Digiconomist (Alex de Vries) and Ben Gagnon (Chief Mining Officer, Bitfarms) join me on the show to debate Bitcoin Mining energy. We talk through:

  • Bitcoin Mining machine efficiency assumptions
  • Where do the models break down? 
  • Media referring to scary numbers in the bull cycle
  • Transactions per second metrics

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Stephan Livera links:

Podcast Transcripts:

Stephan Livera 00:02:25

 Alex and Ben welcome to the show thank you for having me. 

Ben Gagnon 00:02:27

Glad to be here. 

Digiconomist 00:02:29

Same for me. 

Stephan Livera 00:02:30

So,  we’re gonna have a let’s say a casual debate there’s been a lot of back and forth about Bitcoin mining what are the actual impacts of Bitcoin mining what are the costs and what are the benefits of Bitcoin mining and so lets I guess we can probably set some of the contexts Alex AKA teach Economist you’re a data scientist and you’ve been putting out some statistics on what you believe Bitcoin energy consumption is and what those impacts are Ben is the chief mining officer of bit farms has some disagreements around methodology and perhaps other questions around the impacts of that so I think it’s probably best to start with Ben if you want to start with any of your concerns around Alex’s modeling and then we can take it further from there.

Ben Gagnon 00:03:23

Yeah, sure and thank you Alex for agreeing to come out here and talk with Stefan and I you know very happy to be here and go over this issue you know I’ve been following you for several years and have been pulling your data and have it integrated into my model for about the last three and a half years you know basically you know we as a network are consuming a very trivial amount of energy I think it’s very clear when you look at all the different metrics and the different indexes for electricity consumption like on a global basis we’re a fraction of a percent and there’s no disagreement from you or from did you know from anybody else that Bitcoin mining’s electricity consumption is a fraction of a percent worldwide where we get into problems here is people’s understanding and people’s kind of  Distortion of the real world via these metrics and that I think there’s a couple of things that are going on there one I think there’s a number of assumptions in your model which are flawed secondly I think a lot of the kpis are designed to  mislead or over exaggerate bitcoin’s impact and if I can just start maybe on the model design so on your assumptions the way that you calculate energy assumption is you assume that the miners electricity costs are fixed at sixty percent of the mining revenue and while this is a you know a logical assumption I think to make from an outside perspective you know because you have to make some sort of a you know a margin there for the electricity the reality is the margin is incredibly volatile for us as a company to operate we have fixed costs but the revenue in terms of Bitcoin price Bitcoins that we’re mining on a daily basis the transaction fees are incredibly volatile and so we see margins that can grow go anywhere from high 80s low 90s to down to low you know low teens low single digits or even zero you know for periods of time and when we assume that the electricity consumption is 60 percent year-round what that means is that when we’re in a rising price environment and when we’re mining economics are bullish that means that we keep inflating the amount of electricity that we’re consuming because we’re assuming that the miners are growing at the same rate that the price of Bitcoin is and it’s not it’s not possible because we have real world lag effects with building out energy infrastructure acquiring new miners deploying new miners for us to catch up to the incentive and so you know in a situation like last the last bull Mark in 2021 we had a situation where the prices is going up and so is your electricity consumption index but then we have the China mining ban and the China mining ban had a very real very measurable very noticeable drop in hash rate of about 60 percent and you know what happens when your model assumes fixed costs on electricity on sixty percent of the mining reward that means that that 60 of the hash rate dropped off that means the mining Revenue profit up for everybody else who’s plugged in and the profitability skyrocketed but our operations in change our electricity consumption didn’t change just the profitability increased and what your model shows is that we Skyrocket off to like 23 gigawatts something double the electricity consumption that your model shows now two years ago and you know something that can be checked with the efficiency by comparing that with network hash brown wallpaper Ash basis and it just it just goes out the door and so that’s my big problem is the model is not designed according to how operators operate you know me as Chief mining officer bid Farms I’m looking at profitability I’m looking at operating costs I’m looking at relative competitiveness on my cost efficiencies as a minor you know I don’t have fixed costs and you know in a situation where the price is going down I’m under clocking I’m trying to find ways to cut my costs I’m trying to curtail more I’m trying to do all these different things to drive down my energy consumption drive down my cost because of that energy consumption and improve my profitability so I’d say that’s the first part and that’s a pretty large part so maybe we just maybe we just start with that single we start with that a 60 assumption.

Digiconomist 00:07:53

Yeah so, I don’t know maybe we should first of you know try to find some common ground I mean there might be at least one thing we can maybe agree on which is let’s say the minimum energy consumption of the network and I don’t know if you have any problems with that but that is one other estimate that is featured well also by Cambridge and that’s a very simple calculation how I mean then you just take the network hash rate you look at what type of machine is available in the market what is the Energy Efficiency of that machine and then you just multiply the hash rate with the Energy Efficiency of the most efficient machine out there and you get a certain number which then represents a lower Bound for what we think the energy consumption of the network is and if you look at that today at least for Cambridge they put it at about 70 terawatt hours of electrical energy consumption a year and then the only guarantee we have is that the real fuel energy consumption is probably going to be higher than that lower bound but that’s where this discussion starts and that’s where all the assumptions come in and that’s where all the models come in because that’s where we’re trying to figure out what is really going on with the energy consumption of the network and then there’s different ways to do it I mentioned Cambridge well you specifically mentioned the 60 assumption in my model maybe just to first of all clear up a misconception about my model is that it assumes that minus spent six percent sixty percent of their revenues on electricity in a long run equilibrium so it actually varies over time it’s more like the 60 percent in the long run is a point where energy consumption over time will hover too but it’s not going to be 60 at all times and actually you can find the current percentage typically at the bottom of my Bitcoin energy consumption index page at the moment it is in that direction simply because well the Bitcoin price is not super high the hash rate is super high Cambridge is actually estimating the network to consume even more energy than I’m guessing but I just wanted to highlight that it’s not always 60 percent it’s more like this dot on the horizon where over time the number will hover towards but it’s not always going to be 60 percent and what you said can be true it can be much less it can also be more in the short run like you said there are no fixed costs and the only thing that matters in the short run is your electricity cost what you need to keep your machines going and then in in the long run everything becomes fluid everything becomes variable so even your Hardware investments in the long run become variable but in the short run that doesn’t play a role in the short run Hardware costs what we in economics consider to be sun cost hey you made the investment you can’t recover that so the only thing that matters going forward your perspective fastest just the cost you need for keeping your machines running which is mainly going to be electricity cost so in the very short run electricity gas can go to well worst case 100 of your revenues and that’s where you reach the point where you’re going to be forced to cut your machines I mean if you start making a loss you’re going to turn them off so I don’t know I just wanted to clear this this thing up it’s 60 percent but only in the long run equilibrium it’s not it varies over time.

