Welcome everybody to the second day of our money market conference. And let's jump right away into that third session, which is on the demand for central bank reserves. And just maybe to remind you of a few logistics. So we have one and a half hours for this session, 45 minutes for each paper. So the presenter has 30 minutes and the discussion 10 minutes and then we have a we have a quick round for also questions from from the whole audience. The questions that you that you want to ask, please, please put them in the in the chat and direct them to all panelists. I will put that information in the chat as well. And then, just to say we have to be a little bit disciplined with the time because the market panel after us has to start on time at 335. Yeah, we have to we have to finish on time.  And then, then we should be fine. So, so yeah let's let's jump right away into the first paper. The, the first paper is is on scars abundant or ample a time varying model of the reserve demand curve. And yeah, Gabela you're already visible so this is presented by Gabela last father from the from the New York Fed so welcome to you and over to you for the for the presentation. Yes, so let me first make sure that I can share my paper. By thanking of course the conference organizers for including our paper in the program. It is a great pleasure to be here to present it here in front of this audience. So President John Williams and our former colleague Domenico Giannone was now at us. The usual this camera applies is our own personal views that do not necessarily reflect the views of the New York Fed or the federal system at large, or the FOMC. The title suggests the paper is about banks and specifically what we are after is the reserve demand curve, which is the price of which banks are willing to borrow and lend reserves with each other as a function of aggregate reserves. So, as all of you know, this is a key monetary policy object for two reasons. The first reason is that when the FOMC communicates his stance on monetary policy, it does so by specifying a range for the rates of which banks. And the second reason is that the Fed can indeed change the aggregate level of reserves in the system, but other factors outside the Fed's control can do that too. So, from the perspective of the monetary authority, it becomes of paramount importance to get a sense of fully in real time of where you are in this curve and even more importantly of its flow. Because that tells you by how much Fed funds rates so that rates of which banks lend and borrow reserves are going to respond to reserve shocks. So the natural question is, can we have a well-identified high frequency, and here I mean daily frequency, estimate of this demand curve and its flow? And that's exactly what we do in this paper. So we propose a time-varying structural estimation of the daily frequency of the reserve demand curve over a period of 10 years going from 2010 until March 2021. So encompassing basically the old post-crisis period. Obviously, there are two challenges with such exercise. The first one is quite obvious. There are the typical endogenated issues of any demand. And here I'm thinking about disentangling supply versus demand shocks, omitted variable bias, any underlying compound factor. But there is a challenge that is more peculiar to what we're doing here, which has to do with the fact that there have been many structural changes in the market for reserves after the great financial crisis. And as a result, the curve may have moved over time significantly. So how do we address these challenges? Well, we use a time-varying structural model on the editor, and you can think of our model as having two components. So first, we propose a flexible forecasting model of the joint dynamics of prices and quantities, so the rates and the aggregate reserves. Then the second component of this strategy, we use the forecast errors for the path of reserves over time coming from the forecasting model as an instrument, for our instrumental variable estimation of the structural reserve of the market. And we use the path forecast error. Now let me anticipate right away what would be upfront daily data for our identification strategy. It's very important. Let me show you, let me give you a preview of our results right away. So here at the top, in the top figure, I'm just showing you the data. That's the time series of our main variables of increases of prices. So rates of which reserves are length and point aggregate reserves. So on the x-axis, you have time from 2010 until March 2021. The solid line is aggregate reserves in the US banking system, normalised by banks that allow to account for the growth of the banking industry over time, which is quite sizable since we're looking at more than 10 years of time. Now the dashed line instead is the weighted average rates at which reserves are borrowed in the market for reserves, minus the interest on reserve balance to control for changes in the monetary policy system. And I would be clear in a few slides about why we need to do that. The graph is color coded. So we start with dark blue from the left when it's around 2010. Then it gets lighter, lighter blue, 2011, 2012. It becomes gray for the period that goes from 2014 to 2017. And then we have pink for 2018 and 2019 and dark red for the last part of ourselves, 2020 and 2021. But what I want to focus on, of course, is the chart at the bottom. Because in that chart, we are comparing our model for the reserve market with the data. So the dots are our model-implied estimates of the reserve market functions. Those are five days ahead in sample joint workers of prices and quantities. So on the x-axis we have normalised reserves and on the y-axis we have prices. So that's rates, minus IRP. And the squares here represent the realisation of the data. So this figure is telling us the thing. The first thing is that the model is the data very well. As you can see from the part that all the dots sits on nicely on the square. The second thing is that the model is able to predict, to forecast the non-linear demand function predicted by the theory. And that would be more clear later about what the theory tells us about the reserve market curve. Here you can see if we start in 2010 with the dark blue area, there is a clearly negative slope that it decreases. Then it decreases in absolute value as reserves expense and the curve becomes flat as normalised reserves process 12-13% of banks not elastic. Now the third and most important thing that this chart is telling us is that there is not just one curve over time. There are three curves. So the reserve demand curve seems to have shifted over 2010-2019 outward and then further upward after the onset of the COVID pandemic in March 2020 as represented by the dark dots. So what are the results? The curve is shifted upward over time. It has shifted further upward at the onset of the COVID-19 outbreak. The curve was flat during the period of 2012-2017 and after March 2020 periods that people referred to as abundant, or super-abundant reserves. However, although reserves in the system in our period were almost always above a trillion and most of them above two trillions, we still observe a negative slope at the beginning of our sample in 2010-2011 and in 2018-2019. Now this slope that we observe is more gentle than the steep slope that people estimated in the 90s they referred to as the periods of scarce reserves but it's still there. Finally, the transition, the level of reserves or normalized reserves here at which the curve stops being flat and starts displaying a negative, a significantly negative slope, is around 12% of band-stalked acid, both at the beginning of our sample and in 2018-2019. So here's how the talk will go. I will spend a reasonable amount of time on the institutional background because it turns out to be key for the identification of the reserve demand curve. Then I will talk about model identification strategy. I will skip the part in which we convince you that our model has very good real-time performance in the sense of our sample forecast evaluation because they want it done. And then I will focus on empirical extinguishing on our maps. So let me start with aggregate reserves and their evolution over time. So quantity. So reserves are deposits held by banks at the head. And I think most of you have this figure in mind already but I think it's worth it to spend some time on it because it's a very important figure. This is the time series of aggregate reserves in the US banking system from 2005 until March 2021. And this figure is telling us one important message. There are two worlds, two regimes when we think about aggregate reserves. There is a pre-2008 financial crisis and there is a post-2008 financial crisis. So before 2008, reserves were in the tens of billions and they were quite stable. After 2008, as the Fed responded to the great financial crisis, reserves jumped to the trillions and they exhibited a much richer dynamics over time. So that's the time series of reserves. But how do reserves change actually in accounting? And here I need a bit of accounting and this accounting will turn out to be important. So reserves are assets from the perspective of banks or the positive institutions but they are liabilities for the Fed. So there are two ways reserves can change. The first way is quite intuitive. It's through expansions and contractions of the Fed's balance sheet. So for example, when the Fed purchases securities in the markets, it usually purchases the security from banks and when it does so, it credits their reserve balance of the Fed. There is so there is a one-to-one mapping between the expansion of the balance sheet and the expansion of aggregate reserves of the system. But there is another way the reserves can change. It has to do with the fact that reserves are not the only liability from the Fed's balance sheet. There are other liabilities, for example, the account of the U.S. Treasury, the Treasury General Account. And when this normal reserve liability is decreased, holding the size of the balance sheet constant reserves might decrease. So what are these normal reserve liability