ISP Marginal Cost Does Not Drive Consumer Prices

As the U.S. Federal Communications Commission opens an inquiry into ISP data caps, some are going to argue that such data caps are unnecessary or a form of consumer price gouging, as the marginal cost of supplying the next unit of consumption is rather low. 

Though perhaps compelling, the marginal cost of supplying the next unit of consumption is not the best way of evaluating the reasonableness of such policies.  

If U.S. ISPs were able to meet customer data demand during the COVID-19 pandemic without apparent quality issues, it suggests several things about their capacity planning and network infrastructure, and much less about the reasonableness of marginal cost pricing.

In fact, the ability to survive the unexpected Covid data demand was the result of deliberate overprovisioning by ISPs; some amount of scalability (the ability to increase supply rapidly); use of architectural tools such as content delivery networks and traffic management and prior investments in capacity as well. 

Looking at U.S. internet service providers and their investment in fixed network access and transport capacity between 2000 and 2020 (when Covid hit), one sees an increasing amount of investment, with magnitudes growing steadily since 2004, and doubling be tween 2000 and 2016.

Year	Investment (Billion $)
2000	21.5
2001	24.8
2002	20.6
2003	19.4
2004	21.7
2005	23.1
2006	24.5
2007	26.2
2008	27.8
2009	25.3
2010	28.6
2011	30.9
2012	33.2
2013	35.5
2014	37.8
2015	40.1
2016	42.4
2017	44.7
2018	47
2019	49.3
2020	51.6

At the retail level, that has translated into typical speed increases from 500 kbps in 2000 up to 1,000 Mbps in 2020, when the Covid pandemic hit. Transport capacity obviously increased as well to support retail end user requirements. Compared to 2000, retail end user capacity grew by four orders of magnitude by 2020. 

Year	Capacity (Mbps)
2000	0.5
2002	1.5
2004	3
2006	6
2008	10
2010	15
2012	25
2014	50
2016	100
2018	250
2020	1000

But that arguably misses the larger point: internet access service costs are not contingent on marginal costs, but include sunk and fixed costs, which are, by definition, independent of marginal costs. 

Retail pricing based strictly on marginal cost can be dangerous for firms, especially in industries with high fixed or sunk costs, such as telecommunications service providers, utilities or manufacturing firms.

The reason is that marginal cost pricing is not designed to recover fixed and sunk costs that are necessary to create and deliver the service. 

Sunk costs refer to irreversible expenditures already made, such as infrastructure investments. Fixed costs are recurring expenses that don't change with output volume (maintenance, administration, and system upgrades).

Marginal cost pricing only covers the cost of producing one additional unit of service (delivering one more megabyte of data or manufacturing one more product), but it does not account for fixed or sunk costs. 

Over time, if a firm prices its products or services at or near marginal cost, it won’t generate enough revenue to cover its infrastructure investments, leading to financial losses and unsustainable operations.

Marginal cost pricing, especially in industries with high infrastructure investment, often results in razor-thin margins. Firms need to generate profits beyond just covering marginal costs to reinvest in growth, innovation, and future infrastructure improvements. 

In other words, ISPs cannot price at marginal cost, as they will go out of business, as such pricing leaves no funds for innovation, maintenance, network upgrades and geographic expansion to underserved or unserved areas, for example. 

Marginal cost pricing can spark price wars and lead customers to devalue the product or service, on the assumption that such a low-cost product must be a commodity rather than a high-value offering. Again, marginal cost pricing only covers the incremental cost of producing the next unit, not the full cost of the platform supplying the product. 

Many Consumers Will Always Buy "Good Enough Value" Home Broadband

Some question the long-term viability of 5G fixed wireless services, arguing that, eventually, it will prove unable to compete with ever-higher capacities supplied by cabled networks, especially fiber to home platforms. 

