This paper estimates and compares efficiency performance of 32 commercial banks in Vietnam during 2001–2005, as well as identifies possible factors determining such efficiency performance. Efficiency is measured by a data envelopment analysis (DEA) model and super-efficiency measure through a slacks-based model (SBM) under the assumption of variable returns to scale (VRS). We find that there were a small number of efficient banks, and there would be room for these banks to improve their production efficiency. Moreover, in comparison with small banks, large banks do not guarantee high super efficiency scores. The results from a Tobit regression model provide such interesting findings as negative impact of state ownership, positive influence of bank size and market share, but no impact of labor quality.

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The purpose of this paper is to estimate changes in productivity, technical efficiency and technology across the economic sectors during the period 1985-2006. We also seek to identify the turning points for productivity growth to see whether it was accompanied by technological change and/or technical efficiency. For estimating economic growth, aggregate production function is used. We find that, during the study period, technical progress contributed about 19.7 per cent to the country's economic growth. We also estimate total factor productivity for the whole economy as well as for individual economic sectors, and the results show that the economy's productivity growth was largely driven by the industrial sector.

The purpose of this study is to investigate the determinant of Vietnamese banks' capital adequacy ratio (CAR) by internal banking factors. Secondary data is collected from banks' annual reports in the period of 2009-2015. FGLS method and panel data are used to examine a regression model with CAR is the dependent variable and five independent variables: bank size (SIZE), loans (LOA), loan loss reserve (LLR), liquidity (LIQ), profitability (ROE). The results show that SIZE and LIQ impact negatively on CAR with significant meanings. On the other hand, LLR and LOA also affect CAR negatively but they are insignificant.

ABSTRACT

This paper proposes a new approach for ranking efficiency units in data envelopment analysis as a modification of the super-efficiency models developed by Tone [1]. The new approach based on slacks-based measure of efficiency (SBM) for dealing with objective function used to classify all of the decision-making units allows the ranking of all inefficient DMUs and overcomes the disadvantages of infeasibility. This method also is applied to rank super-efficient scores for the sample of 145 agricultural bank branches in Viet Nam during 2007-2010. We then compare the estimated results from the new SCI model and the exsisting SBM model by using some statistical tests.

This study applies a stochastic frontier production approach to decompose the sources of total productivity (TFP) growth into technical progress and changes in technical efficiency of 8057 firms in Vietnamese manufacturing industries during 2003-2007. Using both total manufacturing industry and sub-manufacturing industrial regressions, the analysis focuses on the trend of technological progress (TP) and technical efficiency change (TEC), and the role of productivity change in economic growth. According to the estimated results, the annual technical progress for the manufacturing industry and sub-manufacturing industries are calculated directly from the estimated parameters of the translog stochastic frontier production function by taking a partial derivative of output with respect to time t. The average technical changes in manufacturing industry and sub-manufacturing industries are positive, with an average technical change about 5.2%, 5.8%, 5.4%, 11.8%, 4.6%, 4.1%, 7.3%, 4.8%, 4.8% and 4.8% for total sample, food products & beverages, textile & wearing apparel, footwear, paper & products, industrial chemicals, rubber & plastic products, non- metallic mineral, basic & fabricated metal and other sub-industries, respectively. Total TFP in the manufacturing sector has grown at the annual rate of 0.052, although the rate of growth decreased continuously during the sample period. For the sub-industry estimates during the sample period, TFP grew fastest in the footwear sub-industry, with annual average growth rate of 11.8%, followed by the rubber & plastic products with a rate of 7.3%, and the food products & beverages with a rate of 5.8% per annum

Purpose The purpose of this paper is to measure TFP growth and job reallocation in the Vietnamese manufacturing industry after the Doimoi period. Design/methodology/approach The study uses firm-level panel data from Vietnam’s annual enterprise survey data for 2000–2016 period in the Vietnamese manufacturing industry using Olley–Pakes static and dynamic productivity decomposition methods. Findings The aggregate productivity estimated from the WRDG method increased 2.323 percent, of which over 40 percent is due to the reallocation toward more productive firms. Olley–Pakes dynamic decomposition according to ownership, scale and industry shows that the contribution of private and state-owned firms and the contribution of small and medium firms and large firms to the TFP growth are 133, −33 percent, 58.56 and 41.44 percent, respectively. The within-firm productivity and net entry components are the main reasons for TFP growth rather than reallocation. The results show that the composition of the aggregate TFPs, estimated from WRDG, OP, LP and ACF, is correlated very high (over 80 percent) except for net entry components. Research limitations/implications The major limitation of this study is that the authors compute an aggregate productivity index using actual employment-based shares (still misallocation in labor), rather than optimal employment-based shares (no misallocation in labor). Originality/value Job reallocation between industries is attracting attention in developing countries, especially transition economies. However, knowledge about job reallocation among industries is limited. This paper assesses the level of job reallocation among private and state-owned firms, small and medium firms and large firms in Vietnam.