Analysis of factors affecting the import demand for wheat and corn in Türkiye using the Seemingly Unrelated Regression Method

Objective: In this study, it is aimed to analyze the determining factors on the import demand for wheat and corn, which have an important place in Türkiye's grain imports, with the "Apparently Unrelated Regressions" model. Material and Methods: The data set used in this study consists of annual data covering the years 2006-2021. Stata program was used to analyze the data used in the study. Since Stata or Eviews programs do not provide the Standardized Beta (β) coefficient, statistical analyzes were performed using the formula in Microsoft Excel (β=B*SSXi / SSY). Results: Only the one-year delayed value of wheat imports, which is one of the explanatory variables in the wheat import model, was found to be significant, according to the study's findings. In terms of factors influencing corn import demand, similar results were obtained. Only total corn consumption was found to be statistically noteworthy among the explanatory variables in the corn import model. Conclusion: Based on these findings, wheat imports are influenced by changes in wheat imports from a year ago, while corn imports are influenced by changes in total corn consumption. Based on Türkiye's current structure and the findings obtained, it is understood that the country may continue to maintain its position as an importer of wheat and corn in the future.

Authors

Institutions

Publication Details

Journal
Ege Üniversitesi Ziraat Fakültesi Dergisi
Published
2025-03-13
DOI
https://doi.org/10.20289/zfdergi.1467449
Citations
1
Primary Topic
Agricultural Economics and Practices
Type
article
Field-Weighted Citation Impact
4.83
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of factors affecting the import demand for wheat and corn in Türkiye using the Seemingly Unrelated Regression Method

şafak çomaklı, Kurtuluş MERDAN
1 citations
Ege Üniversitesi Ziraat Fakültesi Dergisi
Agricultural Economics and Practices
4.83
article

Analysis of factors affecting the import demand for wheat and corn in Türkiye using the Seemingly Unrelated Regression Method

şafak çomaklı, Kurtuluş MERDAN
article en
1 citations

Abstract

Objective: In this study, it is aimed to analyze the determining factors on the import demand for wheat and corn, which have an important place in Türkiye's grain imports, with the "Apparently Unrelated Regressions" model. Material and Methods: The data set used in this study consists of annual data covering the years 2006-2021. Stata program was used to analyze the data used in the study. Since Stata or Eviews programs do not provide the Standardized Beta (β) coefficient, statistical analyzes were performed using the formula in Microsoft Excel (β=B*SSXi / SSY). Results: Only the one-year delayed value of wheat imports, which is one of the explanatory variables in the wheat import model, was found to be significant, according to the study's findings. In terms of factors influencing corn import demand, similar results were obtained. Only total corn consumption was found to be statistically noteworthy among the explanatory variables in the corn import model. Conclusion: Based on these findings, wheat imports are influenced by changes in wheat imports from a year ago, while corn imports are influenced by changes in total corn consumption. Based on Türkiye's current structure and the findings obtained, it is understood that the country may continue to maintain its position as an importer of wheat and corn in the future.

Ege Üniversitesi Ziraat Fakültesi DergisiVol. 62(1)
Gümüşhane University (TR), Ankara Hacı Bayram Veli University (TR)
Openalex Percentile: Top 8%
Agricultural Economics and Practices
4.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.