Economics

The Indonesian Government has set ambitious climate targets and commitments, and now appropriate climate action is needed to achieve these targets. This viewpoint article identifies gaps in financing to achieve Indonesia's climate commitments and suggests funding mobilisation strategies for climate action; it also recommends policy options to utilise available funding effectively and efficiently. It was estimated that realising climate commitments requires up to USD 276 billion in total, and the financing gap to realise this is around 53 per cent. To achieve the climate target, the government needs appropriate financing strategies. Securing funding from national and international sources, as well as from public and private sources, is critical to filling the gap and establishing financial source diversification. The limited state budget must be optimised through financial instruments such as green bonds, carbon pricing, and fiscal transfers. International financial sources must also be mobilised through bilateral, regional, and multilateral channels.

The Indonesian Government has set ambitious climate targets and commitments, and now appropriate climate action is needed to achieve these targets. This viewpoint article identifies gaps in financing to achieve Indonesia's climate commitments and suggests funding mobilisation strategies for climate action; it also recommends policy options to utilise available funding effectively and efficiently. It was estimated that realising climate commitments requires up to USD 276 billion in total, and the financing gap to realise this is around 53 per cent. To achieve the climate target, the government needs appropriate financing strategies. Securing funding from national and international sources, as well as from public and private sources, is critical to filling the gap and establishing financial source diversification. The limited state budget must be optimised through financial instruments such as green bonds, carbon pricing, and fiscal transfers. International financial sources must also be mobilised through bilateral, regional, and multilateral channels.

According to Islamic law, the Islamic banks deliver return to depositors based on profit and loss sharing principle. Consequently, the return will be uncertain following real business and economic condition. However, this research investigates the phenomenon that Indonesian Islamic banking industry seems to mimic interest rate in generating return to depositors. This investigation utilizes artificial neural networks (ANN) model to examine the importance rate of each macroeconomic variables used. The rate indicates the level of domination or contribution of each variable in determining the volatility of Islamic time deposit return. The research uses ten years of monthly macroeconomic data as independent variables. Additionally, the average rate of return from one-month time deposit of all Indonesian Islamic banks (RR) is used as dependent variable. As a result, the N (9-4-1) , a chosen neural networks architecture, found that BIRT and INTR as proxy of interest rate, dominantly affect RR volatility with almost 98% of importance rate. It shows the very high dominance of interest rate in determining RR volatility, as indication of mimicking behavior, rather than remaining variables as proxy of real economic condition. 45 J an-00 J ul-00 J an-01 J ul-01 J an-02 J ul-02 J an-03 J ul-03 J an-04 J ul-04 J an-05 J ul-05 J an-06 J ul-06 J an-07 J ul-07 J an-08 J ul-08 J an-09 J ul-09

The main aims of this paper are, firstly, to investigate the extent to which Yemen's banks, in particular its Islamic banks, are applying Risk Management Practices (RMPs) and related techniques to deal with various types of risk, and secondly, to compare and distinguish between the RMPs used in Islamic, national and foreign banks. Semi-structured interviews were conducted to identify the current RMPs in Yemen. The main research instrument was a questionnaire, divided into two sections. The first section covered the following five aspects: understanding risk and risk management, risk identification and analysis, risk monitoring, RMPs, and credit risk analysis. The second section consisted of four aspects: methods of risk identification, risk management, credit risk management, and types of risk. Multinomial regressions and other statistical tools were applied to determine whether there are differences between Islamic banks and other banks in Yemen. Our results revealed that there are significant differences between Islamic and national banks in terms of their understanding of risk and risk management, risk identification and analysis and credit risk analysis. However, there are no major differences found between national and Islamic banks in terms of risk management and RMPs. For Islamic and foreign banks, however, there are significant differences in terms of understanding risk and risk management and risk identification and analysis, but no differences between their risk management, RMPs and credit risk analysis.