Supporters might make the case that “eventually” is the key phrase, as the market potential for fixed wireless between “today” and “tomorrow” is likely to be quite extended. At the moment, perhaps 51 percent or 52 percent of all U.S. homes or dwelling units have service available from at least one provider. 

By 2030 that percentage might increase to 76 percent to 80 percent. 

At the moment, perhaps 10 percent to 15 percent of U.S. homes have FTTH service available from at least two providers, growing to possibly 30 percent to 40 percent by 2030. 

For starters, FTTH is expensive enough that no single service provider can afford to build new networks ubiquitously, even if the customer demand is present. By some estimates, the cost to pass one urban home might be just $1,000, but the cost to pass suburban locations might range up to $3200, while rural passings can easily cost $7,000 or more. 

Area Type	Density	Estimated Cost per Home/Passing
Metropolitan	High	$1,000
Suburb (Flat Terrain)	Medium	$2,700
Suburb (Hilly Terrain)	Medium	$3,240
Rural (Flat Terrain)	Low	$6,300
Rural (Hilly)	Low	$7,000

And that is construction cost only, not including the cost to activate an account, which can add costs between $300 to $500 for each install. 

An equally-important issue is the take rate for such networks. It has been common for any new FTTH provider that is a telco to get up to 40 percent take rates over a few years, with initial uptake in the 20-percent range, often. Independent ISPs competing with both cable operators and a telco might expect take rates not exceeding 20 percent (where the cable operator can offer gigabit service and the telco does not offer FTTH). 

So the longer-term issue is how big the market might be for wireless service offering speeds in the lower ranges (100 Mbps to 200 Mbps now; undoubtedly higher speeds in the future), as more fiber access is available. To the extent that fixed wireless is taking market share from cable operators (perhaps even operators able to sell gigabit-per-second connections), we can infer that a substantial portion of the market is happy to pay the prevailing rates for access at such speeds, especially when able to bundle home broadband with their mobile access services. 

When comparing fixed wireless to either cable modem or FTTH service, many consumers might not be especially interested in services operating the 500-Mbps and faster ranges, much less gigabit ranges, when the slower speeds cost less. 

But demand will continue to shift over time, with most consumers eventually buying services operating faster than 200 Mbps, and in many instances much faster than 200 Mbps (gigabit to multi-gigabit ranges, for example). To be sure, fixed wireless providers are likely to find ways to increase their speed tiers as well, beyond 200 Mbps in the future, even if virtually all observers suggest wireless will continue to lag cabled networks in terms of speed. 

Speed Tier Take Rates, in Percentage	2023	2030	2040
Less than 100 Mbps	20-30	5-10	1-2
100 Mbps to 200 Mbps	30-40	10-20	5-10
Faster than 200 Mbps	30-40	70-80	85-90

Perhaps the best analogy is what cable operators have been able to do with their hybrid fiber coax networks, boosting speeds over time. 

Keep in mind that cable networks and FTTH networks back around 2000 were only offering top speeds in the 10-Mbps range. Fixed wireless networks also will be able to increase speeds over time, if never on the scale of cabled networks. 

Year	Typical Cable Operator Maximum Speed
1996	1.5 Mbps
Early 2000s	10 Mbps
Late 2000s	50 Mbps
2010	100 Mbps
2015	300 Mbps
2016	1 Gbps
2024	2 Gbps

But absolute ability to match cabled network speeds is not the question. The issue is what percentage of customers will, in the future, be willing to buy fixed wireless home broadband, at then-prevailing speeds, prices and offers. 

High-Cost Home Broadband Subsidies Work

Very few major social problems have clear and uncomplicated causal relationships, which makes virtually impossible the task of determining whether public policies actually work, or not. 

For complex social problems like poverty, housing, crime, education, carbon reduction or traffic, it remains quite difficult to prove causal links between policies and outcomes. Basically, policies are tried without any real way of knowing whether they work. 

