How much should subscribers pay for broadband? Without a sound economic benchmark, it is difficult to tell if the old expression "whatever the market will bear" is too high. We need a good benchmark, but we do not have one.
Why do we need one? Consider recent experience. In September 2001, approximately 45 million U.S. households accessed the Internet through a dial-up connection, while only 10 million used a broadband connection. By March 2006, the situation was moving to the opposite: Approximately 47 million households (and growing) had broadband connections, while 34 million (and declining) used dial-up connections. According to the latest survey of the Pew Internet and American Life Project, in April, 2009, less than 10% of U.S. households had dial-up Internet connections, and 63% of U.S. households had broadband.
What happened to the price of broadband during and after that deployment? In our study, "The Broadband Bonus: Accounting for Broadband Internet's Impact on U.S. GDP," http://www.nber.org/papers/w14758, Ryan McDevitt and I inquired into broadband's value. We approached this question from a novel angle. We asked: "How fast would prices have to come down to reflect the value created from the replacement of dial-up access with broadband?"
What was so novel about that question? While answering that question we strictly followed the standard procedures used by the U.S. Bureau of Labor Statistics (BLS) to estimate the Consumer Price Index (CPI).
We had several reasons for doing this. First, the consumer price index is the primary measure of inflation in the U.S.for example, the Social Security Administration uses it to adjust its checks. However, economists have long suspected the CPI index contains biases. Many years ago those suspicions were confirmed in integrated circuits and personal computers, as well as in cellular telephony. Accordingly, measurement procedures in those markets changed.
Should broadband change too? It is a big and open question because nobody has yet estimated the size of the bias (if any). Governments in the developed world use procedures similar to those used in the U.S. If U.S. statistics contain a bias, it is also likely in other countries.
A big policy issue also motivated us. Price indices can measure improvements (or not) in competitive performance in markets with few suppliers, as in broadband. Yet, a policymaker cannot address questions about pricing without understanding whether the CPI measures prices accurately.
As it does elsewhere, BLS uses very cautious procedures for recording benefits from upgrading to broadband. There is a rationale behind that caution: Not all users experience the benefits of broadband in the same way. For example, capacity/bandwidth differs between households and the location in the national grid matters. Accordingly, rather than merely assuming households benefit from the availability of a new service, such as broadband, the BLS waits for clear evidence that buyers like the improvements.
This approach leads to what is sometimes called a "transactional" index. Standard procedures do not measure technical progress at the frontier unless users transact for a better good or service. Moreover, the CPI focuses on the average experience, getting an average price by taking a weighted average over all transactions, including those not at the frontier.
That is why, for example, wireless broadband tended not to play a big role in the official price index until after 2006. Wireless broadband revenue was small in comparison to the revenue for wireline broadband. Incidentally, that is also why McDevitt and I focused our study on wireline broadband, the bulk of transactions for which there is public data up until 2006.
The CPI for Internet access is officially called Internet services and electronic information providers, and the BLS began compiling data in December 1997. BLS deserves some credit for starting this index not long after the diffusion of the Internet began. At that point approximately 20% of U.S. households had adopted dial-up commercial Internet service, and less than 1% had adopted broadband. The second and third rows of the table illustrate this point.
In the fourth row is a monthly quote from the official price index, taken from December of each year, and normalized to 100 for the year in which the index began. It indicates that the CPI for Internet access in the U.S. went mildly down and up and down for eight years. Then, in late 2006, it broke with all prior patterns and declined more than 18% from its base (i.e., (94.5 77.2)/94.2 = 0.183). That drop continued and settled at a 23% from its base in January 2007 (i.e., (94.5 73.4)/94.5), staying near that level ever since.
Did that last drop reflect increasing competitiveness of broadband markets? In fact, it does not. The dramatic drop in the official price index for the U.S. primarily reflects the pricing of the declining good, dial-up service. An informed reading of the business news explains why. The largest U.S. dial-up provider, America Online (AOL), altered its pricing policies in the fall of 2006. AOL announced it was moving to advertising-supported service. On top of that, BLS used its standard cautious procedures. That gave AOL's prices close to a quarter of the weight in the index (even though AOL's market share was dropping).
