 everyone really expected inflation circa 10% to persist indefinitely you can see that in consumer surveys you can see that in those of the inflation rates actually can we move on to the next slide then to show you the difference well maybe not all right let me just tell you what the next slide will show if it ever appears there we are this is survey data there's a real question how seriously should we take this but every piece of information I have points to the same story in the last time we had really major inflation we came in with all significant players market participants households firms expecting that high inflation would persist for the indefinite future this time around we have much much lower expected inflation again by all indications market surveys and we have very few there's a question about how good are the surveys but for what it's worth they show that people are expecting medium term inflation on the order of not basically the Fed's target and we are not hearing we look at anecdotal evidence we're not hearing a lot of cases of firms granting big wage settlements and the expectation that everybody else is going to be granting big wage settlements over the next several years so we don't appear to have a lot of inflation momentum out there the question is in that case why is inflation so high the answer is that although the unemployment rate looks comparable to what it was before the pandemic every other indicator suggests that the economy is running unsustainably hot I don't like that I like to see the full employment but vacancy rates we can question them but quid rates are telling the same story wage increases are telling the same story the economy is running unsustainably hot the good news is that's all because of a hot economy not because of expected inflation so that the task of monetary policy in the United States is to cool the economy off before it starts to bleed into expectations now question is how much cooling do we need and if I respect the efforts to estimate U-star from the beverage curve I've been doing some very back to the envelope stuff with quits which is not that different wage increases are also suggesting it's possible that and under current circumstances we might need to the unemployment rate to rise to 5% to cool the economy off it's hard for me to believe that U-star has really permanently jumped that much this quickly that we might be looking at lingering effects of pandemic disruptions but nobody knows and the policy indication for the Fed is pretty simple high rates until you see the whites of disinflation's eyes until you start to see a convincing range of underlying inflation measures falling and pretty clear sign it's just much as I don't like prospect of higher unemployment much as I don't like the whole that and the definite risks of recession because this is not something that you can fine tune I don't think that there's really any alternative to a policy of gradual rate hikes in the months ahead I'm relatively optimistic that the U.S. will get through this without a severe recession maybe no recession at all but it's clearly there's going to be some pain along the way the European situation which is what you're mostly interested in let me just say that it is quite wild and I have one more slide if we can just get it I just picked this one up I stole it from daily shop because it's and I won't vouch for the reliability of the numbers but surely the general picture is right Europe is facing a gigantic energy price shock as a result of having become reliant on Russian gas this is huge this is far bigger than the oil price shocks of the 1970s there is very little reason to believe that the European economy is especially overheated so it doesn't actually it's not showing it's not looking like the U.S. in that respect and so you might say well we normally tend to think of that policy should react to evidence of overheating and not to fluctuations in volatile prices and I wish that I was confident that was a safe strategy to follow but when you have a shock this big in fact European core inflation has gone up substantially although that's almost certainly basically energy prices bleeding into other prices as well rather than that sort of underlying inflation problem but the can we be can we feel secure in the belief that inflation expectations will remain anchored in the face of a shock this large and the answer actually we can kill the slide now the answer is I don't really think I wouldn't if I were at the UCB I would not feel comfortable relying upon the shock being transitory I would probably be tightening I think there's high risk of a recession in Europe at this point but it's now for what it's worth unfortunately US data on inflation expectations are flaky a lot of it is really just gasoline prices European data as best I can make out are even flakier if we believe the Bundesbank survey inflation expectations consumers in Germany have gone completely off the rails I guess I don't really know what to make of that but the odd thing is that although by normal criteria the US has a overheating problem that requires rate rises the European Euro area has an energy shock problem that ordinarily would not call for rate rises the precautionary principle basically says that the UCB has to do some hiking the moment markets are pricing in equivalent amounts of hiking on both sides of the Atlantic which is probably excessive in Europe but it's just a very difficult situation and so I I've been a big dove I was wrongly convinced that we were facing mainly a transitory shock I still think that there was a substantial transitory element to US inflation and there's certainly a large transitory element to European inflation right now but for the time being monetary tightening seems to be unavoidable on both sides of the Atlantic and you need to feel your way forward to try to be data dependent as much as possible if that sounds a little bit less hard hitting than you'd like to hear I'm sorry it's we really have never seen a shock like this and we're all I think everybody is making it up as they go along let me conclude it there on the situation also I keep on losing sound from the moderator I said that Larry's