Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Technical Efficiency Performance among Micro Enterprises in Dibrugarh District (Assam): A Stochastic Frontier Analysis


Affiliations
1 Department of Economics, DHSK College, Dibrugarh 786001, Assam, India
2 Department of Mathematics, Dibrugarh University, Dibrugarh 786001, Assam, India
     

   Subscribe/Renew Journal


This study analyses technical efficiency performance among micro enterprises in Dibrugarh; a developed and industrialised district in Assam using the Stochastic Production Frontier Model. It is based on cross sectional firm-level data collected through a field survey from 115 micro manufacturing enterprises. The results indicate the presence of a high degree of technical inefficiency in the production process. Output is more responsive to labour than capital, which points that higher productivity can be obtained by increasing labour and not by increasing mechanization. The enterprises are subject to decreasing returns to scale, suggesting that they are of supra-optimal size and need to adopt a policy of rational downsizing.

Further, an attempt has been made to identify firm-specific and entrepreneurial background variables responsible for inefficiency using Coelli’s Inefficiency Effects Model. It is found that skilled labour ratio, firm-age, gender and experience of the entrepreneur significantly affect technical efficiency in the firms. From policy perspective, the strong influence of skilled labour points to the needfor skill upgradation and training of the local labour force. The influence of age of firms is a pointer to the benefits of the principle of learning-by-doing and accumulated knowledge. Thus, along with the establishment of new enterprises, government support policies must focus on reorganization and rehabilitation of existing old firms. The empirical evidences also point to the need for industry–specific and gender-specific policy guidelines.


Subscription Login to verify subscription
User
Notifications
Font Size

  • Admassie, A. and F.A.S.T. Matambalya (2002), Technical Efficiency of Small and Medium Scale Enterprises: Evidence from a Survey of Enterprises in Tanzania, Eastern African Social Science Research Review, 18(2): 1-29.

  • Ahmadi, V. and A. Ahmadi (2012), Application of Data Envelopment Analysis in Manufacturing Industries of Iran, Interdisciplinary Journal of Contemporary Research in Business, 4(8): 534-544.

  • Amornkitvikai, Y and C. Harvie (2010), Identifying and Measuring Technical Inefficiency Factors: Evidence from Unbalanced Panel Data for Thai Listed Manufacturing Enterprises, Department of Economics, University of Wollongong, Working paper 05-10, 2010, p. 36, http://ro.uow.edu.au/commwkpapers/222.

  • Banerjee, A. (1971), ProductivityGrowth and Factor Substitution in Indian Manufacturing, Indian Economic Review, 6(1): 1-23, April.

  • Battese, G.E. and T.J. Coelli (1995), A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data, Empirical Economics, 20(2): 325-332.

  • Bhavani, T.A. (1991), Technical Efficiency in Indian Modern Small Scale Sector: An Application of Frontier Production Function, Indian Economic Review,26(2): 149-166.

  • Bhowmik, I. and P. Bose (2015), Efficiency and Impact of MGNREGS in Tripura, Social Change and Development, OKDISCD, Guwahati, XII(1): 1-18.

  • Coelli, T.J. (1996), A Guide to Frontier Version 2.1: A Computer Program for Stochastic Frontier Production and Cost Function Estimation, Working Papers, Armidale, The University of New England.

  • Coelli, T.J., D.S.P.Rao, C.J. O’Donnell and G.E. Battese (2005), An Introduction to Efficiency and Productivity Analysis 2, Springer, New York, USA.

  • Cooper, W.W., L.M. Seiford and K. Tone (2006),Introduction to Data Envelopment Analysis and Its Uses with DEA-Solver Software and References,Springer Science.

  • Duzakin, E. and H. Duzakin (2007), Measuring the Performance ofManufacturing Firms with Super Slacks Based Model of Data Envelopment Analysis: An Applicationof 500 Major Industrial Enterprises in Turkey, European Journal of Operational Research, 182(3): 1412-1432.

  • Little, I.M.D., D. Mazumdar and M. Page Jr John (1987), Small Manufacturing Enterprises: A Comparative Study of India and Other Economies, Oxford University Press, New York.

  • Memon, M.A. and I.M. Tahir (2012), Size and Operational Performance of Manufacturing Companies in Pakistan using DEA, Journal of Information Engineering and Application, 2(4): 39-49.

  • Mujaddad, H.G. and H.K. Ahmad (2016), Measuring Efficiency of Manufacturing Industries in Pakistan: An Application of DEADouble Bootstrap Technique, Pakistan Economic and Social Review, 54(2): 363-384, Winter.

  • Neogi, C. and B. Ghosh (1998), Impact of Liberalisation on Performance of Indian Industries: A Firm Level Study, Economic and Political Weekly, 33(9): 853-862, February 28.

  • Nikaido, Y. (2004), Technical Efficiency of Small-scale Industry: Application of Stochastic Production Frontier Model, Economic and Political Weekly, 39(6): 593-597, February 7.

  • Page, Jr John M. (1984), Firm Size and Technical Efficiency: Applications of Production Frontiers to Indian Survey Data, Journal of Development Economics, 16(1-2): 129-152.

  • Ramaswamy, K.V. (1994), Technical Efficiency in Modern Small-Scale Firms in Indian Industry: Applications of Stochastic Production Frontier, Journal of Quantitative Economics, 10(2): 309-324.

  • Sankar, U. (1970), Elasticities of Substitution and Returns to Scale in Indian Manufacturing Industries, International Economic Review, 11(3): 399-411.


Abstract Views: 389

PDF Views: 0




  • Technical Efficiency Performance among Micro Enterprises in Dibrugarh District (Assam): A Stochastic Frontier Analysis

Abstract Views: 389  |  PDF Views: 0

Authors

Rubab Fatema Nomani
Department of Economics, DHSK College, Dibrugarh 786001, Assam, India
Tazid Ali
Department of Mathematics, Dibrugarh University, Dibrugarh 786001, Assam, India

Abstract


This study analyses technical efficiency performance among micro enterprises in Dibrugarh; a developed and industrialised district in Assam using the Stochastic Production Frontier Model. It is based on cross sectional firm-level data collected through a field survey from 115 micro manufacturing enterprises. The results indicate the presence of a high degree of technical inefficiency in the production process. Output is more responsive to labour than capital, which points that higher productivity can be obtained by increasing labour and not by increasing mechanization. The enterprises are subject to decreasing returns to scale, suggesting that they are of supra-optimal size and need to adopt a policy of rational downsizing.

Further, an attempt has been made to identify firm-specific and entrepreneurial background variables responsible for inefficiency using Coelli’s Inefficiency Effects Model. It is found that skilled labour ratio, firm-age, gender and experience of the entrepreneur significantly affect technical efficiency in the firms. From policy perspective, the strong influence of skilled labour points to the needfor skill upgradation and training of the local labour force. The influence of age of firms is a pointer to the benefits of the principle of learning-by-doing and accumulated knowledge. Thus, along with the establishment of new enterprises, government support policies must focus on reorganization and rehabilitation of existing old firms. The empirical evidences also point to the need for industry–specific and gender-specific policy guidelines.


References





DOI: https://doi.org/10.21648/arthavij%2F2020%2Fv62%2Fi3%2F203583