Frontier Technology, Trade, FDI, and TFP in the Electrical and Electronic Industries: Exporting or Processing Trade?

Does “openness” determine “catching-up” of establishments to frontier technology and total factor productivity (TFP) in Malaysia's electrical and electronic (E&E) industries? We contribute to this debate by applying a new measurement of processing trade intensity. Utilizing stochastic frontier analysis and Levinsohn and Pertrin (LP) TFP, we investigate determinants of technical efficiency (TE) and TFP. The results show that processing trade intensity and not export intensity determines TE and TFP for the overall sample and subsample of foreign establishments. In the processing trade subsample, export intensity is negatively related to TE and unrelated to TFP, obtaining an unconventional result that exporters are inefficient and not associated with TFP. The results show that higher foreign ownership shares of establishments are negatively associated with LP TFP.

Assessment of port efficiency within Latin America

The Panama Canal expansion has influenced the development of ports within the Latin America and the Caribbean (LAC) region, intending to capitalise on economic opportunities through seaborne trade. Examining port performance is essential to ascertain the PCE impact on port efficiency within the LAC region. Stochastic frontier analysis (SFA) was used to determine the technical efficiency of the 19 major ports within the LAC from 2010 to 2018. The result indicates that, among the four (4) port performance indicators (berth length, port area, the number of cranes (STS gantry and mobile), and the number of berths), the number of STS gantry cranes and berth length had the largest and most significant impact. Some ports with high technical efficiency experienced TEU losses despite port infrastructural development and privatization. The findings also revealed that the increased competition among regional and US East and Gulf Coast ports has negatively impacted some LAC ports’ TEU volumes due to port proximity. The dynamism of the maritime sector, especially containerization, requires ports to implement value-added services and logistics centers in tandem with port performance indicators to remain sustainable and competitive in the maritime industry.

Does Agricultural Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?

Agricultural mechanization is an important factor to improve the green total factor productivity of planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Based on the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of output oriented distance function to measure the green total factor productivity of China’s planting industry based on net carbon sink, and empirically studies the impact of agricultural mechanization on the green total factor productivity in China’s planting industry. The empirical analysis finds that mechanization can significantly promote the planting green total factor productivity, and this basic conclusion is still robust after using instrumental variables, sub sample regression. Further research found that the path of mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover. The mechanism of operation scale expansion, factor allocation optimization and technical efficiency change is not significant. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

A Novel Hybrid Parametric and Non-Parametric Optimisation Model for Average Technical Efficiency Assessment in Public Hospitals during and Post-COVID-19 Pandemic

The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly return to financial stability, hospitals should implement efficiency measure. An average technical efficiency (ATE) model made up of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) for assessing efficiency in public hospitals during and after the COVID-19 pandemic is offered. The DEA method is a non-parametric method that requires no information other than the input and output quantities. SFA is a parametric method that considers stochastic noise in data and allows statistical testing of hypotheses about production structure and degree of inefficiency. The rationale for using these two competing approaches is to balance each method’s strengths, weaknesses and introduce a novel integrated approach. To show the applicability and efficacy of the proposed hybrid VRS-CRS-SFA (VCS) model, a case study is presented.

Does Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?

Mechanization is an important factor to improve the green total factor productivity of planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Using the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of output oriented distance function to measure the green total factor productivity of planting industry based on net carbon sink, and empirically studies the impact of mechanization on the planting green total factor productivity. The empirical analysis finds that mechanization can significantly promote the planting green total factor productivity, and this basic conclusion is still robust after using instrumental variables, sub sample regression. Further research found that the path of mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover. The mechanism of operation scale expansion, factor allocation optimization and technical efficiency change is not significant. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

The Influence of Energy Price Distortion on Region Energy Efficiency in China’s Energy-Intensive Industries from the Perspectives of Urban Heterogeneity

As typical representatives of China’s industrial sectors, energy intensive industries are the focus of energy conservation. This study constructs a trans-log production function and stochastic frontier analysis model to analyze the impact of energy price distortion on total factor energy efficiency in energy intensive industries on the city level. The results reveal that the phenomenon of energy price distortion existed in all cities from 2003 to 2019, with an average degree of −0.175; and the total factor energy efficiency in China’s energy intensive sectors showed an upward trend, with an average efficiency of 0.729. Further deep analysis of affecting mechanisms concluded that the price distortion showed a significant restraining effect on improving energy efficiency, while the improvement of urban agglomeration systems had an opposite effect. In addition, energy consumption structure, foreign trade, and infrastructure construction are positively correlated with energy efficiency. Therefore, promoting the market-oriented reform of China’s energy market is of great significance to improve city energy efficiency and build a resource-conserving society.

Benchmarking the economic and environmental performance of water utilities: a comparison of frontier techniques

PurposeThe purpose of this paper is to estimate and compare the efficiency of several water utilities using three frontier techniques. Moreover, this study estimates the impact of several qualities of service variables on water utilities’ performance.Design/methodology/approachThe paper utilizes three frontier techniques such as data envelopment analysis (DEA), stochastic frontier analysis (SFA) and stochastic non-parametric envelopment of data (StoNED) to estimate efficiency scores.FindingsEfficiency scores for each methodological approach were different being on average, 0.745, 0.857 and 0.933 for SFA, DEA and StoNED methods, respectively. Moreover, it was evidenced that water leakage had a statistically significant impact on water utilities’ costs.Research limitations/implicationsThe choice of an adequate and robust method for benchmarking the efficiency of water utilities is very relevant for water regulators because it affects decision making process such as water tariffs and design incentives to improve the performance and quality of service of water utilities.Originality/valueThis paper evaluates and compares the performance of a sample of water utilities using three different frontier methods. It has been revealed that the choice of the efficiency assessment method matters. Unlike SFA and DEA, a lower variability was shown in the efficiency scores obtained from the StoNED method.

WASTE MANAGEMENT SERVICE IN INDONESIA BASED ON STOCHASTIC FRONTIER ANALYSIS

Waste management in the big cities of Indonesia is still become a complicated problem. This article aims to analyze the influence of socio-economic factors which consist of GRDP per capita, population density, gender ratio, the proportion of population productive age and education on the efficiency of waste management service (WMS) in provincial capitals in Indonesia. The method used was Stochastic Frontier Analysis (SFA). The resulted WMS efficiency from this study were 0.39. Based on that value, it means the efficiency of WMS are still low and the efficiency can be improved about 61%. It also can be concluded that all variables were significantly influenced the WMS efficiency, except gender ratio. Expected that the result of this study can be used by both central and local government to improve the WMS in Indonesia.