Pengendalian Kurs Rupiah Terhadap Dollar Amerika Serikat Melalui Suku Bunga SBI = Rupiah Against US Dollar Exchange Rate Control Through SBI Discount Rate

Changing on Indonesian exchange rate system from fixed to dirty floating system since August 14, 1997, had made rupiah against US dollar rate fluctuating freely and achieved its higher rate on June 1998 at Rp I4,900/USD. Sharp depreciation of Indonesian exchange rate, like ones on 1998 and on late 2000, raised again the issue whether policy makers should raise Indonesian domestic interest rate if the exchange rate depreciated or the FED had a plan to raise its future discount rate, or let its value would be determined by market mechanism. Opinions said that Bank Indonesia as monetary authority in Indonesia should intervene by raising its discount rate based on an understanding that interest rate should be raised until its value was competitive enough relative to interest rate abroad so exchange rate depreciated could be stopped or its magnitude could be avoided. This thesis studies the problem in controlling rupiah\u27s exchange rate against US dollar through Bank Indonesia\u27s SBI discount rate. The result was SBI discount rate 1 mount capable in controlling rupiah\u27s exchange rate against US dollar for the period being observed. 90.476% sample of observation of exchange rate growth could be controlled by SBI discount rate one monthother 9,524% could not controlled by this policy tool. Key Word: Monetary Policy, Interest Rate, Exchange Rate Contro

Spatial Contagion of Global Financial Crisis

The global financial crisis triggered by the credit crisis in the USA as its epicenter, quickly spread across the globe. The crisis starts spreading around the world in the middle of 2007 and along the 2008, where stock markets in major economies fell, followed by collapses of large companies and leading financial institutions. In a world where economies are integrated, the spread of such crisis is unavoidable. In this paper, we try to estimate the spill over effect of the global financial crises across borders and regions. Using spatial econometrics method we employ distance based weight matrix to estimate the spatial dependence and spatial heterogeneity of the crises. On the sensitivity analysis, we also employ weights matrix that is corrected by the governance and the economic freedom index to shows how the virtual space of governance, economic institution and regimes affect the spread of the crises.Global Financial Crises, Spillover Effect, Institutions, Globalization, Spatial Econometrics