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"Penelitian ini bertujuan untuk menganalisis faktor - faktor yang mempengaruhi net interest margin (margin bunga bersih) dari bank - bank di Indonesia. Studi mengambil 15 bank dengan jumlah aset tertinggi di Indonesia. Di dalam studi ini, faktor-faktor penentu margin bunga bersih dapat diklasifikasikan menjadi dua bagian yakni mikro dan makro. Faktor mikro terdiri dari besarnya aset bank, kapitalisasi bank, beban operasi bank, kepemilikan pihak asing, serta giro wajib minimum, sedang kan untuk faktor makroekonomi, terdapat produk domestik bruto, inflasi, konsentrasi industri, perkembangan perbankan, serta krisis. Dengan menggunakan model panel disertai efek acak (random-effect) untuk melihat hasil estimasi dari persamaan regresi, dibuktikan bahwa besarnya aset bank dapat mengurangi margin bunga bersih, sedangkan kapitalisasi perbankan dan beban operasi bank berpengaruh positif pada margin bunga bersih, sedangkan kepemilikan luar negeri berpengaruh negatif terhadap margin bunga bersih. Faktor makro pun juga ikut berkontribusi dimana PDB mempengaruhi margin bunga bersih secara positif tehadap margin bunga bersih, perkembangan perbankan serta konsentrasi industri berpengaruh positif terhadap margin bunga bersih, sedangkan krisis memiliki dampak yang negatif bagi margin bunga bersih. Inflasi dan giro wajib minimum pun harus disingikirkan guna menjaga multikolinearitas.

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This research aims to analyze the Determinants of NIM in Indonesian Banks. Determinants factors in this research are divided into two factors, micro and macro. Micro factors are Bank size, bank capitalization, overhead cost, foreign ownership, reserve requirement. Meanwhile for macro factors are GDP, Inflation, Industry concentration, banking development, and crisis. This research choose 15 top banks on asset-based in Indonesia.. NIM is to serve as a means to how efficiency in banking system Employing panel model with random effect to estimate the regression equation, this study proves that bank size has a negative contribution to NIM of fifteen selected banks, while bank capitalization and overhead expense affect positively to NIM, on the other hand, foreign ownership affects negative. Macro-factors also contribute fairly, where GDP affects positively to NIM, industry concentration and banking development affects positively to NIM, on the other hand, crisis affects negative on NIM. Inflation and reserve requirement are ommited due to multicollinearity problem."

"Pemodelan term structure of interest rate merupakan permasalahan yang cukup penting dalam teori finansial modern. Penelitian ini bertujuan mencari model term structure yang tepat digunakan dalam kasus di Indonesia. Dalam penelitian ini diambil lima sampel model term structure yaitu cubic spline (CS), polinimial pangkat empat (POLY), Nelson-Siegel (NS), Extended Nelson-Siegel-Svensson (ENSS) dan Modifikasi model Extended Nelson-Siegel-Svensson (ModENSS) yang diajukan oleh penulis dengan menggunakan data mingguan transaksi obligasi pemerintah untuk periode Februari 2002 sampai dengan 18 Agustus 2004. Dalam penelitian ini juga diperlihatkan perbedaan antara pemakaian yield to maturity dengan zero-coupon rate dalam pembentukan term structure di Indonesia. Dapat disimpulkan bahwa model ENSS lebih baik dibandingkan keempat model lainnya dalam kriteria in sample ataupun out of sample analisis. Hal ini ditunjukkan dari nilai RMSE (Root Mean Square Error) ataupun MAYE (Mean Absolute Yield Error) yang terkecil dibandingkan model lainnya. Pengujian ANOVA dan uji lanjutan Tukey turut mendukung kesimpulan tersebut. Dengan demikian penambahan satu parameter lagi ke dalam model ENSS yang diajukan oleh penulis ternyata tidak memberikan peningkatan yang signifikan dalam perbaikan model term structure untuk kasus di Indonesia.

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Modeling term structure of interest rate has been one of important problems in financial modern theory. This research is conducted to find term structure model that appropriate to be implemented in Indonesia case. We choose five famous term structure models i.e.: cubic-spline, polynomial 4th order, Nelson-Siegel, Extended Nelson-Siegel-Svensson and Modified Extended Nelson-Siegel-Svensson by adding one more parameter in Extended Nelson-Siegel-Svensson. We used secondary market government securities data from February 2002 to August 2004 in weekly basis to test the model. This paper also shows the different between yield to maturity and zero coupon spot rate information in modeling term structure. We find evidence that Extended-Nelson-Siegel-Svensson method is superior both in sample and out-of sample analysis that it is indicated by the smallest RMSE (Root Mean Square Error) and MAYE (Mean Absolute Error) value compared to the others. Another conclusion was by adding one more parameter into ENSS model, it did not improve term structure model significantly in Indonesia case."

"Mathematical Optimization and Economic Theory provides a self-contained introduction to and survey of mathematical programming and control techniques and their applications to static and dynamic problems in economics, respectively. It is distinctive in showing the unity of the various approaches to solving problems of constrained optimization that all stem back directly or indirectly to the method of Lagrange multipliers. In the 30 years since its initial publication, there have been many more applications of these mathematical techniques in economics, as well as some advances in the mathematics of programming and control. Nevertheless, the basic techniques remain the same today as when the book was originally published. Thus, it continues to be useful not only to its original audience of advanced undergraduate and graduate students in economics, but also to mathematicians and other researchers who are interested in learning about the applications of the mathematics of optimization to economics.The book is distinctive in that it covers in some depth both static programming problems and dynamic control problems of optimization and the techniques of their solution. It also clearly presents many applications of these techniques to economics, and it shows why optimization is important for economics. Many cchallenging problems for both students and researchers are included."