This paper studies the dynamics of U.S. sectoral producer prices in a large Bayesian Vector Auto Regression (BVAR) model where the Input-Output (IO) matrix is used to structure their long-run relationships. The model provides evidence of a sectoral spillover channel in driving headline inflation without imposing such a mechanism in the model’s structure. Forecasts of headline inflation have accuracy comparable to the Survey of Professional Forecasters’ and greater than those generated by a standard BVAR with the Minnesota prior, confirming that the IO matrix long-run prior conveys relevant information about the data. The study of an oil price shock shows that adding the production network prior alters the transmission of the shock, amplifying headline inflation. Across sectors, the peak price response to the oil shock increases with oil intensity. A narrowly sector-specific disturbance, such as a cereal price shock, has non-negligible aggregate effects once the production network is accounted for. Sectoral asymmetries are crucial for evaluating the macroeconomic consequences of macroeconomic shocks such as an energy price shock and a monetary policy shock, as industries with slower price adjustments amplify inflation persistence, even after the shock dissipates.
Nothing contributes so much to the prosperity and happiness of a country as high profits