Forecasting Inflation in Open Economies: What Can a NOEM Model DO?

Abstract

This paper evaluates the forecasting ability when inflation is viewed as an inherently global phenomenon through the lens of the workhorse New Open Economy Macro (NOEM) model. The NOEM model emphasizes the importance of cross-country spillovers arising through trade and its reduced form solution can be represented by a finite-order VAR which provides a tractable model of inflation forecasting. We use Bayesian techniques to estimate this VAR specification-we name it NOEM-BVAR-and pseudo-out-of-sample forecasts to assess its forecasting performance at different horizons in a diverse set of 18 countries. On average, the NOEM-BVAR specification produces a similar or even lower root mean square prediction error (RMSPE) than its standard competitors, which include both purely statistical models and theoretically-based forecasting models (e.g., Phillipscurve-type alternatives and others with global inflation measures). In a number of cases, the gains in smaller RMSPEs are statistically significant, especially at short horizons. The NOEM-BVAR model is also accurate in predicting the direction of change for inflation and is often better than its competitors along this dimension as well. Even though purely statistical models can be useful prediction tools, the NOEM-BVAR is attractive among those forecasting models motivated by economic theory.