Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2019, Cilt: 3 Sayı: 2, 110 - 115, 28.06.2019

Öz

Kaynakça

  • [1] J. Felipe and G.F. Adams, “A theory of production the estimation of the Cobb-Douglas function: a retrospect view”, Eastern Economic Journal vol 31(3), pp:427-445, 2005.
  • [2] I.P.J. Bagus, M.Z. Yuri and N. Rahmet, “Resilient structure assessment using Cobb-Douglas Production Function: the case of the Indonesian metal industry”, International Journal of technology, vol 9(5) pp:1061-1071, 2018.
  • [3] Y. Zaijian, “Analysis of agricultural input-output based on Cobb-Douglas production function in Hebei Province, North China”, African Journal of Microbiology Research vol. 5(32), pp:5916-5922, 2011.
  • [4] J. Klacek, V. Miloslav, and S. Stefan, “KLE Translog Production Function and Total Factor Productivity” Statistical, 4/2007, pp:281-294, 2007.
  • [5] K. J. Arrow, B. H. Chenery, B. S. Minhas and R. M. Solow, “Capital-Labour Substitution and Economics Efficiency”, The Review of Economics and Statistics, 43(3), pp: 225-250, 1961.
  • [6] A. Hennigsen, and G. Henningsen, “Economic Estimate of the Constant Elasticity of Substitution Functions”, Economics Letters, vol.115, no.1, pp: 67-69, 2011.
  • [7] K. Sato, “A Two-Level Constant Elasticity of Substitution Production Function”, The Review of Economic Studies, vol. 43, pp: 201-218, 1967.
  • [8] E. R. Berndt, and M. Khaled, “Parametric Productivity Measurement and Choice among Flexible Functional Forms”, Journal of Political Economy, vol. 87, no. 6, pp: 1220-1245, 1979.
  • [9] D. Harry, “Fuel Conserving (and Using) Production Functions”, Energy Economics, vol. 38, pp: 2184-2235, 2008.
  • [10] J. W. Graham, and C. Green, “Estimating the Parameters of a Household Production Function with Joint Products”, The Review of Economics and Statistics, vol. 66, no 2, pp: 277-282, 1984.
  • [11] P. D. Constantia, D. L. Martin and E. B. Bastiaan, “Cobb-Douglas Translog Stochastic Production Function and Data Envelopment, Analysis in Total Factor Productivity in Brazilian Agribusiness”, The Flagship Research Journal of International Conference of the Production and Operations Management Society, vol. 2, no. 2, pp: 20-34, 2009.
  • [12] S. Chatterjee, and A.S. Hadi, “Regression Analysis by Example”, 4th Edition, John Wiley and Sons Inc., Hoboken, New Jersey, 2006.
  • [13] W. Mendenhall, and J.E. Reinmuth, “Point Estimate of a Population Mean”, Statistics for Management and Economics, Duxbury Press, Boston Massachusetts, pp: 257-261, 1982.
  • [14] G. C. Ovuworie, and A.O. Banjo, “The Danger in not utilizing appropriate management science tools in manufacturing”, Nigerian Journal of Engineering Management, vol. 7 (2), pp:1-7, 2006.

An Evaluation of Resource Utilisation in Palm Oil Industry using the Modified Cobb-Douglas Decision Model

Yıl 2019, Cilt: 3 Sayı: 2, 110 - 115, 28.06.2019

Öz

Aggregate production functions, particularly the
Cobb-Douglas model have been widely used in modeling input and output
relationships in various organisations and at national economic levels. Most
commonly used is the two-factor model where all inputs are aggregated as
capital and labour factors of production. In this paper, a six-factor
Cobb-Douglas model has been fitted to a ten-year production data obtained from
a palm-oil producer. By logarithmic transformation, the normal equations
obtained from the model were solved by the Least Squares method to obtain the
output elasticities. The bootstrapping technique was used to establish their
validity. The input components were aggregated
and used in the traditional aggregate Cobb-Douglas model to obtain comparative
results. For the disaggregated model, the output elasticities for the six input
components were found to be 0.1653, 0.0457, 0.0864,-0.3136, 0.0403 and 0.3845
respectively, resulting in a decreasing return to scale of 0.4086. In the case
of aggregate model, we have output elasticities of 0.4578 and 0.2730 for
aggregate capital and labour respectively, also indicating a decreasing return
to scale of 0.7308. However it was found that while the aggregate model gave a
generalized result, the disaggregated approach pointed to specific aspects of
the inputs that were adversely affecting the productivity of the organization
and thus requiring stringent management control. Thus the study showed that the
disaggregated Cobb-Douglas production function is superior to the traditional
two-factor model. The model developed which was statistically tested, is novel
and provides robust decision support for budding and seasoned firms.

