UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS PERFORMANCE OF MANUFACTURING ENTERPRISES – VIETNAM CASE STUDY BY NGUYEN VIET CUONG MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, DECEMBER 2013 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS PERFORMANCE OF MANUFACTURING ENTERPRISES – VIETNAM CASE STUDY A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By NGUYEN VIET CUONG Academic Supervisor: PHAN DINH NGUYEN HO CHI MINH CITY, DECEMBER 2013 1 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Acknowledgement This thesis would not have been possible without the support of many people. I wish to express my gratitude to my supervisor, Dr. Phan Dinh Nguyen who was abundantly helpful and offered invaluable assistance, support and guidance. Deepest gratitude to Vietnam-Netherlands programme for sharing the literatures, invaluable assistance and providing me a big opportunity to complete this study.
I wish to express my love and gratitude to my beloved families for their understanding and endless love, through the duration of my studies. 2 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Table of content Chapter 1: Introduction .1 Reason of chosen topic .5 Scope of the study .6 Justification of study .7 Structure of thesis.10 Chapter 2: Literature review .1 Measurements of firm performance .2 Stochastic frontier analysis in transition countries .3 Vietnamese technical efficiency analysis .4 Factors impact firm efficiency.21 Chapter 3: Methodology overview .1 Efficiency measurement concepts .2 The stochastic production frontier .3 Production functions accounting for technical change .4 Decomposition of productivity change .5 Stochastic production frontier with panel data .6 The stochastic frontier model using a single-stage estimation .8 Variables are used in production function .9 Stochastic frontier production function .10 Variables are used in inefficiency model .40 Chapter 4: Data and empirical results .4 Sources of technical inefficiency .5 The estimate technical efficiency.6 Total factor productivity decomposition .52 Chapter 5: Conclusions and policy implications .2 Discussions and policy recommendations .3 Limitation and further studies .65 3 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com List of tables Table 1-Average of some variables by ownership .44 Table 2-Pairwise correlation of continuous variables .44 Table 3-Summary of hypothesis testing .47 Table 4-Estimation of stochastic frontier function and inefficiency model .48 Table 5-Distribution of production efficiency by year .51 Table 6-Frequency distribution of efficiency estimated by year .51 Table 7-The average of productivity by ownership .52 Table 8-Summary of factors impact on technical efficiency .55 4 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com List of figures Figure 1-Conceptual framework .21 Figure 2-Technical and allocative efficiencies from an input orientation .22 Figure 3-Scale efficiency .23 Figure 4-The stochastic frontier .25 Figure 5-Estimation and decomposition of productivity change .27 Figure 7 - Distribution of continuous variables .45 Figure 8-Scatter plot correlation of inefficiency explanatory variables .46 Figure 9-Technical efficiency in period 2000-2008 .53 Figure 10-Technical progress in Vietnamese manufacturing firms .53 Figure 11- Change in technical efficiency by ownership .54 Figure 12 - Total factor productivity growth .54 Figure 13-Total factor productivity growth account return to scale .55 5 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Abbreviations SFA: Stochastic frontier analysis DEA: Data envelopment analysis ML: Maximum likelihood OLS: Ordinary least squares GLS: Generalized least squares TFP: Total factor productivity HHI: Herfindahl index GSO: General Statistics Office SME: Small and medium enterprises FDI: Foreign direct investment SOE: State owned enterprises CSO: Central state owned enterprises LSO: Local state owned enterprises LTD: Private, private limited or private joint-stock enterprises COO: Cooperative, collective or partnership enterprises FIO: Foreign invested ownership enterprises RRD: Red River Delta NMM: Northern Midlands and Mountain Areas NSCC: North Central Coast and South Central Coast CH: Central Highlands SE: South East MRD: Mekong River Delta 6 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 1: Introduction Nowadays, macroeconomic developments, particularly macroeconomic stabilization is focused in many analyses of economies undergoing transition. Recent studies suggest macroeconomic reforms through improving enterprise performance plays important role in sustaining macroeconomic stability for transition economies. Besides, firms are assumed importance of accelerating economic growth in developing countries.
They promote capital formation, create wealth in the country, and help to reduce unemployment and poverty. Studying the enterprise’s efficiency always plays an important role in economic research, especially in developing countries.1 Reason of chosen topic Vietnam began re innovation in 1986 and transited from planned economy to market oriented economy. Besides achieving many successes in economic development and reduce poverty, Vietnam still confronts with unsustainable development issues and middle income trap. Specifically, the comparative advantages of Vietnamese manufacturing firms remain heavily upon cheap labor and foreign direct investment, without enhancing their productivity.
A low level of productivity has been observed in this sector, since they lack new technology, product and process innovation, financial access , skilled labor, raw materials, high value added production and managerial skills (UNIDO, 2011). The practices demonstrated that the sustainable development can be maintained only if increasing productivity is engine of growth rather than accumulation of resources. Moreover, structural evolution and the input productivity, which compose the quality of economic growth, are solutions for the middle income trap problem. Through identifying sources affecting firm inefficiency, direct impact on the overall growth of the economy can be revealed.
The appropriate policies and recommendation can be learned from these analyses. As a result, measuring technical efficiency to improve productivity and competitiveness over the long term is urgently needed especially for the manufacturing sector. For this kind of study, 7 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com there are two approaches to measure firm efficiency and examine firm inefficiency effects. The former is the parametric stochastic frontier analysis and the latter is non parametric data envelopment analysis.