telling us? The reserves are not at those systems and that's because on a daily basis banks transact with holders of no reserve at liabilities. And I want to focus on two important examples here. One is the Treasury General Account. The account of U.S. Treasury has a defect. So when then, why is newly issued Treasuries from the Treasury? They do so. They pay for the security by using their own reserves. So there is an increase in the Treasury General Account and a decrease of aggregate reserves of the system when banks submit the payment. And the similar dynamics occurs for tax payments. When banks submit tax payments to the Treasury, it won't be up to the clients. The other account, the other non-reserved liabilities that we like to focus on is the overnight reserve of the city, simply overnight reserve, which is used by money market funds to place cash at the Fed to reverse repos color-utilized by Treasuries. But when money funds place cash at the Fed, they are instructing their custodian banks to make the transfer. And the custodian banks are using their own reserve balance. So for an increase in the overnight hierarchy, there must be a decrease in aggregate reserves in the system. So if no reserve liability is very small, a negligible part of the tax balance sheet or stable over time, intuitively, it wouldn't matter for our access. But it turns out that they are neither small nor stable over time. So in the chart at the top, I'm showing you the ratio between the dollar value of all reserve liabilities excluding currency in circulation over aggregate reserves. And as you can see, it's a sizeable number and it changes a lot over time. So for example, it started around 40% in 2010. Then it dropped to less than 20% in 2011. It stayed there until 2014. And then it started to steadily increase over time, exceeding 80% of aggregate reserves in the system in much 20 countries. But not only sizeable, it also displays a very rich dynamics. So at the bottom here, I'm focusing on the two liabilities that I mentioned earlier, the TGA on the left and the overnight RRP on the right. As you can see, the TGA was almost always below 100 billion from 2010 until 2015. And then it started to increase steadily and it exceeded 1.5 trillion in mushroom defense. The overnight RRP on the other hand did not exist before 2013. But then it's usually exploded until before 2013. Then it's usually exploded with big exceeding 400 billion. And now you can see in this chart but the overnight RRP in September has exceeded 1.5 trillion, just like the TGA. Now let me talk a bit about the market in which reserves are traded. So that's called the Fed Funds Market in the US. It consists of unsecured lending, mainly overnight. And the rates at which reserves are traded, called Fed Funds Rates, are the rates targeted by the Fed in its more variable sentimentation, as I said before. Now, what does the theory tell us about these rates? So absent frictions, they should always be above the interest paid on reserves balances, which was zero, by the way. And that's because no bank would ever incentive to lend its reserves at a rate which is below the rate that it earns. Or it's a count of just letting cash stay. At the same time, it should always be below that this can win the rate, which is the rate at which banks can borrow from the bank, because no bank is an incentive to borrow from another bank at a higher rate than what they get from the Fed. I'm abstracting from market segmentation and stigma, but that's not important for what we are trying to do. So what does the theory tell us about these reserves? So all the models of the reserve demand curve identify two regions. There is a region in which the curve displays a very steep slope that's region of scarce reserves, and it's usually around aggregate reserves required. Then there is a region far away from aggregate reserves requirement, in which the curve is perfectly flat. And that's called the region of abundant reserves. Now, what's in between scarce and abundant? Well, that depends on the model you're looking at. All models without trading frictions, they predict a piecewise linear relationship with a king between flat and steam. Now, more modern models that allow for trading frictions actually predict an intermediate region in which the curve displays a gentle slope, so a smooth region of transition. Now, let me talk briefly about monetary policy implementation to motivate why what we're doing is important. And let me start with pre-2008, okay? So before 2008, reserves at the site were in the terms of billions, they were now remunerated, thanks to strong incentives to actively trade with each other on a daily basis, and the demand curve had a very steep slope. So that meant, from the Fed's perspective, that the Fed could keep the target rate by just tuning with small adjustment the reserve supply through the open market operations, because even a small change in the reserve supply would imply a sizable change in the price. But how can you do monetary policy with abundant reserves? Well, when reserves are in the trillions and they are remunerated, banks have lower incentives to trade, so supply tuning is ineffective. Even some large, relatively large changes in the supply will not materially affect the food. So the Fed started implementing monetary policy for administrative rates, so basically it changed the interest on reserve balances and the discount win rate. And by doing so, it changes the opportunity cost of banks of all name, their reserves in their accounts. So changing overnight in the interest on reserve balances, the IRB, basically corresponds to vertical shifts in the reserve demand curve, which we want to control for, because they would contaminate our estimation of the reserve demand curve. We are not interested in these vertical shifts, we are interested in the curve itself. Okay, let me close the institutional section by talking about drivers of the demand for reserves by bank. And the literature has identified many thin drivers of an upward pressure in the precautionary demand for reserves for the crisis. The first one is quite obvious, is the new regulatory supervisory framework. So think of liquidity and poverty ratio, living bills, supervisory stress taxes. And even setting aside regulators and supervisors, banks themselves have changed their internal liquidity risk management in response to the crisis. And now they have a higher demand for safe and liquid assets such as reserves. And then there is a third driver, which I think is very important and sometimes people forget about it. And I find that over time after the crisis, the interbound market for reserves has become quite a trope in terms of, so the volume in terms of liquidity has become much lower than what it used to. So the lack of debt in the late day funding markets combined with the need to submit large intraday payments has increased the precautionary demand of banks for reserves. And my co-author and colleague, Gara Fonso, will present a paper exactly on dystopic later in this afternoon. So let me move now to model identification trash. So we postulate these structural demand curve. So that's the demand curve that if we can see that we postulate for bank reserves. So as is the weighted average bank transfer rate minus the IRB, and that's the dependent variable. The main independent variable is aggregate reserves in the banking system normalized by banks for the last few. So all parameters in the model, including the variance in front of the structure are allowed to be time-varyed. Our object of interest is of course beta. That's the time-varying elasticity of rates to reserve shocks because that's the time-varying slope of the demand curve. So what's the trick behind this model? They're basically using a high frequency time-varying linear model to cast the volatility to capture the non-linearities predicted by the team. So that's the assumption here for this to work. And the assumption is that the structural parameters that govern the structural equation have all more slowly than the liquidity shocks that hit banks every day. And that's reasonable because it took banks months to adjust to the post-crisis frame for the drives that was mentioned. So let's talk about the endogeneity issues we are facing. So the first one is obvious and has to do with Fed's interventions. And on a daily basis to open up operations, that's correct. But it still does respond to unusual dislocations in the Fed's market. And here the example I want you to have in mind is in September 2019 when Fed funds rates and overnight repo rates spiked up on September 16th and 17th when the effective Fed funds rates actually reached the target proportion. Over the following days, the Fed responded by expanding their reserve supplies to the market, and within a few days both Fed funds and repo rates went back to their private liabilities. Second type of liquidity has to do with no reserve liabilities and that's why it's time so much time. So not only they change mechanically the level of reserves in the system but they also correlate to reserve the main shocks. And the reason is that the main holders of these no reserve liabilities are key money market participants think of the Treasury, money market funds having or no reserve liabilities and they are acting both in the Fed funds market and in the repo. So they are actually the users of these no reserve liabilities both affect and depend on banks and banks overnight. And again, an important example is what happened in mid September 2019 when spillover from the repo market was made onto the Fed funds market at the same time where it correlated with changes in aggregate users. So let me be a bit more specific to fix ideas and I give you two examples and four examples of entertaining. The first one has to do with the window dressing of European banks that are on offense. So our on offense European banks reduced their wholesale wholesale short-term borrowing. They do so to improve their regulatory capital ratios that are calculated. Now that means that they demand for reserves so they demand for borrowing in the Fed funds market also decreases because that's wholesale