Guide to Modern Econometrics

Häftad, Engelska, 2017

Av Marno Verbeek, Marno (KU Leuven and Tilburg University) Verbeek

849 kr

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A Guide to Modern Econometrics, Fifth Edition has become established as a highly successful textbook. It serves as a guide to alternative techniques in econometrics with an emphasis on intuition and the practical implementation of these approaches. This fifth edition builds upon the success of its predecessors. The text has been carefully checked and updated, taking into account recent developments and insights. It includes new material on casual inference, the use and limitation of p-values, instrumental variables estimation and its implementation, regression discontinuity design, standardized coefficients, and the presentation of estimation results.

Produktinformation

Utgivningsdatum2017-09-22
Mått178 x 255 x 20 mm
Vikt854 g
FormatHäftad
SpråkEngelska
Antal sidor520
Upplaga5
FörlagJohn Wiley & Sons Inc
ISBN9781119472117

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Preface1 Introduction 1.1 About Econometrics1.2 The Structure of This Book1.3 Illustrations and Exercises2 An Introduction to Linear Regression 2.1 Ordinary Least Squares as an Algebraic Tool2.2 The Linear Regression Model2.3 Small Sample Properties of the OLS Estimator2.4 Goodness-of-fit2.5 Hypothesis Testing2.6 Asymptotic Properties of the OLS Estimator2.7 Illustration: The Capital Asset Pricing Model2.8 Multicollinearity2.9 Missing Data, Outliers and Influential Observations2.10 PredictionWrap-upExercises3 Interpreting and Comparing Regression Models 3.1 Interpreting the Linear Model3.2 Selecting the Set of Regressors3.3 Misspecifying the Functional Form3.4 Illustration: Explaining House Prices3.5 Illustration: Predicting Stock Index Returns3.6 Illustration: Explaining Individual WagesWrap-upExercises4 Heteroskedasticity and Autocorrelation 4.1 Consequences for the OLS Estimator4.2 Deriving an Alternative Estimator4.3 Heteroskedasticity4.4 Testing for Heteroskedasticity4.5 Illustration: Explaining Labour Demand4.6 Autocorrelation4.7 Testing for First-order Autocorrelation4.8 Illustration: The Demand for Ice Cream4.9 Alternative Autocorrelation Patterns4.10 What to do When you Find Autocorrelation?4.11 Illustration: Risk Premia in Foreign Exchange MarketsWrap-upExercises5 Endogenous Regressors, Instrumental Variables and GMM 5.1 A Review of the Properties of the OLS Estimator5.2 Cases Where the OLS Estimator Cannot be Saved5.3 The Instrumental Variables Estimator5.4 Illustration: Estimating the Returns to Schooling5.5 Alternative Approaches to Estimate Causal Effects5.6 The Generalized Instrumental Variables Estimator5.7 Institutions and Economic Development5.8 The Generalized Method of Moments5.9 Illustration: Estimating Intertemporal Asset Pricing ModelsWrap-upExercises6 Maximum Likelihood Estimation and Specification Tests 6.1 An Introduction to Maximum Likelihood6.2 Specification Tests6.3 Tests in the Normal Linear Regression Model6.4 Quasi-maximum Likelihood and Moment Conditions TestsWrap-upExercises7 Models with Limited Dependent Variables 7.1 Binary Choice Models7.2 Multiresponse Models7.3 Models for Count Data7.4 Tobit Models7.5 Extensions of Tobit Models7.6 Sample Selection Bias7.7 Estimating Treatment Effects7.7.1 Regression-based Estimators7.8 Duration ModelsWrap-upExercises8 Univariate Time Series Models 8.1 Introduction8.2 General ARMA Processes8.3 Stationarity and Unit Roots8.4 Testing for Unit Roots8.5 Illustration: Long-run Purchasing Power Parity (Part 1)8.6 Estimation of ARMA Models8.7 Choosing a Model8.8 Illustration: The Persistence of Inflation8.9 Forecasting with ARMA Models8.10 Illustration: The Expectations Theory of the Term Structure8.11 Autoregressive Conditional Heteroskedasticity8.12 What about Multivariate Models?Wrap-upExercises9 Multivariate Time Series Models 9.1 Dynamic Models with Stationary Variables9.2 Models with Nonstationary Variables9.3 Illustration: Long-run Purchasing Power Parity (Part 2)9.4 Vector Autoregressive Models9.5 Cointegration: the Multivariate Case9.6 Illustration: Money Demand and InflationWrap-upExercises10 Models Based on Panel Data 10.1 Introduction to Panel Data Modelling10.2 The Static Linear Model10.3 Illustration: Explaining Individual Wages10.4 Dynamic Linear Models10.5 Illustration: Explaining Capital Structure10.6 Panel Time Series10.7 Models with Limited Dependent Variables10.8 Incomplete Panels and Selection Bias10.9 Pseudo Panels and Repeated Cross-sectionsWrap-upA Vectors and MatricesA.1 TerminologyA.2 Matrix ManipulationsA.3 Properties of Matrices and VectorsA.4 Inverse MatricesA.5 Idempotent MatricesA.6 Eigenvalues and EigenvectorsA.7 DifferentiationA.8 Some Least Squares ManipulationsB Statistical and Distribution TheoryB.1 Discrete Random VariablesB.2 Continuous Random VariablesB.3 Expectations and MomentsB.4 Multivariate DistributionsB.5 Conditional DistributionsB.6 The Normal DistributionB.7 Related DistributionsBibliographIndex