Decomposing the performance metrics of coconut cultivation in the South Indian States

Coconut, a crucial crop in South India, has experienced fluctuating growth trends despite its economic and cultural significance. This study focuses on Kerala, Tamil Nadu, and Karnataka, which together account for over 80% of India's coconut production and area. The research aims to analyze the performance of coconut cultivation in these states from 2000-2001 to 2017-2018 by examining growth trends in area, production, and yield. It will also decompose the factors contributing to changes in coconut output, identifying the relative contributions of area expansion, price fluctuations, yield improvements, and crop mix effects. Finally, the study will assess the instability in these growth trends, which is crucial for understanding the risks associated with coconut cultivation and informing investment decisions by various stakeholders, including farmers, processors, and policymakers. This comprehensive analysis will provide valuable insights for developing effective policies and strategies to enhance the sustainability and productivity of coconut farming in the region.

Existing literature on coconut farming focuses largely on international and national-level growth aspects and determinants. Studies in Tanzania and Sri Lanka have explored factors influencing coconut production and adoption of modern management practices, respectively. Research in Malaysia examined the impact of agricultural practices and socio-economic factors on profitability. In India, studies have highlighted the positive growth rates in coconut cultivation, particularly in coastal regions like Kerala, Tamil Nadu, and Karnataka, emphasizing the roles of area expansion and productivity enhancements. However, existing research often lacks a detailed analysis of growth dynamics in the 21st century and the comprehensive decomposition of factors driving production changes. This study addresses this gap by applying advanced analytical techniques to investigate the performance of coconut cultivation across the three selected South Indian states during the early 21st century.

The study employs a mixed-methods approach. First, it uses time series data from the Coconut Development Board for the period 2000-2001 to 2017-2018, encompassing data on area under cultivation (hectares), production (million nuts), productivity (nuts per hectare), and wholesale price (Indian rupees per quintal) for Kerala, Tamil Nadu, and Karnataka. Growth rates are estimated using the exponential growth equation, allowing for the detection of patterns in growth through log-quadratic trend analysis. Decomposition analysis, using the multiplicative method of Jamal and Zaman (1992), is used to isolate the contribution of area, price, yield, and crop-mix effects to the total change in coconut output. Finally, the Cuddy Della Valle Instability Index (CDVI) is calculated to quantify the instability in the growth trends of area, production, and yield for each state. The analysis is conducted for the entire period and for two sub-periods (2000-2001 to 2008-2009 and 2009-2010 to 2017-2018) to identify changes in instability over time.

The results reveal a significant variation in coconut cultivation performance across the three states. While Karnataka exhibited the highest growth rates in area, production, and yield, it also experienced substantial fluctuations. Kerala, despite its historical dominance, showed a negative growth rate in area, although production and yield remained positive. Tamil Nadu presented a mixed picture with positive growth but a deceleration in production and yield over time. Decomposition analysis showed a positive yield effect and price effect in all three states, with the price effect being particularly substantial in Kerala. Area effect was found to be negative across all states, highlighting its limited role in driving production increases. Crop-mix effects showed state-specific variation, suggesting a need for state-level tailored strategies. Instability analysis using CDVI indicated relatively low instability in Kerala for the entire period, medium instability in Tamil Nadu, and high instability in Karnataka, especially in production and yield. The period-wise analysis revealed that the fluctuations in the growth variables of coconut intensified in the second phase (2009-2010 to 2017-2018) in most cases.

The findings underscore the complex interplay of factors influencing coconut production in South India. While Karnataka's high growth is promising, its high instability highlights the need for risk mitigation strategies. Kerala's declining area under coconut cultivation suggests the need for policies to incentivize its continued production and address the factors leading to its decline. Tamil Nadu presents a moderate scenario, necessitating further investigation into factors impacting yield deceleration. The significant price effect across states underscores the importance of stable and fair pricing mechanisms, possibly through farmer collectives and improved market access. The negative area effect indicates that expansion of area alone is not a sufficient driver of overall production growth, and emphasis must be put on increased productivity and yield. The results emphasize the need for a nuanced, state-specific approach in policymaking, tailored to address unique challenges and opportunities in each region.

This study provides a comprehensive analysis of coconut cultivation performance in three major South Indian states. The findings highlight the importance of yield and price effects on production, along with the need to address instability. Recommendations include improved access to technology, credit, and marketing facilities for farmers, while also advocating for policies supporting stable prices and reduced production fluctuations. Future research could expand this study to include more states, investigate specific factors influencing instability, and analyze the impact of climate change and technological advancements on coconut cultivation.

The study is limited to three major coconut-producing states in India. The time-series data used limits the analysis of spatial aspects. Furthermore, certain relevant variables such as technical factors and coconut exports were not included due to data unavailability. Future research could address these limitations by including more comprehensive data and adopting a more spatially explicit analytical framework.