turn is now and I'm sorry for that thank you very much it's a privilege to be here with the ECB with you and with Paul I find myself in agreement with Paul on the difficulty of the situation on the broad paradigm for thinking about inflation that emphasizes the degree of tightness and the role of expectations and the general view that the appropriate posture forward in the United States and in Europe both involves tightening albeit for somewhat different reasons the presence of overheating in the United States and the presence of potentially increasingly unanchored expectations given the magnitude of the energy shock in Europe I have a perhaps slightly more simplistic and certainly more hawkish view of all of this than Paul has and I have had that for quite some time I reread over the last week Arthur Burns famous 1979 lecture on the anguish of central banking and read relevant histories of the 1970s and what I was struck by was the pervasive presence of themes we hear today you have to distinguish in a major way between supply and demand shocks recessions are enormously costly and for risk aversion reasons you need to avoid taking chances on the risk of recessions it is not clear how anchored or unanchored expectations are movements need to be made gradually it I think bears emphasis just how catastrophic that paradigm was around the world and just how high unemployment had to get in the United States and elsewhere with how much pain to control the inflation and so when I hear arguments about expectations are anchored I think to myself so far and I think to myself that they are anchored is a tribute to 40 years of policy when the kind of approach that emphasize the role of so called transitory inflation and supply side factors was substantially discounted and the mandate was seen crucially as assuring price stability with respect to the United States I think what was quite plausible was to suppose last year when unemployment insurance had a replacement rate for most workers above 100 percent that the natural rate of unemployment was substantially displaced upwards for transitory reasons relating to those benefits and to COVID the fact that we are now a year past all the cash payments a year past all the elevated unemployment insurance and the beverage curve has not shifted inwards much at all suggests to me that at least as a precautionary assumption we should assume that we are in substantially overheated territory so my judgment would be that neutral in the United States involved in unemployment rate given the current structure of the labor market in the general range of 5 percent I look at core inflation which was faster this month than last month faster this quarter than last quarter faster in the last six months than in the previous six months and faster in the last year than in the previous year and ran at 7.2 percent this month I look at wage inflation that according to what I regard is the best available data from the Atlanta Fed is surely running above 5 percent and I cannot understand the view that it is likely to return to a 2 percent target without unemployment being meaningfully above the natural rate of unemployment so I think that if we pursue policies in the United States that successfully restore inflation to target is very likely that we will have a recession that will bring the unemployment rate to 6 percent or more that is of course the situation vastly different than the 10.8 percent that Paul Volcker had to bring about or that we saw during the financial crisis or that we saw in the aftermath of COVID but the stark fact in the industrial world is that there are almost no examples in which inflation was above four unemployment was below four and a recession did not start within the last two within these subsequent two years and that there are no examples in the United States in which the unemployment rate was driven up by half a percent without being driven up by more than two percent and so it seems to me that the likelihood is that if we are to bring inflation down in the vicinity of target we will have a meaningful recession it seems to me that for us to make a decision not to do that because it was too painful would be to invite the end of the bit of good news that Paul is pointing to the fact that expectations are now substantially lower for three years than for one year and are running substantially below the level of headline inflation I think that Paul's comments with respect to Europe that highlighted the much greater difficulty of the problem because it was made exogenously or made externally rather than made internally by bad policy and because of the recessionary consequences of the large terms of trade loss I think all of that is correct but I also do not see an alternative to a significant increase in rates if expectations are to become anchored are to remain at all anchored and I think there is the additional factor certainly in the United Kingdom potentially in other parts of Europe of significant fiscal leader responsibility leading to reductions in credibility I am less convinced of the case for gradualism in central bank adjustments than I think many are I don't think there is any substantial probability in the United States that this episode can be managed without rates being risen being raised to close to 4% and in that context it seems to me better to move rapidly than to move slowly it has seemed self evident to me for some time now that a 75 basis point move in September is appropriate and if I had to choose between 100 basis point move in September and a 50 basis point move in September I would choose a 100 basis point move so as to reinforce credibility seems to me that the move that many regarded as surprisingly large by the ECB recently was also entirely was also entirely appropriate and I think moving more strongly sooner has benefits in terms of credibility and therefore reducing the ultimate amount of restriction that is necessary that exceed any costs of the possibility that the move will need to be reversed quite quickly in general I think it is possible but the judgments currently expressed in markets about likely tightening represent something that I would regard as a simplistic scenario in