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

The study investigates how area, production, and yield of coconut evolved in India’s three dominant coconut-growing states—Kerala, Tamil Nadu, and Karnataka—from 2000–2001 to 2017–2018. Motivated by observed fluctuations in coconut output and shifting regional dominance, the paper aims to: (1) analyse trends and performance in area, production, and yield; (2) identify the components responsible for output change via decomposition (area, price, yield, crop-mix); and (3) examine instabilities in growth trends. The context highlights coconut’s economic and cultural importance, government and CDB initiatives to promote cultivation and value addition, and the need for stakeholders to understand growth dynamics to make informed decisions. The study addresses gaps in recent literature by applying a rigorous, post-2000 period analysis with attention to both growth rates and their underlying drivers and instabilities.

International studies show determinants of coconut production include extension services, tree density, farmers’ socio-economic characteristics, and adoption of modern practices (Tanzania, Sri Lanka, Malaysia). In India, Kerala historically dominated coconut area and output, but Tamil Nadu and Karnataka have gained share over time. Prior work (Lathika and Kumar, 2005) suggests area expansion drove output growth in Karnataka, while productivity gains mattered more in Kerala and Tamil Nadu; price increases and improved management also supported national trends. Decomposition approaches—additive (Minhas & Vaidyanathan, 1965) and multiplicative (Parikh, 1966)—have been refined, with Jamal and Zaman’s (1992) multiplicative model preferred for addressing indexing and residual issues. Instability analyses indicate that growth coupled with low instability is desirable (Ray, 1983), and that instability can impact farmer incomes (Chand & Raju, 2008). The paper fills a gap by providing a state-level, early 21st-century analysis with decomposition and instability metrics for coconut.

Data: Cross-sectional time series for Kerala, Tamil Nadu, and Karnataka over 18 agricultural years (2000–2001 to 2017–2018). Variables sourced primarily from Coconut Development Board: area under coconut (hectares), production (million nuts), productivity (nuts per hectare), and wholesale price (Rupees per quintal) of milling/ball copra. Gross sown area (GSA) used for shares. Growth estimation: Exponential growth model was used to estimate compound growth rates for area, production, and yield, assuming a constant percentage change from year to year. Acceleration/deceleration: A log-quadratic trend model ln(Yt) = a + bt + ct^2 + ut was fitted. A significant positive c indicates acceleration; negative c indicates deceleration of growth. Decomposition analysis: Employed Jamal and Zaman’s (1992) multiplicative decomposition to attribute total change in value of output V to area, price, yield, and crop-mix effects (logarithmic contributions), avoiding residuals and indexing issues. The framework splits ln(Vt/V0) into additive log components for area, price, yield, and crop-mix based on combinations of area shares (a), yield (Y), prices (P), and gross cropped area (A) between base and terminal periods. Instability: Cuddy-Della Valle Index (CDVI) computed for area, production, and yield to assess instability, de-trending the coefficient of variation using adjusted R^2 from time-trend regressions. Benchmarks: CDVI <15% (low), 15–30% (medium), >30% (high). The total period was split into Phase I (2000–2001 to 2008–2009) and Phase II (2009–2010 to 2017–2018) for sub-period instability analysis.

