دوره 7، شماره 26 - ( 10-1395 )                   سال7 شماره 26 صفحات 165-141 | برگشت به فهرست نسخه ها


XML English 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-fa.html
محمودزاده محمود، فتح آبادی مهدی. عوامل پیشران بهره‌وری کل عوامل تولید در صنایع تولیدی ایران. تحقیقات مدلسازی اقتصادی. 1395; 7 (26) :141-165

URL: http://jemr.khu.ac.ir/article-1-1371-fa.html


1- آزاد فیروزکوه ، mahmod.ma@yahoo.com
2- آزاد فیروزکوه
چکیده:   (6905 مشاهده)

هدف این مقاله «شناسایی عوامل پیشران بهره‌وری کل عوامل تولید در صنایع تولیدی ایران» است. بدین منظور بهره‌وری کل عوامل تولید 21 صنعت تولیدی به چهار عامل پیشرفت تکنولوژیکی، کارایی فنی، کارایی تخصیصی و اثرات مقیاس بر مبنای روش حسابداری رشد جدید در دوره  1379-90 تجزیه شده است. یافته‌ها نشان می‌دهد کشش تولیدی نیروی کار و سرمایه به ترتیب 57/0 و 13/0 بوده و بازدهی نسبت به مقیاس، کمتر از واحد است. محاسبات گویای این است که فقط 8 صنعت از 21 صنعت، رشد بهره‌وری را تجربه ‌کرده‌اند. در این میان، صنایع الکترونیکی و ارتباطاتی، پزشکی و اپتیکی و کاغذ بیشترین رشد بهره‌وری را داشته‌اند. بیشترین پیشرفت فنی در صنایع شیمیایی، کانی غیرفلزی، فلزات اساسی و وسایل نقلیه موتوری، تریلر و نیمه‌تریلر با نرخ رشد متوسط 11 درصد و کمترین رشد متعلق به صنعت پوشاک با نرخ رشد متوسط 7 درصد بوده است. اگرچه پیشرفت تکنولوژیکی (به عنوان عامل پیشران) سبب بهبود وضعیت بهره‌وری کل شده است؛ اما تغییرات کارایی فنی، اثرات مقیاس و کارایی تخصیصی اثرات آن را خنثی کرده‌اند.

متن کامل [PDF 242 kb]   (3159 دریافت)    
نوع مطالعه: كاربردي | موضوع مقاله: سایر
دریافت: 1394/11/26 | پذیرش: 1395/8/26 | انتشار: 1395/12/11

فهرست منابع
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.

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

ارسال پیام به نویسنده مسئول


بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به فصلنامه تحقیقات مدلسازی اقتصادی می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

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

Designed & Developed by : Yektaweb