overnight. At the same time though they reduce also their borrowing from money market funds which are their main lending wholesale. And what do money market funds do when they face this decrease in the demand for funding while they place their cash at the overnight European? Which implies that the overnight European goes up and aggregate reserves go down. So the good thing about this compounding factor is that it reverts within a few days and it's highly predicted. Now the second type of indigeneity has to do with the Treasury. And for example with Treasury office. So on settlement dates banks demand for overnight funding especially Ripple Fund. And the reason is that they finance their purchase of Treasury's and new Treasury's through overnight Ripple Fund. Now this puts up for pressure on the reserve demand because borrowing in the Fed funds market so borrowing reserves overnight and borrowing Ripple's collateralized by Treasury's so there is an upper pressure in the reserve demand. But at the same time when banks submit their payments to the Treasury for the new securities, they use the reserves. So there is an increase in the TGA and a corresponding decrease in reserves. So these are shortly a very frequent compounding factor and corporate tax payments display a similar demand. They have a very similar demand. So how do we deal with indigeneity? So first of all between the data we drop one-day wind those around one times and these take care of the wind addressing of European banks. And that's the first example that telling you that using daily data is key for this type of exercise. But then we have a more general which is an instrumental variable approach. As I said, it's two components. So in the first part we build a forecasted model of the joint dynamics of quantities so reserves Q and rates prices X. The model is basically an adaptation of the daily time-varying VR with stochastic volatility proposed by Prime Minister in 2005. And again the key assumption is that the forecasted model the parameters of the model move more slowly than the daily forecasted model. Then we take the past forecast errors coming from this forecasted model for the path of reserves over time as instruments in an IV estimation of the structure of the manipulation. To fix ideas we estimate our forecasting VR we obtain forecast errors here. We use five days ago forecast errors as instruments for Q in our structural application. So the IV estimate that we written is usual as a ratio of two covariances yet the cool thing is that we allow these covariances to be ten-vary but instead of doing instead of using the usual two-stage square we pull back our covariances from the estimation of the reduced form VR. And that allows us to write the theta as a ratio of two impulse response functions. A denominator of the impulse response function of prices to quantity and a denominator of the impulse response function of the impulse response function. So in terms of additional IV I just want you to think of this IRS denominator as the reduced form regression and one other denominator as a first-stage. So since we are doing IV let me convince that our instrument is exogenous and again the data will not be key. So the exclusion restriction is that the forecast forecast errors are uncorrelated with demand structure errors. So let me tackle Fed's intervention first. So since 2008 the policy has been implemented through administer rates. So I know that you have a market approach and Fed's research supply only responded to unusual dislocations in the Fed's market. And that happened typically with a delay of at least a day. Think of it as a time-consuming thing. So this is telling you that it is key to use daily data to build the model and construct the forecast error. Now let me talk about no reserve liabilities and very much made. So the key thing here is that these confounding factors that typically are transitory and they last for less than five days. And good examples, again, are treasury options to explain this. So let me briefly talk about the relevance of our instrument very briefly. So it turns out that our sorry just to say is relevant and this comes from the fact that we are looking at the post-prize period where the path of reserves displays great persistence and the second reason is that our model is good in the path of reserves. Now let me move to the results and let me close with the results. So as I said at the beginning the main result, the first result of the paper is that the reserve demand curve is shifted over time. So here in this slide I'm showing you at the top the same chart I showed you at the beginning. So those are in-sample joint forecast of prices and quantities from 2010 to March 2021 and the bottom chart I'm showing you the out-sample joint forecast. So that's our model implied demand curve in-sample and the one at the bottom in real-time. So the first thing to notice is that there is markedly seen and that speaks to the real-time performance of our model. Then the second thing to notice in terms of economics is that there are these clear outburst shifts over 2010 to 2019 so the blue and then March 2020 as represented by the red the dark red dots Now let's move to the main object of interest in our data which is the LSTC of fat transfer rates to stocks and reserves So you are learning the LSTC of fat transfer rates and basis points to stocks and normalized reserves percentage points the dark blue over time so 2010 to March 2021 the dark blue line is our posterior median or S2 and the shaded areas represent credible sets around. So what this picture is telling us is that there was a significantly negative slope at the beginning, 2010 to 2011 then it disappeared from 2012 to 2017 and then it will emerge again in 2018 and 2019 and the curve became flat again as the pair responded to the COVID-19 outbreak by expanding. I also want to emphasize that this affects actually this negative LSTC at the beginning our sample in 2018 to 2017 are actually economically important if you think that a one standard deviation shall in aggregate reserves would explain 50% of the in-sample standard deviation of fat transfer rates in 2010 and 30% of the standard deviation However the numbers are much more than the numbers researchers used to obtain for the scarce period or at least for the pre-2008 period in the 90s So there are several robust instructions in the paper of course the idea of our main robust instructions is to explicitly control for family transfers that people have put forward like other money market that can also not only can be lower on to the fat transfer rate but also correlate with aggregate reserves and clear examples that are repo rates, fee bill yields or money market funds and the idea behind what we do is to just augment our forecasting model to explicitly control for this compounded fact This for example is the LSTC that we obtain when we control explicitly for repo rates in our forecasting model and as you can see the results are remarkable this year So let me conclude with the question or maybe the question I think is key for the fat and I believe some of you may be wondering about it quite some time and the question is so for now I've just shown you our estimates of the LSTC, the slope of the curve we're trying but the question could be for what level of results actually the curve stops being flat because the theory tells it that the demand curve is no limit so in terms of the old model the question is where is the king in the demand curve or if you want to think in terms of the more modern models where does a gentle slope start for more here I'm showing you the same chart I showed you before at the bottom so let's aware that I'm a structural estimation of the sample structural estimation of the time varying LSTC of the reserve demand curve the only difference from our baseline the only difference is that at the top now I'm showing you the path of aggregate normalised reserves in the system so aggregate reserves divided by banks of points and the dash red vertical lines correspond to the points in time at which the 95% credible set crosses zero so in frequentist terms if you want those are the points in which the LSTC stops being significant from the 95% points and as you can see the point in 2011 was slightly below 12% and it's slightly above 12% of banks of the LSTC at the beginning of 2018 so there seems to have been a shift to the right in this point however if you think in terms of money those two points roughly 12% for banks of the LSTC correspond to completely different levels in dollar values but they corresponded to less than 1.6 freedom at the end of 2011 and slightly more than 2 treatment at the beginning of 2018 so to wrap up in this paper we propose a structural time varying estimation of the reserve demand curve over 2010 to 2021 and the whole post crisis period we do so by using a combination of a stochastic volatility time varying for casting model casting era and we combine it with an instrumental variable approach applied at the date I didn't show you about our forecasting model as excellent out sample real-time performance but the most important thing is that what we show is that the reserve demand curve has moved upward over time consistent with drivers the presence of upward pressure in banks demand precautionary demand for reserves and its slope has changed significantly also in particular in 2018-2019 we estimate a significantly negative slope even though reserves were around 2 treatment thank you Galileo thanks a lot for the presentation and yeah let's move right away into the discussion and we have Hubert O. Ennis from the Richmond Fed about the floor zeroes thank you let me start by saying this is a really good paper and my plan is sort of to share some thoughts with you about the paper you know I have this disclaimer down there that I don't think of myself as having views but in case some of what I said comes across as views those are not of the views of the reserve but what I'm going to try to do is just share some thoughts to start let me just say you know briefly the sort of motivation behind this kind of discussions is that the Fed intends to implement monetary