Barley Productivity Decomposition in Iran: Comparison of TT, GI, MGI, and GTTI Approaches

International Journal of Agricultural Management and Development

مقاله 4، دوره 7، شماره 3، آذر 2017، صفحه 305-312   

نوع مقاله: Research Article

نویسنده

Habib Shahbazi^*

Sayyed Jamaleddin Asadabadi University

چکیده

In this paper, the authors present new indices for estimating technical change, return to scale, and TFP growth, as well as its decomposition. These indices, Modified General Index (MGI), Generalized Modified General Index (GMGI), and General Time Trend index (GTTI), are generalization of General Index approaches. These approaches were used for productivity decomposition of Iran's barely production across the period 2000-2012 in 20 provinces. To select the best approaches, estimated TFP growth of TT, GI, MGI and GTTI are compared with Divisia Index. Results show that differences between Barley TFP growth of TT, GI, MGI, and GTTI approaches with Divisia Index are 39.12, 17.94, 9.71, and 1.61 percent, respectively. The findings revealed that MGI method is appropriate when time series data or panel data with limited cross-section data are used. In addition, when only need to compare periods of time that are not regular (for evaluation plan or policies), it is suggested GMGI method. When time series data or panel data with limited cross section data are used, and there is a trend in every period, the GTTI method is recommended for estimating technical change, return to scale, and TFP growth.

کلیدواژه‌ها

Barley, productivity؛ Modified General Index؛ Generalized Modified General Index؛ General Time Trend index

مراجع

Baltagi, B. H., & Griffin, J. M. (1988). a general index of technical change. Journal of Political Economy, 96, 201-241.

Baltagi, B. H., Griffin, J. M., & Rich, P. (1995). Airline deregulation: the cost pieces of the puzzle. International Economic Review, 36, 245-258.

Capalbo, S. M. (1988). Measuring the Components of aggregate productivity growth in U.S. agriculture. Western Journal of Agricultural Economics, 13, 53-62.

Diewert, W. E. (1976). Exact and superlative index number. Journal of Econometrics, 4, 115-145.

Diewert, W. E. (1981). The Economic Theory of index number: survey essay in the theory and measurement of consumer behavior. (R. Deaton, Ed.) Cambridge Unversity Press.

Diewert, W. E. (1981). The Economic Theory of index number: survey essay in the theory and measurement of consumer behavior. (R. Deaton, Ed.) Cambridge university press.

Kavoosi, M., Peykani, G. R., Shahbazi, H., & Akrami, A. (2010). Determining a suitable sugar cane utilization system using total factor productivity (TFP) case study: Imam Khomeini cultivation and processing center in Khuzestan province. Journal of Agricultural Science and Technology, 12, 511-521.

Kumbhakar, S. C. (2002). Productivity and Technical change: measurement and testing. Emprical Economics, 9(5), 331-334.

Kumbhakar, S. C. (2004). Productivity measurement: a profit function approach. Applied Economics Letter, 29, 185-191.

Kumbhakar, S. C., & Heshmati, A. (1996). technical change and total factor productivity growth in Swedish Manufacturing Industries. Econometric Reviews, 15, 275-298.

Kumbhakar, S. C., Nakamura, S., & Heshmati, A. (2000). Estimation of Firm-Specific Technological Bias, technical change and total factor productivity growth: a dual approach. Econometric Reviews, 19, 493-515.

Kumbhakar, S. C., Nakamura, S., & Heshmati, A. (2000). Estimation of Firm-Specific Technological Bias, technical change and total factor productivity growth: a dual approach. Econometric Reviews, 19, 493-515.

Salami, H., & Shahbazi, H. (2010). Measurement and decomposition of Iran's wheat TFP, comparison of time trend, general index and Divisia indices. Iranian Journal of Agricultural Economics and Development, 41(2), 127-135.

Shahbazi, H., & Abbasifar, A. (2014). Iran's agricultural subsectors technical change bias. 2nd international conferences on economics, accounting, mangment and social sciences. Szczecin, Poland.