Stephan Livera 00:11:43 

So, can I then ask the question if it’s true that as Ben mentioned at some points in the Bitcoin cycle yes it might be as Ben mentioned in the high 80s as a percentage maybe the point is that it only spends a very small amount of time at that level and a lot more time below that I’m curious Ben if you have any thoughts there?

Ben Gagnon 00:12:07 

I mean it just depends on the direction of the market right because bitcoin price when it goes up goes up faster than we can deploy new Miners and grow our hash rate or grow our footprint in terms of megawatts and so there is a very large lag effect between Rising prices and faster deployments of hardware and increasing amounts of electricity consumption and so you do get you do get a gap whenever that happens but it’s really dependent on the Bitcoin price you know  I’m glad that you brought up the lower bound outs because I actually don’t I actually don’t disagree too much with your lower bound it’s not your local lower bound that I have too many issues with because your lower bound is at least fluctuating with daily changes it’s your normal bound that I have issues with because your normal bound does not fluctuate daily there are periods of times where it goes months on end where there is zero percent change and it’s not being impacted At All by any variables and Bitcoin is very volatile when it comes to bitcoin price Bitcoin mining economics Bitcoin Network cash rate assumptions and their periods for months on end where there’s zero volatility there are also periods where there’s months on end of a fixed growth rate 0.3 percent for months and these are not factors that are responding to the changes I think your lower bound actually does respond to the changes I think your lower bound is following your methodology as best as I can tell it’s your normal bound which is feeding your kpis which is feeding the numbers that people screenshot which is feeding the Argentina and the country comparisons which is what everybody cites in every newspaper article which is not following those numbers and that’s where that’s where I have the big issue with your model there is a big difference between the normal bound and the lower bound and what we saw in the 2021 bull market was your upper bound went up to 23 gigawatts in a matter of months I mean the ability for the industry to go up and add 10 gigawatts in a period of months is it’s just impossible logistically  it doesn’t exist in terms of the equipment in terms of the electricity Supply none of these factors exist and then now what we saw is during the bear Market your lower bound crashes back down or your upper bound crashes back down to your lower bound and so for several months now your expected has been at your lower bound right but there was there was a very long period of time there where it’s just gapped up  and that’s the big problem here you know when you look at what goes on that main bound and you actually look at the energy consumption and the way I like to verify this is take that energy consumption index you have on a terawatt hour annual I like to and or I like to take that and DN utilize that to make it kind of a daily a daily rolling figure in terms of megawatts and then I divide that with the hash rate and what I get with that is I get an industry overall watt per Terra hash assumption based on network hash rates which are mathematically you know statistically verifiable by probabilities of finding so many blocks in a certain day and in a difficulty period the network assumption is especially if you’re looking at a seven day or longer average is quite accurate like a one day average is not but you know longer periods of time are quite accurate and your Wattpatera hash assumption figures go off the chart with that we go from just before the Chinese mining band we had a walk or Terrax assumption on your chart of 60 watts per Tera hash according to your data at the peak of the China mining ban we had 163 watts per Tera hash and so this is this is showing how the model is breaking down here in these bullish mining Market environments by assuming that electricity cost is going up in a similar rate that the mining economics are going up we’re vastly overestimating the amount of electricity being consumed and you know when you’re looking at okay how does that work from an operator’s perspective so let’s take it from my perspective I’m Chief mining off BitFarms the mining ban happens in China we’ve got all of these different miners sitting on our racks in Quebec powered by Hydro we’re ready to go we’re sitting here we’re absorbing these mining economics what do we do now well according to your model we’re pulling down our best miners and we’re putting up five-year-old s19s or s9s or even s7s to get down to like 163 Watford Terrace efficiency drastically reducing our throughput drastically reducing our revenue and for what purpose like where you know there’s no way that that math checks out it it’s not possible to go from a 60-woper Terra hash to 160 Watford Terra Ash efficiency across the entire industry in the real world it defies all the incentives you know and the reality is that I’m a profit maximalist I’ve I have no shame about saying I’m a profit maximalist and I think there’s a lot of negative opinion put out there towards Bitcoin miners as we’re greedy miners we don’t care about things we don’t care about the environment you know all we care about is the profit of mining Bitcoin it’s like we care about the problem buying Bitcoin doesn’t mean we don’t care about anything else like you know we find over 21 000 Bitcoins with just hydropower here at bit Farms like we we’re a company that has powered almost every single Bitcoin that we’ve mined with hydropower for almost the entire existence of our operation I won’t say that’s something that necessarily that you know every investor is very focused on but the reality is like we as a company we focus on profit and we focus on these other areas where we can we can get better deals and we primarily invest in areas where the energy is overlooked it’s underutilized and it’s often being wasted like it that’s what helps us to reduce our costs.

