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Showing posts with label Introduction. Show all posts
Showing posts with label Introduction. Show all posts

An Introduction to Mathematical Analysis for Economic Theory and Econometrics

Great Price "An Introduction to Mathematical Analysis for Economic Theory and Econometrics" for $57.82 Today



Every undergraduate who wishes to pursue a PhD in economics is told to take a sequence of certain math classes, the hardest of which is usually real analysis. I took a real analysis course based on Rudin's blue book and found it a painful transition from my previous courses. I had to quickly get used to reading and writing proofs. It was unclear if and how these tools can be used in economics. This book is a great solution because it helps the reader to gently transition to writing proofs and is chock-full of applications at every step.

This book has three parts: The first 3 chapters introduce the reader to abstract math and proof writing techniques. The second part, chapters 4-8, teach standard material that is often covered in a 2-semester sequence on real analysis. This includes metric spaces, measure theory and probability, and Lp spaces. This also includes a chapter on convex analysis which is rarely covered in books on real analysis designed for math students. The last 3 chapters cover advanced material which is useful for readers interested in economic and econometric theory.

The thing that I liked most about this book is its impressive collection of applications to economics, here are some:

The first chapter on Logic discusses general equilibrium and proves the first fundamental theorem of welfare economics. In the second chapter on set theory they discuss lattices and apply these tools to introduce Monotone Comparative Statics (MCS) (which was a hot topic in the 90's and hasn't even been introduced into most microeconomics textbooks yet, not even in MasColell). They explain how MCS is a generalization of regular Comparative Statics based on the implicit function theorem, which requires strong assumptions about differentiability. The discussion of real numbers in chapter 3 is very thorough, so an econ student doesn't need to follow every detail but in case he gets curious about some property of the real numbers he can always refer back to it.

In chapter 4 they talk about the finite dimensional vector space of real numbers. This is a more gentle approach than I experienced when I learned analysis, because we jumped straight into general metric spaces. They apply these tools to Linear Dynamical Systems, Markov Chains, and most notably to Dynamic Programming. Chapter 5 covers finite-dimensional convex analysis, which includes all kinds of convex separation theorems and applies these tools to prove the second fundamental theorem of welfare economics. They also cover everything you ever wanted to know about constrained optimization, the implicit function theorem and Kuhn Tucker conditions in horrendous detail. The authors proceed to discuss general metric spaces and include more applications to dynamic programming generalizing many of the topics discussed in previous chapters.

Chapter 7, which is a bit more technical than the previous chapters, discusses measure theory and measure-theoretic probability. This includes applications to all kinds of useful limit theorems and 0-1 laws, and a cool application to quantile estimation on page 405 and state dependent preferences on page 445. Chapter 8 introduces Lp spaces with applications to Statistics and Econometrics including a theoretical discussion of parametric and non-parametric regression. This chapter also includes an application to Artificial Neural Networks.

I haven't spent much time on the final 3 chapters, though I look forward to studying Chapter 11 on expanded spaces (Nonstandard Analysis) which Berkeley's Robert M. Anderson claims can be very useful in the future. In his manuscript on Nonstandard Analysis, Anderson writes "a very large number of papers could be significantly simplified using nonstandard arguments."

The applications make this the only book of its kind that I have seen. Efe Ok's text on Real Analysis assumes a stronger background than this text, and doesn't include such an eclectic collection of applications. Ok's text is more suitable for someone who wants to work in pure theory.

I would have liked to have seen additional material on general topological spaces covered earlier in the text so for example their discussion of open sets in Euclidean space can be seen as a special type of topological space.

I would strongly recommend this book to anyone who wants to see how mathematical analysis can be applied to economics.


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An Introduction to Mathematical Analysis for Economic Theory and Econometrics Overviews

Providing an introduction to mathematical analysis as it applies to economic theory and econometrics, this book bridges the gap that has separated the teaching of basic mathematics for economics and the increasingly advanced mathematics demanded in economics research today. Dean Corbae, Maxwell B. Stinchcombe, and Juraj Zeman equip students with the knowledge of real and functional analysis and measure theory they need to read and do research in economic and econometric theory.

Unlike other mathematics textbooks for economics, An Introduction to Mathematical Analysis for Economic Theory and Econometrics takes a unified approach to understanding basic and advanced spaces through the application of the Metric Completion Theorem. This is the concept by which, for example, the real numbers complete the rational numbers and measure spaces complete fields of measurable sets. Another of the book's unique features is its concentration on the mathematical foundations of econometrics. To illustrate difficult concepts, the authors use simple examples drawn from economic theory and econometrics.

Accessible and rigorous, the book is self-contained, providing proofs of theorems and assuming only an undergraduate background in calculus and linear algebra.

  • Begins with mathematical analysis and economic examples accessible to advanced undergraduates in order to build intuition for more complex analysis used by graduate students and researchers
  • Takes a unified approach to understanding basic and advanced spaces of numbers through application of the Metric Completion Theorem
  • Focuses on examples from econometrics to explain topics in measure theory

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Customer Review



easy to read; good exercise questions - T. Chen -
I'm currently a economics graduate student. I was in Max's class when he used the manuscript of this textbook as the course material. This book definitely covers what an economics student will need during the infancy of research. I especially like the questions in the book. They help a lot in understanding. I highly recommend this book to any economics graduate student.



