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Production Structure and Technical Efficiency of the Indian Pharmaceutical Industry : A Parametric Analysis


Affiliations
1 Assistant Professor in Economics, PG Department of Economics, Khalsa College, Amritsar, Punjab, India
2 Professor of Economics, Former Head, and Dean Faculty, Punjab School of Economics, Guru Nanak Dev University, Amritsar, Punjab, India

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This paper endeavored to examine the production structure and technical efficiency in Indian pharmaceutical industry during 1974-75 to 2011-12. In view of achieving the above objective, data was culled out from the various reports of the Annual Survey of Industries and Handbook of Statistics. For analysis purpose, the stochastic frontier approach was used to estimate the production function and the time varying technical efficiency in the Indian pharmaceutical industry. The empirical analysis based on the econometric technique showed that the Cobb-Douglas production function with Hicks-neutral technical progress was not appropriate in case of the Indian pharmaceutical industry. Therefore, it was observed that the translog production function with capital using non-neutral technological progress represented the technological relationship in the Indian pharmaceutical industry. Moreover, the time-variant prediction of technical efficiency at constant returns to scale, at varying returns to scale, and scale efficiency in the Indian pharmaceutical industry during the study period revealed that the average technical efficiency at constant returns to scale for the Indian pharmaceutical industry during the entire period turned out be 0.995 and it implied that the Indian pharmaceutical industry had realized about 99.5% of its technical abilities. Thus, there were very less variations in the technical efficiency in the Indian pharmaceutical industry and showed the stable trends throughout the study period.

Keywords

Pharmaceutical Industry, Technical Efficiency, Stochastic Frontier

C21, L65, Q12

Paper Submission Date : July 17, 2017 ; Paper sent back for Revision : September 27, 2017 ; Paper Acceptance Date : October 28 , 2017.

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  • Production Structure and Technical Efficiency of the Indian Pharmaceutical Industry : A Parametric Analysis

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Authors

Jaswinder Singh
Assistant Professor in Economics, PG Department of Economics, Khalsa College, Amritsar, Punjab, India
Parminder Singh
Professor of Economics, Former Head, and Dean Faculty, Punjab School of Economics, Guru Nanak Dev University, Amritsar, Punjab, India

Abstract


This paper endeavored to examine the production structure and technical efficiency in Indian pharmaceutical industry during 1974-75 to 2011-12. In view of achieving the above objective, data was culled out from the various reports of the Annual Survey of Industries and Handbook of Statistics. For analysis purpose, the stochastic frontier approach was used to estimate the production function and the time varying technical efficiency in the Indian pharmaceutical industry. The empirical analysis based on the econometric technique showed that the Cobb-Douglas production function with Hicks-neutral technical progress was not appropriate in case of the Indian pharmaceutical industry. Therefore, it was observed that the translog production function with capital using non-neutral technological progress represented the technological relationship in the Indian pharmaceutical industry. Moreover, the time-variant prediction of technical efficiency at constant returns to scale, at varying returns to scale, and scale efficiency in the Indian pharmaceutical industry during the study period revealed that the average technical efficiency at constant returns to scale for the Indian pharmaceutical industry during the entire period turned out be 0.995 and it implied that the Indian pharmaceutical industry had realized about 99.5% of its technical abilities. Thus, there were very less variations in the technical efficiency in the Indian pharmaceutical industry and showed the stable trends throughout the study period.

Keywords


Pharmaceutical Industry, Technical Efficiency, Stochastic Frontier

C21, L65, Q12

Paper Submission Date : July 17, 2017 ; Paper sent back for Revision : September 27, 2017 ; Paper Acceptance Date : October 28 , 2017.




DOI: https://doi.org/10.17010/aijer%2F2017%2Fv6i5%2F119515