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Dynamics of Stabilization and Structural Transformation of Wheat Productivity in Iraq: A Markov Switching Modeling Approach | ||
| Anbar Journal of Agricultural Sciences | ||
| Article 17, Volume 24, Issue 2, July 2026, Pages 498-506 PDF (714.76 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.32649/ajas.2026.191734 | ||
| Authors | ||
| R. F. Mohammed1; A. D. Kassar2; N. S. Madlul3 | ||
| 1Department of Economics, College of Administration and Economics, University of Thi-Qar, Iraq | ||
| 2Department of Agricultural Economics, College of Agriculture, University of Anbar, Iraq | ||
| 3Department of Agricultural Economics and Extension, College of Agriculture, University of Tikrit, Iraq | ||
| Abstract | ||
| The study aimed to conduct a dynamic analysis to explain the behavior of wheat production in Iraq using a Markov-switching autoregressive model (MS-AR), covering an annual time series from 1990 to 2023. Using data from the Iraqi Central Bureau of Agricultural Statistics, it assumed that there are underlying systems linked to a historical record of state policies and climate factors. The results revealed two distinct systems governing the behavior of the wheat production sector in Iraq. The first is characterized by its flexibility and continuity, which exceeds five years, and its ability to absorb shocks and return to its long-term average of 611.5 kg/dunum, indicating the high potential for cultivating this strategic crop. The second system is unstable and vulnerable to the shocks it is exposed to, which constantly affect it. However, it tends to recover from them within about a year, indicating an internal dynamic that drives it to return to its stable and flexible state. The research found that the dynamic behavior of productivity is what specifically distinguishes these two systems, not the average productivity itself. The distinctive feature is how they behave over time and respond to shocks. The research recommended adopting proactive risk management policies, not just those related to increasing production, such as developing drought-resistant seed varieties and investing in water infrastructure. It also recommended adopting such analytical models as a diagnostic tool to monitor the resilience of the wheat production sector and anchor it in its stable system | ||
| Keywords | ||
| Structural resilience; Agricultural risk management; Exogenous shocks; Agricultural productivity; Transitional possibilities | ||
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