Much has been written recently about the potential adoption of a "chained consumer price index (chained CPI)" as the official measure of inflation and cost of living increases for the purposes of calculating government benefits, boundaries between tax brackets, and so on. Because this chained CPI gives lower estimates of inflation than does the traditional consumer price index (CPI), adopting such an index would result in slower growth in Social Security benefits and a slower upward shift of marginal tax rates. As a result, a switch to chained CPI is viewed by many politicians as a palatable (read, not obvious) way to mitigate the debt problem in the United States. But, putting political expediency aside, is adopting chained CPI a good idea from an economic perspective?
Being a nerdy economist, I decided to go straight to the source in order to answer this question. In this case, the source is the Bureau of Labor Statistics (BLS), the government agency responsible for calculating inflation and other related measures, which published a white paper on chained CPI methodology back in 2003. (The BLS started calculating and publishing a chained CPI series in August 2002.) This paper is 56 pages long and full of mathematical equations, so I don't suggest that you tuck in and read the whole thing. (That's what I'm here for.) Instead, I will go through the relevant points.
The BLS defines a Cost of Living Index (COLI) as "the ratio of the minimum expenditure required to attain a particular level of satisfaction in two price situations, a comparison period and a base period." In other words, a cost of living index answers the question "how much more or less money do you need in order to be as happy now as you were before?" Using the traditional CPI as a cost of living index makes an implicit assumption that the only way to be as well off as you were before is to buy the same stuff, which is not true in a lot of cases.
For example, to reference a popular meme, suppose I am indifferent between purchasing one horse-sized duck and 100 duck-sized horses. Both groups of items would give me the same level of happiness, and my choice between them would therefore be determined by which one is more expensive. Let's say that, for now, the prices of both bundles are the same and I randomly decide to go with the horse-sized duck (so I could ride it like Nicholas Kristof, obviously). Now fast forward to next year, and imagine that the price of the horse-sized duck has risen by 10 percent but the price of the 100 duck-sized horses has remained constant. The CPI would imply that my cost of living has increased by 10 percent, whereas I, as a utility-maximizing consumer, would simply switch over to the 100 duck-sized horses and be just as happy with no additional expenditure required. The chained CPI, therefore, should state that my cost of living has remained constant.
The BLS estimates this sort of substitution willingness by combining its traditional CPI data with data from the Consumer Expenditure Survey (CES) (i.e. a data series showing how much money households spend on different types of stuff). The general idea is that if you know how much money people spent on stuff and the price of that stuff, you can back out the quantities purchased over time and the substitutions made in response to changing prices.
So what are the limitations of this methodology? First, the chained CPI would ideally account for substitution at two different levels- both between different brands or types of item (intra-item, e.g. between cars and trucks) and across different items (inter-item, e.g. between vehicles and public transit). Unfortunately, while the CPI data exists at both levels, the Consumer Expenditure Survey only collects data at the higher level. Therefore, the method for the lower-level price aggregation is the same for the chained CPI as it is for the regular CPI, making chained CPI not a completely accurate reflection of consumer behavior. (To be fair, however, it comes closer than the traditional CPI.)
Second, and more problematic from a practical perspective, the expenditure data from the CES is only available annually and with a lag of almost a year, so it's not really possible to construct chained CPI in real time. The BLS is therefore limited to publishing a final chained CPI with a two-year lag schedule (which would mean, for example, that 2012 data is not available until 2014). The BLS's solution to this problem is to compute interim values of the index and then update them with final values once the expenditure data becomes available. If current figures are needed in order to calculate benefits and tax brackets, then policy makers would have to rely at least temporarily on these interim numbers, which are good forecasts but are not perfect. (Policy makers would also have to decide whether to retroactively adjust policy once the final numbers come out, which would be a bear from a logistical perspective.)
Is there any good news regarding this proposed policy? Of course. Theoretically, chained CPI seems like a totally reasonable way to think about changes in the cost of living in an economy, so it's hard to object on principle to using this measure to adjust changes in government benefits, tax brackets, and so on. In addition, there is a potential efficiency argument to be made in favor of chained CPI approach to deficit reduction. When it comes to taxes and policy changes, there are two types of costs that occur. The first is a transfer of money from households and companies to the government, and the second is a loss of economic activity that occurs (deadweight loss, in economic terms). (For example, if I value a t-shirt at $15 and you can produce it for $13, a $3 tax will prevent an otherwise value-creating transaction.) While the first cost is important from a distributional perspective, the second is important from an efficiency perspective as well. As counterintuitive as it may seem, taxes and policy changes are more efficient (not necessarily more fair, however) when people don't change their behavior in response to them, since then there is only transfer and no loss of economic activity. And hey, people can't change their behavior fully if they don't understand how policy changes are affecting them, right?
As an economist, I think that there is long-term potential to improve policy by incorporating chained CPI as a more accurate cost of living index. That said, the government shouldn't try to leverage the lack of understanding of it's citizens, efficient or not, and should instead work on educating the public about what the change means for them. In addition, the government needs to avoid a rush to adopt the index as a short-term fix without fully thinking through the logistics and distributional impact of its implementation.