First published in 2004, this is a rigorous but user-friendly book on the application of stochastic control theory to economics. A distinctive feature of the book is that mathematical concepts are introduced in a language and terminology familiar to graduate students of economics. The standard topics of many mathematics, economics and finance books are illustrated with real examples documented in the economic literature. Moreover, the book emphasises the dos and don'ts of stochastic calculus, cautioning the reader that certain results and intuitions cherished by many economists do not extend to stochastic models. A special chapter (Chapter 5) is devoted to exploring various methods of finding a closed-form representation of the value function of a stochastic control problem, which is essential for ascertaining the optimal policy functions. The book also includes many practice exercises for the reader. Notes and suggested readings are provided at the end of each chapter for more references and possible extensions.
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Professor Chang received his BS from National Taiwan University, holds a PhD in Economics from the University of Chicago and a PhD in Mathematics from State University of New York at Stony Brook. His graduate-level courses include price theory sequence and mathematical economics (stochastic control theory and applications, economics of uncertainty). He has been an invited visiting scholar to the Center for Economic Studies (CES) of the University of Munich, Germany, and the Economic Research Center (ERC) of Nagoya Univeristy, Japan. He is also a recipient of the 1986 Outstanding Junior Faculty Awards of Indiana University, a recipient of the 2004 IU Trustees Teaching Awards, and a research fellow of the CESifo Research Network. Professor Chang has published papers in prestigious journals in economics and mathematics, including Econometrica, the Review of Economic Studies, the Journal of Economic Theory, the Proceedings of American Mathematical Society, and the Journal of Optimization Theory and Applications. In 2004 he published Stochastic Optimization in Continuous Time with Cambridge University Press.
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