policy using a floor system and this is sort of the language of the Federal Open Market Committee and on the 30 2019 they said they intend to implement monetary policy with a regime of ample supply of reserves that ensures control over short term interest rates but setting administer rates and no active management of the supply of reserves and there's a bunch of keywords here you know ample control active management but we'll maybe talk about some of those key question how much is ample and this is kind of what they are addressing and the Fed tries some other stuff they try to ask the banks with some mixed results and what these guys are going to do is they're going to try to estimate the sensitivity of rates to the level of outstanding reserves and kind of get the sense of ample from that so the paper estimates an aggregate daily excess demand for bank reserves in the US and I say excess because in principle some banks demand reserves and others supply reserves the Fed provides the net aggregate supply but there are endogenous like Gabriele explained so well there's a bunch of endogenous and autonomous factors that change the supply so what they do they consider this equation S is the spread between the effective funds rate and the interest on reserves and Q is the aggregate quantity of reserves in the system normalized by total bank assets and so it's just basically price on quantity regression the slope cost and you know it's a sophisticated you know procedure and so they have the slope coefficient this beta and all the other coefficients are allowed including the variance of the shop is allowed to change over time and Gabriele explained very well why this is important in this exercise there's a classic endogeneity problem this sort of you learning is the first exercise in econometrics like the supply maybe moving in response to market conditions and so you get the supply and the demand moving simultaneously and what they do is they use a idea approach to estimate the coefficient beta based on sort of exogenous changes in Q and it's kind of a nice procedure but I'm not going to talk much about it Gabriele on this topic I think it's important is that Gaara told us that you know most of the lending in the Fed funds market is being done by FHLBs fair home loan banks their government sponsor enterprises that cannot earn interest on reserves and this creates a composition effect that combined with some internal management practices of these GSEs tends to push the effective rates below the interest on reserves and Gabriele touched on this topic also Gaara told us that most of the borrowing is done by foreign banks to arbitrage interest on reserves so this makes the pricing in the Fed funds market the ideas in practice in my opinion and so if you are accustomed to think about the pool model of the money I feel like that's not necessarily a good framework to understand the dynamics of rates and how rates move as total standard reserves change during this period and the regulatory changes that Gabriele mentioned and other things tend to influence the demand and also this demand and this supply are very kind of the demand is coming from FBOs and the supply is coming from HLB that are not earning interest on reserves so it's tricky the standard logic of that one tend to use for downward sloping demand curves is really I think not a great abstraction to use Gabriele emphasized the endogeneity I'm going to square it if you know in their paper they discuss several channels that make the endogeneity the Fed moves supply and reaction to market conditions and Gabriele explained that really well non-reserve Fed account balance is moving reaction to market conditions repo markets and Fed fund markets are tightly connected affecting reserve supply and rate but they are running examples of these events in September 2019 the Fed intervene and successfully calm this what appear to be this functional markets I get the sense that expectations of Fed intervention partly explain the spike in the repo rates in 2019 so it's sort of like even the spikes were endogenous in my mind think of think of the case where there were funds in the sideline so there were there was short term funding available after a long period of very high reserves but those arbitrage rates that were needed to counter the spike did not happen had not happened for a while and then there were set up costs and other administrative procedures that were needed to arbitrage to turn on the arbitrage machine and so on top of that market participants probably anticipated that the Fed would intervene and squash those arbitrage opportunities in a few hours or days just that it happened and some paying those costs was un-economical because you wouldn't have a lot of time to take advantage of the arbitrage so I think it's important to keep in mind that the way markets function depends on the anticipation of central bank intervention okay so there are results the authors find that the rates start to become sensitive to the quantity of total standing reserves the level of reserves is approximately 12% of total assets in the system and that's approximately $2.6 trillion of reserves right now now I want to say that the Fed recently placed a standing repo facility that in principle might have changed that because early on in the discussion of this facility one of the motivations was to reduce the demand for reserves by balance now the slope coefficient is roughly equal to minus 1 when reserves are 8% of assets so that's about 1.8 trillion of reserves now the way I look at things is the Fed targets a range of 25 basis points wide for the effective Fed funds rate and the range of short-term fluctuations in total reserves is around $2 billion now there are these slow moving things but the blips are around $2 billion maximum so that's like 1% of banking assets that translate into a one basis point fluctuation in rates so it suggests to me that even with reserves at 8% these things will work fine in terms of targeting a range okay so why am I thinking that well there are benefits of having a small there are important benefits of having a small balance sheet for the central bank political economy you know reasons and also you know price risk and this perception that so things that impact the central bank independence which I think are very important to sort of protect so my I come out with some broader policy questions should choose small and short-lived fluctuations in overnight interest rates measuring basis points be avoided at all costs and I wonder is this about bond trading and should it be about industrial production and more broadly about GDP and social welfare now this picture is these are 5-year periods and then I plotted the FedFans rate volatility so it's the fluctuations in the FedFans rate in these windows and the windows are 92 to 96 2002 to 2006 so that's black and green and then you get 2012-2016 and then the red is three years for 2019 2017 to 2019 and you can see that the September 2019 blip is kind of small relative to what we were asking to see before and I'm not thinking about how well we do with controlling rates I'm talking about how the US economy worked during these periods so just to conclude this I think is a good and important paper it's very well executed has ingenious and sophisticated estimation procedures I think the finding seems reasonable to me though the interpretation seems less obvious to me and that's kind of what I try to discuss with you and then the policy implications is again even I don't have it clear I think they seem to suggest that maybe 12% of reserves over total assets is a reasonable it's a good place to be in terms of total reserves but I'm not sure that it's the right way to think about it and thank you very much and great paper thank you Hubert well just to check maybe whether there's a question from the audience just seeing whether there's anything in the chat I don't see anything so given the advanced time unfortunately maybe just back to you Gabriela whether you have a one minute response or two minute response to Hubert has just laid out sorry for the pressing on the time I understand and do my best so first of all thank you so much Hubert for the wonderful discussion I will pass upon a few points so the theory and the fact that holds model or other models may not be the right models to look about I think you're absolutely right we want to be agnostic about the theory we need them to understand we just look what theoretical models tell us about the curve and then we try to bring those theories to the data in a natural I agree with you in particular that I think there's need for most theory that looks at market segmentation in a role of different players in this market because they're not all the same it's not just about liquidity shock needing identical banks so there's something more and at the same time I think there should be more models about that and more empirical analysis about the reserve demand curve at the individual bank level or bank time so that's key now I want to briefly talk about interpretation and what we mentioned near the end about the timing of these attacks and again I want to reiterate these are my own personal views not the views of the Federal Reserve System so I agree with you I think in the sense of what our paper is telling us is that there was a negative slope let's take September 10th there was a significantly negative slope back then how big was the slope it wasn't big enough probably to explain the huge jump with the Federal Reserve System so this is telling us that it was not just about movements along the curve there was something else so this is pointing to the importance of the slow moving factors that push the curve up and down not just the slope but also the position of the curve changes and may get closer to the upper limit of the target range and which we have in the model but and in particular is pointing out to the role of stocks to high frequency demand stocks that is exactly what we want to filter out when we estimate structurally the reserve demand factor so I agree with you and I think that one of the messages from the paper is that researchers should spend a long time thinking about modeling these high frequency demand stocks in the reserve demand factor that correlate also with how we are preserving this system and there is a growing literature there and our colleague Ivan Kopan is a paper with Darryl Duffy Anton Matan is a paper with Simon Porter in some sense speaks to the same talk so I agree with you and I think that we should not only think about ample mass scarcity and abundance in terms of the reserve demand factor itself in the movement along the curve but we should also think about it in terms of how to correlate about the shocks the high frequency demand shocks that affect that constraint and that is the basis Thank you so much Thank you Gamela Thank you very much for presenting a very interesting and very relevant paper I am sure there will be ample opportunity to put this paper to test in the future so we will look forward to that or look forward to your results in the future and also thank you So thank you for all that, of course, for the discussion. Thanks a lot.


