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

Decomposition of Output and Productivity Growth in the 2-Digit Manufacturing Industries in India:An Interstate Analysis


Affiliations
1 Department of Economics, Midnapore College, Midnapore, Paschim Medinipur 721101, West Bengal, India
2 Vidyasagar University, Midnapore, West Bengal and Vinod Gupta School of Management, IIT, Kharagpur, Paschim Medinipur 721302, West Bengal, India
     

   Subscribe/Renew Journal


The study examines and applies the theoretical foundation of the decomposition of output total factor productivity growth (TFPG) of the 2-digit manufacturing industries in India and in its fifteen major industrialized states from 1981-1982 to 2010-2011, during the pre- and post-reform period (1981-1982 to 1990- 1991and 1991-1992 to 2010-2011). Output growth is decomposed into input growth effect and TFPG where the three attributes of TFPG are adjusted scale effect technological progress and technical efficiency change. A stochastic frontier model with a translog production function is used to estimate the growth attributes of TFP of the 2-digit manufacturing industries in 15 major industrialized states vis-a-vis all-India. Empirical results show that input growth effect is the major contributor to output growth, whereas TFPG sometimes remains inadequate even though it has a significant effect on output growth. Technological progress is found to be the major contributor to TFPG and the decline in it of the 2-digit manufacturing industries in almost all the states as well as in all-India during the post-reform period is due to decline in technological progress of the same. The scale effect has also become important in recent years, but the impact of technical efficiency effect becomes negative in most cases. The relevant policy implication for a sustainable post-reform Indian economy is the need to improve TFPG components of the manufacturing industries for the overall balanced growth of the economy.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Aigner, D.J.C., A.K. Lovell and P. Schmidt (1977), Formulation and Estimation of Stochastic Frontier Production Function Models, Journal of Econometrics, 6(1): 21-37, July.
  • Battese, G.E. and T.J. Coelli (1988), Prediction of Farm Level Technical Efficiencies with a Generalized Frontier Production Function and Panel Data, Journal of Econometrics, 38: 387399, North Holland.
  • Battese, G.E. and T.J. Coelli (1992), Frontier Production Functions, Technical Efficiency and Panel Data: With Application to Paddy Farmars in India, Journal of Productivity Analysis 3(1/2), 153-169, June.
  • Bauer, P.W. (1990), Recent Developments in the Econometric Estimation of Frontiers, Journal of Econometrics, 46(1/2): 39-56.
  • Brummer, B., T.G. Glauben and W. Lu (2006), Policy Reform and Productivity Change in Chinese Agriculture: A distance function approach, Journal of Development Economics, 81: 61-79.
  • Charnes, A., W.W. Cooper and E.L. Rhodes (1978), Measuring the Efficiency of Decision Making Units, EJOR, 2(6): 429-444.
  • Christensen L.R, Jorgensen D.W and Lau L.I (1971), Conjugate Duality and the Transcendental Logarithmic Production Function, Econometrica, 39: 225-256.
  • Coelli, T.J. (1996), A Guide to FRONTIER Version 4.1: A Computer Program for Stochastic Frontier Production and Cost Function Estimation, CEPA Working Paper, 7/96, Dept. of Econometrics, University of New England, Armidale.
  • CSO (2007), National Account Statistics, Government of India, New Delhi.
  • Denny, Michael, M. Fuss, C. Everson and L. Waverman (1981), Estimating the Effects of Diffusion of Technological Innovations in Telecommunications: The Production Structure of Bell Canada, Canadian Journal of Economics, 14(1): 24-43.
  • Fu, X., S. Heffernan (2005), Cost X-efficiency in China’s Banking Sector, Working Paper, Cass Business School, City University, London.
  • Goldsmith, Raymond W. (1951), Perpetual Inventory of National Wealth, Studies in Income and Wealth, Volume, 14: 5-61, NBER, New York.
  • Gounder, R. and V. Xayayong (2004), A Decomposition of Total Factor Productivity Growth in New Zealand’s Manufacturing Industries: A Stochastic Frontier Approach, Paper presented at the New Zealand Association of Economists’ Conference, Wellington, 30th June to 2nd July, 2004.
  • Greene, W. (2005), Reconsidering Heterogeneity in Panel Data Estimators of the Stochastic Frontier Model, Journal of Econometrics, 126: 269-303.
  • Jorgenson, Dale and Z. Griliches (1967), The Explanation of Productivity Change, The Review of Economic Studies, 34(3): 249-280, July.
  • Kim, S. and G. Han (2001), A Decomposition of Total Factor Productivity Growth in Korean Manufacturing Industries: A Stochastic Frontier Approach, Journal of Productivity Analysis, 16(3), 269-281.
  • Kumbhakar, S.C. (1990), Production Frontiers, Panel Data and Time-varying Technical Inefficiency, Journal of Econometrics, 46(1/2): 201-212, (Oct/Nov).
  • Kumbhakar, S.C. and C.A. Knox Lovell (2000), Stochastic Frontier Analysis, Cambridge University Press, Cambridge, U.K., pp. 279-309.
  • Li, Kui-Wai and Tung Liu (2011), Economic and Productivity Growth Decomposition: An Application to Post-reform China, Economic Modeling, 28: 366–373
  • Meeusen, W. and J. Van den Broeck (1977), Efficiency Estimation form Cobb-Douglas Production Function with Composed Error, International Economic Review, 18(2): 435-444, June.
  • Nishimizu, M. and J.M. Page (1982), Total Factor Productivity Growth, Technological Progress and Technical Efficiency Change: Dimensions of Productivity Change in Yugoslavia, 1965-78, Economic Journal, 92(368): 920-936, Dec.
  • Roy, P.K. and P.S. Das (2018), Productivity Growth Decomposition in the Manufacturing Industries of Food, Beverages and Tobacco Products in India: A Stochastic Frontier Approach, Arthashastra: Indian Journal of Economics & Research, 7 (1): 37-57, Jan. & Feb.
  • Roy, P.K., P.S. Das and C. Neogi (2015), Interstate Analysis of the Decomposition of Total Factor Productivity Growth in the Organized Manufacturing Industries in India: A Stochastic Frontier Approach, Artha Vijnana, LVII (2): 135-160, June.
  • Roy, P.K., P.S. Das and M.K. Pal (2016), Productivity Growth in Indian Manufacturing: Panel Estimation of Stochastic Production Frontier, Indian Journal of Industrial Relations, Sri Ram Centre for Industrial Relations, Human Resources, Economic & Social Development, 52(1): 71-86, July.
  • ---------- (2017), Decomposition of Total Factor Productivity Growth of the 2-Digit Manufacturing Industries in West Bengal: A Stochastic Frontier Approach, Arthaniti, XVI (1&2): 101-124, December.
  • ---------- (2018), Output and Productivity Growth Decomposition: A Panel Study of Manufacturing Industries in India, The Indian Journal of Industrial Relations, Sri Ram Centre for Industrial Relations, Human Resources, Economic & Social Development, New Delhi, 53(3): 361-377, January.
  • Solow, Robert M. (1957), Technical Change and the Aggregate Production Function, The Review of Economics and Statistics, 39(3): 312-320, August.
  • Trivedi, P., A. Prakash and D. Sinate (2000), Productivity in Major Manufacturing Industries in India: 1973–74 to 1997–98, Development Research Group Study No. 20, Department of Economic Analysis and Policy, Reserve Bank of India, Mumbai.