Digiconomist 00:18:05

Okay so, there’s a lot to respond to and let me first of all say that what Patera hash is not an assumption of my model and also not of Cambridge well they make about Patera hash average which they then apply to the networked through the calculations but it’s not like they assume any Direction on that I mean it will go down over time in the Cambridge model in my model if you calculated well you can calculate it from the energy consumption it puts out but the thing is the what Patera hash it includes energy consumption from all sources so you know it includes that maybe people are going to go crazy in some kind blue Mark where they even start cooling their machines with air conditioning or start heavily overclocking their machines I mean there’s no there’s no assumption on that in my model there is an assumption on let’s say the time it takes to get to that long run equilibrium point that I mentioned before and I think that is an important one because if that one is very short what you’re going to see is that the big compiler goes up and immediately the estimated energy consumption goes up and  the thing is if you compare my model to Cambridge I’m actually the only one that accounts for manufacturing lack if you look at the Cambridge model in a bull market their model always goes up right away the moment the price starts going up because they don’t have anything to account for that they don’t account for manufacturing I do account for manufacturing but my leg is set at one year and that is a fixed amount of time based on calculations made in 2018 so it is totally possible that that doesn’t apply more recently it’s that is the Assumption of my model that the manufacturing lag is going to be one year and yeah you can be totally right it can maybe especially when there’s a ship shortage it may be longer but then again when the market starts going down maybe it’s shorter because you don’t need to produce that much anymore there is simply not enough new information to really make a new calculation on that and by the way the 60 percent is also supported by now pretty old survey by Cambridge several years ago they did this survey among Miners and then they found that close to 60 percent of their costs were going to hardware but again this number might be outdated also the five cents per kilowatt hour which is a crucial assumption in both my model and that of Cambridge is coming from the same survey I think it’s 2018 2019 that number you know we’ve had the energy crisis recently we have we have no clue how this number has developed we know that there are some miners in the US that pay less than that we know for example Riot platforms is paying just three cents per kilowatt hour recently saw a nuclear Miner in Pennsylvania doing just two cents per kilowatt hour so the r minus paying less but we don’t really know how the average is developing over time and these are known unknowns it’s we know that these are assumptions and these assumptions can be wrong the thing is we don’t have anything better to go on than the information that we’re currently applying in these models so and then you specifically mentioned China which is also a very interesting case because my model assumes competitive markets and the thing is in China’s situation when half of the network suddenly gets well kicked out forced to go offline then it breaks the competitiveness assumption so my model doesn’t work when a massive player is Banning a crypto mining because then the competition is well reduced significantly which is great for you if you’re located in Canada because you’re basically getting free money or your income doubles but yeah then the model stops working it is it does return back to a competitive market I mean we do see that in the Cambridge model also had they do they do respond more to the hash rate so in that case their model probably works better and you do see a drop in their data at that point which then you see it quickly recover after just a couple of months so yeah it does kind of indicate that yeah these markets are essentially competitive how people are trying to get these machines up and running as fast as possible when it is profitable to do so it’s just that there can be distortions and if you looked at my website during the time of the China band there was actually notification on the website that had this was impacting the accuracy of the data and the reason I did not adjust it was that it’s not just energy consumption estimates that I put on my website but also carbon emission estimates and it gets really complicated if you want to adjust for that especially during the summer months in China because historically we saw that China during the summer months miners were using hydropower over there so the carbon emissions related to that were actually low and then of course I can adjust the energy consumption estimate but the energy consumption estimate the way it translates to a carbon estimate is on a fixed Factor for the carbon intensity of the energy consumed so then I have to make two adjustments I first of all need to adjust the energy consumption but then the carbon intensity what we later Learned was going up because these mines were relocating to Kazakhstan we’re relocating to the U.S and well at the time I didn’t have the information to be making that adjustment and I can start guessing and I can start putting out random numbers but what I thought was the most Fair would be to just put up a notice that hey this is changing during the summer time miners in China I use hydropower mostly and I think the carbon estimate that I’m putting out is actually the most important one because that’s you know you can use a lot of energy But ultimately environmental impact matters and likely the carbon emissions at the time weren’t going down so the energy consumption was probably going down when China banned these mines because we saw half of the network hash rate forced to relocate but the carbon emissions related to that well because they were going to be using hydropower in the summertime probably didn’t drop as much there’s just no way you can do an estimate for that so I did put a notice saying that Cambridge actually had more or less the same problem because you know they their data did show a decrease but the thing is they don’t know how the mining landscape looks like locally in China they don’t know if those machines running over there are relatively all the devices relatively inefficient whether the cooling that is being applied is very high so they probably would have had to do some kind of adjusting adjustment for that anyway but because in their default model they just assume an equal distribution of the wire they put a basket of machines in their model and they assume that there is an equal distribution of machines being used so if you have for example 10 devices one of them is an s19 one of them is a I don’t know a s19 Pro every machine gets a 10 share and that and that doesn’t change only thing that changes is if there’s more machines being added then the distribution does change but otherwise you’re looking at a equally weighted basket of devices and we just don’t know we there’s no data to say okay when China banned these machines in China they were all using old s9s for example so maybe it cut a lot more energy use than Cambridge estimate or maybe it were all newer machines we don’t know there is unknowns and I don’t think it’s a big problem as long as we know that these unknowns are there and we know how this is being used and we know how this affects the outputs of these models so yeah and these models sometimes just don’t work my model doesn’t work when there is a really massive mining ban in China I’m not going to say it does what I typically tell people is hey if you’re going to be looking at energy consumption estimates it’s probably best to look at my model and the Cambridge model combined because they tell depending on the situation very different stories and one model can be more correct in one situation one more can be more correct in another situation so for example during the most recent bull market or even this year Well we see the Bitcoin price has kind of recovered since the low point of loss here now we see that in the Cambridge model electricity consumption of the Bitcoin network is reaching record highs very recently higher than ever before whereas in my estimate the numbers are currently a lot lower and that’s because like I said I account for manufacturing installation you know a delay on getting those machines up and running compared to the price going up whereas Cambridge they don’t do that price goes up energy consumption estimate goes up so in that case maybe you want to look at my model instead you can’t often verify either model so and this is also a bit of a generic problem

Ben Gagnon 00:28:22

Well, that’s actually why I brought up the Watford Terror hash because I know it’s not a model that you have or a metric that you have on your website or in your data set but it’s how you verify what’s rational right, and what’s reasonable and let me just let me just share my screen here just so I can make this clear.

Stephan Livera 00:28:35

Yeah, just make sure to explain for the audio only listeners because most Audio Only, but just Yeah if you could explain what you’re pointing out.

Ben Gagnon 00:28:54

And it’s just showing up here now yep okay perfect so what this chart is showing is basically it’s digiconomist is electricity consumption it it’s your main estimate divided by the network hash rate average over 30 days the same thing is done for both my model here the HC BC acbc hcbec the red line and the red line as well as for your model here and came for Cambridge here in the yellow and what we see here is that you know here’s where the China mining ban comes into place here is 2021 and we start seeing this skyrocketing wat for Terra hash figure on your chart and this is because your energy consumption is going up in a way that just is not tracking with actual operations on the ground at the peak here what does to say this peak is it says the peak is 196 watt per Tera hash you know that is that’s not even an S7 efficiency and what we’re talking about here is not the you know a single operator’s choice to plug in some older Miners and take advantage of some lower cost electricity this is an industry overall average so that means that the industry on average is running about an S7 you know that means that there are people who are running worse than that in order to get that average because there are certainly people who are running better and this is how you know looking at this you can see that this model you know was within reason for a long period of time but during bull markets it breaks down and then you’ve crashed back to reality and if you see here you know your blue line or my your blue line in my red line are basically the same and have been the same for all of 2023 right so this is because you’ve crashed back to your lower estimate line here back at the beginning of the year this whole over you know when we switch over to the Chart this is your upper bound and your lower bound this is your matching down to the lower bound where it stayed at the entire year and then here’s the Gap like this is this is what everybody is citing as your numbers is this number that’s up here you know which one is not changing on a daily basis zero percent changes fix flat for months on end same thing here same thing here growing out of fixed rate of 0.3 like this is not a model that’s responding to changes you know we have massive changes that are going on in this network and what I’m trying to do is like you said we’ve got known knowns and we’ve got known unknowns we’re trying to verify this and I’m looking at your data here I’m saying well I can’t verify what is the actual you know electricity consumption for the entire industry but I can tell you with certainty that this is wrong there is no way that a fixed volatility you know a fixed growth rate of zero percent or zero point three percent per month is accurate and there’s no way that an industry average that shows that the  industry is consuming around 196 watt per Terra hash when just prior to this bull run that same industry was operating about 65 watts per Tera hash there’s no way that that data is accurate and that’s the point you know is there a way to track this better absolutely but you know there’s a lot of different ways that we can argue about this and we can debate the best the best methodology for trying to calculate the electricity consumption but you know we also have to verify and you know what we can see here by trying to do a comparison because we know the network hash rate estimates are pretty accurate especially on longer time frames as I talked about earlier the electricity consumption is what’s unknown and when you blend them together you get that what per Terra hash and this is a clear indicator that something is very broken in the model or purposefully manipulated and that’s when I see periods of volatility for months on end I mean this this extends almost two full fiscal quarters zero volatility in 2022 when we had massive volatility in the underlying bitcoin price there’s no change until we have the Bitcoin collapse you know breakthrough through 30k down to 20K here in 2022. That’s the only time this. changed and that’s how I know that the data is wrong 

