Forecasting Indonesian inflation within an inflation-targeting framework: Do large-scale models pay off?
Solikin M. Juhro, Bernard Njindan Lyke (Bank Indonesia Institute, 2019)
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| 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-off of approximately 50%. We show that nearly 87% of the predictors can forecast inflation 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. |
| No. Panggil : | 332 BEMP 22:4 (2019) |
| Entri utama-Nama orang : | |
| Entri tambahan-Nama orang : | |
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| Penerbitan : | Jakarta: Bank Indonesia Institute, 2019 |
| Sumber Pengatalogan : | LibUI eng rda |
| ISSN : | 14108046 |
| Majalah/Jurnal : | Bulletin of Monetary Economics and Banking |
| Volume : | Vol. 22, No. 4, December 2019: Hal. 423-436 |
| Tipe Konten : | text |
| Tipe Media : | unmediated |
| Tipe Carrier : | volume |
| Akses Elektronik : | |
| Institusi Pemilik : | Universitas Indonesia |
| Lokasi : | Perpustakaan UI, Lantai 4, R. Koleksi Jurnal |
| No. Panggil | No. Barkod | Ketersediaan |
|---|---|---|
| 332 BEMP 22:4 (2019) | 08-21-873503766 | TERSEDIA |
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| Tidak ada ulasan pada koleksi ini: 20512317 |