So you've probably heard of the inner child we have and my understanding of the inner child is the most fundamental need we have as humans which is really as children certainly it's for connection and that's a need that you know we're humans we're social animals we're designed to be in relationship that's a need that never goes away really throughout the whole lifespan for people but it can become a little bit too simplistic when we think of I have this inner child that wants connection because there are other needs we have within us that if they are not catered to or they're not met they're not validated we run into problems now one of these needs we have is the need to be lazy and it is not a need that is talked about enough very few people I hear actually talk about it at all so I see kind of part of my mission here in this life to advocate for the inner lazy child because you know it has a very bad name and we're all trying to get rid of our inner lazy child which is a shame which I'll talk about here so the question in this video the title of this video is how do you treat your inner lazy child the answer for most of us is we treat them terribly you know they are they're like the original inner child they are a valid emotional need to be lazy to be lazy is a completely valid need now also productivity or what I call the need to take responsibility is also completely valid but the thing is that's an inner child we're all very aware of and we give plenty of validation to in terms of psychotherapy we would say that we're all deeply identified with that need we like that inner child we take the side of that inner child now that does not necessarily mean we are productive in our behavior you see the thing with something like procrastination is it's the result of it's kind of like driving with the the handbrake on in your car right you may want to be productive you may want to meet that need for to to be take responsibility and to do things but if there's this unmet need over here this need will become resentful to any efforts to meet this need longer it's unmet the more it'll sort of hold it back essentially with our emotional needs the only real way forward with them is to see them all as valid and your inner lazy child is one of those needs that is valid as the need to be productive or the need for anything else so yes we have an inner child in fact we have more than one inner child and all of these inner children are inside us they're sort of trying to get our attention they're trying to get some of our time and energy but really the thing they need most of all is to be validated and that is to be seen as okay not a nuisance now laziness this this inner lazy child we have is typically seen as the black sheep of the family we're all trying to get rid of it and transcend it and overcome we can find ourselves becoming what I refer to in my book on procrastination as chronic doers where we're constantly identified with this doing and productivity and because we're we're either thinking about it we should be doing it we tell ourselves or where we actually are doing it but more often than not we're not doing it but we're certainly never sort of consciously saying to this inner lazy child I really appreciate you I see you as valid and the thing is once we start to give this need this inner child this this lazy inner child some validation some space to be itself productivity comes a lot more naturally because there's less inner conflict ultimately what happens with our inner needs is when we're not validating some of those needs or all of them maybe they're all in competition with each other they're all sort of undermining each other but once you start to see them all is equally valid and you start to validate them all they start to cooperate with each other and they start to complement each other so what happens is that the inner lazy child starts to complement and assist and help the productive inner child you could say and there become much more willing to cooperate and share with each other it also feels a hell of a lot better emotionally for you you could consider yourself in all this to be the the parent to all these inner children so what I want this video to be is just a gentle reminder that with this this inner lazy child there's nothing wrong with it the only thing we have to start to do is to validate it more often to give it what it needs but not passively intentionally god forbid that might mean you intentionally play video games because it's a lazy thing to do or you might watch a movie sometime but you do it intentionally rather than finding yourself passively watching it and feeling guilty about it okay some of those behaviors can become addictive and I'll talk about addictive behaviors more in future videos and a few people have been asking me to talk more about that and I'm actually I'm working on that right now but that's something that's coming but the need for laziness should not be considered an addiction it's a very valid healthy need to not be in goal setting mode all the time to switch off from that in fact it's an essential thing that we do for ourselves so my goal again here is to remind you validate that need you know sit down and really say okay there's there's lots of things I want to do here but how am I going to validate this need what can I give that need to make it feel validated and unmet for myself and see what happens to me emotionally when I do that do I feel do I feel more centered do I feel more balanced with them myself and my feeling is that you will you will as soon as you start to validate that need for laziness so guys I hope that's a useful video if you want to learn more about this there's two resources one is my book on procrastination which talks a little bit about this and the other one is a book it's actually a free book you can check it out it's on my website and it is called forget happiness which is basically a book on self parenting how to meet your own personal emotional needs laziness being one of those needs I hope that's a useful video and I'll see you guys again very soon in the next one take care


things that happened was the students learned all of these things that were sort of an accessory to learning statistics because they were engaging with community partners. So students learned to draft somewhat professional emails to their partners and many of them asked me for help with that so that was a really good experience for them. They learned to work together in groups and how to divide up the tasks to complete a large project and I think they do group work in many different courses at Western but the some of the feedback I got from students was this was the best group experience that they've had so far in their college career. So something about figuring out how they were going to distribute the workload I think worked well in this project. Students also got to meet professionals in the community and get a sense of the range of jobs that are available for biology graduates. I think many of them hadn't really thought about some of the possible roles that they could play in the future. The fact that tribes hire biologists to help them survey the environment that the Wacom Department of Public Works hires biologists to help assess water quality and make and make planning decisions for the county. So the fact that students both got to meet these people and also see what kind of ideas were and jobs are out there inspired them. And also many of the students were really excited about having an experience with a project that was sort of a real world experience that they felt like they could put on a resume so they could say when they were going out to apply for jobs I have worked with this agency and I analyzed their data and I wrote a report and and that's actually really something they would do when they go out and get a job. So I think they appreciated that that real world experience as well. Another unintended positive outcome of working in groups was that students got to practice different types of leadership skills and I gave them an additional evaluation to ask them about how they felt about being a leader and that was again me sneaking in some of this experiential education outdoor leadership type of philosophy into the course and many of them said that being in a leadership role was challenging for them and that they tried a new kind of leadership role which is great because it's hard for students to sometimes step into those leadership roles and play different roles and so just even getting them to think about it to process that to try new roles was I think really an important piece of the group work. Again they leave with this real world experience and so when they go out to their wherever they go after they leave college they're going to have this experience that they can reflect on. I think that also gives them confidence that they've learned how to tackle a problem. I think that that confidence piece is an important part of the character building aspect so when you have a real experience and authentic experience it often leads you feeling more confident in the skills that you've learned.


