Assessment of Rice Production Total Factor Productivity in several Province: Application of Separable Stochastic Frontier Function

مجله اقتصاد و توسعه کشاورزی

Article 4, Volume 30, Issue 3, October 2016, Pages 207-217   

Document Type: Research Article

DOI: 10.22067/jead2.v30i3.57530

Authors

H. Shahbazi^* ; A. Samdeliri

Sayyed Jamaleddin Asadabadi University

Abstract

Introduction: In this study, total factor productivity growth components in rough rice production are assisting by econometric approach and stochastic frontier function during 2005-2013 for several provinces (Mazandaran province, Guilan province, Golestan province, Fars province, Khoozestan province). According to Food and Agriculture Organization statics, Iran is the 3rd importer and 20th exporter of rice in the world. But, during the study years (2005-2013), Iran has been one of the 6 largest importers of these products that on average about 33 percent of domestic needs are provided by imports. Annual per capita consumption of rice during 1990-2012 had been changed from 38.6 to 43.9 Kilogram. So, it can be concluded that rice has a special place in the Iranian consumption bundle. But in the production sector, cultivation area has been decreasing 15 percent during 2005-2009 and was fixed during 2009-2013. These matters indicate that domesticate production cannot provide domesticate consumption. One of the suitable ways of increasing production is increasing in total factor productivity. This strategy is needed to identify components of TFP growth sources. So, the main goal of this study is the decomposition of rice TFP in Iran.
Materials and Methods: TFP decommission growth can be analytically by four approaches included econometric estimation of production and the cost function, TFP indices of Divisia and Turnqvist, Data envelopment approaches (DEA) such as Malmqvist and stochastic frontier analysis. This study uses a stochastic frontier analysis to decompose total factor productivity (TFP) growth into four components: technical change (TC), technical efficiency (TE) change, scale efficiency (SE) change, and allocative efficiency (AE) change. For this new approach, at first, Translog production function is estimated by gathering data. So, by estimation of Translog production function, total factor productivity growths are decomposed to TC and changes in TE, SE, and AE. For the total factor productivity decomposition, we employ the time-varying model for technical inefficiency. Firm inefficiency is assumed to be distributed as a generalized truncated–normal random variable which is distributed independently of the normally distributed random errors.
Results and Discussion: Results indicate technical efficiency have been 0.86, 0.79, 0.69, 0.73 and 0.86 for Mazandaran, Guilan, Golestan Khoozstan and Fars provinces, respectively for the year of 2012. That is, most technical efficiencies were for Mazandaran and Fars provinces. Also, technical efficiency has been 0.73, 0.75, 0.77, 0.81 and 0.81 for a farm with size less than 0.5 Ha, between 0.5 and 1 Ha, between 1 and 2 Ha, between 2 and 3 Ha and more than 3 Ha, respectively for years of 2012. That is, most technical efficiencies were from a farm with the size of more than 2 ha. The annual growth rate of technical efficiency changes during 2005-2013 have been 2.3, 1.6, 0.3, 0.9 and 1.6 percent for Mazandaran, Guilan, Golestan Khoozstan and Fars provinces, respectively. For Iran, also has been 1.5 percent. The annual growth rate of scale efficiency change during 2005-2013 have been 1.5, 1, 1, 1.2 and 2.3 percent for Mazandaran, Guilan, Golestan Khoozstan and Fars provinces, respectively. Also, for Iran it has been 1.9 percent. Annual growth rate of Allocative efficiency change during 2005-2013 have been 0.01, 0.6, 0.3, 0.5 and 0.5 percent for Mazandaran, Guilan, Golestan Khoozstan and Fars provinces, respectively. Also, for Iran it has been 0.8 percent. Finally, annual growth rate of TFP change during 2005-2013 have been 4.8, 3.8, 2.05, 3.1 and 4.7 percent for Mazandaran, Guilan, Golestan Khoozstan and Fars provinces, respectively. For Iran, also has been 4.3 percent. The most and least growth were for Mazandaran and Golestan Provinces. Differences in rough rice total factor productivity growth rates in the provinces were found to be explained primarily by differences in scale efficiency and technical efficiency. Scale elasticities for a year between 2005 and 2013 were between 1.13 and 1.12 for Mazandaran, between 1.12 and 1.13 (with fluctuation) for Guilan, between 1.14 and 1.13 for Golestan, between 1.18 and 1.19 for Khoozestan and between 1.14 and 1.18 for Fars. So, scale elasticities average between the sum of farms (between 1.12 and 1.18) shows that economics of scale exists in rough rice production technology. Scale elasticities for a year between 2005 and 2013 was between 1.24 and 1.27 for farm with size of less than 0.5 ha, between 1.17 and 1.22 for farm with size of between 0.5 and 1 ha, between 1.0.8 and 1.18 for farm with size of between 1 and 2 ha, between 1.05 and 1.13 for farm with size of between 2 and 3 ha and between 1.01 and 1.09 for farm with a size of more than 3 ha.
Conclusions: With the assumptions that rough rice production technology is similar in all provinces, approximately, differences between provinces in scale elasticities are about the size of the farm. That is, smaller farms in comparison with larger farms have more economics of scale. Finally, it can be noted that by increasing in size of farms, we can increase technical efficiency and TFP of rice production.

