High energy use is increasingly a feature of many technology processing industries, including quantum computing, artificial intelligence, natural language processing, and cryptocurrency mining (cryptomining). For example, data centers and Bitcoin mining alone consume 0.9% and 0.5% of global electricity, respectively.
This electricity consumption results in what economists describe as externalities, or the costs and benefits of an activity to an uninvolved third party. In this case, intensive electricity use can cause two negative externalities. The first is the carbon emission resulting from electricity production of cryptomining, with recent studies estimating that global emissions from Bitcoin mining alone equal the emissions produced by Pakistan.
This paper concerns a second, unstudied externality, the real effects of technology processing on local economies. What, for example, are the spillovers from cryptomining on households and small businesses? How does the interaction of supply and demand impact prices and delivery of electricity to homes and businesses? As we shall see below, cryptomining also has positive externalities in that cryptomines produce local tax revenues, raising questions for the authors about net costs and benefits.
Before describing the authors’ methodology and findings, a note about cryptomining, which is the clearing of payment transactions for certain decentralized blockchain-based payment systems called (proof-of-work) cryptocurrencies. Any person or firm can become a cryptominer, which means solving increasingly complex computational puzzles to verify the validity of transactions. This has led to an arms race among firms who run large cryptomines, essentially warehouses full of specialized computers, crunching numbers across the world. And the key point here is that these cryptomines need lots of electricity.
The authors analyze the negative externalities of the high electricity use of cryptomining through two channels: prices, and quantity rationing. In the first case, the authors study New York State, specifically Upstate NY, excluding New York City and Long Island, which was an early market for cryptomining in the United States due to its cold climate, cheap electricity, and proximity to large hydropower sources. The region’s grid operator employs a marginal supply pricing algorithm, whereby upward pressure on prices from demand gets passed to households and small businesses. The authors combine detailed data on these local electricity prices, electricity usage, and other economic outcomes with hand-collected data on the likely location of cryptominers, to analyze whether and how the use of electricity by cryptominers affects local communities. Their findings include the following:
As noted, the authors also study the negative externalities of the high electricity use of cryptomining through quantity rationing. To do so, the authors turn to China, which hosted 65-82% of the world’s cryptomining during the last decade before a ban in 2021. Other details aside, in a quantity rationing system, when total demand increases, prices do not adjust; rather, the electricity supply is rationed among locations to align with physical infrastructure. The authors study 52 inland China city-areas to find the following:
Bottom line: This paper presents novel empirical evidence of the real effects of cryptomining on local economies. For US policymakers, the optimal response is likely not to ban cryptomining, which would only shift the problem elsewhere and restrict any possible tax revenue gains. Rather, the more optimal response is likely the development of electricity pricing schemes or dynamic quotas that minimize the adverse impact on the local community.