Forecasting maize yield in the Republic of Serbia by using Box-Jenkins methodology
Apstrakt
As food supply is one of the most important issues for national security, forecasting agricultural production represents a necessity for every country. Forecasting yields and production volume is a very complex task that requires both application of formal statistical methods and assessment of experts. Considering not only the significant role of maize in the immediate diet and processing industry in the Republic of Serbia, but also its absolute dominance in the structure of sown areas, the analysis of the time series and projections of future maize yield were carried out. Maize yield projections obtained through Box-Jenkins methodology, for 2017 and 2018, are 4.97 t/ha and 7.01 t/ha. Comparing the projected with realized yield in 2017 (for which there is available data), it was noticed that the model's forecast indicated a smaller reduction than actually realized. According to the results of the conducted study, it is clear that although the time series model cannot anticipate precise... yield quantities, it can certainly be useful in terms of predicting future tendencies in maize yield oscillations.
Ključne reči:
maize yield / time series / Box-Jenkins methodology / forecastIzvor:
Ekonomika poljoprivrede, 2019, 66, 2, 525-540Izdavač:
- Naučno društvo agrarnih ekonomista Balkana, Beograd, Institut za ekonomiku poljoprivrede, Beograd i Akademija ekonomskih nauka, Bukurešt
Institucija/grupa
Poljoprivredni fakultetTY - JOUR AU - Djoković, Jelena AU - Munćan, Mihajlo AU - Paunović, Tamara PY - 2019 UR - http://aspace.agrif.bg.ac.rs/handle/123456789/5203 AB - As food supply is one of the most important issues for national security, forecasting agricultural production represents a necessity for every country. Forecasting yields and production volume is a very complex task that requires both application of formal statistical methods and assessment of experts. Considering not only the significant role of maize in the immediate diet and processing industry in the Republic of Serbia, but also its absolute dominance in the structure of sown areas, the analysis of the time series and projections of future maize yield were carried out. Maize yield projections obtained through Box-Jenkins methodology, for 2017 and 2018, are 4.97 t/ha and 7.01 t/ha. Comparing the projected with realized yield in 2017 (for which there is available data), it was noticed that the model's forecast indicated a smaller reduction than actually realized. According to the results of the conducted study, it is clear that although the time series model cannot anticipate precise yield quantities, it can certainly be useful in terms of predicting future tendencies in maize yield oscillations. PB - Naučno društvo agrarnih ekonomista Balkana, Beograd, Institut za ekonomiku poljoprivrede, Beograd i Akademija ekonomskih nauka, Bukurešt T2 - Ekonomika poljoprivrede T1 - Forecasting maize yield in the Republic of Serbia by using Box-Jenkins methodology EP - 540 IS - 2 SP - 525 VL - 66 DO - 10.5937/ekoPolj1902525D ER -
@article{ author = "Djoković, Jelena and Munćan, Mihajlo and Paunović, Tamara", year = "2019", abstract = "As food supply is one of the most important issues for national security, forecasting agricultural production represents a necessity for every country. Forecasting yields and production volume is a very complex task that requires both application of formal statistical methods and assessment of experts. Considering not only the significant role of maize in the immediate diet and processing industry in the Republic of Serbia, but also its absolute dominance in the structure of sown areas, the analysis of the time series and projections of future maize yield were carried out. Maize yield projections obtained through Box-Jenkins methodology, for 2017 and 2018, are 4.97 t/ha and 7.01 t/ha. Comparing the projected with realized yield in 2017 (for which there is available data), it was noticed that the model's forecast indicated a smaller reduction than actually realized. According to the results of the conducted study, it is clear that although the time series model cannot anticipate precise yield quantities, it can certainly be useful in terms of predicting future tendencies in maize yield oscillations.", publisher = "Naučno društvo agrarnih ekonomista Balkana, Beograd, Institut za ekonomiku poljoprivrede, Beograd i Akademija ekonomskih nauka, Bukurešt", journal = "Ekonomika poljoprivrede", title = "Forecasting maize yield in the Republic of Serbia by using Box-Jenkins methodology", pages = "540-525", number = "2", volume = "66", doi = "10.5937/ekoPolj1902525D" }
Djoković, J., Munćan, M.,& Paunović, T.. (2019). Forecasting maize yield in the Republic of Serbia by using Box-Jenkins methodology. in Ekonomika poljoprivrede Naučno društvo agrarnih ekonomista Balkana, Beograd, Institut za ekonomiku poljoprivrede, Beograd i Akademija ekonomskih nauka, Bukurešt., 66(2), 525-540. https://doi.org/10.5937/ekoPolj1902525D
Djoković J, Munćan M, Paunović T. Forecasting maize yield in the Republic of Serbia by using Box-Jenkins methodology. in Ekonomika poljoprivrede. 2019;66(2):525-540. doi:10.5937/ekoPolj1902525D .
Djoković, Jelena, Munćan, Mihajlo, Paunović, Tamara, "Forecasting maize yield in the Republic of Serbia by using Box-Jenkins methodology" in Ekonomika poljoprivrede, 66, no. 2 (2019):525-540, https://doi.org/10.5937/ekoPolj1902525D . .