The Predictive Performance of Fundamental Inflation Concepts: An Application to the Euro Area and the United States

Does theory aid inflation forecasting? To date, the evidence suggests that there is no systematic advantage of theory-based models of inflation dynamics over their astructural counterparts. This study reconsiders the issue by developing a 'semi-structural' forecasting procedure comprised of two key ingredients. First, a prediction for the cyclical component of inflation is obtained employing the concept of 'fundamental inflation'. The latter is computed from a canonical two-country monetary model, either via estimation of the reduced-form parameters of the New Keynesian Phillips Curve by the generalized methods of moments, or via calibration of its structural parameters. The computation of fundamental inflation requires multistep forecasts for the model-implied cyclical inflation drivers, which we generate via respective auxiliary vector autoregressions. Second, a driftless random walk prediction is employed for the trend component of inflation, on which theory has little to say. Using quarterly data for both the United States and the Euro Area for the period 1970-2010, and rolling window re-estimation to accommodate gradual structural change, we find that such semi-structural inflation forecasts outperform conventional univariate forecasts at all examined horizons. Our results thus suggest that theory can indeed play an important role in forecasting inflation, when appropriately combined with relevant data-driven features.