This paper uses firm-level panel data to study the development and determinants of technical efficiency and productivity in the textile and garment sector in Vietnam during the period 1997-2000.
PRODUCTIVITY ANALYSIS FOR VIETNAM’S TEXTILE AND GARMENT INDUSTRY Nguyen Thang To Trung Thanh Vu Hoang Dat Remco H Oostendorp ABSTRACT This paper uses firm-level panel data to study the development and determinants of technical efficiency and productivity in the textile and garment sector in Vietnam during the period 1997-2000 Applying the methodology of Battese and Coelli (1995), we find that average technical efficiency of the textile and garment sectors is relatively high, but that technical efficiency differs significantly across ownership, location, size, age, and export orientation The most productive firms in the textile sector are old, mid-sized, private, South-based, export-oriented firms, while in the garment sector old, medium to large, private or foreign invested, South-based firms have the highest technical efficiency In the garment sector TFP has increased over the study period, reflecting changes in technical efficiency as well as technical progress Acknowledgements This paper was written based on a competitiveness study funded by the International Development Research Center of Canada as part of the Vietnam Economic Research Network We like to thank Bernard Decaluwé and John Cockburn for their valuable assistance in the course of the study, and we are also grateful to the seminar participants at the Hue, Halong Bay and Hanoi workshops for their helpful discussions and comments on earlier versions of the paper Any remaining errors remain our own PART I INTRODUCTION The 90s decade witnessed the impressive performance of Vietnam Textile and Garment industry Quickly recovered from great difficulties caused by the collapse of the former Soviet Union and Eastern European socialist countries and the resulted loss of CMEA market, Vietnam T&G industry managed to develop with the average growth rate of 10.6% per annum and make up 7.5% of the overall GDP during past years (GSO, 2003) The sector has consistently featured in the list of top exporting industries In 2004, the export value of the T&G industry reached approximately US$4.3 billion and the sector thus became the second largest earner of badly needed foreign exchange in Vietnam (Vietnam Economic Times, 2005) Of equal to importance, the industry is highly labor intensive by nature, generating the largest number of jobs among manufacturing industries and sharing 22.2% of total employment in the manufacturing sector (VLSS 97/98) T&G sector has therefore been regarded as an important and strategic industry in solving the acute problem of unemployment and poverty, by exploiting Vietnam’s comparative advantage in labor intensive production Although these unprecedented achievements are undeniable, the T&G industry is not without problems regarding productivity which could threaten the sustainable development of the sector This has naturally aroused interest of researchers in doing careful studies on efficiency and productivity, and on this basis, making well-founded policy recommendations towards the improvements in the industry’s performance This research is made in the effort to continue and upgrade the previous VEEM report in productivity analysis for T&G industry, which bears some shortcomings First, the use of total wage bill as measure of labor input may cause problem of identity and non-absoluteness of controlling the difference in both production function and technical inefficiency effects may lead to bias in estimate results Second, assumption of all firms’s minimizing costs and maximizing profit which is inherent in the Tornqvist index number approach applied may be a constraint to the analysis Third, the analysis does not take advantage of properties of unbalanced panel data available Fourth, the results of TFP growth and TP could be considerably improved if better deflators can be calculated The methodology applied in this study will partly improve the productivity analysis through obtaining better deflators and using stochastic frontier method to directly calculate Malmquist TFP index and its components To acquire above objectives, the rest of the study is organized as following: Part II briefly describes the methodology that will be used for the subsequent empirical analysis Based on the regression result and estimates of indices, Part III gives a detail picture on technical efficiency performance of the textile and garment sub-sectors and determinants of technical efficiency And then Part IV will give the whole content growth pattern of TFP over the years The final part presents main findings and suggestions for further research PART II METHODOLOGY This section presents the methodological framework that will be used for the subsequent empirical analysis A brief discussion of sources of output growth, which include input growth and TFP change, will be presented in the beginning Next, the section mentions the Malmquist TFP index that will be applied in the study It then discusses the stochastic frontier method to estimate Malmquist technical efficiency change, technical progress change and TFP growth Some other methodological issues will be also shown in this section Source of Output Growth and Mamlquist Index On the supply side, any output growth is determined by the expansion of productive resources and by the improvement in their use (Micko, M and John, M.P, 1991) The latter is expressed through TFP concept, which measures joint productivity of all inputs used in combination to produce certain goods and/or services TFP change, as mentioned earlier, can be in turn broken down into technical efficiency change and technical progress The concept of TFP is closely related to disembodied technological change in that it does not increase the productivity of a particular input but rather that of all input jointly To have clearer picture on this issue, a production function is specified as: Q (t ) = F [Z (t ), t ].e u ( t ) (1) where Q(t): observed output level at time t Z(t): the set of inputs used at time t F[Z(t),t] is potential output at best practice level at time t eu(t) is the level of technical efficiency with u(t)