Sawmill production in the interior of British Columbia: A stochastic ray frontier approach

We examined the productive efficiency of the interior sawmilling industry in British Columbia using stochastic frontier analysis. Prior sawmilling studies using this method have neglected the multi-output nature of sawmills. To accommodate both lumber and chips as outputs, we used a ray production function and adopted it into the stochastic frontier framework. A translog functional form was specified with three inputs (i.e., capital, labour, and roundwood) and applied to five years (2003-2007) of mill specific production data. The ray production function is flexible allowing factor productivity to vary with the output mix. Results indicated the presence of both economies of scale and technical inefficiency. This suggested that a long-run equilibrium had not yet been reached during this time and might explain recent restructuring occurring in this region.

[1]  P. Fousekis.  Distance vs. Ray Functions: An Application to the Inshore Fishery of Greece , 2002, Marine Resource Economics.

[2]  Subal C. Kumbhakar,et al.  Stochastic frontier analysis , 2000 .

[3]  F. Martinello,et al.  Substitution, technical change and returns to scale in British Columbian wood products industries , 1987 .

[4]  P. Schmidt,et al.  Production Frontiers and Panel Data , 1984 .

[5]  T. Coelli.  Estimators and hypothesis tests for a stochastic frontier function: A Monte Carlo analysis , 1995 .

[6]  T. Awoyemi,et al.  Technical efficiency of sawnwood production in Ondo and Osun states, Nigeria , 2010 .

[7]  Di Jin,et al.  Stochastic frontier analysis of total factor productivity in the offshore oil and gas industry , 2006 .

[8]  David M. Drukker,et al.  On boundary-value likelihood-ratio tests , 2001 .

[9]  Harold O. Fried,et al.  The Measurement of Productive Efficiency and Productivity Growth , 2008 .

[10]  M. Farrell.  The Measurement of Productive Efficiency , 1957 .

[11]  W. Meeusen,et al.  Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error , 1977 .

[12]  M. Tambour,et al.  Internal markets and health care efficiency: a multiple-output stochastic frontier analysis. , 1999, Health economics.

[13]  Timothy Coelli,et al.  ESTIMATION OF FRONTIER PRODUCTION FUNCTIONS AND THE EFFICIENCIES OF INDIAN FARMS USING PANEL DATA FROM ICRISAT'S VILLAGE LEVEL STUDIES , 1989 .

[14]  Klaus Frohberg,et al.  Stochastic Efficiency Measurement: The Curse of Theoretical Consistency , 2006 .

[15]  Ted L. Helvoigt,et al.  A stochastic frontier analysis of technical progress, efficiency change and productivity growth in the Pacific Northwest sawmill industry , 2009 .

[16]  Taraneh Sowlati,et al.  Dynamic efficiency analysis of primary wood producers in British Columbia , 2007, Math. Comput. Model..

[17]  Jonas Månsson,et al.  Economies of scale in the Swedish sawmill industry , 2003 .

[18]  Runsheng Yin.  Alternative measurements of productive efficiency in the global bleached softwood pulp sector. , 2000 .

[19]  Mickael Löthgren,et al.  Specification and estimation of stochastic multiple-output production and technical inefficiency , 2000 .

[20]  J. C. Nautiyal,et al.  Short-run actual and least-cost productivities of variable inputs for the British Columbia interior softwood lumber industry , 1988 .

[21]  Subhash C. Ray,et al.  Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research , 2004 .

[22]  D. Aigner,et al.  P. Schmidt, 1977,?Formulation and estimation of stochastic frontier production function models,? , 1977 .

[23]  Estimating hedonic price equations for a timber stumpage market using stochastic frontier estimation procedures , 1997 .

[24]  H. Nelson,et al.  Are forest sector firms maximizing the economic returns from their timber? Evidence from British Columbia , 2009 .

[25]  C. Lovell,et al.  On the estimation of technical inefficiency in the stochastic frontier production function model , 1982 .

[26]  W. Greene.  The Econometric Approach to Efficiency Analysis , 2008 .

[27]  F. W. Cubbage,et al.  Stochastic frontier estimation and sources of technical efficiency in southern timber harvesting , 1995 .

[28]  Shiuh-Nan Hwang,et al.  DATA ENVELOPMENT ANALYSIS IN MEASURING THE EFFICIENCY OF FOREST MANAGEMENT , 1993 .

[29]  Mickael Löthgren,et al.  Generalized Stochastic Frontier Production Models , 1997 .

[30]  E. Morey.  An introduction to checking, testing, and imposing curvature properties: the true function and the estimated function , 1986 .

[31]  T. Coelli.  RECENT DEVELOPMENTS IN FRONTIER MODELLING AND EFFICIENCY MEASUREMENT , 1995 .

[32]  Taraneh Sowlati,et al.  Performance analysis of primary wood producers in British Columbia using data envelopment analysis , 2005 .

[33]  D. Mckeever,et al.  Profile 2007: Softwood sawmills in the United States and Canada , 2007 .

[34]  H. Hänninen,et al.  Measuring the Efficiency of Public Forestry Organizations , 1998, Forest Science.