Volume 7, Issue 26 (12-2016)                   jemr 2016, 7(26): 141-165 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

mahmodzadeh M, fathabadi M. Driving Factors of Total Factor Productivity in Iranian Manufacturing Industries. jemr 2016; 7 (26) :141-165
URL: http://jemr.khu.ac.ir/article-1-1371-en.html
1- Azad university , mahmod.ma@yahoo.com
2- Azad university
Abstract:   (6776 Views)

The aim of this paper is decomposition of total factor productivity (TFP) growth to four factors technological progress, technical efficiency, allocative efficiency, scale effects in 21 manufacturing industries, using a panel data technique, during 2000-2011.Findings show that the production elasticity related to labor and capital is o.57 and 0.13, respectively and economy of scale is less than unit. Also, results indicate that productivity growth is positive only in 8 industries that include electronics, communications, paper, medical and optical industries. The decomposition reveals that, TP has been the main driving force of productivity growth- especially in chemical, non-metal mineral, primary metal, motor vehicles, trailers and semi-trailers- while negative efficiency changes, allocative efficiency and scales effects observed in certain industries have contributed to reduce average productivity growth.

Full-Text [PDF 242 kb]   (3102 Downloads)    
Type of Study: Applicable | Subject: سایر
Received: 2016/02/15 | Accepted: 2016/11/16 | Published: 2017/03/1