Keywords

allocative efficiency; Econometrics approach; Scale economics; Scale efficiency; Technical Efficiency

References

1- Akbari N., and Ranjkesh M. 2003. The Study of productivity growth in agricultural section of Iran. Journal of Agricultural Economics and Development, 11(43&44): 117-142. (In Persian with English abstract)

2- Alirezaei M., Abdollahzadeh GH., and Rajabi M. 2007. Analysis of locale difference in agricultural section productivity. Economics & Agriculture Journal, 1(2): 241-254. (In Persian with English abstract)

3- Baily M.N., Manyika J., and Gupta S. 2013. U.S. Productivity Growth: An Optimistic Perspective, International Productivity Monitor,25: 3–12.

4- Battese G., and Coelli T. 1995. A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function and Panel Data. Empirical Economics, 20(1): 325-332.

5- Battese G.E., and Coelli T.J. 1992. Frontier Production Functions, Technical Efficiency and Panel Data: With Application to Paddy Farmers in India. Journal of Productivity Analysis, 3(1):153–69.

6- Behrooz A., and Emami Meibodi A. 2014. Technical, Economical and Allocative Efficiency and Productivity Measurement of Crop sector, Agricultural Economic Research Journal, 6 (3): 43-66. (In Persian with English abstract)

7- Coelli T.J., Rao D., O’Donnell C.J., and Battese G.E. 2005. An Introduction to Efficiency and Productivity Analysis, 2nd ed. New York: Springer.

8- Coelli T.J.A., Estache S., Perelman A., and Trujillo L. 2003. A Primer on Efficiency Measurement for Utilities and Transport Regulators. Washington, DC: The World Bank.

9- Cummins DJ., and Xie X. 2013. Efficiency productivity, and Scale Economies in the U.S. Property-Liability Insurance Industry, Journal of Productivity Analysis, 39(2):141-164.

10- Diewert W. E. 1992. The measurement of productivity. Bulletin of Economic Research, 44: 1-166.

11- Emami Meybodi A. 2000. The principal of efficiency and productivity analysis. Institute of studies and trade researches. Tehran. (In Persian with English abstract)

12- Heshmati A., and Kumbhakar S. C. 2011a. A General Model of Technical Change with an Application to the OECD Countries, Discussion Paper, No. 6004.

13- Heshmati A., and Kumbhakar S.C. 2011b. Technical Change and Total Factor Productivity Growth: The Case of Chinese Provinces. Technological forecasting and Social Change, 78: 575-590.

14- Jin S., Ma H., Huang J., Hu R., and Rozelle S. 2010. Productivity, Efficiency and Technical Change: Measuring the Performance of China’s Manufacturing Agriculture, Journal of Productivity Analysis, 33(3):191-207.

