The Impact of Export-Oriented Agricultural Policies on Farm-Level Income, Production Efficiency, and Market Stability in the Context of Asia
Shaymaa Hussein Nowfal
Department of Medical Physics, College of Science, University of Warith Al‑Anbiyaa, Karbala 56001, Iraq; Department of Medical Physics, College of Applied Medical Sciences, University of Kerbala, Karbala 56001, Iraq
N. Meena Rani
Post Graduate Diploma in Business Management, Xavier Institute of Management and Entrepreneurship, Bangalore 560100, India
Dinesh Rajassekharan
Faculty of Artificial Intelligence Computing and Multimedia, Lincoln University College, Petaling Jaya 47301, Malaysia
K. R. Praneeth
School of Management, The Apollo University, Chittoor 517127, Andhra Pradesh, India
Sundari Dadhabai
KL Business School, Koneru Lakshmaiah Educational Foundation, Vaddeswaram, Andhra Pradesh 522302, India
S. Ramesh
Indus Business Academy, Bangalore, Karnataka 560082, India
PG Department of Business Administration and Dean ‑ Research and Development Cell, Maris Stella College, Vijayawada 520008, India
DOI: https://doi.org/10.36956/rwae.v6i1.1537
Received: 28 November 2024 | Revised: 26 December 2024 | Accepted: 31 December 2024 | Published Online: 13 March 2025
Copyright © 2024 Shaymaa Hussein Nowfal, N. Meena Rani, Dinesh Rajassekharan, K. R. Praneeth, Sundari Dadhabai, S. Ramesh, Ravi Kumar Bommisetti. Published by Nan Yang Academy of Sciences Pte. Ltd.
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
Abstract
This study investigates the impact of export-oriented agricultural policies on farm-level income, production efficiency, and market stability in three southern states of India: Karnataka, Telangana, and Tamil Nadu. Focusing on smallholder and commercial farms, the research evaluates how these policies impact key economic results in regions characterized by diverse agricultural activities. The study aims to assess the farm-level consequences of agricultural export promotion policies for income volatility, technical efficiency, and price risks and how these consequences are connected to the supply chain and trade relations, food supply, and rural incomes. Using a quantitative approach, the study analyzes data from 363 farms, examining the role of export input, domestic market support, and the adoption of Smart Farming (SF) technologies. The findings demonstrate that export market input leads to higher income levels, improved production efficiency, and enhanced supply chain stability. However, the study also highlights challenges smallholder farmers face, particularly regarding access to Agriculture Exports (AE) and exposure to global price volatility. The study showed that total farm-level income has increased by 22% for exporters, but the market risk has been reduced by 15% due to volatile prices. The production efficiency rate represented 18% among the commercial farms, while the smallholder farms were considered by a 12% resource allocation inefficiency, leading to reduced sustainability and vulnerability to shocks. The market risk has been reduced despite the variation in the price level, which is an aspect of relative efficiency. The exporters and the large farms are better positioned to manage the risks and earn higher income and efficiency. On the other hand, smallholder farms are less efficient and, therefore, more sensitive to prices and sustainability problems. The results recommend that while export-oriented policies have the potential to benefit India's agricultural sector significantly, targeted interventions are required to ensure that these benefits are distributed more equitably across different types of farms.
Keywords: Smart Farming; Export-Oriented Agricultural Policies; Farm-Level Income; Smallholder Farmers; Global Price Volatility; Machine Learning
References
[1] Thow, A.M., Apprey, C., Winters, J., Stellmach, D., et al., 2021. Understanding the impact of historical policy legacies on nutrition policy space: economic policy agendas and current food policy paradigms in Ghana. International journal of health policy and management. 10(12), 909. DOI: https://doi.org/10.34172/ijhpm.2020.203
[2] Paolo, S., Mahadev, N.A. Comparative Analysis of Agricultural Domestic and Trade Policies in India and in the European Union. Available from: https://www.researchgate.net/publication/349077227_Comparative_Analysis_of_Agricultural_Domestic_and_Trade_Policies_in_India_and_in_the_European_Union (cited 10 February 2021).
[3] Thomas, L., Kuruvilla, A., Meena, M., et al., 2023. Handbook of Spices in India: 75 Years of Research and Development, Springer: New York City, NY, USA. pp. 1095–1145.
[4] Awokuse, T., Lim, S., Santeramo, F., et al., 2024. Robust policy frameworks for strengthening the resilience and sustainability of agri-food global value chains. Food Policy. 127, 102714. DOI: https://doi.org/10.1016/j.foodpol.2024.102714
[5] German, L. A., Bonanno, A. M., Foster, et al., 2020. “Inclusive business” in agriculture: Evidence from the evolution of agricultural value chains. World Development. 134, 105018. DOI: https://doi.org/10.1016/j.worlddev.2020.105018
[6] George, A. S., 2023. Evaluating India's economic growth: challenges and opportunities on the path to 5 trillion dollars. Partners Universal International Innovation Journal, 1(6), 85–109. DOI: https://doi.org/10.5281/zenodo.10307006
[7] Food and Agriculture Organization (FAO). Available from: https://www.fao.org/india/fao-in-india/india-at-a-glance/en/ (cited 5 April 2019).
