| Autor: |
SYED, Ateeb Akhter Shah, KIRAN, Humaira, QURESHI, Sumbal |
| Předmět: |
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| Zdroj: |
Pakistan Journal of Applied Economics; 2022, Vol. 32 Issue 2`, p169-190, 22p |
| Abstrakt: |
This study forecasts imports and exports of Pakistan at a disaggregated level. Both in and out-of-sample forecasts are produced using conventional econometric time-series models and the Artificial Neural Network (ANN), a machine learning approach. The forecast performance is reported using the Root Mean Squared Error (RMSE). Given improved forecasts by the 'iterative optimization' nature of the long and short-term method, ANN outperforms other model in-sample. For the out-of-sample period, the autoregressive (AR) and ANN model outperforms other models for import groups, while all univariate approaches outperform each other for two out of six subgroups in out-of-sample forecasts. Hence, performing equivalently well for export groups. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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