Picture 1 of 1
Picture 1 of 1
Essential Mathematics for Economics by Alexis Akira Toda (2024, Trade Paperback)
Great Book Prices Store (357417)
97.8% positive feedback
Price:
$73.43
Free shipping
Returns:
14 days returns. Buyer pays for return shipping. If you use an eBay shipping label, it will be deducted from your refund amount.
Condition:
Essential Mathematics for Economics, Paperback by Toda, Alexis Akira, ISBN 1032698942, ISBN-13 9781032698946, Brand New, Free shipping in the US "Essential Mathematics for Economics covers mathematical topics that are essential for economic analysis in a concise but rigorous fashion. Th covers selected topics such as linear algebra, real analysis, convex analysis, constrained optimization, dynamic programming, and numerical analysis in a single volume. Th is entirely self-contained, and almost all propositions are proved"--
- Buy It NowEssential Mathematics for Economics, Paperback by Toda, Alexis Akira, Brand N...
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
About this product
Product Identifiers
PublisherCRC Press LLC
ISBN-101032698942
ISBN-139781032698946
eBay Product ID (ePID)28068563503
Product Key Features
Number of Pages286 Pages
Publication NameEssential Mathematics for Economics
LanguageEnglish
SubjectEconomics / Microeconomics, Economics / General, Econometrics, Business Mathematics
Publication Year2024
TypeTextbook
Subject AreaBusiness & Economics
AuthorAlexis Akira Toda
FormatTrade Paperback
Dimensions
Item Weight20 Oz
Item Length9.2 in
Item Width6.1 in
Additional Product Features
Intended AudienceCollege Audience
LCCN2024-019785
Dewey Edition23/eng/20240603
IllustratedYes
Dewey Decimal330.01/51
Table Of Content0. Roadmap. Section I. Introduction to Optimization. 1. Existence of Solutions. 1.1. Introduction. 1.2. The Real Number System. 1.3. Convergence of Sequences. 1.4. The Space r n. 1.5. Topology of r n. 1.6. Continuous Functions. 1.7. Extreme Value Theorem. 1.A. Topological Space. 2. One-Variable Optimization. 2.1. Introduction. 2.2. Differentiation. 2.3. Necessary Condition. 2.4. Mean Value and Taylor's Theorem. 2.5. Sufficient Condition. 2.6. Optimal Savings Problem. 3. Multi-Variable Unconstrained Optimization. 3.1. Introduction. 3.2. Linear Maps and Matrices. 3.3. Differentiation. 3.4. Chain Rule. 3.5. Necessary Condition. 4. Introduction to Constrained Optimization. 4.1. Introduction. 4.2. One Linear Constraint. 4.3. Multiple Linear Constraints. 4.4. Karush-Kuhn-Tucker Theorem. 4.5. Inequality and Equality Constraints. 4.6. Constrained Maximization. 4.7. Dropping Nonnegativity Constraints. Section II. Matrix and Nonlinear Analysis. 5. Vector Space, Matrix, and Determinant. 5.1. Introduction. 5.2. Vector Space. 5.3. Solving Linear Equations. 5.4. Determinant. 6. Spectral Theory. 6.1. Introduction. 6.2. Eigenvalue and Eigenvector. 6.3. Diagonalization. 6.4. Inner Product and Norm. 6.5. Upper Triangularization. 6.6. Positive Definite Matrices. 6.7. Second-Order Optimality Condition. 6.8. Matrix Norm and Spectral Radius. 7. Metric Space and Contraction. 7.1. Metric Space. 7.2. Completeness and Banach Space. 7.3. Contraction Mapping Theorem. 7.4. Blackwell's Sufficient Condition. 7.5. Perov Contraction. 7.6. Parametric Continuity of Fixed Point. 8. Implicit Function and Stable Manifold Theorem. 8.1. Introduction. 8.2. Inverse Function Theorem. 8.3. Implicit Function Theorem. 8.4. Optimal Savings Problem. 8.5. Optimal Portfolio Problem. 8.6. Stable Manifold Theorem. 8.7. Overlapping Generations Model. 9. Nonnegative Matrices. 9.1. Introduction. 9.2. Markov Chain. 9.3. Perron's Theorem. 9.4. Irreducible Nonnegative Matrices. 9.5. Metzler Matrices. Section III. Convex and Nonlinear Optimization. 10. Convex Sets. 10.1. Convex Sets. 10.2. Convex Hull. 10.3. Hyperplanes and Half Spaces. 10.4. Separation of Convex Sets. 10.5. Cone and Dual Cone. 10.6. No-Arbitrage Asset Pricing. 11. Convex Functions. 11.1. Convex and Quasi-Convex Functions. 11.2. Convexity-Preserving Operations. 11.3. Differential Characterization. 11.4. Continuity of Convex Functions. 11.5. Homogeneous Quasi-Convex Functions. 11.6. Log-Convex Functions. 12. Nonlinear Programming. 12.1. Introduction. 12.2. Necessary Condition. 12.3. Karush-Kuhn-Tucker Theorem. 12.4. Constraint Qualifications. 12.5. Saddle Point Theorem. 12.6. Duality. 12.7. Sufficient Conditions. 12.8. Parametric Differentiability. 12.9. Parametric Continuity. Section IV. Dynamic Optimization. 13. Introduction to Dynamic Programming. 13.1. Introduction. 13.2. Knapsack Problem. 13.3. Shortest Path Problem. 13.4. Optimal Savings Problem. 13.5. Optimal Stopping Problem. 13.6. Secretary Problem. 13.7. Abstract Formulation. 14. Contraction Methods. 14.1. Introduction. 14.2. Markov Dynamic Program. 14.3. Sequential and Recursive Formulations. 14.4. Properties of Value Function. 14.5. Restricting Spaces. 14.6. State-Dependent Discounting. 14.7. Weighted Supremum Norm. 14.8. Numerical Dynamic Programming. 15. Variational Methods. 15.1. Introduction. 15.2. Euler Equation. 15.3. Transversality Condition. 15.4. Stochastic Case. 15.5. Optimal Savings Problem.
SynopsisEssential Mathematics for Economics covers mathematical topics that are essential for economic analysis in a concise but rigorous fashion. The book covers selected topics such as linear algebra, real analysis, convex analysis, constrained optimization, dynamic programming, and numerical analysis in a single volume. The book is entirely self-contained, and almost all propositions are proved. Features Replete with exercises and illuminating examples Suitable as a primary text for an advanced undergraduate or postgraduate course on mathematics for economics Basic linear algebra and real analysis are the only prerequisites. Supplementary materials such as Matlab codes, teaching slides etc. are posted on the book website https: //github.com/alexisakira/EME., Essential Mathematics for Economics covers mathematical topics that are essential for economic analysis in a concise but rigorous fashion. The book covers selected topics such as linear algebra, real analysis, convex analysis, constrained optimization, dynamic programming, and numerical analysis in a single volume. The book is entirely self-contained, and almost all propositions are proved. Features Replete with exercises and illuminating examples Suitable as a primary text for an advanced undergraduate or postgraduate course on mathematics for economics Basic linear algebra and real analysis are the only prerequisites. Supplementary materials such as Matlab codes, teaching slides etc. are posted on the book website https://github.com/alexisakira/EME., T his book covers mathematical topics that are essential for economic analysis in a concise but rigorous fashion. The book covers selected topics such as linear algebra, real analysis, convex analysis, constrained optimization, dynamic programming, and numerical analysis in a single volume.
LC Classification NumberHB135.T633 2025
