Sign Restrictions and Supply-demand Decompositions of Inflation

Policymakers are often interested in the degree to which changes in prices are driven by shocks to supply or demand. One way to estimate the contributions of these shocks is with a structural vector autoregression identified using sign restrictions on the slopes of demand and supply curves. The appeal of this approach is that it relies on uncontroversial assumptions. However, sign restrictions only identify decompositions up to a set. I characterise the conditions under which these sets are informative, examining both historical decompositions (contributions to outcomes) and forecast error variance decompositions (contributions to variances). I use this framework to estimate the contributions of supply and demand shocks to inflation in the United States. While the sign restrictions yield sharp conclusions about the drivers of inflation in some expenditure categories, they tend to yield uninformative decompositions of aggregate inflation. A 'bottom-up' decomposition of aggregate inflation is less informative than a decomposition that uses the aggregate data directly.