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.

Dampak Hibah Pariwisata terhadap Kinerja Industri Pariwisata Jawa Tengah dan Daerah Istimewa Yogyakarta

Keberlangsungan industri pariwisata khususnya hotel dan restoran di Jawa Tengah dan D.I Yogyakarta saat pandemi Covid-19 sangat penting karena memiliki dampak simultan terhadap kondisi sosial dan ekonomi. Melalui kebijakan stimulasi keuangan bagi pelaku industri pariwisata hotel dan restoran diharapkan supaya usaha tersebut dapat bertahan disaat jumlah kunjungan wisata menurun dan mempersiapkan upaya pemulihan saat pemberlakuan kebiasaan baru termasuk di kegiatan industri pariwisata melalui penyaluran hibah pariwisata. Mengingat peruntukan dana hibah tersebut diharapkan dapat memberikan stimulasi dan penyesuaian menuju kebiasaan baru industri pariwisata kajian empiris dengan pendekatan Analisis Kuantitatif Efisiensi dengan Frontier Analysis (FA) dan Structural Equation Modelling (SEM) terhadap 116 pelaku pariwisata hotel dan restoran, menunjukkan bahwa pemberian dana Hibah Pariwisata di Wilayah Provinsi Jawa Tengah dan D.I Yogyakarta memberikan efek positif terutama pada efisinesi alokasi kinerja keuangan yang diperoleh atas alokasi biaya gaji karyawan dan biaya operasional untuk meningkatkan efisiensi output berupa penerimaan hotel dan restoran.

Stochastic Final Pit Limits: An Efficient Frontier Analysis under Geological Uncertainty in the Open-Pit Mining Industry

In the context of planning the exploitation of an open-pit mine, the final pit limit problem consists of finding the volume to be extracted so that it maximizes the total profit of exploitation subject to overall slope angles to keep pit walls stable. To address this problem, the ore deposit is discretized as a block model, and efficient algorithms are used to find the optimal final pit. However, this methodology assumes a deterministic scenario, i.e., it does not consider that information, such as ore grades, is subject to several sources of uncertainty. This paper presents a model based on stochastic programming, seeking a balance between conflicting objectives: on the one hand, it maximizes the expected value of the open-pit mining business and simultaneously minimizes the risk of losses, measured as conditional value at risk, associated with the uncertainty in the estimation of the mineral content found in the deposit, which is characterized by a set of conditional simulations. This allows generating a set of optimal solutions in the expected return vs. risk space, forming the Pareto front or efficient frontier of final pit alternatives under geological uncertainty. In addition, some criteria are proposed that can be used by the decision maker of the mining company to choose which final pit best fits the return/risk trade off according to its objectives. This methodology was applied on a real case study, making a comparison with other proposals in the literature. The results show that our proposal better manages the relationship in controlling the risk of suffering economic losses without renouncing high expected profit.

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.