Paper ini berupaya menganalisa implikasi perilaku bank dalam menentukan portofolio terhadap tingkat efektivitas kebijakan moneter. Dengan kerangka analisa comparative static, paper ini mengetengahkan model industri perbankan yang bersifat monopolis dimana pemilik bank memaksimalkan profit dengan kendala tertentu baik yang berasal dari kesanggupan modal maupun kendala akibat regulasi.Kalibrasi model pada kondisi optimal, mengindikasikan bahwa penurunan fungsi disintermediasi bank yang didominasi oleh faktor asymmetric information, akan berakibat pada menurunnya efektifitas kebijakan moneter.Kesimpulan ini berimplikasi pada (i) perlunya Biro Kredit dan rating agencies untuk menyempurnakan informasi, (ii) perlunya investasi yang lebih besar oleh perbankan atas kapasitas riset dan sistem monitoring, (iii) perlunya mempertimbangkan skema garansi kredit, (iv) perlunya koordinasi yang lebih baik antara kebijakan mikro dan makro demi kestabilan makro yang akan meningkatkan keyakinan publik dan terakhir, (v) perlunya mempromosikan perkembangan lembaga keuangan non-bank, untuk mengurangi ketergantungan pembiayaan atas lembaga perbankan.JEL: E52, E58, G21Keyword: Disintermediation, monetary policy, banking sector, interest rate.

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In this paper, we use hourly exchange rate data for selected ASEAN countries (Singapore, Indonesia, Malaysia, Thailand and the Philippines) to test the hypothesis that exchange rate own shocks dominate exchange rate volatility. We find strong evidence that own exchange rate volatility explains between 64% to 86% of their own exchange rate volatility movements. These results do not change when we include the Chinese CNY currency in the analysis. Moreover, we find that exchange rate shocks of ASEAN countries explain 36%, 24% and 23% of exchange rate volatility movements of Indonesia, Thailand, and Singapore, suggesting that for these countries are more synchronized.

Recibido (22/05/2020) Revisado (14/02/2021) Aceptado (07/05/2021) RESUMEN: Entender y predecir el fenómeno inflacionario es un problema central para los economistas y agentes tomadores de decisiones. Tradicionalmente se han utilizado técnicas econométricas de series de tiempo para estudiar este fenómeno; pero, ¿puede la economía de la complejidad aportar una visión complementaria a los estudios anteriores?

Modeling banking systems using a network approach has received growing attention in recent years. One of the notable models is that developed by Iori et al, who proposed a banking system model for analyzing systemic risks in interbank networks. The model is built based on the simple dynamics of several bank balance sheet variables such as deposit, equity, loan, liquid asset, and interbank lending (or borrowing) in the form of difference equations. Each bank faces random shocks in deposits and loans. The balance sheet is updated at the beginning or end of each period. In the model, banks are grouped into either potential lenders or borrowers. The potential borrowers are those that have lack of liquidity and the potential lenders are those which have excess liquids after dividend payment and channeling new investment. The borrowers and the lenders are connected through the interbank market. Those borrowers have some percentage of linkage to random potential lenders for borrowing funds to maintain their safety net of the liquidity. If the demand for borrowing funds can meet the supply of excess liquids, then the borrower bank survives. If not, they are deemed to be in default and will be removed from the banking system. However, in their paper, most part of the interbank borrowing-lending mechanism is described qualitatively rather than by detailed mathematical or computational analysis. Therefore, in this paper, we enhance the mathematical parts of borrowing-lending in the interbank market and present an algorithm for simulating the model. We also perform some simulations to analyze the effects of the model's parameters on banking stability using the number of surviving banks as the measure. We apply this technique to analyze the effects of a macroprudential policy called loan-to-deposit ratio based reserve requirement for banking stability.