Kaynakça

  • [1] J. Felipe and G.F. Adams, “A theory of production the estimation of the Cobb-Douglas function: a retrospect view”, Eastern Economic Journal vol 31(3), pp:427-445, 2005.
  • [2] I.P.J. Bagus, M.Z. Yuri and N. Rahmet, “Resilient structure assessment using Cobb-Douglas Production Function: the case of the Indonesian metal industry”, International Journal of technology, vol 9(5) pp:1061-1071, 2018.
  • [3] Y. Zaijian, “Analysis of agricultural input-output based on Cobb-Douglas production function in Hebei Province, North China”, African Journal of Microbiology Research vol. 5(32), pp:5916-5922, 2011.
  • [4] J. Klacek, V. Miloslav, and S. Stefan, “KLE Translog Production Function and Total Factor Productivity” Statistical, 4/2007, pp:281-294, 2007.
  • [5] K. J. Arrow, B. H. Chenery, B. S. Minhas and R. M. Solow, “Capital-Labour Substitution and Economics Efficiency”, The Review of Economics and Statistics, 43(3), pp: 225-250, 1961.
  • [6] A. Hennigsen, and G. Henningsen, “Economic Estimate of the Constant Elasticity of Substitution Functions”, Economics Letters, vol.115, no.1, pp: 67-69, 2011.
  • [7] K. Sato, “A Two-Level Constant Elasticity of Substitution Production Function”, The Review of Economic Studies, vol. 43, pp: 201-218, 1967.
  • [8] E. R. Berndt, and M. Khaled, “Parametric Productivity Measurement and Choice among Flexible Functional Forms”, Journal of Political Economy, vol. 87, no. 6, pp: 1220-1245, 1979.
  • [9] D. Harry, “Fuel Conserving (and Using) Production Functions”, Energy Economics, vol. 38, pp: 2184-2235, 2008.
  • [10] J. W. Graham, and C. Green, “Estimating the Parameters of a Household Production Function with Joint Products”, The Review of Economics and Statistics, vol. 66, no 2, pp: 277-282, 1984.
  • [11] P. D. Constantia, D. L. Martin and E. B. Bastiaan, “Cobb-Douglas Translog Stochastic Production Function and Data Envelopment, Analysis in Total Factor Productivity in Brazilian Agribusiness”, The Flagship Research Journal of International Conference of the Production and Operations Management Society, vol. 2, no. 2, pp: 20-34, 2009.
  • [12] S. Chatterjee, and A.S. Hadi, “Regression Analysis by Example”, 4th Edition, John Wiley and Sons Inc., Hoboken, New Jersey, 2006.
  • [13] W. Mendenhall, and J.E. Reinmuth, “Point Estimate of a Population Mean”, Statistics for Management and Economics, Duxbury Press, Boston Massachusetts, pp: 257-261, 1982.
  • [14] G. C. Ovuworie, and A.O. Banjo, “The Danger in not utilizing appropriate management science tools in manufacturing”, Nigerian Journal of Engineering Management, vol. 7 (2), pp:1-7, 2006.
Toplam 14 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Tina Francis-akilaki

Monday Omoregie

Yayımlanma Tarihi 28 Haziran 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 3 Sayı: 2

Kaynak Göster

IEEE T. Francis-akilaki ve M. Omoregie, “An Evaluation of Resource Utilisation in Palm Oil Industry using the Modified Cobb-Douglas Decision Model”, IJESA, c. 3, sy. 2, ss. 110–115, 2019.

ISSN 2548-1185
e-ISSN 2587-2176
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