However, the stochastic frontier analysis approach is more relevant in this context. The reasons are the stochastic frontier approach closer to reality while it considers both factors beyond the control of the firm and firm-specific factors. Moreover, the stochastic frontier method separates effect of inefficiency and other random shocks. Whereas, the data envelopment approach does not differentiate technical efficiency and statistical noise and it is a non-statistical technique.
Despite of the stochastic frontier analysis advantages, the SFA studies about Vietnamese enterprise’s efficiency are still inefficient, scatter and rare. For example, Vu (2002) analyzed focus on SOE with a database of 164 manufacturing SOE for 1996-1998 and using two stage stochastic frontier analyses. He revealed the skilled workers, engaged in exports activities impact positively on SOE performance. Nguyen (2005) estimated technical efficiency of 32 manufacturing sector in Hanoi and Ho Chi Minh cities using 2000-2002 industrial data with both SFA and DEA approaches.
He found that Vietnamese industries operate with labor- intensive way. Nguyen et al. (2007) studied panel data of 1,492 firms in 2000-2003 using both SFA and DEA. In this study, they found Vietnamese manufacturing firms improve productivity by capital accumulation rather than increase productivity.
Tran et al. (2008) investigated 800 SME in 1996 and 1,500 SME in 2001 using cross sectional stochastic frontier model. They claimed that SME lack of management skill through their firm’s age and size affect negatively on performance. Le and Harvie (2010) used the 2002, 2005 and 2007 SME database and cross sectional stochastic frontier model to estimate firm efficiency.
They observed that the cooperation, subcontract and product improvement are positive factors impact on technical efficiency. Nguyen et al. (2012) estimated the enterprise’s efficiency and decomposed TFP growth into technical progress and technical efficiency change. However, they did not examine the inefficient effects in their model 8 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com In brief, “Performance of manufacturing enterprises – Vietnam case study” topic is chosen for revealing Vietnamese manufacturing firms’ technical efficiency over the period 2000-2008 which can answer the question “Did Vietnam develops sustainable?”.
Although there were various literatures about Vietnamese manufacturing firms technical efficiency but these studies still incoherent and failed to investigate the impact of ownership, finance, technology on technical efficiency. This thesis tries to overcome the shortcoming of previous studies.2 Research objectives The main objectives addressed in this thesis are: First, this thesis estimates the technical efficiency of Vietnamese manufacturing enterprises in the period 2000-2008. Further, this analysis tries to identify firm-specific and business environment factors, which significantly affect the inefficiency of Vietnamese manufacturing firms? Finally, total factor productivity growth of in Vietnamese manufacturing firms is decomposed to find which source mainly contributes.3 Research questions The following research questions are posed to complete objectives of the thesis: How do Vietnamese manufacturing enterprises perform in term of technical efficiency? Which factors significantly contribute to the technical efficiency performance of Vietnamese manufacturing enterprises? Which sources contribute to total factor productivity growth of Vietnamese manufacturing firms? 1.4 Research methodology This study uses a stochastic frontier method introduced by Battese and Coelli (1995) to estimate firms’ technical efficiency and examine inefficiency factors. 9 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.5 Scope of the study This thesis will focus on Vietnamese firm technical efficiency for the period 2000 to 2008.
This study will also examine the sources of TFP growth and investigate inefficient factors using one stage stochastic frontier analysis.6 Justification of study At the practical level, the information of technical inefficiency and factors affect it is necessary for economic policies to improve production efficiency. At the theoretical level, topics about technical inefficiency of firm in the multi sector economy, as Vietnam still rare and inappropriate. This study aims to bring some contribution to this area.7 Structure of thesis For completing the thesis objective, it has organized as follows. The chapter two selects the measure of firm performance, reviews the stochastic frontier studies and factors affect efficiency used in the analysis.
Chapter three introduces efficiency concepts, development of stochastic frontier methods. Chapter three also describes the econometric model, variable, and model testing hypotheses. Chapter four discusses the estimation results, inefficiency factors of firms and decomposition of TFP growth. And chapter five contains the main findings, discussions and limitations.
10 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 2: Literature review This chapter selects measurement of firm performance, reviews empirical studies in stochastic frontier analysis area and inefficiency factors use in this study.1 Measurements of firm performance Firm performance can be measured by accounting ratios, productivity and efficiency. The accounting ratios have several disadvantages when used to measure firm performance. First, they cannot effectively reflect the multidimensional characteristic of the production process of many industry sectors. Second, their interpretation can provide a lot of misleading information due to the fact that they can be artificially modified by managers.
Finally, using accounting ratios are subjective when the analyst can choose ratios in order to assess the overall performance. Productivity is defined as the ratio of the firm’s outputs with inputs firm uses. Productivity measure normally refers to total factor productivity which includes all factors of production. The other partial productivity measure, which considers firm’s productivity with aspect of one production factor, can provide a misleading result of overall productivity.
Also, productivity measure does have meaningful units of measurement. Efficiency is measured by comparing firm’s actual output with maximum producible quantity from its observed inputs. The efficiency measure provides the benchmark of how firm allocates resources for production. Comparing with accounting ratio and productivity measure, efficiency reflects firm performance more precisely and consistently.
This study chooses efficiency as a measurement of firm performance due to these reasons.2 Stochastic frontier analysis in transition countries Data envelopment analysis and stochastic frontier analysis are estimating technical efficiency methods. However, the stochastic frontier method is commonly used to estimate efficiency and it applied in many studies about transition countries. 11 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.