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Elements of Numerical Mathematical Economics with Excel: Static and Dynamic Optimization [Pehme köide]

(Independent Financial Advisor)
  • Formaat: Paperback / softback, 816 pages, kõrgus x laius: 235x191 mm, kaal: 1720 g
  • Ilmumisaeg: 27-Nov-2019
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128176482
  • ISBN-13: 9780128176481
Teised raamatud teemal:
Elements of Numerical Mathematical Economics with Excel: Static and Dynamic OptimizationSuurem pilt
  • Formaat: Paperback / softback, 816 pages, kõrgus x laius: 235x191 mm, kaal: 1720 g
  • Ilmumisaeg: 27-Nov-2019
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0128176482
  • ISBN-13: 9780128176481
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128176481.html
Märksõnad:

Elements of Numerical Mathematical Economics with Excel: Static and Dynamic Optimization shows readers how to apply static and dynamic optimization theory in an easy and practical manner, without requiring the mastery of specific programming languages that are often difficult and expensive to learn. Featuring user-friendly numerical discrete calculations developed within the Excel worksheets, the book includes key examples and economic applications solved step-by-step and then replicated in Excel.

After introducing the fundamental tools of mathematical economics, the book explores the classical static optimization theory of linear and nonlinear programming, applying the core concepts of microeconomics and some portfolio theory. This provides a background for the more challenging worksheet applications of the dynamic optimization theory. The book also covers special complementary topics such as inventory modelling, data analysis for business and economics, and the essential elements of Monte Carlo analysis.

Practical and accessible, Elements of Numerical Mathematical Economics with Excel: Static and Dynamic Optimization increases the computing power of economists worldwide. This book is accompanied by a companion website that includes Excel examples presented in the book, exercises, and other supplementary materials that will further assist in understanding this useful framework.