both the United States and in Europe not as a best guess finally while I am very much aware of the differences between the United States and Europe and the differences between the United States and Europe and Japan and other places I am struck by the lack of common international commitment and international signaling in the current moment it seems to me that for there to be a general recognition of the salience of inflation as a central problem of the challenges that will face the developing world as a consequence of the necessary adjustments in the industrial world of the possible risks not yet realized from excessive exchange rate instability and the sense that there is a collective macroeconomic management on the case globally we enforce everybody's credibility in a very valuable way and I have been disappointed by the absence of the kind of strong global signaling that has been present at a variety of other very difficult financial moments thank you very much I am very happy to share with you the question that was very clear and you have also already anticipated some of the next questions I was going to go into namely the question of where do we go from here and at what velocity in terms of interest rates but let me nevertheless dwell on this forward question that is what is going to happen in Europe especially in Germany people are buying firewood and it is hard to buy firewood that price has also gone up not only the one of gas recession is something that is clearly very much on people's minds and fears will be available so your views on the European economy you recently called it an agonizing choice that the Europeans and the European central bank is facing here so the question about how does the economy evolve and what is the appropriate path for interest rate increases and the outlook for them and maybe you can also say something about fiscal policy which clearly also has an impact and is right now also mostly busy with dealing with the energy crisis and shielding households at great expense so Paul back to you with a bit more detail please on path of the interest rate in Europe actually having a very hard time just to say in terms of trying to put a number on how much ECB rates need to rise it's just a very part of the problem is that we have a quite weak estimates they're not great for the US but estimates of the transmission mechanism from interest rates to real activity in Europe are even less secure but I regretfully agree with Larry that the 75 basis point rise by the ECB was necessary and that there will have to be more and let me in terms of the policy actually I think we narrow it too much in the European case by talking about fiscal versus monetary policy because there really is now the question of policy to limit energy prices to households and businesses is very much on the table and in fact it is inevitable there are going to be price controls and subsidies to limit the the cost of energy to the European public over the course of this winter this is ordinarily economists are very negative on price controls and Larry mentioned Arthur Burns and actually the when one talks about Arthur Burns we think about the Nixon price controls and the expansionary monetary policy probably politically motivated that helped to set off the 70s inflation but this situation is I think a case where things are quite different it is going to be necessary to limit price rises for households just on sheer equity social cohesion grounds if current energy prices are fully passed on to households a lot of people will be ruined financially in Europe and so there is going to have to be now you could in principle devise a program of financial aid that offsets the price rises sufficiently but in practice trying to devise such a policy is probably beyond what you can do so there are in fact going to be price controls with substantial subsidies to the energy sector to make them workable and probably in order also there is going to have to be some kind of rationing instructions to limit maybe even I don't know enough yet to figure out what it is going to look like and you might say isn't this a recipe for disaster didn't we see that happen again Arthur Burns and the 70s inflation and the answer will be the reason to think that this time is different infamously sarcastic Reinhardt Roghoff title is that there in the infamous Arthur Burns incident price controls were used to suppress inflation while the central bank was juicing up the economy in this case it's going to be price controls used to try to hold down inflation while the central bank is tightening sharply which could be a quite different outcome and there is a macroeconomic aspect as well we don't really know what the mechanism for inflation expectations in Europe is going to be but to the extent that we are fearful that energy prices will lead to a wage price spiral then limiting energy prices even at the cost of substantial fiscal outlays and some rationing may have substantial macroeconomic benefits so I think if we are trying to think about the European response it's just focusing on the ECB and just focusing on fiscal impulses missing the point everything is going to depend a lot on how European nations try to cushion the blow from energy prices I just want to back up on one point to the extent to which Larry and I are disagreeing everything that Larry is pointing to which is that inflation has stayed high and possibly accelerated is consistent with an economy that is still highly overheated there is nothing in there that says that expectations are driving this we to the extent that we have a model it is one that says that inflation expectations are the reason why you need to have a period of high excess unemployment it might be that that model is wrong but what I think I learned what I got wrong in the inflation debate back in the beginning was that I kind of decided that I knew better than the model and I was wrong I would like to know what the story is through which we need a period of sustained high unemployment if it is possible it is possible but I do think when in doubt stick to this kind of canonical model which does say that we need a rise in unemployment clearly but probably not a sustained