Catastrophes, like earthquakes, bring sudden and severe damage, causing fatalities, injuries, and property loss. This often triggers a rapid increase in insurance claims. These claims can encompass various types, such as life insurance claims for deaths, health insurance claims for injuries, and general insurance claims for property damage. For insurers offering multiple types of coverage, this surge in claims can pose a risk of financial losses or bankruptcy. One option for insurers is to transfer some of these risks to reinsurance companies. Reinsurance companies will assess the potential losses due to a catastrophe event, then issue catastrophe reinsurance contracts to insurance companies. This study aims to construct a valuation model for catastrophe reinsurance contracts that can cover claim losses arising from two types of insurance products. Valuation in this study is done using the Fundamental Theorem of Asset Pricing, which is the expected present value of the number of claims that occur during the reinsurance coverage period. The number of catastrophe events during the reinsurance coverage period is assumed to follow a Poisson process. Each impact of a catastrophe event, such as the number of fatalities and injuries that cause claims, is represented as random variables, and modeled using Peaks Over Threshold (POT). This study uses Clayton, Gumbel, and Frank copulas to describe various dependence characteristics between random variables. The parameters of the POT model and copula are estimated using Inference Functions for Margins method. After estimating the model parameters, Monte Carlo simulations are performed to obtain numerical solutions for the expected value of catastrophe reinsurance based on the Fundamental Theorem of Asset Pricing. The expected reinsurance value based on Monte Carlo simulations using Indonesian earthquake data from 1979–2021 is Rp 10,296,819,838.

Financial literacy and financial intermediation are vital tools for all businesses, particularly women micro-entrepreneurs. Even with modest means, they have been shown to considerably contribute to economic independence at the family, national, and international levels. Since Indonesian women microentrepreneurs still have trouble getting bank loans (being unbanked), the majority of them join cooperatives. Cooperatives are without doubt the financial intermediation institutions of choice for micro-communities; nonetheless, research on the subject is still scarce, particularly in developing nations. In order to bridge this gap, this study looks at the role of cooperatives as financial intermediation organizations. Examining the impact of financial literacy through cooperative financial intermediation on the financial performance of Indonesian women microentrepreneurs is the main goal of the study. The cross-sectional data were identified using purposive approaches and processed with the use of Smart PLS as part of an explanatory research approach. The direct influence test results demonstrate that enhancing financial performance and financial intermediation are directly impacted by financial literacy. Additionally, financial intermediation (cooperatives) was successful in influencing the impact of financial literacy on the financial performance of micro-entrepreneurs in Indonesia, according to the findings of the mediation effect test.

The study looks into how governance qualities of decentralized governments mediate the impacts of decentralization on development. Based on a set-oriented approach, the study analyzed data from a nation-wide survey conducted with business managers from all provinces in Indonesia, and found evidence that, despite the country’s uniform decentralization reform, individual provinces exhibited great variation in the qualities of their various physical and institutional infrastructures. Notably, these qualities assumed nested relations, with order and security as well as accountability and rule of law seemingly being the preconditions of basic infrastructure provision as well as local governments’ coordination. Moreover, business investment decisions (measured as staff expansion and product innovation) were found to vary with some specific combinations of these infrastructural conditions. The result provides evidence supporting the argument that both physical and institutional infrastructures are instrumental to realize the supposed benefits of decentralization and supports the recent call of the literature to look into the political-institutional complex in the process of decentralization reform.

Regions rich in natural resources often exhibit a high dependency on revenue from Revenue Sharing Funds (DBH). This dependency can pose long-term challenges, especially when commodity prices experience significant fluctuations. This study examines the role of Revenue Sharing Funds from Natural Resources (DBH SDA) on economic growth in 491 regencies/cities in Indonesia during the 2010–2012 period. The analysis employs panel data regression. The selection of this period was based on the occurrence of a resource boom characterized by a surge in global demand for natural resource commodities, accompanied by an increase in commodity prices. This condition positively impacted the revenues of both the nation and resource-rich regions. The results of the study show that economic growth is not influenced by DBH SDA but rather by General Allocation Funds (DAU). This indicates that the central government still plays a significant role in determining economic growth at the regency/city level in Indonesia. Regions need to prioritize economic diversification to reduce reliance on DBH SDA and DAU. Investment in productive sectors, such as infrastructure, education, and technology, can be a strategic approach to accelerating regional economic growth.

 Public-private partnerships (PPPs) are vital for infrastructure development in developing countries, integrating private efficiency with public oversight. However, PPP models often face risks, particularly in Indonesia’s water sector, due to its unique geographical and regulatory challenges. This study aims to identify and evaluate risk factors specific to drinking water PPP projects in Indonesia. Using a quantitative approach, structured questionnaires were distributed to experts in the sector, and the data was analyzed using a fuzzy evaluation method. Risks were categorized into location, design and construction, financial, operational, revenue, and political. The study emphasizes that effective risk management, including identification, analysis, and mitigation, is essential for project success. It highlights the importance of stakeholder involvement and flexible risk management strategies. Comprehensive and proactive risk management is key to the success of drinking water infrastructure projects. The research suggests that an integrated and collaborative approach among stakeholders can enhance risk management effectiveness. These findings provide valuable insights for policymakers, project managers, investors, and other stakeholders, underscoring the necessity for adaptable regulatory frameworks and robust policy guidelines to improve the sustainability and efficacy of future water-related PPPs.

The relationship between aid and corruption remains ambiguous. On the one hand, aid may benefit a country if the aid management system runs efficiently and transparently. On the other hand, aid tends to create new problems, namely corruption, especially in developing countries. This research examines the aid-corruption paradox in Indonesian provinces from a spatial perspective. The data was obtained from the Indonesian Ministry of Finance, the National Development Planning Agency of Indonesia, the Corruption Eradication Commission of Indonesia, and the Electronic Procurement Service, referring to 34 Indonesian provinces between 2011 and 2019. The research applies the spatial panel method and uses Haversine distance to construct the weighted matrix. The spatial error model (SEM) is the best for Model 1 (Grants) and Model 2 (Loans) and the best corruption model in Model 3 (Gratification). The spatial autoregressive model (SAR) is the best approach for Model 4 (Public Complaints) and Model 5 (Corruption). The findings show that there is no spatial dependence between provinces in Indonesia in terms of grants or loans. However, corruption in Indonesia is widespread.