Digiconomist 00:33:16

So I think maybe just to start with this roughly three states in which my model can be in  that can either be this bull market state where the market or the energy consumption of the market is just going up as miners expand their business well the price allows them to put more machines into operation and so there is a state where it’s profitable to add more machines to the market that is when no let’s say the cost of mining are very low yeah so when the profit margins are very high you are going to be expecting that miners are going to be using or employing more machines if you cross the 60 percent how do you have this interesting zone between 60 and 100 percent where you get a flat energy consumption estimate because in that zone what’s going to happen at least according to the model is that it doesn’t really pay off to invest more in more machines but at the same time keeping the machines that you have running still generates money and you need certain amount of money to you know get these new machines and you need to make the money on those or you want to get you want to earn those machines back but at some point the profit margins may become too thin to for that to be an attractive option but at the same time you’re not shutting down your machines that’s like this the 60 to 100 percent Zone and then you when you hit the 100 percent that’s when the energy consumption just dives off a cliff and that’s where you know miners are not just not investing in new machines but they are just shutting down their existing devices now of course there are some nuances in reality because adding new machines may always be profitable and minus 19 Pro for a long time and maybe probably even now adding those machines to the network is still going to be profitable but then if you turn on those machines how you’re going to also witness some machines dropping off at the tail end so it can be the case that new and more power efficient machines are still coming off online while all the relatively inefficient devices are dropping off at the tail in any case if that that occurs then hey you can be at a state where energy consumption is sort of stable but that’s roughly the three states that my model can be in so you either have growth you either have stability where you know energy consumption going up is not expected or when you hit the 100 percent at least based on the cost input of 5 cents per kilowatt hour it doesn’t pay off anymore to keep the machines running now that that’s just where the General State of my model I already mentioned that during the China ban you probably shouldn’t be looking at this number the carbon emission number was probably still valid during that time but the energy consumption estimate certainly wasn’t and then when you look at the what part of our estimate that you just showed from starting from 2020 to recently one of the issues I’ve been having with that is that the starting point is probably too low because back in 2020 I did manage to do somewhat of a verification it’s not you know ideally the way you verify this is you go to all miners in the network you’re after energy consumption you add it all up and then bam you have your perfect number now unfortunately that doesn’t work especially nowadays I mean China kicked out these minus 20 of the network at least according to Cambridge is still operating in China which means they’re operating illegally according to their most recent estimate which is probably outdated by now as well 15 of the network was in Kazakhstan the majority of that also taking place illegal it just means that you know at least back in the start of 2020 sorry 2022 when Cambridge put out the last update to this data a third of mining around the globe was happening illegally so you can’t just go to them and ask like what’s your energy consumption they actually want to stay under the radar and you can’t you can’t really do a proper survey that’s problematic but what I could do back in 2020 you know when how in that time all these major Hardware manufacturers wanted to go and do an IPO well Bitmain was one of them still the largest manufacturer I think out there today that also wanted to do a lot and it put out a lot of information regarding the machine the machines they produced in the prior years and if you have that information you can kind of do a adjusted minimum calculation whereas you still calculate the minimum energy consumption estimate for the network except you correct it for the amount of machines that have been produced according to the IPO filings and at least following that approach I established that over 2020 both my own model and the Cambridge model were showing too low results for different reasons the Cambridge model was severely overestimating the share of newer machines and underestimating the share of all the device especially as nines and my own model was simply too pessimistic on the time lag and the tired amount of time it takes to get new machines up and running so and now we’re looking at a what Patera hash where we can always establish okay you know if you look at the start of that number is probably way too low yeah so that is a bit of an issue here because you do hey you kind of expect when you look at the number to go down over time but in this case and the starting point is already too low and then of course you have this weird situation in 2021 where China kicks out these Miners and then the energy consumption the what Patera hash estimate just goes through the roof because my model breaks down during that specific event there’s no competitive markets at least for a short while so in terms of verification what can we do what can we do I do agree that it can help you as a sort of you know sensibility check but at the same time given these constraints it’s also very difficult to put any hard conclusions along with that about whether these marbles are right or wrong and I think it’s just not a very solid way of doing verifications.

Stephan Livera 00:42:19

Okay but I mean let’s take that I mean then why are these models are being used to sort of Drive fear in the media amongst people who do who don’t understand this and if you’re you yourself are saying well certain aspects of the models can’t easily be verified because yes some of the Midas miners would prefer to hide that information or its competitive information then why is you know are you are you okay with these numbers being used to basically attack the industry. 