period of excess unemployment but anyway coming back you are mostly interested in the European situation and I think the question for Europe has to be how can you make this change with the extremely high energy prices tolerable and that is requires that there be a disinflationary monetary policy but it also requires substantial direct action on keeping energy affordable for the general public Thank you very much Paul Larry if there is something you want to respond otherwise I can go to my last question and then I will open up to the public in the room we also have a few board members of the ECB in the room as well as audience I'm sure worldwide so my last question would be about the long run perspectives on inflation and again your perspectives for the US and Europe if you think they differ you might also want to comment on the strategies the monetary strategies which in your last debate you were back in January discussing in the view of today's situation of then situation which today looks even more grave so to you Larry let me make a few observations Paul I think the inflation mechanism involves heavily overlapping wage contracts and the like and I put substantial weight on the fact that job switchers are seeing much larger wage increases than job stayers and that gap is larger than it has ever been and that suggests to me that there is a lot of wage momentum that is currently built in I guess I think of Bob Gordon Phillips curves as being canonical models and people who want to make assumptions different from Bob Gordon Phillips curves probably have the burden of thinking that they're using the different models we're in agreement on the importance of fiscal as well as monetary policy in Europe I'd offer the general observation that it would be surprising to me if this was a good moment for there to be a significant decline in European real interest rates and without significant increases in nominal interest rates that's likely to be what happens as inflation accelerates I recognize there's a subtlety about which inflation measure goes into the construction of real interest rates I agree with you Paul on the central importance of fiscal policies that question what's happening in energy prices as I heard you though I thought less about Arthur Burns' price controls in the early 70s than Jimmy Carter's energy prices in the late 70s that were motivated almost exactly by the kind of motivations that you described and I think it's fair to say we're generally regarded as disastrous in their effect and I think the idea that if you repress inflation and through rationing then there won't be inflation and then there won't be inflation expectations and that will end up good I think is conceivable and I can construct the argument for it but I think is unlikely these are not entirely new problems it is standard advice in developing countries to protect people rather than to protect prices I do not doubt that it will be necessary for the reasons you describe and given the difficulties in targeting to engage in a certain amount of and perhaps a significant amount of energy subsidy but I think all possible ingenuity should go into finding ways to increase supplies as rapidly as possible even at the cost to other values I think that it is appropriate to engage in significant support policies for households rather than simply trying to maintain prices at current levels through subsidies I think there is some elasticity of demand for energy and that is worth keeping in mind there is a substantial playbook about subsidies versus compensating households from which we can learn I would be the last to take a doctrinaire view of opposition to any kind of substantial subsidy and I share your view about what is necessary I also think that there is a non-trivial chance that Britain has put itself on a catastrophic course with the degree of commitment to subsidizing energy coupled with the utter absence of any signs of commitment to fiscal responsibility and I would hope we could agree that that was not a model for Europe so I share your view but I think it is central banks who have a long history of commentary on the desirability of structural reform to try to orient energy policies in as sound away as is possible given the need to maintain a sense of national cohesion two other points very quickly one is I hope it is entirely clear that the goal of everything Paul and I are discussing and debating is to maximize living standards employment comfort good lives for people across all of our economies that inflation control is not an end of itself we do that end and that those who advocate more vigorous approaches to inflation control do not do it because we think austerity is a good thing but we think that by acting more promptly we will minimize the total burden and sacrifice that will be felt over time my best guest speakers that while I do not think it is the right thing to plan for right now average inflation rates will be somewhat higher over the next decade than they were over the last decade I think a central question for monetary policy will be where neutral rates go back to as things normalize after the pandemic and I am agnostic as between the view that the forces of secular stagnation will reassert themselves and the view that the massive increases in government debt that we have seen and the substantial investments directed at the green economy will raise neutral rates I believe that we all should learn a lesson of humility from the events of the last five years and I am increasingly skeptical of the merits of forward guidance as a policy my fear is that markets do not much pay attention and believe the forward guidance and so it does not heavily influence the posture of medium or long-term rates but institutions pay attention to their past forward guidance and so feel constrained from doing what would otherwise be the right thing down the road and therefore you get the worst of all worlds and I would as a general doctrine favor returning to the extent that it is possible to a more delphi-oracle approach to monetary policy communication and a last forecast every moment and describe every reaction function kind of approach. Thank you very much Larry Paul very