Contrast that with a few instances where the primary causation mechanisms are relatively clear. The causal link between smoking tobacco and various health issues like lung cancer, heart disease, and respiratory problems is well-established.

There is a direct causal relationship between alcohol consumption and impaired driving leading to accidents and fatalities.

Conditions such as scurvy (vitamin C deficiency) or rickets (vitamin D deficiency) have clear causation mechanisms related to lack of specific nutrients in the diet. Likewise, the danger of lead exposure, especially in children, is clear.

The overuse and misuse of antibiotics in healthcare and agriculture has a direct causal relationship with the development of antibiotic-resistant bacteria.

Home broadband supply now is likely one problem for which we know at least one causal relationship, namely that financial subsidies work. Since the cost of home broadband infrastructure is directly related to population density, financial subsidies are required in low-density rural areas. 

Urban households tend to have access to better home broadband than households in rural areas, rural residents might note, policymakers might agree and OpenSignal says. 

And though there are correlations between income, education and age in any market, “income levels are less predictive of reliability than density,” OpenSignal notes.

It might be noteworthy that although sharing of network infrastructure often is touted as a way of reducing the cost of home broadband infrastructure, OpenSignal studies find there is no correlation between network infrastructure sharing and either high reliability or a narrow digital divide. “Countries with limited infrastructure sharing but targeted subsidies for private rural investment mostly perform better than those relying on widespread infrastructure sharing,” OpenSignal notes.

Topography and density are key factors in the size of the divide between urban and rural home broadband experience. 

Markets with highly-concentrated populations in urban areas show small gaps between urban and rural reliability, and spread-out middle-income countries with difficult terrain show big gaps. “But a few countries with lots of medium-density areas, like the U.S., and Spain, have relatively small digital divides,” the firm says. 

In fact, the U.S. market might better be characterized as having huge low-density areas. population density has a huge impact on the cost of building new networks, mobile or fixed, but especially fixed networks.  

U.S. population density is quite thin across most of its geography, which directly affects the cost of building broadband networks, as hefty subsidies are required to reach the last one percent or two percent of remote locations. 

And the United States has a huge percentage of its land mass that is thinly settled, if at all settled. In Canada, 14 percent of the people live in areas of density between five and 50 people per square kilometer. In Australia, 18 percent of people live in such rural areas.

In the United States, 37 percent of the population lives in rural areas with less than 50 people per square kilometer.

Put another way, less than two percent of Canadians and four percent of Australians live in such rural areas. In the United States, fully 48 percent of people live in such areas.

Put another way, about six percent of the U.S. land mass is “developed” and relatively highly populated. Those are the areas where it is easiest to build networks. But about 94 percent of the U.S. land surface  is unsettled or lightly populated, including mountains, rangeland, cropland and forests. And that is where networks are hardest to build and sustain.

So it should not at all be surprising that broadband reliability is, on average, 23 percent higher in urban areas than in rural areas across all markets we analyzed,” say analysts at OpenSignal. The firm uses a 100 to 1000 point scale to measure broadband experience in a typical household where multiple devices are used simultaneously. 

The metric is based on ability to connect (uptime); ability to complete tasks and speed, latency, jitter performance. 

source: OpenSignal 

Financial subsidies for service providers in rural areas are one way governments try to close digital divides, and arguably are the most effective ways to do so. Whether in the form of subsidies for anchor institutions or per-passing or per-connection support is the clearest way to reduce the cost of rural infrastructure for suppliers. 

Beyond that, policymakers often try to encourage competition and promote deployment of alternative platforms (satellite, fixed wireless, mobile access). 

Governments can help communities create cooperatives; reduce permitting and other regulatory costs or train people to use broadband. But perhaps nothing works so well as simple subsidies, for the simple reason that population density and network cost are inversely related. 

High population density leads to lower costs; low density leads to higher costs. So subsidies for home broadband in rural areas are a relatively clear example of cause-and-effect relationships.