Evaluation of financial performance of agricultural sub-sectors with DuPont analysis technique

Abstract

Purpose: The agricultural sector is a sector with different sub-sectors and a wide range of products and is of critical importance for every country. Considering the structures of agricultural sub-sectors, each of them has different characteristics. The aim of this study is to evaluate the financial status of the enterprises operating in the agricultural sub-sectors in Türkiye between 2009 and 2023 and to compare the profitability of the sub-sectors. Design/Methodology/Approach: Using the sector balance sheet data prepared by the Central Bank of the Republic of Türkiye (CBRT), the financial performances of agricultural sub-sectors between 2009 and 2023 were calculated by DuPont analysis technique and various evaluations were made. In addition, variance analysis and Post-Hoc tests were conducted to test whether there is a significant difference in the profitability ratios of the sub-sectors between 2009-2023. Findings: As a result of DuPont analyses, when the average profitability ratios for the period 2009-2023 are examined; A02-Forestry sub-sector showed the highest performance in all three profitability ratios (return on sales, return on assets and return on equity). The lowest profitability averages for the relevant period were observed in the A01-Crop and animal production sub-sector. In addition, it was determined that the return on sales, return on assets and return on equity ratios of the A02-Forestry sub-sector differed significantly from the other sub-sectors for the 2009-2023 period. Originality/Value: Analysing the financial situation of the agricultural sector in detail is very important for enterprises, investors, entrepreneurs, economic management and other related groups operating in this sector. In this study, the agricultural sector has been analysed in depth by considering sub-sectors with different characteristics and comparisons have been made between sub-sectors. The results of the study provide important indicators for all information users who will make decisions about agricultural sub-sectors. © 2025 Elsevier B.V., All rights reserved.