quickly because I really do want to open up your expectation for longer run inflation rates in the US and Europe do you want to give a number your number? I actually do believe that we're going back to 2% and this is an interesting thing where oddly I may be more hawkish than than some of the other people who have been much more hawkish than I have there is a view Jason Furman has expressed it that maybe we should when we hit 3% 2% is a very arbitrary target maybe at 3% we should declare victory and pull out but that only makes sense if you think that we are engaged in a vulgar style of disinflation in which case there's a point at which you need to how much more do you want to squeeze it if you believe as I do that what we have now is essentially 2% expected inflation plus an overheated economy then you need to remove the overheating then you basically go back to where you were before now maybe there's enough wiggle room in there that maybe a bit higher but I see nothing in the current situation that would lead me to expect that long run inflation will be significantly above target over the past decade on an average just below target but I don't think that we're really I don't see any reason to think that inflation is going to be persistently higher I think the world in 2025 is going to look an awful lot like the world in 2019 that's good news can I now ask our audience if they would like to ask any questions I see Isabel raising her hand a microphone is coming your way can you hear me so thank you very much to Paul and Larry for their interesting contribution so monetary policy is facing a communication problem which stems from the fact that monetary policy affects economic activity and inflation only with a lag and this becomes a real problem I think for us going forward because as Paul rightly said we are entering a difficult winter but I think there is a need for a tightening of monetary policy but of course what we are doing now is not going to affect inflation during that winter partly because monetary policy only works with a lag but also because certain parts of inflation cannot even be affected so we have a very little impact on energy prices so how can we deal with this communication problem that we tighten some people may not like that let's say that have loans on variable rates they will actually be quite unhappy possibly we enter a recession and inflation nevertheless stays high I think the question goes to both of you who wants to go first can I say way in there it's actually even worse than that because monetary policy operates with both a lag and a lead that is central banks control very short term interest rates which have very little relevance to the real economy and what matters for the real economy are longer term rates which reflect expected monetary policy that's why even before the recent ECB hike long term rates in Europe had risen by almost exactly the same amount as they had in the United States even though the Fed had moved sooner and more aggressively markets had already priced in comparable tightening on the part of the ECB and look it's a very difficult problem even leaving aside the lead issue we are in a situation a little bit of the thermostat that responds to the temperature of the room 20 minutes ago and it's a very difficult problem to solve normally what you want to do is have a pretty good model of what the firm is going to do to the heat in the room unfortunately a two app metaphor but we have very little sense of the models I think this is in the end why I am for more gradualism than Larry is simply because we are so uncertain about how things work and the chance of overreacting badly is there now of course if you the chance of underreacting is there as well but we're going to get it wrong it's clear the odds that we're either going to have high inflation persisting longer than people wanted or if I had to make a guess the odds that both the ECB and the Fed will turn out to have overshot is pretty high but you do the best you can there is no good answer thank you Fabio Panetta do you want to go at this one yeah I think I use the analogy of taking a shower in an old hotel where the water temperature changes with a 20 second lag from the time you turn the faucet and it's very hard to avoid scalding yourself for freezing yourself I can't resist saying with respect to the United States this is why it seems to me the errors made during 2021 were so egregious that precisely because of the magnitude of the lags allowing yourself to fall behind the curve was a mistake and I would have to record the judgment that the least responsible central banking statement of the last decade was the 2020 Fed framework that explicitly disavowed the possibility of tightening until both they had seen substantial inflation rather than expecting it and until they were convinced that they were at full employment which seemed to me to be a doctrine that didn't make any sense at all in a world where there was substantial lags that you described but I agree on the difficulty of the problem on the question of gradualism my reaction is that that's right but if there's a place you know you're going to go I don't see the great advantage of getting there with a little bit more gradualism if for example you know or you're 98% certain that you're going to raise rates by 100 basis points doing it over 6 months seems to me to have no advantage of doing relative to doing it over 2 months if it is beneficial you will start to get the benefits or given the lags if you do it over 2 months and if it turns out to be a mistake you can start correcting it that much more quickly so I agree but I think the principle basis for gradualism is that you preserve the right to maintain optionality about not doing things about not taking further steps and I agree there but where it's essentially inevitable that the step will be taken I think that less gradualism than we've customarily thought in terms of would be desirable okay great thank you Larry now the question the next one or comment is Fabio Panetta first of all I want to thank both panelists for their comments which are interesting and stimulating I would like to go back to this issue of gradualism versus a