Kaj so tudi prikazati, kaj sem nasunjala o partiesneh spremstv? Nadavanje spremstv imamo o isberg. Vsega se ta weba, nekaj nekaj je tebe dejlj skupane v tipi. Če so, da k saw opetnej do pavement nekaj priprasno, je zrenjena spremstv srednje veska. Vse ver, da vzostavljaj všeče pravno, kako prišljava in prokratiruje. Vse zelo je to zelo izgledo, v unijtah stavnega vsega in izgleda začetnima informacij, in tudi vse zelo izgleda, izgleda dnega, ki je tudi izgledal, zelo, da je bilo zapravljenja, bo je jozno tako uniklje, skupovoslega, bo je in glada, prijevaj, je to, da je začajno, in je bilo vizivno začajnega. Prejevaj je zelo, da je in potenčnega, in potenčnega števna. In nekaj, da so je vsočen, je se nilat počel na to, in je to, da počel ne veče, da naredimem, nekaj dobro, in vsočen našli z Evropo. Is it an important market? If we relate this to the estimate we produced with Europe over the last year of the size of the European drug market, it's still a very small part of it. But it's still important. It's around 80, between 80 to 90 million of euros, which means it's an important value, which means also that this money is recycled through other serious and organized crime activities. And as the commissioners said, drug-related chemicals represent around 62% of the total commodities that are available on the darknet. So drugs in that darknet area represent a very important part of it. In the case for buying on the darknet, people perceive that they offer safer environments. There is also a perceived higher quality of the products. Now, this perception is not necessarily wrong, but it is not always guaranteed. And there may be a negative side effect in the sense that if it is indeed true there is a higher quality and especially higher quality or purity of the substances. This may also mean that it's more dangerous for health. So what is perceived as a quality or an asset for the users may be a risk also for them. Certainly the darknet offers a wider range of drugs and it's perceived as giving, offering greater convenience. However, it's important to say that not all drugs are being sold everywhere the same way. And for instance, the new psychoactive substances with the exception of some countries like the UK, normally they are more sold on the surface web, the top of the iceberg that I was referring to before. This study is very unique also in the sense that it is the first comprehensive study of the darknet since its apparition, which means that we have studied together with Europe all the evolution of around 100 different darknets. We have observed the evolution. We have tried to analyze in detail what those darknets were offering. And we have also followed the evolution and also the closure of many of those darknets for the last years. Since darknets exist, there were more or less 100 and today we estimate that there are around 14 that are in operations. And those are the data since last August when we finished the study. So this means that it's rapidly changing. Certainly low enforcement action are extremely important and Rob Rain Wright gave the examples of the last operations coordinated with the support of Europe. But of course the darknets, they adapt themselves, they protect themselves and one of the objectives is to guarantee better encryption or protection of their users. So it poses an important challenge for the low enforcement community. But for the society in general in the sense that the right or the use of encryption, the right to anonymity is also important for the economy. Indeed if there is no good level of protection this means that there would not be e-commerce possible. So the challenge is that we need to find the appropriate responses while avoiding that we block any progress and any use for the normal purpose of those technologies. The last data I would like to share with you before to close and to answer the questions relates to what is the proportion of the drugs that are being sold in Europe compared with the global offer for sales. And as far as the value of the sales is concerned the sales in Europe and Turkey and Norway as Turkey and Norway are also members of the EMC-DDA and are covered by this study. The EU countries represent 46% of global drugs revenue. In terms of weight they represent only 34%. But this is due to the fact that according to the different areas in the world different substances are being sold on the dark net and for instance if it is cannabis or marijuana being sold the weight of those substances is more important. Last point that you certainly will have noticed in the report is that in the European Union we have three countries where there are more sales originating in Europe it is Germany, the United Kingdom and Netherlands and this is valid both for the quantities but also for the revenues. It doesn't mean that everything is sold or produced or is truly originating from those countries for instance in some cases there can be some drugs that are in fact sold by providers or vendors that are in the Netherlands but that are sold or sent from the other side of the border with Germany for instance we see also that there are differences in the ways that the users are selling and consuming and I think it reflects a moment in the story of those dark net so if I may conclude on this point I would say that it's extremely important first that thanks to all the data including data we got thanks to the law enforcement in the law enforcement interventions on Alfa Bay and the Hansa dark net we have a more deep understanding and concrete understanding but also we have a list of questions and as this reality is changing very fast this means that we need to continue to monitor, we need to harmonize some of our methodologies and tools in order to make sure we can catch up with the technical progress and this is what we are going to continue to do together Europol and EMC-DDA and I would like once more to thank the commissioner for his support not only the support but also for his commitment and for the commitment of the commission to address the broader issue of cyber crime and cyber security and for the necessary dialogue with the tech industry because again it's not the question of black or white to close or to open but certainly it's important to ensure and safety not only of the businesses but before all of the citizens Thank you very much


We are pro cannabis media. Hi everyone, welcome to We Talk News. I'm Jimmy Young, the founder of pro cannabis media. And I'm Kurt Dalton, the founder of cannabis.net. Every week, Kurt and I get together and talk about the biggest stories in the cannabis universe locally here in Massachusetts, coast to coast and around the world. And this week's no different, Jimmy. Vermont is actually getting a little bit closer to recreational sales. We have hemp thieves stealing hemp, thinking that they're getting marijuana. And one of the biggest brands in the world, cookies, is making its way to Florida. But let's go right to Deb Borchard of the Green Market Report for our Wall Street Minute. Take it away, Deb. Thanks guys. This week, the Vermont Senate cast a final vote in favor of S54 legislation that would legalize, regulate and tax cannabis sales. The bill now proceeds to the desk of Governor Phil Scott and he hasn't said whether or not he's going to sign it. This would be the latest New England State to legalize cannabis and that puts more pressure on the bordering state of New York. Aurora Cannabis delivered its official results for the fourth quarter. Only problem is, they said that revenues are going to decline in the coming first quarter. Now a couple of weeks ago, you may recall, Aurora said its fourth quarter net revenue fell 5% to $72 million. Now they're saying first quarter revenue is only going to come in between $60 million and $64 million. Kushko holding said that it expects its fourth quarter revenue now to come in between 25 and a half million and 26 million. This is better than the third quarter revenue that came in and only $22.3 million. And it's an improvement over the previous guidance where they said they thought revenue was going to come in at between $24 and $26 million. Kushko said that the 14 to 17% expected increase in revenue is being driven primarily by an increase in sales to its top 100 customers. And that's the big business news for this week. I'm Deborah Borchart from The Green Marker Report for We Talk News. So while we wait for Vermont Governor Phil Scott to pen the legalization bill for sales of cannabis in Vermont, there's another part of that bill that we should mention. It has to do with the expungement of records of inmates who've been convicted for small cannabis possession crimes. Laura Subin, who is the executive director of the Vermont Coalition to Regulate Cannabis released this quote, we view this as a critical component of a movement towards racial justice and cannabis policy. It recognizes and aims to repair some of the horrific legacy of racism and the enforcement of cannabis prohibition laws. Unquote. Kurt, I think she nailed it right on the head. Yeah, an expungement is such an important part of this process because the things that were taken away from their lives when they were arrested, like voting rights, access to jobs with a background check, a criminal check, that has to be reversed as well. So they have to have the ability to vote. People have to have the ability to get a job or have a record cleaned when there's a background check done, it's the right way to do it. And another news item out of Washington, DC from the marijuana moment, is that there is now a coalition of cannabis advocacy businesses who are trying to legalize interstate commerce between legal states. The Alliance for Sensible Markets Campaign is pushing governors of legal cannabis states to enter into an interstate compact. Now, before the lawyers get involved with this and kind of challenge the constitutionality of this, keep in mind that a recognized agreement between two or more states to establish a framework for interstate commerce is actually a precedent that was set back in 1921 when New York and New Jersey signed a similar agreement that created the Port Authority of New York. So if New Jersey makes it legal and New York has a medicinal program, they could work out an exchange as well as Western states, California and Oregon. Kurt, do you think we'll ever see this? In this form, it has 0% chance of going through. What they don't mention, and God bless the effort, is that you're dealing with a Schedule I drug by the federal government and states do not have the authority to supersede federal law or create it or change it. That's kind of been the whole problem. So while I value the look at history and the loophole that they're trying through, it'll never happen this way and it has zero chance of that going through. So obviously after the election, if there actually is a change of leadership in the United States, it has a better chance of going through, agreed? I would agree that that is certainly the first choice. Lawsuits like Steve DiAngelo's challenging the constitutionality at the federal level are second. This is another kind of wink, wink, hail Mary that I don't see this ever working. Not to mention, even if you've got momentum, the federal government could challenge us for years in different appeals courts. All right, so it is harvest season for hemp and marijuana, but it's the fields of hemp that are being targeted by thieves, since of course it's tough to tell the difference between a hemp plant and the same cannabis plant with DHC in it. It has always been a target of people who think they're stealing weed and end up with non-intoxicating hemp. It happened in Georgia when a farmer interrupted an attempted theft from his industrial hemp patch. Over 10 pounds of hemp was recovered when the thieves were caught and cooperated with police. The price of those plants, about $1,000 for 10 pounds. Kurt, a big difference between 10 pounds of hemp and 10 pounds of marijuana. Yeah, this is a seed right out of a Will Ferrell or Mark Wahlberg movie where the thieves sneak into the field, they cut down a truck load and they're all happy and realize they have hemp. So unless they're planning on making some CBD take-to-chairs or some really nice CBDs drops, they're gonna be greatly disappointed after they use the hemp. And pay their fines for doing it. All right, another story about illegal grows is coming from New Mexico, where illegal cannabis is growing amongst legal grows of hemp. Now, adding the fact that these farms are just off Native American lands and owned by Chinese businessmen, they have caught the attention of the Council of the Navajo Nation, the Department of Homeland Security and many other law enforcement entities. It seems that kids are being trafficked into New Mexico to tend to these crops. Some of these kids are as young as 10 years old. Illegal grows are starting to get more and more attention from law enforcement and this may have uncovered a human trafficking ring, certainly probably something they'd like to stop, especially the human trafficking and certainly not what you wanna see in a hemp or in a cannabis field, correct? Yeah, we talked about things that are compressing the margins all the way around on the bottom line where you have to find a way to create some margin. And unfortunately, child labor and forced labor, it's certainly a way to find some margin on the bottom line.  Absolutely, has to start, has to stop. So now in Fortuna, California, a $1,000 a day fine will be administered as a deterrent for local illegal grows once local enforcement issues are warning. Now, those who do get fined will not be prosecuted or arrested for this misdemeanor, but is that $1,000 a day enough to stop growing illegally, Kurt? Depends how big your grow is. And if you're thinking about this, you'd wanna have grows in multiple locations and just realize this may be the new cost of doing business on the black market. If you have four or five locations and you know, hey, one's gonna get taken down every six months and you work that into your financial equations, the fact it's not a criminal charge and as a warning first, I think people are gonna continue to push the limits as we like to say. Everybody's doing a little bit of a cash grab. Meanwhile, up in Canada, it's time for Solomon Israel's MJ Biz Daily International Report and another record set from our Northern borders. Take it away, Solomon. I'm Solomon Israel from Marijuana Business Daily International and this is your Weed Talk News Canadian cannabis report. Canadian sales of recreational marijuana hit yet another new high in July. The regulated markets surpassed 231 million Canadian dollars, up more than 15% over June. On an annualized basis, July's figures imply a market worth 2.8 billion Canadian dollars. Meanwhile, Aurora Cannabis posted a net loss approaching 1.9 billion Canadian dollars for the quarter ended June 30th. All told, the company lost 3.3 billion during its 2020 fiscal year. New CEO Miguel Martin said he plans to refocus Aurora's grant portfolio to prioritize premium brands. And the government of British Columbia is working on a program to allow farm gate sales from small licensed cannabis producers. That would let those drovers sell their own crop directly from stores located at their production sites. But there's a catch. The program isn't scheduled to launch until 2022 and a provincial election is scheduled before then. You can read those stories and more at mjbizdaily.com. I'm Solomon Israel from Marijuana Business Daily. According to M.J. Bizdaily, cannabis consumers are spending more during COVID per visit in California, Nevada, Washington State and Colorado. Facts like that are available in the M.J. Bizdaily 2020 Factbook. You can get yours at mjbizdaily.com. A California company known for its celebrity ownership called Cookies has just bought a license to operate a medical dispensary in Florida. Kurt, do you know of a rapper named Burner? I've heard of him before, yes. I haven't before I read this story. Anthony Mulan is his real name and he will be the first person of color to own a license to operate in Florida and it will be located in Port Richie scheduled to open in 2021. So I guess