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An Introduction To Analysis

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In this textbook the authors have provided an important classroom tool for teaching undergraduates introductory real analysis. Without sacrificing rigor, they treat all the classical topics and principal theorems (convergence of sequences, limits and continuity of functions, differentiation, integration) in a lucid manner by exploiting the elementary machinery of sequences. This approach, free from the technical abstractions of general topology, makes the book much more readable for the average junior/senior level student majoring or minoring in mathematics. I have used the book for a one-semester course, and I don't think I would revert to the standard topological method for ordinary students in a first course in real analysis. Some of the main results can be re-derived as corollaries in a follow-up course on point-set topology for students interested in attending graduate school.


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An Introduction To Analysis Overviews

Complete coverage without sacrificing learning quality is made possible by the authors of this new introductory text. The fundamental concepts of mathematical analysis and proofs of single variable calculus are presented in a patient and accessible manner that will not overwhelm the average math student. An Introduction to Analysis offers a large variety of examples and exercises that will engage your students in active learning and help them develop an ability to perform analysis.

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Customer Review


Beautiful book! - Marisa - Rural Heartland, USA
I have taught this book at least five times. I use it to teach non-graduate track math majors (many are math-secondary math ed majors). I absolutely love working with this book. Since it is currently out of print I have regularly sought the author's permission for the students to make copies if they can't find it used. I can't wait to see it printed again. It is a joy for me to work the material this way.
It is very thorough math, while all the way allowing for almost taking the students by the hand through their first analysis proofs class. The exercises are a real gem. I spend about 1/3 of the class time working recitation-like on exercises.




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Metrics, Norms and Integrals: An Introduction to Contemporary Analysis

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Metrics, Norms and Integrals: An Introduction to Contemporary Analysis Overviews

Metrics, Norms and Integrals is a textbook on contemporary analysis based on the author s lectures given at the University of Melbourne for over two decades. It covers three main topics: metric and topological spaces, functional analysis, and the theory of the Lebesgue integral on measure spaces. This self-contained text contains a number of original presentations, including an early introduction of pseudometric spaces to motivate general topologies, an innovative introduction to the Lebesgue integral, and a discussion on the use of the Newton integral. It is thus a valuable book to inform and stimulate both undergraduate and graduate students.

Contents:Metrics and Topologies:; Metric Spaces; Convergence and Completeness; Continuity in Metric Spaces; Topological Spaces; Compactness; Connectedness; Linear Analysis:; Normed Spaces; Inner Product Spaces; Linear Operators and Functionals; Self-Adjoint Compact Operators; Introductory Functional Analysis; Integration:; Measure Spaces; The Abstract Lebesgue Integral; Integral on the Real Line; Construction of Measures; Product Measures. Integration on ℝk; Lebesgue Spaces.

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An Introduction to Involutive Structures (New Mathematical Monographs)

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An Introduction to Involutive Structures (New Mathematical Monographs) Overviews

Detailing the main methods in the theory of involutive systems of complex vector fields this book examines the major results from the last twenty five years in the subject. One of the key tools of the subject - the Baouendi-Treves approximation theorem - is proved for many function spaces. This in turn is applied to questions in partial differential equations and several complex variables. Many basic problems such as regularity, unique continuation and boundary behaviour of the solutions are explored. The local solvability of systems of partial differential equations is studied in some detail. The book provides a solid background for others new to the field and also contains a treatment of many recent results which will be of interest to researchers in the subject.

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Calculus Concepts and Contexts (Includes Introduction to Vectors Chapter) (Volume 1)

Calculus Concepts and Contexts (Includes Introduction to Vectors Chapter) (Volume 1) Review

















Overviews

This is a custom Northeastern University textbook used in Calculus 1(MTHU241) and Calculus 2(MTHU242).

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An Introduction to Frames and Riesz Bases

An Introduction to Frames and Riesz Bases Review




The subject of the book is a new tool in math, with a host of exciting applications. Of course, the subject has roots in classical ideas from harmonic analysis. But the book covers an explosive and exciting variety of developments since roughly 1990, and it is presented in the form of a graduate text. The basic idea begins with linear algebra, and progresses to expansions in function spaces, and multiresolutions. It will be useful to anyone who wants to learn from scratch about the underlying principles, the new results, and the applications. It is well written. A student of mine picked it up accidentally from my desk, and couldn't put it down. After awhile, he had completely forgotten what he came to see me about. It could have been some of the applications, such as antenna theory, wavelets, time-frequency analysis, uses in Radar, speech processing...



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Overviews

The theory for frames and bases has developed rapidly in recent years because of its role as a mathematical tool in signal and image processing. In this self-contained work, frames and Riesz bases are presented from a functional analytic point of view, emphasizing their mathematical properties. This is the first comprehensive book to focus on the general properties and interplay of frames and Riesz bases, and thus fills a gap in the literature.

Key features:

* Basic results presented in an accessible way for both pure and applied mathematicians

* Extensive exercises make the work suitable as a textbook for use in graduate courses

* Full proofs included in introductory chapters; only basic knowledge of functional analysis required

* Explicit constructions of frames with applications and connections to time-frequency analysis, wavelets, and nonharmonic Fourier series

* Selected research topics presented with recommendations for more advanced topics and further reading

* Open problems to stimulate further research

"An Introduction to Frames and Riesz Bases" will be of interest to graduate students and researchers working in pure and applied mathematics, mathematical physics, and engineering. Professionals working in digital signal processing who wish to understand the theory behind many modern signal processing tools may also find this book a useful self-study reference.

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Customer Review






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