more aggressive policy trying to refer it more specifically to the situation of the Euro area as you both mentioned wages in the Euro area at least for the time being are growing at a moderate pace while inflation expectations remain in line with our target they are by and large in a narrow range around 2% of course either condition could change very rapidly as it was mentioned in the discussion and especially if inflation above target inflation persists for long time in this case if wage growth becomes much more rapid or if inflation is much more rapid and if inflation becomes the anchor the monetary policy strategy would be very clear but let's assume that this does not happen wage growth remains moderate and expectations do not the anchor in this case taking into account the fact that in the Euro area the output gap has not been closed the dominant determinant of the inflation spike we are seeing is a sequence of supply shocks would you still advocate for an aggressive adjustment of monetary conditions or take into account the specific conditions of the Euro area would you not suggest that a more gradual adjustment being ready to fine tune in case something happens in terms of second round effects might be preferable I think this question is mostly to Larry who was advocating the faster right I think if you I think if you assume that even given the current structure of the economy you are well short of potential you assume there are no important credibility issues you assume that things are completely anchored in terms of expectations then surely all your premises then surely your conclusion follows but I think it is a matter of judgment whether that is the case I think that and I don't mean to be saying that you know policy should be a random walk where you should if you think there are 150 basis points off you should move 150 basis this is obviously a matter of balance but as I look at the history of monetary the history of monetary policy I can think of a fairly wide variety of occasions on which policy moved to gradually exposed it's pretty clear that that happened during the 1970s it happened excessively gradually with respect to the gathering financial storm in Europe after the financial crisis it happened in the United States during the Vietnam War I could proliferate a wide variety of examples when with the benefit of hindsight it seems to us that policy has been too gradual and I find it more difficult to enunciate examples in which in retrospect policy moved too sharply and had excessive consequences and that's why and it's a natural tendency of human beings facing difficult decisions to model a bit and choose incremental measures that try to split the difference that's what brought us the Afghanistan and Vietnam wars and so when I speak up in general with a bit of skepticism about gradualism particularly at a moment when credibility is in question that's right but I guess I'd be interested in Paul's view I think I have a variety of examples in which with the benefit of hindsight policy was clearly too gradual and I guess I would be looking for the famous examples of financial policy that was too precipitous and if they're in equipoise then I guess right but if they're not in equipoise that would seem to me to constitute an argument for thinking about less gradualism Larry and Paul I really wish you were here because obviously this is something that we should be keeping discussing for a long time and there is a lot of interest in the room I see people that would love to continue discussion but unfortunately we're running out of time we have run out of time Paul can I give you one minute to reply to everything please okay Justin there are two famous examples of a central bank overreacting to an energy price shock and possibly doing substantial damage and they both involve the ECB both in the you know on the eve of the global financial crisis and then on the eve of the euro crisis now they were relatively small moves but they do if you want examples of a central bank that is reacting too fast and let's just say that not to reverse market factor not all surprises are negative just in the last few days we're seeing some remarkable drops in European energy prices which still remain extremely high but it may be that the European situation is not going to be quite as dire as we think so I think that's about we can go on for another five or six hours on this probably but that's where I would put it thank you so much to both of you thank you from Frankfurt and thank you Paul for finishing it on a bit of an optimistic note it is worth saying that sitting here in the northern European plain where there is flat from Paris to Moscow it does feel like we are close to a big crisis and to a battlefield and probably in the US it is a bit more remote but thank you very much for engaging with the European situation as well as with the US thanks for being with us here to this evening or in your morning and see you again online or in person even preferably the second bye bye ok so that brings us to the end I'll keep it really short but what I really need to do now is thank all those many colleagues that made this possible and I'm not sure you realize that this was a hybrid event but way more people online and one thing I can assure you a hybrid event is so much more difficult to organize in an on-site event I do hope at some point we will return to those but this basically is mantis that we have let me just because I will forget otherwise we have the logistics team of the ECB the audio services team the multimedia team the webcast team the webmaster team don't know the difference and in particular I want to name just a few individuals here Justina you're in the room somewhere Stefan Angela Lars Christian from those various teams and from the research department Bartosz here first row Sabina and all the DGR trainees around the room that have been very helpful jumping in when things look to go wrong but they did not and I'm very proud of that and with all that I want to say thank you very much for being with us here of course Beatrice as well our board members and all of you in the room all of you looking and tuning in offline and see you next year, thank you