[8] Kolloju, P.K., Kolloju, N., Siriman, N., 2024. Food Security As A Public Policy Concern In India Amidst The 2030 agenda: A historical trajectory. Glocalism: Journal of Culture, Politics and Innovation. (1). DOI: https://doi.org/10.54103/gjcpi.2024.22790
[9] Ranjan, O.J., 2021. Food Security Policy in India: Challenges and Performance. Available from: https://policy-practice.oxfam.org/resources/food-security-in-india-performance-challenges-and-policies-346637/ (cited 8 October 2021).
[10] Saxena, R., Singh, R., Agarwal, P., et al., 2023. Sustainable Food Value Chain Development: Perspectives from Developing and Emerging Economies. Singapore: Springer Publishing: New York City, NY, USA. pp. 295–317.
[11] Saxena, R., Kumar, A., Singh, R., et al, 2024. Examining export advantages in Indian horticulture: an approach based on product mapping and seasonality. Journal of Agribusiness in Developing and Emerging Economies. 14(2), 161–192. DOI: https://doi.org/10.1108/JADEE-12-2021-0310.
[12] Ghosh, M., 2023. Growth and Development under Alternative Policy Regimes in India: A Political Economy Perspective. Journal of Asian and African Studies. 58(7), 1134–1155. DOI: https://doi.org/10.1177/00219096221079324
[13] Bandolkar, K.N., 2023. Impact of Regional Trade Agreements on India's Agricultural Trade (Doctoral dissertation). Taleigao Plateau: Goa University. pp. 379–392.
[14] Pavan, V., Vishnupriya, V., HR, H.K., et al., 2023. Emerging Trends in Agricultural Economics and Agribusiness: An Edited Anthology, Stella International Publication: Haryana, India. p. 39.
[15] Ravi Kumar, K.N., Naidu, G.M., Shafiwu, A.B., 2024. Exploring the drivers of Indian agricultural exports: a dynamic panel data approach. Cogent Economics & Finance. 12(1), 2344733. DOI: https://doi.org/10.1080/23322039.2024.2344733
[16] Anderson, K., 2022. Trade-related food policies in a more volatile climate and trade environment. Food Policy. 109, 102253. DOI: https://doi.org/10.1016/j.foodpol.2022.102253
[17] Aragie, E., Balié, J., Morales, C., Pauw, K., 2023. Synergies and trade-offs between agricultural export promotion and food security: Evidence from African economies. World Development. 172, 106368. DOI: https://doi.org/10.1016/j.worlddev.2023.106368
[18] Marcina, K., Sauhats, A., Lavrinovics, V., et al., 2018. Efficiency Analysis of the Baltic Balancing Market. In Proceedings of the 2018 15th International Conference on the European Energy Market (EEM), Lodz, Poland, 2018; pp. 1–6. DOI: https://doi.org/10.1109/EEM.2018.8469992
[19] Mulongo, N.Y. Optimisation of Manufacturing Workflow Through Generative Artificial Intelligence. In Proceedings of the 2024 International Symposium on Networks, Computers and Communications (ISNCC), Washington, DC, USA, 2024; pp. 1–6. DOI: https://doi.org/10.1109/ISNCC62547.2024.10758970
[20] Gadipudi, S.B., Kalpana Kalaimani, R. Reinforcement Learning for Dynamic Pricing under Competition for Perishable Products. In Proceedings of the 2024 28th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania, 2024; pp. 297–302, DOI: https://doi.org/10.1109/ICSTCC62912.2024.10744760
[21] Li, Y., Cui, C., Lu, T., et al., 2024. Study on the Value of Lost Load of Three Provinces in China Based on Production Function Approach. In Proceedings of the 2024 4th Power System and Green Energy Conference (PSGEC), Shanghai, China, 2024; pp. 557–561. DOI: https://doi.org/10.1109/PSGEC62376.2024.10721032
[22] Eimear Leahy and Richard S.J. Toi, An estimate of the value of lost load for Ireland. Energy Policy. 39(3), pp. 1514–152. DOI: https://doi.org/10.1016/j.enpol.2010.12.025
[23] Panneerselvam. S, Thangavel, S.K., Ponnam V.S. et al., Federated learning-based fire detection method using local MobileNet, Scientific Reports. 14 1-24, DOI: https://doi.org/10.1038/s41598-024-82001-w
[24] Madhubala, P., Ghanimi, H.M.A., Sengan, S., et al., 2024. Bridging the gap in biomedical information retrieval: Harnessing machine learning for enhanced search results and query semantics. Journal of Intelligent & Fuzzy Systems. 46(6), 1–20. DOI: https://doi.org/10.3233/JIFS-237056
[25] Khan G, Mishra P K, Agarwal A K, et al., 2024. Energy-Efficient Routing Algorithm for Optimizing Network Performance in Underwater Data Transmission Using Gray Wolf Optimization Algorithm, Journal of Sensors, 2024(1),, pp. 1-15. DOI: https://doi.org/10.1155/2024/2288527
[26] Arumugham, V.; Ghanimi, H.M.A.; Pustokhin, D.A., 2023. An Artificial-Intelligence-Based Renewable Energy Prediction Program for Demand-Side Management in Smart Grids. Sustainability. 15(6), 5453. DOI: https://doi.org/10.3390/su15065453
[27] Abdulkader, R., Ghanimi, H.M.A., Dadheech, P., 2023. Soft Computing in Smart Grid with Decentralized Generation and Renewable Energy Storage System Planning. Energies. 16(6), 2655. DOI:https://doi.org/10.3390/en16062655
[28] Ni, D.B., Tang, X.W., 2024. Study on the relationship between production function and cost function, Chinese Management Science. 12(4), 64–68.