  • Explains how Excel provides a practical numerical approach to optimization theory and analytics
  • Increases access to the economic applications of this universally-available, relatively simple software program
  • Encourages readers to go to the core of theoretical continuous calculations and learn more about optimization processes
I Excel and fundamental mathematics for economics
1 Excel VBA, solver, and other advanced worksheet tools
1.1 VRA introduction and main statements
3(18)
1.2 The Excel Solver: simplex LP, Generalized Reduced Gradient, and evolutionary
21(8)
1.3 What-if analysis: scenario manager, Goal Seek, Data Table, and contour lines
29(11)
1.4 Scatter charts and trendlines
40(5)
2 Univariate and multivariate calculus
2.1 Numerical methods for univariate differentiation
45(13)
2.2 Numerical methods for univariate integration
58(8)
2.3 Numerical partial differentiation
66(9)
2.4 Applications in economics
75(8)
Exercises
83(5)
3 Elements of linear algebra
3.1 Built-in Excel matrix functions and basic operations
88(7)
3.2 Linear systems and resolution methods in Excel: Cramer, Solver, Inverse
95(12)
3.3 Eigenvalues and eigenvectors search: analytical and graphical approach
107(8)
3.4 Quadratic forms and definiteness of a symmetric matrix
115(6)
3.5 Leontief open model
121(3)
3.6 Equilibrium in n markets
124(5)
3.7 Economic policy modeling: objectives and instruments
129(5)
Exercises
134(6)
4 Mathematics for dynamic economic models
4.1 Ordinary differential equations and numerical methods: Euler and Runge-Kutta
140(7)
4.2 Force of interest, Walrasian stability, utility functions, and capital formation with ordinary differential equation
147(12)
4.3 Difference equations and phase diagrams
159(11)
4.4 Cobweb model of price adjustment and other economic models with difference equations
170(11)
4.5 Systems of linear differential equations
181(21)
4.6 Tourism fight between two competing regions
202(4)
4.7 Walrasian adjustment with entry
206(3)
Exercises
209(11)
II Static optimization
5 Classical static nonlinear optimization theory
5.1 Classical unconstrained optimization of a univariate function
220(12)
5.2 Classical unconstrained optimization of a multivariate function
232(15)
5.3 Some economic applications of the nonlinear unconstrained optimization
247(9)
5.4 Numerical steepest descent method applied to the unconstrained optimization with VBA
256(8)
5.5 Nonlinear problems in Rn with equality constraints: Lagrange multipliers and Solver
264(8)
5.6 Nonlinear problems in R2 with equality constraints: contour lines
272(13)
5.7 Nonlinear problems with inequality constraints
285(3)
Exercises
288(8)
6 Microeconomic theory in a static environment
6.1 The consumer problem: cardinal versus ordinal utility approach
296(1)
6.2 Consumer optimization and derivation of the demand curve in the cardinal approach
297(10)
6.3 Consumer optimization and derivation of the demand curve in the ordinal approach
307(12)
6.4 The firm problem
319(1)
6.5 One-input classical production function
320(2)
6.6 Two-inputs production functions
322(9)
6.7 Isoquants and the constrained production optimization with two inputs
331(4)
6.8 Production Edgeworth box, contract curve, and the possibility frontier construction
335(5)
6.9 Short-run, long-run costs and the envelope average total costs derivation
340(10)
6.10 Perfect competitive markets: short-run, long-run supply curves and market equilibrium
350(6)
6.11 Monopolistic market equilibrium: the Chamberlin model
356(4)
6.12 Markets with high-entry barriers: monopoly and the Cournot duopoly model
360(10)
6.13 Game theory. Zero-sum games and minimax criterion: matrix and graphical resolutions
370(6)
Exercises
376(7)
7 Linear programming
7.1 Standard formulation of a linear program and resolution methods
383(6)
7.2 Applications to the static production planning and capital budgeting
389(19)
Exercises
408(9)
8 Nonlinear optimization applied to the portfolio theory
8.1 Portfolio modeling and the efficient frontier construction
417(10)
8.2 Investor's utility and the optimal portfolio choice
427(5)
Exercises
432(6)
III Dynamic optimization
9 Calculus of variations
9.1 The fundamental problem of the Calculus of Variations
438(4)
9.2 Discrete approximate Calculus of Variations: Lagrange multipliers and contour lines solutions
442(9)
9.3 Set up of the Excel worksheet for Calculus of Variations problems: the Solver solution
451(2)
9.4 General cases developed in Excel with fixed and variable terminal points
453(16)
9.5 Dynamic optimization for a monopolist
469(2)
9.6 Unemployment and inflation
471(4)
9.7 The Eisner---Strotz model
475(4)
9.8 The optimal consumption Ramsey model
479(2)
9.9 Inventory dynamic optimization
481(1)
9.10 Optimal capital structure and the firm cost of capital
482(5)
9.11 Contour lines solution for Calculus of Variations using the VBA code
487(7)
9.12 Calculus of Variations with functionals involving two independent functions
494(3)
9.13 Calculus of Variations constrained problems
497(8)
9.14 Checking the Second-Order Conditions in Excel
505(6)
Exercises
511(11)
10 Theory of optimal control
10.1 The optimal control problem and the Pontryagin's maximum principle
522(1)
10.2 Nonlinear Hamiltonian and linear Hamiltonian (bang-bang control)
523(2)
10.3 Setup of the Excel worksheet for optimal control problems
525(17)
10.4 Bang-bang control problems
542(5)
10.5 Consumption model
547(7)
10.6 Investment model
554(7)
10.7 Inventory optimization
561(2)
10.8 Two state variables control problems
563(8)
10.9 Current-value Hamiltonian
571(5)
10.10 Constraints on the state variable: a linear case with an inventory application with VBA
576(11)
10.11 Steepest descent numerical approach for optimal control problems using VBA
587(6)
10.12 Checking the sufficient conditions in Excel
593(7)
Exercises
600(12)
11 Discrete dynamic programming
11.1 Bellman's principle, discrete shortest path problems, and the Excel MINIFS function
612(7)
11.2 Discrete dynamic systems: tabular method, Excel data table, and Solver
619(10)
11.3 Cargo loading allocation problems: tabular method and the Excel Solver
629(3)
11.4 Multistage allocation problems using the Excel Solver
632(4)
11.5 Equality constrained optimization problems using the recursive Bellman's approach
636(3)
11.6 Dynamic economic problems solved with Discrete Dynamic Programming
639(10)
11.7 Discrete Dynamic Programming, Optimal Control theory, and Calculus of Variations: a synthesis
649(3)
Exercises
652(9)
IV Special topics
12 Dynamic production planning and inventory modeling
12.1 Multiperiod production models with linear programming
661(8)
12.2 Wagner---Whitin algorithm for inventory dynamic modeling
669(8)
12.3 Eliezer Naddor stochastic single-period inventory models
677(10)
Exercises
687(9)
13 Data analysis for business and economics
13.1 A simple way to organize a spreadsheet using the VBA code and bookmarks
696(1)
13.2 Pivot tables, Pivot charts, and dynamic dashboards for managerial data analysis
697(14)
13.3 Basic descriptive statistics
711(10)
13.4 Some numerical calculus applied to continuous densities
721(6)
13.5 Univariate, multivariate regression analysis and the ANOVA tables
727(29)
Exercises
756(8)
14 Essential Monte Carlo analysis
14.1 The Monte Carlo method and the generation of random numbers
764(9)
14.2 The Monte Carlo method for business decisions
773(15)
14.3 Numerical integration
788(4)
Exercises
792(5)
Index 797
Giovanni Romeo is an independent financial advisor in Mergers & Acquisitions and Corporate Finance services. He received his bachelors and masters degrees in economics and management from University of Pavia and earned a master in corporate finance from SDA Bocconi Business School.