Description

Book Synopsis


Table of Contents

Preface

1 Introduction

1.1 About Econometrics

1.2 The Structure of This Book

1.3 Illustrations and Exercises

2 An Introduction to Linear Regression

2.1 Ordinary Least Squares as an Algebraic Tool

2.2 The Linear Regression Model

2.3 Small Sample Properties of the OLS Estimator

2.4 Goodness-of-fit

2.5 Hypothesis Testing

2.6 Asymptotic Properties of the OLS Estimator

2.7 Illustration: The Capital Asset Pricing Model

2.8 Multicollinearity

2.9 Missing Data, Outliers and Influential Observations

2.10 Prediction

Wrap-up

Exercises

3 Interpreting and Comparing Regression Models

3.1 Interpreting the Linear Model

3.2 Selecting the Set of Regressors

3.3 Misspecifying the Functional Form

3.4 Illustration: Explaining House Prices

3.5 Illustration: Predicting Stock Index Returns

3.6 Illustration: Explaining Individual Wages

Wrap-up

Exercises

4 Heteroskedasticity and Autocorrelation

4.1 Consequences for the OLS Estimator

4.2 Deriving an Alternative Estimator

4.3 Heteroskedasticity

4.4 Testing for Heteroskedasticity

4.5 Illustration: Explaining Labour Demand

4.6 Autocorrelation

4.7 Testing for First-order Autocorrelation

4.8 Illustration: The Demand for Ice Cream

4.9 Alternative Autocorrelation Patterns

4.10 What to do When you Find Autocorrelation?

4.11 Illustration: Risk Premia in Foreign Exchange Markets

Wrap-up

Exercises

5 Endogenous Regressors, Instrumental Variables and GMM

5.1 A Review of the Properties of the OLS Estimator

5.2 Cases Where the OLS Estimator Cannot be Saved

5.3 The Instrumental Variables Estimator

5.4 Illustration: Estimating the Returns to Schooling

5.5 Alternative Approaches to Estimate Causal Effects

5.6 The Generalized Instrumental Variables Estimator

5.7 Institutions and Economic Development

5.8 The Generalized Method of Moments

5.9 Illustration: Estimating Intertemporal Asset Pricing Models

Wrap-up

Exercises

6 Maximum Likelihood Estimation and Specification Tests

6.1 An Introduction to Maximum Likelihood

6.2 Specification Tests

6.3 Tests in the Normal Linear Regression Model

6.4 Quasi-maximum Likelihood and Moment Conditions Tests

Wrap-up

Exercises

7 Models with Limited Dependent Variables

7.1 Binary Choice Models

7.2 Multiresponse Models

7.3 Models for Count Data

7.4 Tobit Models

7.5 Extensions of Tobit Models

7.6 Sample Selection Bias

7.7 Estimating Treatment Effects

7.7.1 Regression-based Estimators

7.8 Duration Models

Wrap-up

Exercises

8 Univariate Time Series Models

8.1 Introduction

8.2 General ARMA Processes

8.3 Stationarity and Unit Roots

8.4 Testing for Unit Roots

8.5 Illustration: Long-run Purchasing Power Parity (Part 1)

8.6 Estimation of ARMA Models

8.7 Choosing a Model

8.8 Illustration: The Persistence of Inflation

8.9 Forecasting with ARMA Models

8.10 Illustration: The Expectations Theory of the Term Structure

8.11 Autoregressive Conditional Heteroskedasticity

8.12 What about Multivariate Models?

Wrap-up

Exercises

9 Multivariate Time Series Models

9.1 Dynamic Models with Stationary Variables

9.2 Models with Nonstationary Variables

9.3 Illustration: Long-run Purchasing Power Parity (Part 2)

9.4 Vector Autoregressive Models

9.5 Cointegration: the Multivariate Case

9.6 Illustration: Money Demand and Inflation

Wrap-up

Exercises

10 Models Based on Panel Data

10.1 Introduction to Panel Data Modelling

10.2 The Static Linear Model

10.3 Illustration: Explaining Individual Wages

10.4 Dynamic Linear Models

10.5 Illustration: Explaining Capital Structure

10.6 Panel Time Series

10.7 Models with Limited Dependent Variables

10.8 Incomplete Panels and Selection Bias

10.9 Pseudo Panels and Repeated Cross-sections

Wrap-up

A Vectors and Matrices

A.1 Terminology

A.2 Matrix Manipulations

A.3 Properties of Matrices and Vectors

A.4 Inverse Matrices

A.5 Idempotent Matrices

A.6 Eigenvalues and Eigenvectors

A.7 Differentiation

A.8 Some Least Squares Manipulations

B Statistical and Distribution Theory

B.1 Discrete Random Variables

B.2 Continuous Random Variables

B.3 Expectations and Moments

B.4 Multivariate Distributions

B.5 Conditional Distributions

B.6 The Normal Distribution

B.7 Related Distributions

Bibliograph

Index

A Guide to Modern Econometrics

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    A Paperback / softback by Marno Verbeek

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      View other formats and editions of A Guide to Modern Econometrics by Marno Verbeek

      Publisher: John Wiley & Sons Inc
      Publication Date: 22/09/2017
      ISBN13: 9781119472117, 978-1119472117
      ISBN10: 1119472113

