East Java is one of the provinces in Indonesia that carries out intensive development in the industrial sector to improve the welfare of its society. However, massive industrial activity will pose its challenges, such as increased emissions and environmental degradation. This study aims to determine the manufacturing sub-sector that produces CO2 emissions and has the lowest green efficiency as well as its determinant variables. There are three stages of analysis applied in this research i.e. carbon emission measurement, Slack Based Measurement-Data Envelopment Analysis (SBM-DEA), and Tobit regression. The study use 5-digit manufacturing subsector data based on the International Standard Industrial Classification (ISIC) system, obtained from the Indonesian Central Agency of Statistics (BPS) which is deflated against the East Java Regional Gross Domestic Product (GRDP) deflator with 2010 as the base year. The results of the analysis show that in general, the manufacturing subsector in East Java produces quite high CO2 emissions of 85.28 tons. The subsector with the highest average CO2 emissions in East Java in 2017 was the fertilizer industry, in 2018 the non-ferrous base metal manufacturing industry, and in 2019 the steel rolling industry. Then, the drying industry and tobacco depreciation became the sub-sector with the lowest average green efficiency in East Java Province in 2017. Meanwhile, in 2018 it was the milling industry of various nuts (including Leguminous) and in 2019 it was the coffee processing industry. The Tobit regression results show that the energy structure and industrial concentration have no significant effect on the green efficiency value of the manufacturing subsector. Meanwhile, spending on R&D has a significant negative effect on green efficiency. Therefore, the recommendations given are encourage the use of environmentally friendly raw materials and fuels, increasing green innovation, and increasing consumer awareness regarding environmental issues.

The economic condition of North Sumatra province due to the COVID-19 pandemic has weakened, especially on the supply side, by a negative growth rate in the productivity of the business sector. Industrial downstream could boost economic recovery and inclusive development by creating solid domestic relations with supporting regional industries and increasing high-value-added exports. This study aims to identify priority sectors and analyze the impact of these priority sectors on the manufacturing industry in North Sumatra based on linkage analysis using data during the economic recovery. The data from the I-O table of North Sumatra province in 2016 was sourced from the Central Statistics Agency (BPS) and covered 50 economic sectors. In addition, this study also used data on the GRDP of North Sumatra in 2021. This study applied the RAS Method to determine the value of the technical coefficient matrix of the input-output table in 2021. Then, this study also calculated the value of forward and backward linkages, output multiplier, value-added multiplier, and inoperability. The results revealed three priority sectors in North Sumatra, the Food and Beverage industry; the Base Metal industry; and the Paper and Paper Goods industry, Printing and Reproduction of Recording Media. The study recommends that the government encourage the acceleration of infrastructure by providing financial and policy support to these leading sectors and facilitating distribution channels so that industrial downstream runs optimally to the overall economy.

This study aims to analyze the relationship between market share and technical efficiency in the Indonesian general insurance industry. The data for the period 2010-2020 is used, which was obtained from the Indonesian Financial Services Authority (OJK). The results show that efficient companies emerged from the category of industry possessing comparatively higher and lower market shares. Furthermore, the panel Granger-causality test indicates a one-way direction of causality, where only the market share has an impact on the technical efficiency score. The panel regression using the Feasible Generalized Least Square (FGLS) model shows that market share has a negative impact on technical efficiency scores. Other variables, such as the age of the industry, merger, and acquisition are listed in the stock exchange and do not have a significant effect on the efficiency score. Based on the aforementioned findings, it can be inferred that the quiet-life hypothesis is applicable within the Indonesian general insurance sector. Consequently, the government must foster competition among the businesses operating within the industry.