Purpose The purpose of this paper is to investigate the technical efficiency (TE) of micro and small enterprises (MSEs) and its determinants in the Indonesian manufacturing sector covering comprehensive subsectors. Design/methodology/approach This research uses the data from the micro and small industry survey sourced from the Indonesian Bureau of Central Statistics for the period 2010–2015. The TE is estimated using data envelopment analysis (DEA) with bootstrapping approach. The TE is also estimated at the firm-level survey data, classified at the five-digit level of the International Standard Industrial Classification system. In addition, a truncated regression model is applied to estimate the effects of the determinants on the TE. Findings This research finds that there is a low average TE of the MSEs for the subsectors investigated. It is also found that the TE is associated with firm size, location, export orientations on domestic and world markets, firm age, level of technology, and owner education. Originality/value The literature investigating the TE of the MSEs and its determinants is still rare in Indonesia. Most of the previous research limited the studies for specific subsectors and/or specific small regions. Therefore, this research has a contribution in measuring the TE of the MSEs for comprehensive subsectors as well as its relation with the determinants in the Indonesian manufacturing sector. Also, the DEA with bootstrapping approach is applied to estimate the TE of the firms based on each relevant subsector, which is rare in the previous research of the Indonesian MSEs.

One of the problems exist in almost all countries is unemployment that has not been resolved perfectly. It occurs because employment cannot absorb all the job seekers who have diverse expertise, as well as domestic investment that is still unable to create new jobs. Indonesia which has an increase of population above the economic growth has not been able to alleviate unemployment so that it needs to encourage and enlarge export services. Researchers take unemployment, economic growth, and remittance as the topic of discussion, where data reveals that number of unemployed people increases very rapidly and remittances tend to be stable. The method used in this study is Ordinary Least Square (OLS) with the study location in Indonesia and using annual data (time series) from 1984 to 2016. The research results show that remittances, population growth, and economic growth have a significant positive effect on unemployment, while investment has a significant negative effect on unemployment. In the end, the problem of unemployment cannot be resolved partially but need to jointly encourage all possible variables for the solution.

This study aims to determined the impact of investments in the agricultural sector to the Gross Domestic Regional Products (GDRP) of agriculture in West Java. The sample was taken from 26 regions in West Java.The results showed that Foreign Capital Investment (FCI) and Exchange rate have positive and significant impact to GDRP. Domestic Capital Investment (DCI) has positive effect of labor but not significantly to GDRP. BI Rate has significant negative effect on GDRP. Fixed effect model allows the analysis of individual securities to be interpreted as the position of the relative potency of a districts / cities. There are nine districts/cities that have a significant positive intercept. These districts are categorized as areas which contribute highly to agricultural sector. The highest sector is in Indramayu district, the second is in Sukabumi, Banjar, Subang and so on. Cimahi has the lowest score of intercept. Negative intercept is an area of low agricultural contribution, generally those which are categorized as industrial areas, such as Bandung, Cirebon, Bogor, Bekasi, Karawang. These areas are classified as industrial area which have negative contribution of agricultural sector to the GDRP.

The current world development agenda led to a focus called the 2030 Sustainable Development Goals (SDGs). There were 17 development goals that became the world’s commitment to be achieved soon. The results of the consensus in 1995 at the World Summit for Social Development stated that the development must make humans as the center of development. One of the benchmarks for human development was based on the Social Capital index. Various countries had developed the concept of social capital. So far, the capital of the OECD had become the most referenced, such as Canada, Australia and the United Kingdom, as a reference in developing indicators of social capital. This study aimed to prove Lin’s theory which stated that assets or economics were directly proportional to the development of social capital. The results showed that economic variables such as GRDP per capita were inversely proportional to social capital. Subsequently social capital was significantly influenced negatively by Indonesia’s democracy index and significantly influenced positively by population density