It can be shown that inflation expectations and associated forecast errors are characterized by a high degree of persistence. One reason may be that forecasters cannot directly observe the inflation target pursued by the central bank and, hence, face a complicated forecasting problem. In...

We study how millions of granular and weekly household scanner data combined with machine learning can help to improve the real-time nowcast of German inflation. Our nowcasting exercise targets three hierarchy levels of inflation: individual products, product groups, and headline inflation. At...

Forecasting consumer prices for package holidays, which represent a major driver of the inflation rate in Germany, poses some practical challenges. With a substantial share in the underlying consumer basket, prices for package holidays exhibit strong seasonality, notable volatility, and...

We study how millions of highly granular and weekly household scanner data combined with novel machine learning techniques can help to improve the nowcast of monthly German inflation in real time. Our nowcasting exercise targets three hierarchy levels of the official consumer price index. First,...

Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast accuracy for euro area real GDP growth and HICP...

Die Einschätzung und Vorhersage der gesamtwirtschaftlichen Situation im laufenden und im folgenden Quartal ist eine der zentralen Aufgaben der Konjunkturprognose. Das ifo Institut stützt sich bei seiner Kurzfristprognose des Bruttoinlandsprodukts auf den dreistufigen IFOCAST-Ansatz. In der...

Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast accuracy for euro area real GDP growth and HICP...

Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articles suggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches....

Since the seminal article of Bates and Granger (1969), a large number of theoretical and empirical studies have shown that pooling different forecasts of the same event tends to outperform individual forecasts in terms of forecast accuracy. However, the results remain heterogenous regarding the...