Digiconomist 00:42:56

Well, you know the thing is and one of the things that I often tell people who are interested in this is just look at the lower bound you know there’s no discussion about the lower bound and if you take that number you have plenty to go on for your policy discussions and we can ever you know if you look at Cambridge today they’re saying okay the Bitcoin network is consuming 140 terawatt hours of electrical energy per year the lower bound is 70. well that factor two isn’t really going to make all the difference from the policy perspective the factor two is way too low because ultimately what policy makers are concern about is you know they look at Bitcoin and they’re looking at the existing Financial system and they see that okay you know how Bitcoin is consuming somewhere in this range of electrical energy consumption at the same time the amount of electrical energy consumption related to The Current financial system is estimated to be in the same range as this number there was a very recent paper in the Journal of cleaner production it actually put the total energy consumption for the financial industry so that means branches ATMs everything related to banknotes and cashless payments at 128 tailored hours of electrical energy consumption a year and you know their concern is going to be like okay you know whether Bitcoin is going to be consuming 70 or 140 kilowatt hours you know ultimately Bitcoin is using all that energy while the network is only processing 100 million transactions a year well the regular Financial system does 2.1 trillion cashless payments plus unspecified amount of cash transactions and that’s and that’s where the disproportion in this starts to come in and the factor two doesn’t you know doesn’t fix that 

Stephan Livera 00:44:49

Okay so okay fine but even on that point I think it also depends on what you think are the consequences of the monetary standard that we are operating under right and so this is where I would say and Ben may have his own views on this as well but the way I see it is you would compare a Fiat money standard versus a gold standard versus a Bitcoin standard and there are certain consequences of living on a Fiat standard and those are not just the banking industry you know you could say well what about the military what about other aspects what about other aspects of society that are impacted by us living on a Fiat standard so at least that’s how I would answer that question I’m curious how Ben you think about it 

Ben Gagnon 00:45:19

Yeah I think at about a little bit more differently especially when it comes to transactions like as a miner I think my primary role is providing security to the network and secondary is processing transactions it’s more important that nobody gets their Bitcoin stolen out of their wallet then somebody gets like the most rapid transaction speed that they can possibly have and when we look at how Bitcoin works as an actual payment medium you know Bitcoin transactions are comparable to Swift and lightning transactions are comparable to MasterCard you know nobody is out there doing 100 million transactions every day you know on the Swift Network for cans Coke right there are different payments mediums and different payment settlement networks for different kinds of transactions with different purposes and different values associated with those transactions that give different degrees of certainty and are also associated with different processing times so you know that’s the more comparable and when we’re talking about you know just transactions on layer one that ignores all the transactions that are happening on Lightning Network and that growing ecosystem where is which is really where the payments are supposed to be being done especially for smaller goods and services and the second thing is that sorry I lost my train of thought there 

Stephan Livera 00:46:36

So not just the lightning Network transactions 

Ben Gagnon 00:46:41

You’re ignoring everything that’s happening on the exchanges right which is which is probably the vast majority of actual Bitcoin moving between people’s balances is it actually just happening on the exchanges people just trading every day like that’s the vast majority of transactions is the buy and sell on the exchanges and it’s all being you know ignored so I mean personally I don’t really think about it in terms of the transaction fees I think it’s a pretty I don’t think it’s a very good metric to look at things I think it skews the way that people see things and it’s not really accurate with regards to what’s actually happening on the ground and how people are using Bitcoin and how people have been using Bitcoin for years but going back to your point there I’m very glad we can agree on we found some agreement here your model breaks down in Bull markets and the that’s one of my big challenges with this is because nobody really cares to be honest with you

Digiconomist 00:47:50

When there is no competition that’s when it breaks down not necessarily in all bull market 

Ben Gagnon 00:47:57

Okay well okay so we found some agreement there it the situation is that like look Bitcoin goes down to 16k nobody talks about bitcoin’s electricity consumption bitcoin’s at 67k in a bull market everybody’s talking about Bitcoin electricity consumption and so your model is designed to inflate and overestimate at the time when people have the most attention for this statistic right when it comes back to reality nobody cares when it’s at those inflated stages that’s when everybody’s paying attention that’s when everybody’s writing the Articles and that’s when everybody’s citing the main estimate nobody is citing your lower level estimate I have yet to see a single newspaper article that cites your lower bound not one and you know it’s all on your main bound estimate every single article every single policy paper everything is on Main bound estimate and that’s the one that has the vast majority of the problems and so you know there is no there is no certainty there will never be a certainty hey today this is exactly the amount of electricity that the network is consuming hey this is the breakdown of the machines like this is something that’s changing every second of the day because there’s a lot of volatility both in you know different site situations company situations mining economics there’s a lot of volatility no one will know for sure what we can do is like any good scientist is we can rule out what is obviously false right we can’t prove that this is necessarily true but we can prove something to be false and that’s what these metrics do these metrics prove something to be false you know what can we do to improve that I think there’s lots of different ways to change that to improve that to make it actually reflect what a company like bid pharmacist doing on the ground from an operational perspective I mean my model is all based on what we do as a company because you know it’s designed to help us inform our decisions are we being competitive enough do we need to improve our efficiency what are other people’s you know cost position like we are trying to compete on a relative basis we were of the firm. Belief that you know if we’re in the lower quartile or lower third of low-cost producers we’re effectively hedged against you know lower mining market economics at least relative to our peers and so you know these sorts of things we can we can verify what doesn’t work and the Walker Terra hash is a great way for verifying that that something doesn’t work when it comes to you know other estimates too like there are other estimates that we have here I’m not even going to get into the carbon estimates because that is a that is a really there’s a really wonky math that I don’t think anybody has figured out in any industry there’s a lot of different definitions for how to measure that how to track that and then when you look at you know especially if you don’t have that specificity on the data set you don’t know where the electrons are going anywhere I mean you look at like our operations in Quebec it’s all powered by Hydro but if you look at us as Canada you might be including a bunch of that gas into our mix right if you look at the United States as a whole you might be looking at a bunch of Nat gas and coal and other things in the mix but if you look at where miners are specifically locating behind the meter and nuclear power plants behind the meter of solar panels behind the meter at wind farms like you’re going to have a very different view of that but we like you said we don’t have a whole lot of that data outside of the public companies who are making press releases and are being audited to make sure that that information is accurate but the public companies I think are starting to change the space because there are now a significant amount of the hash rate it’s a meaningful sample size you know it’s well over 20 of the network cash rate is owned and operated by public companies at this point this is a meaningful sample size that is verifiable information and it’s audited information and I think that probably is going to be a good basis for things rolling forward certainly there’s you know things that have been proven wrong need to be adjusted and if you know we agree that you know the model breaks down in certain economic conditions then maybe the conversation should be why is it breaking down on those certain economic conditions and what can be done to the model so that it doesn’t break down in those economic scenarios 

Digiconomist 00:52:48

Yeah, sure I mean you know when it comes to the question which model should you like more a little bit of a fun fact is that my model gets cited mostly by crypto media during bull markets because my numbers are always in boommark is lagging the Cambridge index because the because of the embedded lag which is not in the Cambridge model so if you look at the headlines earlier this year you will see Headlines by Barons and others saying oh Bitcoin is consuming a record amount of energy consumption that’s not coming from me that’s coming from Cambridge and if you put the numbers next to each other and next to the price you will see that fight goes up the Cambridge model is going to be the first one so if you’re concerned about what’s going what are people going to be looking at in Bull markets well the Cambridge model is probably going to be in the one you like this list but the Cambridge model has the advantage that they don’t really look and you know is it you know they don’t they don’t they don’t do the energy consumption per transaction that a lot of people in the Bitcoin world and crypto World hate but you do need some kind of metric to capture that you know Bitcoin isn’t as large at The Current financial industry so if we estimate it to consume as much power as the rest of the financial industry with everything that’s going on cash and digital payments and all the offices that are out there and then then we need some additional metric to show that you know this this is a well the proportionate or not and that you need some kind of relative measure because Bitcoin is still growing and well the regular financial industry is growing as well.

