Parametric And Non-Parametric Techniques In Estimating Technical Efficiency Of Crude Palm Oil Production In Malaysia
The main purpose of this study is to apply parametric and non-parametric techniques in evaluating the technical efficiency (TE) of crude palm oil (CPO) production by the states in Malaysia. To achieve this, the parametric stochastic frontier analysis (SFA) approach as well as the non-parametric data...
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.usm.my/48165/1/MARIAH%20BINTI%20SABAR%20cut.pdf |
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| Summary: | The main purpose of this study is to apply parametric and non-parametric techniques in evaluating the technical efficiency (TE) of crude palm oil (CPO) production by the states in Malaysia. To achieve this, the parametric stochastic frontier analysis (SFA) approach as well as the non-parametric data envelopment analysis (DEA) and stochastic data envelopment analysis (SDEA) methods were applied. This study involves a panel data consisting of 12 CPO producing states in Malaysia, over a 18 year time period from year 1999 to 2016. The output variable chosen was the annual CPO production and the input variables considered were plantation area, fruit mill capacity, labour and time variable. We found fruit mill capacity, labour and time as input variables that significantly affect the level of CPO output. Plantation area was proven to be statistically insignificant. Technical efficiency was found to be increasing over time. It was also found that the inefficiencies in the industry were mainly caused by ‘pure’ technical inefficiency rather than scale inefficiency. The outputs produced from SFA, DEA and SDEA were compared. The overall mean TE of SFA, DEA and SDEA are 0.79, 0.88 and 0.97 respectively. It was found that DEA produced efficiency values that have weak positive correlation to both the efficiency scores produce from SFA and SDEA. Meanwhile, the results from SFA and SDEA were uncorrelated. We discovered that the choice of technique in efficiency measurement greatly influences the efficiency values estimated and the efficiency rankings of the states. |
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