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This book offers a comprehensive yet approachable introduction to essential mathematical concepts, tailored specifically for undergraduate and first-year graduate students in Economics and Social Sciences. Based on lectures delivered at the University of Pavia's Department of Economics and Management, and also in UNED' Department of Applied Mathematics in Madrid, it aims to equip students with the mathematical tools necessary to better understand their courses in economics and finance, where math is applied directly.
Unlike texts focused on formalized topics like Mathematical Economics or Operations Research, this book presents basic mathematical principles and methods that are immediately relevant to students. With a clear, accessible approach, it includes numerous examples, some with economic applications, to illustrate key concepts and make them easier to grasp.
The authors have carefully chosen proofs that are straightforward and beneficial for students to encounter, offering an introduction to important proof techniques without overwhelming complexity. The book also provides a select bibliography, allowing readers to explore topics in greater depth if desired.
Drawing on years of teaching experience, the authors have created a valuable resource that serves as both a foundation and a practical guide for students navigating the mathematical aspects of economics and social science courses.
Sommario
Topics of Linear Algebra.- Introduction to Functions of Several Real Variables.- Introduction to Convex Analysis.- Static Optimization.- Linear Programming.- Continuous Dynamical Systems.- Discrete Dynamical Systems.- Introduction to Dynamic Optimization.
Info autore
Prof. Giorgio Giorgi teaches Mathematics at the Faculty of Economics of the University of Pavia, Italy. His research interests essentially focus on mathematical economics, generalized convexity, and optimization.
Bienvenido Jiménez and Vicente Novo are professors of Applied Mathematics at the National University of Distance Education, Madrid, Spain. Their research focus on smooth and nonsmooth optimization, mathematical programming and multiobjective, vector and set optimization.
