Are British Mobile Phone Shoppers Getting a Bargain?
The pervasive digitalization of daily life is ultimately to the credit of a tightly integrated manufacturing ecosystem centered in the Pacific Rim. Relentless advances in efficiency drive down the cost of producing myriad electronic devices, including mobile phones, the key consumer platform for the latest wave of digitalization. As these devices are distributed around the world, those falling production costs show through to consumer price trends.
However, official consumer price indices (CPIs) indicate that different national markets have benefited from this windfall to markedly different degrees. From 2008 to 2018, mobile phone CPI growth ranged from no change in Japan to average declines of 24 percent per year in the United Kingdom. In other words, for an equivalent phone, a UK consumer paid in 2018 one-tenth of what they paid in 2008; the Japanese consumer paid the same price in both years. In a paper in the current issue of the National Institute Economic Review (“The Mysterious Cross-Country Dispersion in Mobile Phone Price Trends”), I explore the origins of this phenomenon by examining data for 12 countries—the members of the G7 plus Australia, China, Finland, Korea, and New Zealand—and find that although fundamental factors are at play, the spread in national CPIs may be overstated.
What are those fundamental factors? First, the mobile phone consumer landscape varies across countries. China, for example, experienced rapid growth in mobile phone penetration in this period: mobile phone contracts per 100 households was roughly 50 in 2008 and exceeded 100 ten years later. The UK market, by contrast, seemed to be saturated: Mobile phone contracts per 100 households was relatively stable and exceeded 100 in all years. Second, some markets are more competitive than others. The top mobile phone brands account for a noticeably larger share of sales in the South Korean market, for example, than is the case in the UK and concentration in South Korea rose over these years as well. Mobile phone inflation is correlated with both of these factors, suggesting a rush toward mobile phone use in some markets and rising market power in others enabled vendors to include an increasing profit margin in mobile phone sales, reducing the pass through of falling production costs to consumer prices. This exploratory analysis does not provide a precise measure of the share of spread in inflation one can attribute to these effects.
In addition to the fundamental factors, it may also be the case that statistical methods contribute to the cross-country dispersion in price trends. Conventional methods for CPI construction follow the path of prices for individual items in a “basket” over time and average the price changes for those items to construct an overall index. Products like mobile phones with rapid technological innovation present a thorny problem for this approach: Product turnover frequently causes items in the basket to disappear from the market and replacement items typically feature higher performance. The statistician must “quality-adjust” the price of the new phone before folding it into the basket, meaning she must judge what share of any premium paid for the phone (compared to the phones already in the basket) is a payment for the higher performance, leaving the remainder to be recorded as pure inflation. The policies set by national statistical agencies (NSIs) that provide guidance for this process vary from country to country. And, even with that guidance in hand, NSI analysts must apply judgment and little information is published about the decisions made for specific products; the public cannot see “how the sausage is made.”
Are the benefits of the technical advances in mobile technology passing through to some markets more than others? The answer provided by a literal reading of national CPIs appears to be “yes, to a remarkable degree.” It seems there is an overlooked cross-country analogue to the much-discussed “productivity puzzle” of slowing macroeconomic performance in recent years. As is the case for the time-series puzzle, some of the cross-sectional puzzle may be the result of differences in statistical methods, but the contribution of mis-measurement is obscure.