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Forecasting Indonesian inflation within an inflation-targeting framework : do large-scale models pay off?
We examine the usefulness of large-scale inflation forecasting models in Indonesia within an inflation-targeting framework. Using a dynamic model averaging approach to address three issues the policymaker faces when forecasting inflation, namely, parameter, predictor, and model uncertainties, we show that large-scale models have significant payoffs. Our in-sample forecasts suggest that 60% of 15 exogenous predictors significantly forecast inflation, given a posterior inclusion probability cut-of of approximately 50%. We show that nearly 87% of the predictors can forecast inflatio if we lower the cut-off to approximately 40%. Our out-of-sample forecasts suggest that large-scale inflation forecasting models have substantial forecasting power relative to simple models of inflation persistence at longer horizons..
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| PSB lt.2 - Karya Akhir | 1 |
| Penerbit | Bulletin of Monetary Economics and Banking., 2019 |
|---|---|
| Edisi | - |
| Subjek | Inflation Large Forecasting inflation targeting framework scale models Dynamic model averaging |
| ISBN/ISSN | - |
| Klasifikasi | - |
| Deskripsi Fisik | - |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas | Tidak Ada Data |