Stephan Livera 00:54:30

Alex I think to be fair here this is something where I’ve seen you commonly say this even in your tweets where you commonly cite this three to seven TPS transactions per second but we all know that’s not really that’s not comparable as Ben was saying as many Bitcoin people are saying that’s we know as an example as I’m sure you know every 10 minutes on average there’s a Bitcoin block those blocks have on average about 4,000 transactions each three or four thousand maybe five thousand at the max so it’s not that it’s not like even if Bitcoin had greater adoption that it would go much above that because that’s basically the theoretical maximum of to be clear on-chain transactions per block now we know that per on-chain transaction there can be multiple payouts so for example if an exchange is doing one on-chain transaction but paying out to 100 customers is that one transaction or is it really 50 or 100 and then don’t forget that’s again not counting lightning that’s not counting all these transactions that rarely ever hit the chain so how can you defend this three to seven TPS number when you are in my view unfairly conflating or comparing that with swift or with you know or with sorry Visa Mastercard.

Digiconomist 00:55:36

You meant you mentioned the lightning Network as a as a payment layer but the thing is had the most recent estimate that I saw for the lighting network was that it was processing one transaction a second and that estimate is a little bit outdated but it was coming from some crypto research institution and if you’re interested, I can send you the link after this conversation but that doesn’t add a whole lot on top of the handful of transactions that the Bitcoin network is doing

Stephan Livera 00:56:07

It adds a lot more in theory because what happens is a lot of people will extrapolate right they’ll say oh look three to seven TPS per second oh let me just scale that to the entire existing modern day payment system and just naively quote unquote naively scale it when lightning could do a lot more than one TPS per second and I think it’s quite clear that it is doing a lot more than one DPS per second if you think about a lot of these payments that are happening on for example podcasting value for Value Nostra zapping and all of these little things that are just not being not able to be so easily measured right

Digiconomist 00:06:43

Sure but you know there hasn’t been any new number out there that says okay there’s this many transactions happening on light Link so we can add them and even if we did have a number it’s now it’s not going to be and we’re not going to be talking thousands now in order to bridge the gap with the regular Financial system you need in order to have a comparable energy consumption per transaction you need thousands of more transactions per second not just a few more hey if you have one or two more per second yeah okay that’s great but that doesn’t matter the lighting Network could do a whole lot more is I think is a different discussion and we can probably have a separate podcast about that because in the end in order to use the lightning Network well you still need to go through the main chain and well if you don’t do that then you’re going to be dependent on these intermediaries again and then that’s kind of what we try to avoid with Bitcoin I mean the whole thing about Bitcoin is that it’s decentralized peer-to-peer money and that’s the whole core of the of the system and actually you know I always say and people are surprised to hear that that very concept is the very thing that I personally always did find interesting I wouldn’t be active around cryptocurrencies if I didn’t at some point found that a very interesting idea it’s just that in practice we’re seeing that a lot of people aren’t using Bitcoin in that way they’re leaving their money at exchanges and if you try to make ahead if you try to facilitate better peer-to-peer interactions you’re limited by a main chain that is just doing a handful of transactions per second and you still need to go to that main chain in order to get to the second layer and it’s still very debatable what is the real added capacity of the lightning network if your account for other limitations that’s something that has to be seen over time I mean it does the efficiency is not a fixed value hey it’s something that can go up and down over time you know we’ve seen people ever since 2015 state that the energy consumption per Bitcoin transaction average is x amount in 2015 they specifically said like okay it’s as much as a U.S household for a period of one and a half days now if you were to look at the same metric today you’re going to conclude oh now that’s two months or it went back a little bit now it’s just one month but it’s an Energy Efficiency is a value that evolves but one of the key problems that Bitcoin has is that energy consumption is closely related to the price the higher the price goes the more mining activities will typically be going on because miners will simply have more resources to deploy while the at least the on-chain capacity is fixed so the payment capacity is not keeping up with the growth of the energy consumption and that is a trend that needs to be completely reversed yeah what you want to have going forward is that there is no more growth in energy consumption and a lot more capacity for transactions and then the Energy Efficiency can improve the fastest way to get the Energy Efficiency down would simply be to drop mining altogether but that’s also a very sensitive discussion.

Stephan Livera 01:00:05

Yeah, look I mean obviously I think it just really ignores a lot of the security model of Bitcoin it ignores the reason you know it ignores a lot of things about how Bitcoin works it would be like saying oh don’t fly somewhere on a plane just ride your bicycle there well no like it’s a misunderstanding anyway Ben do you have it do you want to have a response. 

Digiconomist 01:00:29

I think we’re already running a little bit out of time so and again this is something that we can devote an entire podcast to if you start to debate proof of work versus proof of stake because yes there’s no question about you know ethereum on pool for steak since last year consuming a lot less energy but their landscape changed in more ways than one and they don’t just consume those energy they also change their security model as you call it the only thing we know is that they have been they managed to run uninterrupted since they made this switch but there’s no guarantee for the future I just want to make one last note in the context of the conversation we’ve been having and that is that you know when we also need to put these estimates in a broader context you know what we can do for cryptocurrencies is unrivaled there is no other industry where every single day you can just take a  little piece of paper and you start very simply making a very easy calculation what is probably the likelier energy consumption of the network especially the lower bound that’s a certainty that you can just calculate every single day and then with a little bit of assumptions you can calculate a more likely number but you can do it every single day and you don’t need a lot of inputs to do it there is there is no other industry out there where we have the same capability so if you’re talking for example about data centers in general the estimates that are there they have a much bigger range you know they will range from 100 or an hour all the way to a thousand tier one hours per year and that’s because it’s much harder the quality of data available is much less and there is still room for improvement what we’re doing in Bitcoin I’m not saying that what we’re doing in Bitcoin is perfect and I think that maybe we can have some agreement there but compared to whatever we are doing for every other industry out there it’s unrivaled transparency we can do these calculations on a daily basis that we can’t do it for anything else yeah 

