This study analyses the current level of technical efficiency of the Sri Lankan rubber industry with respect to its sub-sectors (smallholding sector and estate sector). It also allows for the identification of factors influencing technical inefficiency in both sectors of the rubber industry.
An over-view of the structure of the industry revealed a number of notable differences between the smallholding sector and the estate sector, particularly in regards to yield, trees, tapping system and days, clones, use of labour and fertiliser. Hence, we would expect the two rubber sectors in Sri Lanka to exhibit different productivity/efficiency patterns.
The mean and farm/estate specific technical efficiencies were estimated for both smallholdings and estates using the stochastic frontier production time-varying model for unbalanced panel data. The advantage of this model is that by imposing various restrictions on the efficiency component, the models suggested in the literature could be obtained and estimated.
Data from a sample of 338 rubber smallholdings and 32 rubber estates were gathered from the two major rubber growing districts of Kalutara and Kegalle in order to analyse technical efficiency. The effect of each input factor on yield was determined before including them in production frontier analysis. Results showed that farms between 1.62ha and 40ha using lower level of inputs obtained correspondently lower output levels, while farms less than 1.62ha and estates using higher levels of inputs obtained higher output.
The estimated mean technical efficiency of farms of less than 0.81ha size and 0.81-1.61ha size groups were 73 percent and 67 percent respectively. Also these two farm groups operate at significantly different levels of technical efficiency. Individual farm technical efficiencies of above two farm groups showed a wide range of technical efficiency at farm level. Farms between 1.62ha and 40ha operate at their full technical efficiency. The mean technical efficiency of estates was 93 percent and they operate at a significantly different level compared to smallholdings.
Number of tapping days, growing more than one clone in their farms and Agalawatta soils influenced technical inefficiency in less than 0.81ha size farms whereas farmer experience, Homagama and Parambe soils influenced technical inefficiency in 0.81 to 1.61ha size farms. Estate size, number of tapping days, annual rainfall and Agalawatta soils influenced inefficiency in estates. Several policy measures and some topics for future research are also listed. Listed policy measures should be examined from the standpoint of agricultural science before possible implementation.[Show full abstract]
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