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E-raamat: Microeconometrics and MATLAB: An Introduction

(Associate Professor of Economics, University of Oxford), (Associate Professor of Economics, University of Oxford), (PhD student in Economics, University of Oxford)
  • Formaat: 256 pages
  • Ilmumisaeg: 14-Jan-2016
  • Kirjastus: Oxford University Press
  • Keel: eng
  • ISBN-13: 9780191069437
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  • Formaat: 256 pages
  • Ilmumisaeg: 14-Jan-2016
  • Kirjastus: Oxford University Press
  • Keel: eng
  • ISBN-13: 9780191069437
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This book is a practical guide for theory-based empirical analysis in economics that guides the reader through the first steps when moving between economic theory and applied research. The book provides a hands-on introduction to some of the techniques that economists use for econometric estimation and shows how to convert a selection of standard and advanced estimators into MATLAB code.

The book first provides a brief introduction to MATLAB and its syntax, before moving into microeconometric applications studied in undergraduate and graduate econometrics courses. Along with standard estimation methods such as, for example, Method of Moments, Maximum Likelihood, and constrained optimisation, the book also includes a series of chapters examining more advanced research methods. These include discrete choice, discrete games, dynamic models on a finite and infinite horizon, and semi- and nonparametric methods. In closing, it discusses more advanced features that can be used to optimise use of MATLAB, including parallel computing.

Each chapter is structured around a number of worked examples, designed for the reader to tackle as they move through the book. Each chapter ends with a series of readings, questions, and extensions, designed to help the reader on their way to adapting the examples in the book to fit their own research questions.
List Of Figures
ix
List Of Tables
xi
Prologue xiii
Introduction xv
PART I FOUNDATIONS
1(38)
1 Entering the `Matrix Laboratory'
3(17)
1.1 OLS in MATLAB: `Hello, world!'
5(3)
1.2 The Beauty of Functions
8(5)
1.3 A Simple Utility Function
13(4)
1.4 Review and Exercises
17(3)
2 The Agent Optimizes
20(11)
2.1 Profit Maximization
20(3)
2.2 Utility Maximization
23(4)
2.3 Simulating Economic Models
27(3)
2.4 Review and Exercises
30(1)
3 The Economist Optimizes
31(8)
3.1 Maximum Likelihood
31(3)
3.2 Generalized Method of Moments
34(4)
3.3 Review and Exercises
38(1)
PART II DISCRETE CHOICE
39(42)
4 Discrete Multinomial Choice
41(21)
4.1 Binary Logit
42(6)
4.2 Multinomial Logit
48(4)
4.3 Multinomial Probit
52(8)
4.4 Review and Exercises
60(2)
5 Discrete Games
62(19)
5.1 A Simple Cournot Game
62(7)
5.2 A Discrete Bayesian Game
69(10)
5.3 Review and Exercises
79(2)
PART III DYNAMICS
81(42)
6 Dynamic Choice on a Finite Horizon
83(22)
6.1 Direct Attack
83(7)
6.2 Dynamic Programming
90(4)
6.3 Memoization
94(1)
6.4 Stochastic Dynamic Programming
95(4)
6.5 Estimating Finite Horizon Models
99(3)
6.6 Review and Exercises
102(3)
7 Dynamic Choice on an Infinite Horizon
105(18)
7.1 Value Function Iteration
106(7)
7.2 Policy Function Iteration
113(3)
7.3 Estimating Infinite Horizon Models
116(1)
7.4 Review and Exercises
117(6)
PART IV NONPARAMETRIC METHODS
123(46)
8 Nonparametric Regression
125(25)
8.1 Parametric Versus Nonparametric Approaches
125(3)
8.2 Kernel Regression
128(12)
8.3 Cross Validation
140(5)
8.4 Local Linear Regression
145(2)
8.5 Review and Exercises
147(3)
9 Semiparametric Methods
150(19)
9.1 Multivariate Kernel Regression
151(4)
9.2 Dimension Reduction
155(1)
9.3 Partially Linear Models
156(4)
9.4 Single Index Models
160(6)
9.5 Review and Exercises
166(3)
PART V SPEED
169
10 Speeding things Up...
171
10.1 Introduction
171(1)
10.2 Clever Coding
171
PART III DYNAMICS
81(42)
6 Dynamic Choice on a Finite Horizon
83(22)
6.1 Direct Attack
83(7)
6.2 Dynamic Programming
90(4)
6.3 Memoization
94(1)
6.4 Stochastic Dynamic Programming
95(4)
6.5 Estimating Finite Horizon Models
99(3)
6.6 Review and Exercises
102(3)
7 Dynamic Choice on an Infinite Horizon
105(18)
7.1 Value Function Iteration
106(7)
7.2 Policy Function Iteration
113(3)
7.3 Estimating Infinite Horizon Models
116(1)
7.4 Review and Exercises
117(6)
PART IV NONPARAMETRIC METHODS
123(46)
8 Nonparametric Regression
125(25)
8.1 Parametric Versus Nonparametric Approaches
125(3)
8.2 Kernel Regression
128(12)
8.3 Cross Validation
140(5)
8.4 Local Linear Regression
145(2)
8.5 Review and Exercises
147(3)
9 Semiparametric Methods
150(19)
9.1 Multivariate Kernel Regression
151(4)
9.2 Dimension Reduction
155(1)
9.3 Partially Linear Models
156(4)
9.4 Single Index Models
160(6)
9.5 Review and Exercises
166(3)
PART V SPEED
169(20)
10 Speeding things Up...
171(15)
10.1 Introduction
171(1)
10.2 Clever Coding
171(8)
10.3 Parallel Computing
179(2)
10.4 Parallel Computing with the GPU
181(4)
10.5 Other Tricks
185(1)
11 ... and Slowing Things Down
186(3)
Bibliography 189(4)
Index 193
Abi Adams is an Associate Professor of Economics at the University of Oxford, a Research Fellow at the Institute of Fiscal Studies and a Cowles Foundation Postdoctoral Fellow. Her research focuses on consumer choice, with a particular interest in nonparametric methods and revealed preference theory.





Damian Clarke is a DPhil (PhD) student in economics at the University of Oxford, with research focusing on maternal and child health and education, fertility and family size, and applied microeconometrics. Damian has worked for a range of international organisations and government bodies in Latin America and in West Africa.



Simon Quinn is an Associate Professor of Economics and a Deputy Director of the Centre for the Study of African Economies at the University of Oxford. Simon's research interests lie primarily in the study of firms and development.