Ben Gagnon 01:02:36

I absolutely agree that it is unrivaled transparency in the in the Bitcoin space which is why everybody can go out there and verify these numbers it’s incredibly frustrating to me that nobody does you know news journalists are not going to go out there and verify any of this math they’re really just looking for numbers to cite that confirm their headline and the story that they’re trying to write I mean this is something that I’ve seen dozens of times speaking to mainstream journalists literally do not care they’ll say at the end of the interview hey that’s really interesting but that’s not the story we’re trying to write and they move on and they’ll go on and they’ll cite something like digiconomist or possibly Cambridge as you pointed out can get some citations too that I don’t like the transaction fee methodology because it again it’s not really what I think we’re doing here as miners I think we’re providing security first and foremost I think transactions come secondary and when we look at know electricity consumption I also disagree that electricity consumption for the network should go down over time I fundamentally disagree on that point I think and then she consumption should continue to go up you know when we look at the electricity consumption for the for the industry as a whole like I said we’re a fraction of one percent you know the exact number nobody’s entirely sure but what we’re talking about somewhere in the range probably 20 to 50 basis points right in terms of world electricity Supply that’s going to Bitcoin mining when we look at what are the sources of electricity how it’s generated how it’s distributed and transmitted you know who are the biggest consumers where does that electricity go the number one source of electricity consumption worldwide is waste and the reality is that I as a miner am not looking to go to a place like Manhattan and set up a Bitcoin mine you know downtown like it’s the energy is too competitive I’m not going to get a price that’s going to make it profitable for me so we go to these remote areas where nobody’s invested or people invested decades ago and it’s been sitting vacant for years you know in Quebec we have six of our seven sites are in former industrial plants that have sat vacant for years or in some cases decades right this is this is hydroelectric infrastructure that was built to power heavy industry which is gone left moved on and the you know the snow still Falls the rain still Falls the water still flows through the dam the power still being generated but the demand is gone the distribution doesn’t exist and you know you have to transport that thousands of kilometers or miles away to get to a market that would actually consume it you’d have to agree with the different states the different countries the different Regulators you’d have to line up the capital to build the transmission lines you have to like these are process processes that take a long time and the situation of Quebec some of these deals have been going on for over 10 years and they still have not transmitted a single watt of power and so we have a situation in Quebec where there’s I can’t remember the latest number but the last time I checked it was 40 terawatt hours a year was being spilled over the dam that’s equivalent to four and a half gigawatt hour 4.5 gigawatts of power continuously every single second of the day and this is water that this is power that could be generated but there’s no local demand there’s no Local transportation to bring it to a market and so they’re spilling it over the side of the dam you know that’s enough to power about a third to forty percent of the Bitcoin Network and this is this is just a source of waste you know when what happens if we go in there with Hydro Quebec and start monetizing all this waste electricity well Hydro cut back is going to have greater profitability they’re going to reinvest that into the province of Quebec in terms of social programs roads highways schools hospitals whatever kind of social infrastructure they find or further renewable energy infrastructure you know right now they’ve got a plan to continue growing their renewable energy generation capacity by 2040 and they’re sitting on massive excess capacity right now that they’re not monetizing they’re wondering how are we going to pay for it in 2040. well geez you know we as an industry could continue to grow we could grow 100 fold and just be consuming marginal cost electricity marginal electricity that nobody else wants wasted electricity that would otherwise be on the line and so you know in that point and this is this is where I think the industry is going the idea that you know everybody’s going to be operating at six cents or five cents you know in 2030 I think is absurd you know everybody is moving towards marginal cost sources of energy otherwise overlooked underutilized sources of energy that would otherwise be wasted because if that energy had any other demand its cost is going to be too high by period you have to go with energy sources have literally no other application and therefore the cost is going to be incredibly low and in this case Bitcoin mining is solving a problem that the electrical industry never thought they could solve which was how do you monetize and make use of the gap between electricity Supply and electricity demand because you always have to have electricity Supply exceeding electricity demand if it ever drops below electricity demand that’s when you have a brown out or a blackout right and so you always have to have this excess capacity on the line because you don’t know when somebody’s going to turn on a light switch turn on a washing machine you don’t know when you know people are going to power up this this industrial cooking oven or whatever they’re using their power for so you have to have that excess capacity on the line and what Bitcoin miners are proving again and again is that that’s the energy that we’re looking for and if we’re looking for those sources of energy we are very much incentivizing the creation have more energy generation capacity especially on the renewable side it’s something that you see throughout most of the publicly traded minors a lot of this is going to new renewable projects because the economic incentives on renewable projects are incredibly screwed up if you look at where the miners are going in in Texas in the United States they’re all going to one load Zone in urcot it’s called West Texas and why are they going to West Texas well they’re going to West Texas because they’ve built up all these Hydro or sorry not hydroelectric they built up all these solar panels and wind farms in West Texas with no demand and no transmission capabilities and so why are they building them there because the subsidies and the natural resources and the cheap land and the regulatory footprint of building the west Texas is relatively competitive and so they’re putting massive investment in renewable infrastructure billions of dollars of investment renewable infrastructure into an area where there’s no demand for that energy infrastructure at all and it’s only been financed because of the subsidies and now Bitcoin miners are coming in here and we’re saying okay well let’s actually try and improve the economics of this project because there’s a big gap here between electricity Supply that’s being generated by this plant and electricity demand that’s on the line there’s no reason why we should be building you know continuously gigawatts more projects in West Texas without distribution and transmission and local demand but that’s where that’s where the projects are going and I think the free market works better like Bitcoin is not powered by subsidies Bitcoin is powered by private Capital trying to allocate Capital efficiently and we’re going to places where that energy is wasted it’s the renewable energy sector which is funded by subsidies and is growing out in a way that doesn’t make sense I mean there are there are numerous areas in the United States that are run entirely on carbon like Puerto Rico is my favorite example it’s an island that’s run entirely on diesel you know it’s a very meaningful population around three and a half million and you know why are people not installing solar in Puerto Rico why are they just installing in Texas where they’re getting Texas you’re getting negative energy prices Puerto Rico they charge 32 cents a kilowatt hour I mean I it doesn’t make any sense Bitcoin miners are not in Puerto Rico consuming diesel we’re sitting there on these tail ends of the distribution curve absorbing the inefficiencies in the market and by absorbing those inefficiencies in the market we’re actually making a stronger Market we’re making a more resilient market and we’re improving the economic incentive to drive a transition to Renewables and I think we see this everywhere every like we see this in Paraguay with the tapu dam we’re seeing this in West Texas we see it in Quebec there are certainly examples of you know funding you know non-renewable generation as well but mostly this is going towards renewable because you don’t want that underlying volatility of the fossil fuel price you know the marginal cost to generate a kilowatt hour from hydroelectric power plant is zero you know the things already been built the capital costs are already there the marginal cost to generate one extra kilowatt hour zero the marginal cost to generate one extra kilowatt power on a Nat gas turbine or a coal power plant is not zero and this is where the entire economics are going they’re going long run marginal cost entirely overlooked sources of energy in which case consuming larger amounts of electricity is a good thing and it also means too Alex that that the economic lifespan of those machines is going to get pushed out longer and longer and longer because the lower we can reduce that cost of energy the longer that light longer you know you can generate profit with that minor and so you know I don’t want to open up a whole can of worms here but you know the minor lifespan is like five to seven years predictably in terms of a useful a useful lifespan and that’s only going to get longer and longer and longer as people move to Marginal sources of electricity so this is this is a very powerful Market it’s a very powerful economic incentive and what I don’t like is I don’t like a bunch of misleading figures and kpis that are prohibiting that progress because this is the best thing that’s happened to the energy industry probably since we invented nuclear power