15- Khazaei F., and Amraei B. 2015. Assessment of Tomato TFP by Malmqvist Index, Agricultural Economic Research Journal, 7 (3): 83-98. (In Persian with English abstract).

16- Li J., Zhang J., Gong L., and Miao P. 2015. Research on the Total Factor Productivity and Decomposition of Chinese Coastal Marine Economy: Based on DEA-Malmquist Index, Journal of Coastal Research, 73: 283 – 289.

17- Lovell C.A.K., and Schmidt S. S. 2007. The Measurement of Productive Efficiency: Techniques and Applications. New York, Oxford University Press: 3-67

18- Margono H., Sharma S. C., Sylwester K., and Al-Qalawi U. 2011. Technical efficiency and productivity analysis in Indonesian Provincial Economies, Applied Economics, 43(6): 663-672.

19- Mendi P. 2007. Trade in Disembodied Technology and Total Factor Productivity in OECD Countries. Research Policy, 36: 121-133.

20- Ministry of Agri-Jahad. Various years.Agricultural bulletin.

21- Nigel K., William M., and Roberto M. 2008. Decomposition of Total Factor Productivity Change in the U.S. Hog Industry. Journal of Agricultural and Applied Economics, 40(1):137–149.

22- O’Mahony M., and Timmer M.P. 2009. Output, Input and Productivity Measures at the Industry Level: The EU KLEMS Database. the Economic Journal, 119: 374-403.

23- Oh D.H., Heshmati A., and Lööf H. 2012. Technical Change and Total Factor Productivity Growth for Swedish Manufacturing and Service Industries. Applied Economics, 44(18):2373-2391.

24- Oh D.H. 2015. Productivity growth, technical change and economies of scale of Korean fossil-fuel generation companies, 2001–2012: A dual approach. Energy Economics, 49: 113-121.

25- Orea L. 2002. Parametric Decomposition of a Generalized Malmquist Productivity Index. Journal of Productivity Analysis, 18(1): 5–22.

26- Rezapoor S., Mortazavi S.A., and Mojaverian S.M. 2011. The Study of Main Factors in Productivity Growth of Paddy Producer Provinces in Iran. Iranian Journal of Agricultural Economics and Development Research, 41(2): 467-479. (In Persian with English abstract)

27- Salami H., and Shahbazi H. 2010. Measurement and Analysis of Productivity Growth in Irrigated Wheat Production in Iran: A Comparison between Time Trend, General Index, and Divisia Index Approaches. Iranian Journal of Agricultural Economics and Development Research, 41(2): 127-255. (In Persian with English abstract)

28- Shirani Bidabadi J., Ahmadi Koliji S., and Aminravan M. 2015. Assessment of Dry land Wheat TFP in North of Iran, Agricultural Economic Research Journal, 7 (1): 137-155. (In Persian with English abstract)

29- Syverson Ch. 2011. What Determines Productivity, Journal of Economic Literature, 49(2): 326–365.

30- Tahamipoor M., Saleh A., and Nemati M. 2014. Measuring and decomposing total productivity growth of sugar beet production factors in Iran. Journal of Sugar Beet, 29(1): 113-127. (In Persian with English abstract).

31- Thirtle C., Piesse J., Lusigi A., and Suhariyanto K. 2003. Multi-factor agricultural productivity, efficiency and convergence in Botswana, 1981–1996. Journal of Development Economics, (71): 605– 624.

32- Van Ark B., O’Mahony M., and Timmer M.P. 2008. The Productivity Gap between Europe and the United States; Trends and Causes, Journal of Economic Perspectives. 22(1), 25-44.

33- Zare A., Chizari A.M., and Peykani Gh. 2005. Analysis of Total Factor Productivity Growth of Cotton Production in Iran, the Fifth Biennial Conference of Iranian Agricultural Economics, Zahedan. (In Persian with English abstract)

34- Zohrevand S., Mohammadinejad A., and Gilanpour O. 2015. Analyzing Effect of Rice Import on Iran's Domestic Market for 1982-2011, Agricultural Economics Research. 7 (3):59-71. (In Persian with English abstract)