The official index is less informative about broadband prices for an additional but rather subtle reason. Standard price index survey procedures measure the price at which the new good transacted but not at the price that previously deterred the user from adoption. For example, in many neighborhoods broadband was not available in any form for some time until after 2000. Even when it became available, it may not have been reliable enough (initially) to spur many households to switch immediately from dial-up. These users waited until vendors improved the infrastructure or service arm of the organization. In short, users did not adopt until quality improved.
That common occurrence creates a problem for BLS. Household eventually converted from dial-up to broadband, as rows 2 and 3 of the table indicate. However, there was (seemingly) no measured price change or qualitative improvement affiliated with the upgrade.
What would have happened to the broadband price index if it reflected unmeasured qualitative improvement? That is a succinct way to understand one aim of our study. McDevitt and I followed the standard recommendation for this problem. It goes back to work by Sir John Hicks, a Nobel Prize Laureate in Economics, and has been used many times in economic analysis. The price index should employ what a user would have been willing to expend to get the new service before it was available.
Many surveys tell us what that willingness was. Even the most cautious surveys from the time period suggest the average convert was willing to pay approximately $51.35 per month (on average), but actually had to pay less. If the actual price was $36, for example, the upgrade provided a benefit "equivalent" to a decline in price of $15.35, or a 30% decline.
The last row in the table illustrates our study's estimate of a price index adjusted for upgrades. We follow the norms for a transactional index. Because only a small percentage of households a year upgraded to broadband, a price index that emphasizes transactions cannot give a huge weight to the upgrades in any given year. Upon initial assessment the gains appear modest even in our largest estimate, displayed in the last row of the table, around 2.2% decline per a year, each year prior by 2006.
Yet, it adds up over time. By 2006 the price index should have declined 16.4% more than it did ((73.1 63.1)/73.1). Our study experimented with many other different ways to count it. Depending on how it is counted, we estimate that somewhere between 4.8 and 6.7 billion dollars of benefit went uncounted in 2006 alone.
Notice one other feature. Our new estimate displays a big difference in the timing of the recorded price decline. Accounting for the upgrade when users upgraded would have realized the benefits several years sooner than BLS recorded in its official index.
Overall, our study suggests there are many unresolved issues in the price indices for a wide range of improving electronic goods where users realize discrete gains from upgrading to a new good. After all, broadband is far from the only improving service a user can upgrade. What was true of broadband is likely to be true for smartphones, Netbooks, digital camcorders, and even digital advertising. BLS has its hands full.
Our study also illustrates why a price index constructed for the CPI does not necessarily meet the needs of a policymaker interested in broadband policy, such as the Federal Communications Commission (FCC). We considered the gains from retirement of second phone lines at households. Once again, we experimented with numerous ways to estimate the gains from such retirement. We found that the savings on a second phone line accounts for anywhere from 30%-40% of the total savings in 20022006, or 21%28% of the savings for 1999-2006. However, BLS price indices do not normally count the savings of expenditure in one category (on a second telephone line) as an input into calculating the price index for another (Internet access). While this procedural norm is fine for the CPI, it is misleading for broadband policy.
How fast would prices have to come down to reflect the value created from the replacement of dial-up access with broadband?
That would not have to be a problem if the FCC kept its own price index for its own purposes. However, the FCC has steadfastly refused to keep a broadband price index for many years, even while it tracks many other aspects of broadband. How can the FCC make informed competitive policy when it has to rely on the BLS for a price index that does not reflect the FCC's policy priorities? Our study directs attention at this problem.
Indeed, the FCC has much to do. Its index would have to account for qualitative improvements, as well as the bundling of broadband pricing with other information services, such as cable television and telephony. The FCC also probably would want to measure changes to the frontier more quickly than BLS, watching prices of new access modes (smartphones), as well as the gains from Skype and other VoIP (using other phone services). It might be challenging to figure out the gains from Twitter over other text messaging, but that must be a component of the mix too.
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