Digiconomist 01:12:48

Okay so that would be what I what is known as debating as a Gish gala where you just screw a lot of arguments all together and you leave your opponent with well way overwhelmed to be able to respond to everything making a team as if some of those arguments actually have Merit but I will try to respond to some of them and one of them is that you know in in Quebec he talked about minus using excessive amount of renewable fixing efficiencies in the market Quebec actually imposed a hard quota on the amount of energy that miners are allowed to use simply because you know we’re you know this is why you enter the complicated world of grid management and what they are dealing with is that okay they have an access for a big part of the year but then at the same time during the summer months winter months they also have Peak demands so they need to serve of demand Peaks During certain times of the year and they need to keep their access available during for serving those periods and the thing with Bitcoin miners is that well they typically like to consume power on a 24 7 basis I mean you know even in in China before where a lot of these mines which

Ben Gagnon 01:14:15

Is just one quick point on that one I mean Hydro Quebec has excess capacity basically all year round and two every single Miner in Quebec operates on a curtailment program with Hydro Quebec and so during those coldest hours of the Year where that power is in you know shorter Supply we all turn off we all turn off every single one of the Bitcoin miners in Quebec turns off almost simultaneously and restores that power to the grid and so you know really that’s not even a shortage of Supply it’s more a accounting deal where a lot of different Municipal Utilities are working with the provincial utility and they’re trying to manage their Peak load with the provincial utility this is more about managing the accounting and the economics of it as opposed to a shortage of supply and then there’s one more quick point on that the moratorium that’s in place the 300 megawatts that came into place because there was 18 gigawatts worth of power applications that went into Quebec in 2017 and 2018. 18 gigawatts at the time the industry was consuming four and a half gigawatts right and so you know this was a this was absurd the amount of applications that went in there and of course it created a huge amount of fear but you know if they took any chance any time to look at the numbers and say hey the network industry is consuming four and a half gigawatts we’ve received applications from a bunch of unknown Chinese people for 18 gigawatts these aren’t real

Digiconomist 01:15:41

Yeah, okay and that was actually when I was in contact with one of your colleagues to help show that that total amount of request was completely unrealistic but you know I I think that now this amount is really kept and have we really need to look at okay how does this look for the whole network and you know if you look at for example the US New York Times recently did it in a separate analysis they looked at okay what’s going on in the United States with the mind is using energy over there they did a marginal analysis or a consequential analysis and what that does is it looks at okay what is the real carbon impact of adding more power Demand on a grid more Renewables being used or is it more fossil fuels at least in that analysis that they did they found that almost U.S grids Renewables are getting prioritized and the X and the additional power demand coming from crypto minus is mostly being served from fossil fuels and they actually concluded that the amount of fossil fuels going into the network over there was going to be reaching around 90 percent which is very much higher than what we conclude or what I in Cambridge previously concluded because we tend to look at Great averages how we look at the grid and we take a great average to do our carbon emission calculation and taking a great average is not accounting for all these complicated Dynamics so in some cases it may work out better but at least the general Trend seems to be that it works out worse now if you happen to be one of the ones that are  exclusively using hydropower throughout the year then well that’s great I have a lot of the network that doesn’t apply but then here you have other things to consider you mentioned lifespan of devices there’s electronic waste lifespan increasing lifespan of device as well you could say that’s a good thing because then you have less electronic waste same time it means that you keep inefficient machines operating for longer so then you also end up with higher energy consumption and about working together to improve the amount of renewable generation on the grid well renewable energy projects are typically wrong to projects and ironically you know I was on a stage with bit farms in 2019 at the consensus conference and we were talking about it and I think I literally said at the time that Bitcoin miners make terrible Partners to build out your energy infrastructure for the very simple reason that Bitcoin miners are very dependent on extremely volatile assets so if the asset happens to go south tomorrow then your business partner is going to be gone and well it’s not just me making that note it’s actually been repeated I think last year by feature ratings we also want utility companies to be very careful about interacting with the mining industry as a whole because there is a financial risk involved for them if their business partner suddenly disappears overnight that’s a non-zero risk if you’re dealing with Bitcoin I mean what I do in my models what I can do is I can predict somewhat how the energy consumption is going to evolve given a certain bitcoin price but I don’t attempt to predict the price and I don’t think anyone can predict the Bitcoin price so this isn’t if you are going to if you’re in a utility company you’re going to be involving yourself with Bitcoin miners you’re taking on that risk as well you’re exposing yourself to a highly volatile asset which might not be a good idea but that’s an also a completely separate discussion and by the way by now I reserved an hour for this this talk and we already passed that by 20 minutes so I don’t know if we need to follow up on this on a separate podcast but I kind of need to leave 

Stephan Livera 01:19:50

Okay all right all right well I guess we’ll finish it there thank you both for joining thank you Alex for being gracious with your time and accepting the criticisms from those of us in the Bitcoin industry and thank you Ben for your time as well we’ll leave it there and we might just have to carry on our disagreements on Twitter or on another podcast some other time so thank you both demand I’m always willing

Digiconomist 01:20:16

If there is a high to join again the second one.

Stephan Livera 01:20:18 

 Thanks, guys and I will put the links in the show notes for listeners thank you 

Ben Gagnon/ Digiconomist 01:20:19

Okay thank you

Stephan Livera 01:20:20

So, I hope you enjoyed that and let me know what you think whether there should be another follow-up debate episode and of course, make sure to share this one out there so people can hear different views on Bitcoin mining energy thanks for listening and I’ll see you in the Citadels.

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