Technical statistical details don't usually make headlines, but in Britain they have, and for good reason. The Office for National Statistics (ONS) announced that they would not change the way they calculate the Retail Prices Index (RPI), the country's oldest measure of inflation. A change to the RPI was expected because the formula used to calculate it is widely recognized as flawed.
The Consumer Price Index (CPI) is the price index used for inflation targeting and other macroeconomic purposes. It was introduced in the 1990s and is calculated in a similar fashion across countries. Compared to the CPI, the RPI tends to be higher by around 1.3 percentage points. Why does this upward bias matter? The RPI is used as the price index for inflation-linked government bonds and for many company pension payments. If the ONS had changed the formula, pensioners and holders of these bonds would have received lower future payments. Pensioners tend to be older, so some groups representing older people lobbied against the change. Of course, other people would have benefited from the change, namely some companies and taxpayers who are financing these pensions and bonds.
This actually brings up a broader point about monetary policy. Protection against inflation varies significantly across the population, so monetary policy is redistributive. People don't all experience inflation in the same way. It depends on the share of their income that comes from labor income versus financial income and also on the proportion of their assets indexed to inflation. Moreover, some people's wages are indexed to inflation or at least respond quickly to inflation, while other wages are "stickier." And as illustrated by the RPI situation, even inflation-linked assets may not perfectly track inflation dynamics. Age, income, employment status, and asset holdings all play a role in determining how monetary policy affects a person.
My adviser Yuriy Gorodnichenko and several coauthors have a recent paper called "Innocent Bystanders? Monetary Policy and Inequality in the U.S." They note that there are several theoretical channels through which monetary policy can affect income inequality. For example, if low-income households tend to hold relatively more currency than high-income households, then increased inflation would create a transfer from low-income households toward high-income households. Some of the channels predict that monetary policy will increase inequality, while other channels predict that monetary policy will decrease inequality. So a priori, the effect of monetary policy on inequality is ambiguous. Through careful empirical work, they are able to determine which channels are strongest. They find that monetary policy accounts for about 10-20% of the increase in inequality since the 1980s. In particular, contractionary monetary policy shocks "have effects on labor earnings which vary systematically across the income distribution: labor income rises at the upper end of the distribution and falls at the lower end." (Their empirical results apply to the United States, not to Britain, where the relative strength of the various channels could be different.) Considering the redistributive impacts of monetary policy, not just its overall impact on GDP, is an important challenge.