References
1.  Aigner, D.J., & Lovell, C.A.K. & Schmidt, P. (1977). Formation and estimation of stochasticFrontier production function models. Journal of Econometrics, 6(1), 21-37. [DOI:10.1016/0304-4076(77)90052-5]
2.  Baltagi, B.H & Griffin, J.M. (1988). A generalized error component model with heteroscedastic disturbances, Int. Econ. Rev. 29; 745–753.
3.  Bassem, B. S. (2014). Total factor productivity change of MENA microfinance institutions: A Malmquist productivity index approach. Economic Modelling, 39, 182-189. [DOI:10.1016/j.econmod.2014.02.035]
4.  Battese, G.E. and Coelli, T.J. (1992b). Frontier production functions, technical efficiency andpanel data: with application to paddy farmers in India. Journal of Productivity Analysis,3 (1/2), 153-69.
5.  Battese, G.E. and Coelli, T.J. (1993). A stochastic frontier production function incorporating amodel for technical inefficiency effects. Working Papers in Econometrics and AppliedStatistics No. 69, Department of Econometrics, University of New England, Armidale.
6.  Battese, G.E. and Coelli, T.J. (1995). A model for technical inefficiency effects in the stochasticFrontier production for panel data. Empirical Economics, 20 (2), 325-32. [DOI:10.1007/BF01205442]
7.  Battese, G.E., & Coelli, T.J. (1992a). A model for technical inefficiency effects in the stochasticFrontier production for panel data. Empirical Economics, 20 (2), 325-32.
8.  Cho, Y. C. Shao, B.B.M. (2014). Total factor productivity growth in information technology services industries: A multi-theoretical perspective. Decision Support Systems, 62, 106–118. [DOI:10.1016/j.dss.2014.03.009]
9.  Dashti, N., Yavari,K. and Sabbagh, M. (2009), Decomposition of TFP Spillover in Iranian Industrial Sector, Quantitative Jourbal, 6(1): 101-128.
10. ♣ Diewert, W.E. (1981).The theory of total factor productivity measurement in regulated industries, in: T.G. Cowing, R.E. Stevenson (Eds.), Productivity Measurement in Regulated Industries, Academic Press, New York.
11.  Domazlicky, B.R. and Weber, W.L. (1998), "Determinants of total factor productivity,technological change and efficiency differentials among states, 1977-1986. Review of Regional Studies, 28 (2), 19-33.
12.  Farrell M.J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. 120(3): 253-290.
13.  Fecher, F. and Perelman, S. (1992), "Productivity growth and technical efficiency in OECDindustrial activities", Industrial Efficiency in Six Nations, The MIT Press, Cambridge, MA.
14.  Gebremichael, B. Z., Rani, D. L. (2012). Total factor productivity change of ethiopian microfinance institutions (mfis): A malmquist productivity index approach (mpi). European Journal of Business and Management, 4(3), 105-114.
15.  Heshmati, A. Kumbhakar,S. (2011). Technical change and total factor productivity growth: The case of Chinese provinces. Technological Forecasting & Social Change, 78, 575–590. [DOI:10.1016/j.techfore.2010.11.006]
16.  Heshmati, A. Nafar, N.(1998) A production analysis of the manufacturing industries in Iran, Technol. Forecast. Soc. Change 59; 183–196.
17.  Jorgenson, D (1995) Productivity, 1 and 2, MIT Press, Cambridge, Mass.
18.  Khiabani, N. and Hassani, K. (2010), Technical and allocative inefficiencies and factor elasticities of substitution:An analysis of energy waste in Iran's manufacturing, Energy Economics, vol. 32, pp. 1182–1190.
19.  Kim, S. & Han, G. (2001). A decomposition of total factor productivity growth inKorean manufacturing industries: a stochastic Frontier approach. Journal of Productivity Analysis16 (3), 269-81. [DOI:10.1023/A:1012566812232]
20.  Kumbhakar, S.(2000) Estimation and decomposition of productivity change when production is not efficient: a panel data approach, Econometric Rev. 19, 425–460.
21.  Kumbhakar, S.C. Heshmati, A. (1996) Technical change and total factor productivity growth in Swedish manufacturing industries, Econometric Rev. 15 (3), 275–298.
22.  Kumbhakar, S.C. Heshmati, A. Hjalmarsson, L.(1999) Parametric approaches to productivity measurement: a comparison among alternative models, Scand. J. Econ. 101; 405–424. [DOI:10.1111/1467-9442.00163]
23.  Kumbhakar, S.C. Nakamura, Heshmati, S. A. (2000) Estimation of firm-specific technological bias, technical change and total factor productivity: a dual approach, Econometric Rev. 19 (4), 493–515.
24.  Kumbhakar, S.C. (1990), "Production Frontiers, panel data, and time-varying technicalinefficiency", Journal of Econometrics, Vol. 46 Nos 1/2, pp. 201-11.
25.  Kumbhakar, S.C. and Lovell, C.A.K. (2000), Stochastic Frontier Production, CambridgeUniversity Press, New York, NY, 279-309.
26.  Kumbhakar, S.C., Ghosh, S. and McGuckin, J.T. (1991). A generalized production Frontierapproach for estimating determinants of inefficiency in US dairy farms. Journal of Business and Economic Statistics, 9 (3), 279-86. https://doi.org/10.2307/1391292 [DOI:10.1080/07350015.1991.10509853]
27.  Long, X. Zhao, X. Cheng, F. (2015). The comparison analysis of total factor productivity and eco-efficiency in China's cement manufactures. Energy Policy, 81, 61–66. [DOI:10.1016/j.enpol.2015.02.012]
28.  Mahmoudzadeh, M. (2009), Effect of IT on Labor Productivity in Iranian Manufacturing Industries, New Trade and Economic Journal, 18: 1-22.
29.  Meeusen, W. & van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas productionfunctions with composed error. International Economic Review, 18 (2), institutions (MFIs): Evidence from South Asian countries. Economic Analysis and Policy, 51, 32-45.
30.  Mia, M. A., Chandran, V. G. R. (2015). Measuring Financial and Social Outreach Productivity of Microfinance Institutions in Bangladesh. Social Indicators Research, 1-23.
31.  Nishimizu, M.& Page, J.M. (1982). Total factor productivity growth, technological progressand technical efficiency change: dimensions of productivity change in Yugoslavia,1965-78", Economic Journal, 9, 920-36.
32.  Oh, D.-H. Heshmati, A. Lööf, H.(2009). Total Factor Productivity of Korean Manufacturing Industries: Comparison of Competing Models with Firm-Level Data, CESIS Electronic. Working Paper Series 201.
33.  Oh, D.H. Lee, Y.G. (2016). Productivity decomposition and economies of scale of Korean fossil-fuel power generation companies: 2001-2012. Energy, 100, 1-9. [DOI:10.1016/j.energy.2016.01.004]
34.  Pitt, M. & Lee, L.-F. (1981). The measurement and sources of technical inefficiency in theIndonesian weaving industry. Journal of Development Economics, 9 (1), 43-64. [DOI:10.1016/0304-3878(81)90004-3]
35.  Schmidt, P. & Sickles, R.C. (1984). Production Frontiers and panel data. Journal of Business and Economic Statistics, 2 (4), 367-74. https://doi.org/10.1080/07350015.1984.10509410 [DOI:10.2307/1391278]
36.  Shahiki Tash, M.N., Norouzi, A. and Rahimi, Gh. (2013), Economies Scale, Optimal Product and Substitution Elasticity in Iranian Energy Sectors, Quarterly Journal of Environment Economic and Energy, 2(6): 75-105.
37.  Sharma, S.C., Sylwester, K. and Margono, H. (2007). Decomposition of total factor productivitygrowth in US states. Quarterly Review of Economics and Finance, 47 (2), 215-41. [DOI:10.1016/j.qref.2006.08.001]
38.  Sobhani, H. and Aziz Mohammadlou, Kh. (2008), The Comparision Analysis of TFP in Iranian Industrial Sub Sectors, Economic Research Journal, 82: 87-120.
39.  Solow, R.M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39 (3), 312-20. [DOI:10.2307/1926047]
40.  Sun, K. Kumbhakar, & S.C. Tveteras, R. (2015). Productivity and efficiency estimation: A semiparametric stochastic cost frontier approach. European Journal of Operational Research, 245, 194–202. [DOI:10.1016/j.ejor.2015.03.003]
41.  Wijesiri, M., Meoli, M. (2015). Productivity change of microfinance institutions in Kenya: A bootstrap Malmquist approach. Journal of Retailing and Consumer Services, 25, 115- 121. [DOI:10.1016/j.jretconser.2015.04.004]
42.  Wu, Y. (2011). A Comparative Analysis of the Operating and Economic Efficiency of China's Microfinance Institutions, Traditional Chinese Agricultural Lenders, and Counterpart Indian Microfinance Institutions. University of Georgia.
43.  Zamanian, Gh., Fotros, M.H. and Rezaei, E. (2014), The Effect of R&D Spillover on Iranian Manufacturing TFP, Quarterly Journal of Development Economics and Growth, 5(17): 91-108.

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Economic Modeling Research

Designed & Developed by : Yektaweb