The Economic & Environmental Cost of Bitcoin (6 of 10) – Economic Inputs & Drivers

Welcome back to TEECOB
I’m Hass and you’re watching part six of our 10 part series today we’ll be
looking at the factors that drive the economic cost of Bitcoin. this is one of
the longer episodes of the series so strap yourself in. Before we get started
though I’ll keep you in suspense for a few more seconds as we emphasize what I
think is the central driver of economic cost that consistently and constantly
relentless Network hash rate growth let’s take a quick look at how the
network’s growing since 2009 the dramatic drop in dollars per gig
hash and watts per gig aha discussed in part two of the series has spurred
extraordinary hash rate growth that said this isn’t exactly anything new have a
look at these numbers the network has been growing an average of 9% every
fortnight since 2012 an average of 7% every fortnight since 2014 an average of
5.9 percent every fortnight since 2016 and 7.2 percent per fortnight for the
year-to-date as a result of the constant hash rate
increases the difficulty cycle is rarely 14 days long and based on rough
year-to-date data which is about 7.2 percent increased per cycle the
difficulty cycle is closer to 13 days or 312 hours should Bitcoin ever scale and
reach its potential it is almost certain that mining equipment will exponentially
increase in processing efficiency in line with Moore’s law for at least
another five years and exponentially increase in power efficiency in line
with kumys law for at least another 25 calculating the cost of Bitcoin can be
modeled quite simply through the relationship of these six variables
along with the network hashr a capital expenditure which I’ll be referring to
as capex from here on in operational expenditure or op X the difficulty cycle
length minor revenue electricity costs and the mining mix capex is the capital
expenditure required to maintain a proportional share of mining rewards
upon an increase in difficulty the best way to explain this is with an example
let’s say that a mining pool currently controls 30% of the network with a hash
rate of a thousand Peter hash per second the miner forecasts the hash rate growth
for the period will be close to 7.2% resulting in a total hash rate of 1072
pay dashes therefore in order to maintain their 30% of the network they
need to bring on an additional 20 1.6 Peter hashes of power for the next
difficulty cycle there are other elements of capex too however their life
cycles are much longer than mining equipment these elements of capex can
also be deemed as sunk costs in many cases and don’t affect future decisions
the capex categories are as follows Bitcoin mining equipment which typically
lasts only a few months before their unprofitable power supply units for
mining equipment which typically lasts as long as the mining equipment itself
due to planned obsolescence with hardware manufacturers regularly
changing the required PCU wattage with each generation of miner and finally
server racking and data center construction and fit out which typically
lasts for decades server acts and data centers could also come under
operational expenses or op X if the data center is being rented or leased topics is the expenditure required to
remain operational its scale this is effectively just the cost of power to
the mining equipment and air-conditioning within a datacenter
it’s estimated that cooling can consume thirty to forty percent of overall
energy consumption with 21 percent a benchmark for the most efficient cooling
systems in the world technology such as immersive cooling will reduce energy
usage but as a trade-off for a large initial capital outlay for the purposes
of this model will assume cooling contributes to about twenty percent of
the total power consumption in line with the laws of perfect competition and
technological gravitation towards maximum efficiency this one’s pretty
easy whatever hash rate increases by cycle
length decreases by so for example if hash rate goes up 10% a block will be
produced about 10% quicker as mentioned at the start of this video the cycle
length is about 13 days or 312 hours this is a fixed number there are 2016
blocks of 12 and 1/2 bitcoins mind every difficulty cycle for a total of 25,000
200 bitcoins in addition to the mining rewards though mining fees need to be
counted to the segment walls of the first half of 2017 had fees averaging
over 200 bitcoins per day and the fee madness during the hype cycle of
December 2017 and January 2018 had a revenue average of over 550 per day over
these two months with the Segway wars over and the hike now well settled a
relatively consistent 50 bitcoins per day has been earned in the six months
leading up to July 31st this results in a total of about 650 bitcoins collected
in a 13 day difficulty cycle to evaluate power costs and emissions we
don’t have much of a choice but used worldwide weighted average figures due
to the dispersion of miners all over the world that said thanks for the rules of
perfect competition particularly perfect factor mobility miners will just move to
the place with the cheapest electricity costs although the average rate for u.s.
industrial companies for power is about seven cents per kilowatt hour a safer
assumption for Bitcoin miners will be closer to three or four cents for the
reasons you just mentioned there are several documented case of the largest
Bitcoin operations paying four cents a kilowatt hour with reports that bit main
was receiving a 2 cent per kilowatt hour rate in their yunnan facility and one
particular CEO claiming cost of electricity of only 1 point 7 cents per
kilowatt for their mining operation in Moses Lake Washington in the USA there
are two types of – chip fabricator – and retail – retail – can be split further
into another two categories large retail miners and small and individual – small
and individual miners can also forego buying hardware themselves and instead
purchase mining contracts on the cloud due to intellectual property and some
economies of scale chip fabricators or chip fabs can mine for significantly
cheaper than retail – typical gross profit margins in the semiconductor
industry of average over 45% over a four year period with the most profitable
ones close to 60% the computer hardware industry averages around 35 gross profit
margins are used since operating expenses and depreciation and the like
and dealt with separately in the model it is assumed that miners pay no tax
that is they retain all coins that are mined and/or their asset depreciation
costs are high enough to offset a large amount of tax on the revenue they’ve
made from selling mining Hardware due to the lack of competition in the asset
hardware space margins would likely be 50 to 60 percent obviously there’s a
limit to the margin that can be made on mining hardware as the customer base is
quite savvy and can easily calculate profitability of their purchased miners
at particular price point for the purposes of this study
it’ll be assumed that Bitcoin a sick man factors make 60% gross margin on all
Hardware salt scums the question of chip fabs mining
on their own equipment and how much equipment has made it out into the
market for large scale and small scale – according to an analysis by Sanford C
Bernstein and code it was estimated that bitman captured 75 percent of the market
share in hardware sales in 2017 Kenai creative captured 15 percent of the
market and other manufacturers made up the remaining 10% bit main CEO has
stated that the company earned 2.5 billion in revenue for 2017 so we can
size the market for mining hardware to be about 3.3 billion dollars based on
the 2017 average price of an s9 minor of around $3,000 one could draw the
conclusion that about a million s9 equivalent mining units were shipped out
in 2017 the current hash rate and price per s9i this model estimates that
roughly 115 million dollars is invested in more mining power every difficulty
cycle or around three and a quarter billion dollars per year drawing on the
80/20 rule again we can put chip fab somewhere in the ballpark of 20% of
direct hash power that said with bit main administering at least two mining
pools and pool and BTC com providing 40 odd percent of hash power it is likely
that they contribute about half of that power directly or more throwing the
other chip fabs in proportion to the sales figures mentioned above as well as
any chip fabs that don’t sell to the public and will assume that chip fabs
provide at least 35 percent of direct hash power for this study due to the
laws of perfect competition discussed earlier it can be assumed that only the
most profitable miners are switched on at any given time and that when a new
generation of mining equipment is released equilibrium is reached very
quickly where all miners are operating at a similar cost basis next week we’ll have a look at the
drivers and assumptions used to model environmental costs and after that
you’ll be ready to start calculating as always thanks for watching click like
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