that's a good thing, right? Yeah, Cookies is a great brand. If you've read the backstory, it's still privately held and they've just done such a good job establishing the difference in a commodity, right? We've always talked about how cannabis is gonna be a commodity. Tomatoes, cabbage, grapefruit, whatever it's gonna be. And Cookies has really defined the market. It's what men should have been, right? That's kind of where it's at where Cookies is the success story that went under the radar privately held. They're doing it right in every state. As soon as you see the store, you know it for its quality as well as its design. Again, it's kind of where men should have been. The vision, Cookies actually is the reality. And Cookies is a great name for a weed dispensary. Let's face it, because there's always munchies involved, right? I mean, that's obviously where they came from. Anyway, hard to believe. There is an issue with delivery in Colorado, a state where it's been legal for 10 years. Sure enough, Colorado Springs is banning the delivery of medical marijuana citing a public safety issue and the cost of regulation. Kurt, I do not get this one. No, it's funny, the price of cannabis per pound or marijuana in Colorado is like a three-year high, which tells me if it's just supply and demand. There's a lot of demand, whether it's black market or above the board for that Colorado bud. So it's strange to see a medical thing. Maybe there's an incident there or what about recreational? So I think it's a little more to that story and there could be some players making that happen for strategic purposes in their business, but we'll have to wait and see. And now it's time for the DC Report with Vote Pro Podcast, Phil Adams. Phil? Here with the Weed Talk News, DC Report. Postponing a house vote on the more act until after election day will not slow the momentum toward cannabis reform, say industry lobbyist. That is provided the Democrats retain control of the house. David Manjone of the Liaison Group at DC Lobby Firm for the National Cannabis Roundtable expects lawmakers to push for cannabis de-scheduling with a social justice component. Manjone believes this will offer a more comprehensive solution toward aligning state and federal marijuana laws. Saying, quote, the house has set a new line in the sand. This is what impactful cannabis reform will look like. Cannabis Trade Federation advisor Steve Fox agrees saying, quote, social justice is leading the push for reform and the drive for a regulated market. It's really where we've been at the state level. The Food and Drug Administration will release draft guidelines designed to streamline approvals of CBD-based medications. The FDA announced it is soliciting public feedback from researchers who are interested in submitting new drug applications for CBD products. Guidelines come two years after the agency approved Epidiolex, a brand of CBD-based epilepsy medication. The FDA is also actively seeking research contractors to help study the non-toxicating cannabinoid. In news from outside the Beltway, Ethos Cannabis announced the purchase of three medical dispensaries in Maryland. The Philadelphia-based company has acquired the rights to forefront dispensaries in three locations along the DC Baltimore Corridor. The purchase is part of an $18 million deal with multi-stake cannabis company Forefront Ventures. Currently operating under Forefront's mission brand, the dispensaries will be rebranded to Ethos. That's the Weed Talk News DC Report for this week. I'm Phil Adams from Vote Pro Podcast. A few months ago, Kurt and I talked with Melissa Metley, who was one of the principals at the group called South Dakota for better marijuana laws. Now legalization for adult use and medical marijuana are both on the ballot in South Dakota. And a recent poll says that over 60% of the voters there are planning on approving those initiatives. That group released some disturbing but not so surprising stats about cannabis arrests in that state. Did you know one of nearly 10 arrests in 2018 was for cannabis possession and many were carried out on a racially disproportionate basis? Once again, Kurt, weed legalization is now more about racial profiling than making the plant legal. Yeah, especially in a state like that. I mean, I was gonna say good, we can get the child labor straightened out off the Indian reservations on a state like that. But to see 61%, we had talked to Melissa before, it's really gaining traction. And her group, if you remember, was the one that was really behind both of those ballot questions and pushing it. So congrats to her for not only getting it there, but obviously having a strong majority ready to legalize. Absolutely, and hopefully after election day and if it passes, we'll reach back out to Melissa to congratulate her for sure. Now, one last story about those devastating fires on the West Coast in Oregon specifically. And sure enough, the Small Business Administration confirmed that none of the farms that were destroyed are eligible for any kind of relief funds. Now, the Oregonian is reporting that seven companies lost everything. Canyon Cannabis, Grateful Meds, Blue River Grass Station, and Fireside Dispensary were a few. And amazingly, the fire came within three miles of Jim Belushi's farm, but the wind changed direction and it was spared. Jim Belushi issued an appeal for his fellow growers yesterday. He wants you to go to the Jackson County United Way website, they have a campaign, to try to raise funds specifically for that area. And we are showing the link for you to go to that. Basically it's unitedwayofjaxsoncounty.org, backslash give, backslash. So Kurt, hopefully people will feel bad about this and donate some money back to some of the businesses that were just, you know, isn't it interesting? Our citizens have to do what our federal government won't do. Yeah, it's kind of this tightrope to walk due to insurance policies for cannabis in some states and what's covered in crops. So it's a real disaster, even the California fire.  Just trying to make a living. Growing Belushi, the show on Discovery is hoping for a second season. They're actually in negotiations right now. Now I understand there's a virtual convention this coming weekend, 10X. And I believe we know someone involved with that. Kurt, you and Bruce Linton getting together for that, are you? I think there may be a little banter back and forth. If you wanna check it out, it's the finals of Cannabis 10X coming up this weekend. Judges are Cheech Marin and Bruce Linton and we'll be doing a piece kind of before the final judging. So stay tuned for that.  And Kurt, I discovered it and told them the correct way to spell your name, which they screwed up the first time, although they were very happy and very apologetic. They had done that to you, but I got your back, man. Hey, thank you. There's a level of Belushi's at the Discovery channel. I'm at the YouTube misspelling of my name, but it's a long way to the top, Jimmy, and I'm still going. All right, that'll do it for this week's weed talk news. I'm Jimmy Young for Pro Cannabis Media. And I'm Kurt Dalton with cannabis.net. Remember, it's a whole new world of weed out there. Use it responsibly. Thanks for watching. Thanks for listening. We Talk Now, We Talk News, and In The Weeds are all available on most major podcast distributors like iTunes, Spotify, Google Play, and our friends at clnsmedia.com and our flagship, cannabis.net. So subscribe, share, and like our videos on all the social media networks out there, including LinkedIn, Twitter, Instagram, Facebook, The Weed Tube, and YouTube. We Talk and In The Weeds are two productions of Pro Cannabis Media supported by Revolutionary Clinics, one of the top medical cannabis dispensaries in the Massachusetts area, now with three locations in Greater Boston, two in Cambridge, and one on Broadway in Somerville. Rev Clinics has a patient-first mission. They will customize your needs as a medical patient with the proper titration and combination of strains, flavors, and products. Rev Clinics, where the patient comes first. We are Pro Cannabis Media.