      Description

      Book Synopsis


      Table of Contents

      Preface

      1 Introduction

      1.1 About Econometrics

      1.2 The Structure of This Book

      1.3 Illustrations and Exercises

      2 An Introduction to Linear Regression

      2.1 Ordinary Least Squares as an Algebraic Tool

      2.2 The Linear Regression Model

      2.3 Small Sample Properties of the OLS Estimator

      2.4 Goodness-of-fit

      2.5 Hypothesis Testing

      2.6 Asymptotic Properties of the OLS Estimator

      2.7 Illustration: The Capital Asset Pricing Model

      2.8 Multicollinearity

      2.9 Missing Data, Outliers and Influential Observations

      2.10 Prediction

      Wrap-up

      Exercises

      3 Interpreting and Comparing Regression Models

      3.1 Interpreting the Linear Model

      3.2 Selecting the Set of Regressors

      3.3 Misspecifying the Functional Form

      3.4 Illustration: Explaining House Prices

      3.5 Illustration: Predicting Stock Index Returns

      3.6 Illustration: Explaining Individual Wages

      Wrap-up

      Exercises

      4 Heteroskedasticity and Autocorrelation

      4.1 Consequences for the OLS Estimator

      4.2 Deriving an Alternative Estimator

      4.3 Heteroskedasticity

      4.4 Testing for Heteroskedasticity

      4.5 Illustration: Explaining Labour Demand

      4.6 Autocorrelation

      4.7 Testing for First-order Autocorrelation

      4.8 Illustration: The Demand for Ice Cream

      4.9 Alternative Autocorrelation Patterns

      4.10 What to do When you Find Autocorrelation?

      4.11 Illustration: Risk Premia in Foreign Exchange Markets

      Wrap-up

      Exercises

      5 Endogenous Regressors, Instrumental Variables and GMM

      5.1 A Review of the Properties of the OLS Estimator

      5.2 Cases Where the OLS Estimator Cannot be Saved

      5.3 The Instrumental Variables Estimator

      5.4 Illustration: Estimating the Returns to Schooling

      5.5 Alternative Approaches to Estimate Causal Effects

      5.6 The Generalized Instrumental Variables Estimator

      5.7 Institutions and Economic Development

      5.8 The Generalized Method of Moments

      5.9 Illustration: Estimating Intertemporal Asset Pricing Models

      Wrap-up

      Exercises

      6 Maximum Likelihood Estimation and Specification Tests

      6.1 An Introduction to Maximum Likelihood

      6.2 Specification Tests

      6.3 Tests in the Normal Linear Regression Model

      6.4 Quasi-maximum Likelihood and Moment Conditions Tests

      Wrap-up

      Exercises

      7 Models with Limited Dependent Variables

      7.1 Binary Choice Models

      7.2 Multiresponse Models

      7.3 Models for Count Data

      7.4 Tobit Models

      7.5 Extensions of Tobit Models

      7.6 Sample Selection Bias

      7.7 Estimating Treatment Effects

      7.7.1 Regression-based Estimators

      7.8 Duration Models

      Wrap-up

      Exercises

      8 Univariate Time Series Models

      8.1 Introduction

      8.2 General ARMA Processes

      8.3 Stationarity and Unit Roots

      8.4 Testing for Unit Roots

      8.5 Illustration: Long-run Purchasing Power Parity (Part 1)

      8.6 Estimation of ARMA Models

      8.7 Choosing a Model

      8.8 Illustration: The Persistence of Inflation

      8.9 Forecasting with ARMA Models

      8.10 Illustration: The Expectations Theory of the Term Structure

      8.11 Autoregressive Conditional Heteroskedasticity

      8.12 What about Multivariate Models?

      Wrap-up

      Exercises

      9 Multivariate Time Series Models

      9.1 Dynamic Models with Stationary Variables

      9.2 Models with Nonstationary Variables

      9.3 Illustration: Long-run Purchasing Power Parity (Part 2)

      9.4 Vector Autoregressive Models

      9.5 Cointegration: the Multivariate Case

      9.6 Illustration: Money Demand and Inflation

      Wrap-up

      Exercises

      10 Models Based on Panel Data

      10.1 Introduction to Panel Data Modelling

      10.2 The Static Linear Model

      10.3 Illustration: Explaining Individual Wages

      10.4 Dynamic Linear Models

      10.5 Illustration: Explaining Capital Structure

      10.6 Panel Time Series

      10.7 Models with Limited Dependent Variables

      10.8 Incomplete Panels and Selection Bias

      10.9 Pseudo Panels and Repeated Cross-sections

      Wrap-up

      A Vectors and Matrices

      A.1 Terminology

      A.2 Matrix Manipulations

      A.3 Properties of Matrices and Vectors

      A.4 Inverse Matrices

      A.5 Idempotent Matrices

      A.6 Eigenvalues and Eigenvectors

      A.7 Differentiation

      A.8 Some Least Squares Manipulations

      B Statistical and Distribution Theory

      B.1 Discrete Random Variables

      B.2 Continuous Random Variables

      B.3 Expectations and Moments

      B.4 Multivariate Distributions

      B.5 Conditional Distributions

      B.6 The Normal Distribution

      B.7 Related Distributions

      Bibliograph

      Index

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