Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition
The gross capital formation (GCF), which helps to gradually increase GDP itself, is financed by domestic savings (DS) in both developed and developing countries. Therefore, forecasting GCF is the key subject to the economists’ decisions making. In this study, I use simple forecasting methods, namely...
| المؤلف الرئيسي: | |
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| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Editura Universităţii „Alexandru Ioan Cuza” din Iaşi / Alexandru Ioan Cuza University of Iasi Publishing house
2018-06-01
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| سلاسل: | Scientific Annals of Economics and Business |
| الموضوعات: | |
| الوصول للمادة أونلاين: | http://www.degruyter.com/view/j/saeb.2018.65.issue-2/saeb-2018-0010/saeb-2018-0010.xml?format=INT |
| _version_ | 1831812211414138880 |
|---|---|
| author | Gulay Emrah |
| author_facet | Gulay Emrah |
| author_sort | Gulay Emrah |
| collection | DOAJ |
| description | The gross capital formation (GCF), which helps to gradually increase GDP itself, is financed by domestic savings (DS) in both developed and developing countries. Therefore, forecasting GCF is the key subject to the economists’ decisions making. In this study, I use simple forecasting methods, namely dynamic relation model called “Autoregressive Distributed Lag Model (ARDL)”, and complex methods such as Adaptive Neuro Fuzzy Inference System (ANFIS) method and ARIMA-ANFIS method to determine which method provides better out-of-sample forecasting performance. In addition, the contribution of this study is to show how important to use domestic savings in forecasting GCF. On the other hand, ANFIS and hybrid ARIMA-ANFIS methods are comparatively new, and no GCF modeling using ANFIS and ARIMA-ANFIS was attempted until recently to the best of my knowledge. In addition, Autoregressive Integrated Moving Average (ARIMA) method and Vector Autoregressive (VAR) model serve as benchmarks, allowing for fair competing for the study. |
| first_indexed | 2024-12-22T21:32:17Z |
| format | Article |
| id | doaj.art-23c5710b51a04ee8a3ad781b20b4527b |
| institution | Directory Open Access Journal |
| issn | 2501-3165 |
| language | English |
| last_indexed | 2024-12-22T21:32:17Z |
| publishDate | 2018-06-01 |
| publisher | Editura Universităţii „Alexandru Ioan Cuza” din Iaşi / Alexandru Ioan Cuza University of Iasi Publishing house |
| record_format | Article |
| series | Scientific Annals of Economics and Business |
| spelling | doaj.art-23c5710b51a04ee8a3ad781b20b4527b2022-12-21T18:11:53ZengEditura Universităţii „Alexandru Ioan Cuza” din Iaşi / Alexandru Ioan Cuza University of Iasi Publishing houseScientific Annals of Economics and Business2501-31652018-06-0165215916910.2478/saeb-2018-0010saeb-2018-0010Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting CompetitionGulay Emrah0Dokuz Eylul University, Turkey;The gross capital formation (GCF), which helps to gradually increase GDP itself, is financed by domestic savings (DS) in both developed and developing countries. Therefore, forecasting GCF is the key subject to the economists’ decisions making. In this study, I use simple forecasting methods, namely dynamic relation model called “Autoregressive Distributed Lag Model (ARDL)”, and complex methods such as Adaptive Neuro Fuzzy Inference System (ANFIS) method and ARIMA-ANFIS method to determine which method provides better out-of-sample forecasting performance. In addition, the contribution of this study is to show how important to use domestic savings in forecasting GCF. On the other hand, ANFIS and hybrid ARIMA-ANFIS methods are comparatively new, and no GCF modeling using ANFIS and ARIMA-ANFIS was attempted until recently to the best of my knowledge. In addition, Autoregressive Integrated Moving Average (ARIMA) method and Vector Autoregressive (VAR) model serve as benchmarks, allowing for fair competing for the study.http://www.degruyter.com/view/j/saeb.2018.65.issue-2/saeb-2018-0010/saeb-2018-0010.xml?format=INTdynamic relation modelANFISARIMA-ANFISgross capital formationdomestic savingsC45C53 |
| spellingShingle | Gulay Emrah Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition Scientific Annals of Economics and Business dynamic relation model ANFIS ARIMA-ANFIS gross capital formation domestic savings C45 C53 |
| title | Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition |
| title_full | Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition |
| title_fullStr | Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition |
| title_full_unstemmed | Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition |
| title_short | Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition |
| title_sort | comparing simple forecasting methods and complex methods a frame of forecasting competition |
| topic | dynamic relation model ANFIS ARIMA-ANFIS gross capital formation domestic savings C45 C53 |
| url | http://www.degruyter.com/view/j/saeb.2018.65.issue-2/saeb-2018-0010/saeb-2018-0010.xml?format=INT |
| work_keys_str_mv | AT gulayemrah comparingsimpleforecastingmethodsandcomplexmethodsaframeofforecastingcompetition |