The role of oil price in the forecasts of agricultural commodity prices

© Springer International Publishing AG 2018. The objective of this paper is to examine whether including oil price to the agricultural prices forecasting model can improve the forecasting performance. We employ linear Bayesian vector autoregressive (BVAR) and Markov switching Bayesian vector autoreg...

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Main Authors: Rossarin Osathanunkul, Chatchai Khiewngamdee, Woraphon Yamaka, Songsak Sriboonchitta
Format: Book Series
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037843947&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/58534
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-585342018-09-05T04:26:00Z The role of oil price in the forecasts of agricultural commodity prices Rossarin Osathanunkul Chatchai Khiewngamdee Woraphon Yamaka Songsak Sriboonchitta Computer Science © Springer International Publishing AG 2018. The objective of this paper is to examine whether including oil price to the agricultural prices forecasting model can improve the forecasting performance. We employ linear Bayesian vector autoregressive (BVAR) and Markov switching Bayesian vector autoregressive (MS-BVAR) as innovation tools to generate the out-of-sample forecast for the agricultural prices as well as compare the performance of these two forecasting models. The results show that the model which includes the information of oil price and its shock outperforms other models. More importantly, linear model performs well in one- to three-step-ahead forecasting, while Markov switching model presents greater forecasting accuracy in the longer time horizon. 2018-09-05T04:26:00Z 2018-09-05T04:26:00Z 2018-01-01 Book Series 1860949X 2-s2.0-85037843947 10.1007/978-3-319-70942-0_30 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037843947&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/58534
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
spellingShingle Computer Science
Rossarin Osathanunkul
Chatchai Khiewngamdee
Woraphon Yamaka
Songsak Sriboonchitta
The role of oil price in the forecasts of agricultural commodity prices
description © Springer International Publishing AG 2018. The objective of this paper is to examine whether including oil price to the agricultural prices forecasting model can improve the forecasting performance. We employ linear Bayesian vector autoregressive (BVAR) and Markov switching Bayesian vector autoregressive (MS-BVAR) as innovation tools to generate the out-of-sample forecast for the agricultural prices as well as compare the performance of these two forecasting models. The results show that the model which includes the information of oil price and its shock outperforms other models. More importantly, linear model performs well in one- to three-step-ahead forecasting, while Markov switching model presents greater forecasting accuracy in the longer time horizon.
format Book Series
author Rossarin Osathanunkul
Chatchai Khiewngamdee
Woraphon Yamaka
Songsak Sriboonchitta
author_facet Rossarin Osathanunkul
Chatchai Khiewngamdee
Woraphon Yamaka
Songsak Sriboonchitta
author_sort Rossarin Osathanunkul
title The role of oil price in the forecasts of agricultural commodity prices
title_short The role of oil price in the forecasts of agricultural commodity prices
title_full The role of oil price in the forecasts of agricultural commodity prices
title_fullStr The role of oil price in the forecasts of agricultural commodity prices
title_full_unstemmed The role of oil price in the forecasts of agricultural commodity prices
title_sort role of oil price in the forecasts of agricultural commodity prices
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037843947&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/58534
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