Towards a better measure of income inequality in Indonesia

Indonesia has experienced significant economic growth in recent years (on average, 5% in 2000–08), but many people are still living in poverty. Income inequality, as measured by the official Gini coefficient, has also increased. This paper evaluates household income and income inequality in Indonesia, assessing both market and non-market income to reach a more accurate measure of how actual income affects living standards. We find that if household income considers non-market income, income distribution is significantly more balanced, the coefficient of income inequality falls from 0.41 to 0.21 and the income share of the population's poorest deciles increases more than fivefold. The results suggest that market income alone is a misleading measure of income distribution in Indonesia.     

Tourism destination decisions: the impact of risk aversion and prior experience

This study broadly explores the impact of risk aversion on tourists' destination decisions and, in particular, explores for differences in individuals' leisure and medical tourism destination decisions. The results of this study indicate that risk aversion significantly distinguishes tourists' destination decisions in both leisure and medical tourism in Indonesia, but not in Singapore. All risk-averse groups are less likely to visit Indonesia than Singapore for leisure and medical purposes. By contrast, all risk-averse groups are likely to visit Singapore for leisure purposes, although they remain unlikely to travel to Singapore for medical tourism. In addition, the study found that the impact of prior experience on the likelihood that the two risk-averse groups will travel to Indonesia and Singapore for leisure was significant. Conversely, the effects of prior experience on medical tourism generally do not significantly differ between the two countries.     

A new sub-national multi-region input–output database for Indonesia

ABSTRACT

As a large archipelago with significant geographical variation and economic diversity, Indonesia requires detailed regional information when subjected to economic modelling. While such information is available, it however has not been integrated and harmonised into a comprehensive input–output database, thus preventing economic, social, and environmental modelling for investigating sub-national regional policy questions. We present the new IndoLab, a collaborative research platform for Indonesia, enabling input–output modelling of economic, social, and environmental issues in a cloud-computing environment. Within the IndoLab researchers are for the first time able to generate a time series of regionally and sectorally detailed and comprehensive, sub-national multi-region input–output (MRIO) tables for Indonesia. By integrating a multitude of economic, social, and environmental data into a single standardised processing pipeline and harmonised data repository, the IndoLab is able to generate MRIO tables capturing up to 1148 sectors, and 495 cities and regencies. Researchers can freely choose from this detail to construct tables with customised classifications that suit their own research questions. First results from the IndoLab clearly demonstrate the unique characteristics of regions in terms of their sectors’ employment intensity. Thus, the IndoLab has great potential for investigating policy questions that cannot be comprehensively addressed using a single national database.     

Creating relational rents: The effect of business groups on affiliated firms’ performance in Indonesia

This research attempts to extend the discussion of business groups in emerging economies by treating business groups as a form of interorganizational network that generates relational rents among affiliated firms by creating technological and managerial capabilities. Based on the relational view, this research investigates whether value created by business groups depends upon sharing, combining, and exchanging unique and specific resources or assets among affiliated firms. Results show that technological capabilities contribute to create relational rents in terms of affiliated firms’ investment in R&D and human capital. Managerial capabilities also contributed to generating relational rents through investment in managerial knowledge acquisition for affiliated firms without R&D units and in training for affiliated firms with R&D units. However, learning by exporting and learning from imported input do not yield relational rents within business groups. Overall, these findings reveal that business groups as interorganizational networks are contingent on their internal, unique, and specific capabilities, as social capital theory argues.