• State shares and trends: Kerala, Tamil Nadu, and Karnataka together accounted for roughly 84% of area and 87% of production by 2017–2018. Kerala’s dominance declined, while Tamil Nadu and especially Karnataka advanced in area and output.
• Growth rates (Exponential, 2000–2001 to 2017–2018; Table 2):
  • Kerala: Area −1.405% per annum (significant); Production +1.397% (significant); Yield +2.802% (significant). Evidence of slight acceleration in area, production, and yield (small positive c terms).
  • Tamil Nadu: Area +2.219%; Production +5.488% (significant) with significant deceleration (c < 0); Yield +3.270% (significant) with significant deceleration (c < 0).
  • Karnataka: Area +2.708% (significant); Production +10.844% (significant) with significant acceleration (c > 0); Yield +8.136% (significant) with significant acceleration (c > 0). Karnataka achieved the highest growth in area, production, and yield.
• Decomposition of output change (2000–2017; Table 3, fractions with percentage contribution in parentheses):
  • Kerala (Total effect 1.6275): Area −0.1317 (−8.10%); Price +1.3361 (82.10%); Yield +0.5603 (34.42%); Crop-mix −0.1372 (−8.42%). Price effect dominated.
  • Tamil Nadu (Total effect 1.3108): Area −0.0169 (−1.28%); Price +0.6931 (52.87%); Yield +0.3236 (24.69%); Crop-mix +0.3110 (23.72%). Price and crop-mix substantial.
  • Karnataka (Total effect 1.9942): Area −0.0617 (−3.10%); Price +0.7815 (39.20%); Yield +0.8342 (41.82%); Crop-mix +0.4402 (22.08%). Yield effect strongest, followed by price and crop-mix. Area effect was negative in all states, indicating area expansion did not drive output growth.
  • Period-wise decomposition (Appendix) indicates in later sub-periods area contributed positively in Kerala and Tamil Nadu; in Karnataka, yield and crop-mix were major contributors, with varying price effects across sub-periods.
• Instability (CDVI; Table 4):
  • Overall (entire period): Kerala—Area 5.12%, Production 11.30%, Yield 8.16% (low instability); Tamil Nadu—Area 4.03%, Production 14.58%, Yield 14.60% (low to borderline medium); Karnataka—Area 5.01% (low), Production 31.05% (high), Yield 26.86% (medium-high).
  • Phase trends: Instability in production and yield increased in Phase II for Kerala and Karnataka; Tamil Nadu’s production and yield instability fell markedly in Phase II, though area instability rose.
• Additional observations: Karnataka’s strong acceleration in production and yield is linked to favourable conditions and policy initiatives (e.g., National Horticulture Mission from 2006). Despite higher growth, Karnataka exhibits greater instability, posing risks for producers.

The analysis confirms that coconut output growth in the leading South Indian states during 2000–2017 was driven primarily by price and yield improvements rather than area expansion. The negative area effects in decomposition underscore that, relative to other crops, coconut’s area share either declined or contributed minimally to output changes. Karnataka’s rapid and accelerating gains in production and yield indicate effective productivity enhancements and supportive policy-climate context, but these gains are coupled with higher instability, especially in output and yield, which can elevate income risks for farmers. Kerala’s modest production growth with negative area growth reflects structural constraints (land conversion, labour shortages, pest/disease, volatile prices) but benefits from strong price contributions. Tamil Nadu achieved substantial production growth, though with deceleration and reduced instability over time, suggesting maturation and stabilization of growth drivers. These findings address the research objectives by (1) quantifying growth patterns and acceleration/deceleration, (2) attributing output change to specific components (price, yield, crop-mix, area), and (3) documenting instability magnitudes across states and periods. For stakeholders, the dominance of price and yield effects implies that policies enhancing productivity (technology, extension, quality inputs) and stabilizing or improving prices (market access, collective marketing, MSP effectiveness) are most impactful. High instabilities in Karnataka call for risk management and stabilization measures even as productivity initiatives continue.

The study decomposes coconut output growth in Kerala, Tamil Nadu, and Karnataka (2000–2017), showing that price and yield effects are the primary drivers of production increases, while area expansion contributed negatively across the period. Karnataka posted the highest and accelerating growth in production and yield but also the greatest instability; Kerala and Tamil Nadu showed lower overall instability, with Tamil Nadu’s instability decreasing in the later period. Policy recommendations include: enhancing productivity via modern technology, quality seedlings, pest/disease management, and extension; promoting intercropping and diversification for supplemental income; strengthening marketing and ensuring fair prices, including empowering Coconut Producer Companies to improve bargaining power and reduce intermediary exploitation; and expanding awareness and credit access to attract and retain farmers in coconut cultivation. Future research should expand spatial coverage to additional states and countries, incorporate broader variables (technology adoption, export dynamics), and apply the growth-decomposition-instability framework to other perennial crops.

• Spatial scope limited to three major coconut-producing South Indian states; findings may not generalize to other regions.
• Reliance on time-series data constrains spatial analyses and may omit location-specific heterogeneity.
• Some potentially relevant variables (e.g., detailed technical factors, export measures) were excluded due to data unavailability across the full period.