[29] Chao, Y., Guo Y. G.,, Cheng L., 2002. Customer service reliability promise/compensation method. Automation of Electric Power Systems. 26(18), 11–14.
[30] Nguyen, P.T., Nguyen, T.-A.-T., 2024. Design and Simulation Industrial Wood Furniture Manufacturing Plants. 2024 9th International Conference on Applying New Technology in Green Buildings (ATiGB); Danang, Vietnam, 30–31 August 2024. pp. 280–284.
[31] Milton, L.C., et al., 2024. A Multi Moving Target Localization in Agricultural Farmlands by Employing Optimized Cooperative Unmanned Aerial Vehicle Swarm, Scalable Computing: Practice and Experience. 25(6), 4647–4660, https://doi.org/10.12694/scpe.v25i6.3130
[32] Roque-Claros, R.E., et al., 2024. UAV Path Planning Model Leveraging Machine Learning and Swarm Intelligence for Smart Agriculture. Scalable Computing: Practice and Experience. 25(5), 3752–3765. DOI: https://doi.org/10.12694/scpe.v25i5.3131
[33] Lal Karn, A., Kondamudi, B.R., Gupta, R.K., 2023. An Empirical Analysis of the Effects of Energy Price Shocks for Sustainable Energy on the Macro-Economy of South Asian Countries. Energies. 16(1), 363. DOI: https://doi.org/10.3390/en16010363
[34] Karn, A.L., Manickam, P.S., Saravanan, R., 2023. IoT Based Smart Framework Monitoring System for Power Station, Computers, Materials & Continua. 74(3), 6019–6037. DOI: https://doi.org/10.32604/cmc.2023.032791
[35] Ghanimi, H.M., R, S., Jeyaraj, J.P.G., et al., 2024, Smart Fertilizing Using IOT Multi-Sensor and Variable Rate Sprayer Integrated UAV. Scalable Computing: Practice and Experience. 25(5), 3766–3777. DOI: https://doi.org/10.12694/scpe.v25i5.3132
[36] Rahmani, M. K. I., et al., 2023. Early Pathogen Prediction in Crops Using Nano Biosensors and Neural Network-Based Feature Extraction and Classification. Big Data Research. 38, 100412, DOI: https://doi.org/10.1016/j.bdr.2023.100412
[37] Asgarov, R., 2024. Advantages of Export Promotion Policy in Rural Farming and Factors Conditioning It. Acta Universitatis Danubius. Œconomica. 20(3), 15–22.
[38] Aragie, E., Balié, J., Morales, C., et al., 2023. Synergies and trade-offs between agricultural export promotion and food security: Evidence from African economies. World Development. 172, 106368. DOI: https://doi.org/10.1016/j.worlddev.2023.106368
[39] Koff, H., Bonilla-Moheno, M., Campos-García, L.M., et al., 2023. Agricultural policies and local sustainability: a normative coherence for development analysis of Mexico's pineapple sector. Local Environment. 28(11), 1496–1514. DOI: https://doi.org/10.1080/13549839.2023.2238739
[40] Firas, T.A., Ayasrah, F.T., Alsharafa, N.S., 2024. Strategizing Low-Carbon Urban Planning through Environmental Impact Assessment by Artificial Intelligence-Driven Carbon Foot Print Forecasting, Journal of Machine and Computing. 4(4). DOI: https://doi.org/10.53759/7669/jmc202404105