Abstract Views: 33

PDF Views: 2




  • Decomposition of Output and Productivity Growth in the 2-Digit Manufacturing Industries in India:An Interstate Analysis

Abstract Views: 33  |  PDF Views: 2

Authors

Prasanta Kumar Roy
Department of Economics, Midnapore College, Midnapore, Paschim Medinipur 721101, West Bengal, India
Purnendu Sekhar Das
Vidyasagar University, Midnapore, West Bengal and Vinod Gupta School of Management, IIT, Kharagpur, Paschim Medinipur 721302, West Bengal, India

Abstract


The study examines and applies the theoretical foundation of the decomposition of output total factor productivity growth (TFPG) of the 2-digit manufacturing industries in India and in its fifteen major industrialized states from 1981-1982 to 2010-2011, during the pre- and post-reform period (1981-1982 to 1990- 1991and 1991-1992 to 2010-2011). Output growth is decomposed into input growth effect and TFPG where the three attributes of TFPG are adjusted scale effect technological progress and technical efficiency change. A stochastic frontier model with a translog production function is used to estimate the growth attributes of TFP of the 2-digit manufacturing industries in 15 major industrialized states vis-a-vis all-India. Empirical results show that input growth effect is the major contributor to output growth, whereas TFPG sometimes remains inadequate even though it has a significant effect on output growth. Technological progress is found to be the major contributor to TFPG and the decline in it of the 2-digit manufacturing industries in almost all the states as well as in all-India during the post-reform period is due to decline in technological progress of the same. The scale effect has also become important in recent years, but the impact of technical efficiency effect becomes negative in most cases. The relevant policy implication for a sustainable post-reform Indian economy is the need to improve TFPG components of the manufacturing industries for the overall balanced growth of the economy.

References





DOI: https://doi.org/10.21648/arthavij%2F2019%2Fv61%2Fi1%2F180161