Guide to Modern Econometrics

Name: Guide to Modern Econometrics
Price: 8.61 USD
Availability: InStock
ISBN: 9780471899822

ISBN-10: 0471899828

ISBN-13: 9780471899822

Edition: 2000

Authors: Jos Verbeek, Marno Verbeek

List price: $75.00

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Description:

Marno Verbeek2s intermediate level textbook explores a wide range of topics in modern econometrics and focuses on what is important for doing and understanding empirical work. A wide range of new topics are covered including time series analysis, limited dependent variables, cointegration and panel data analysis. FEATURES Concentrates on the intuition behind various techniques and their practical relevance rather than the formulae End of chapter exercises review key concepts in light of empircal examples discussed in the chapter Examples are drawn from a wide variety of fields including labour economics, environmental economics, finance, international economics and…

Book details

List price: $75.00
Copyright year: 2000
Publisher: John Wiley & Sons, Incorporated
Publication date: 6/23/2000
Binding: Paperback
Pages: 400
Size: 6.67" wide x 9.78" long x 0.78" tall
Weight: 1.518
Language: English



Preface


Introduction


About Econometrics


The Structure of this Book


Illustrations and Exercises


An Introduction to Linear Regression


Ordinary Least Squares as An Algebraic Tool


Ordinary Least Squares


Simple Linear Regression


Example: Individual Wages


Matrix Notation


The Linear Regression Model


Small Sample Properties of the OLS Estimator


The Gauss--Markov Assumptions


Properties of the OLS Estimator


Example: Individual Wages (Continued)


Goodness-of-fit


Hypothesis Testing


A Simple t-test


Example: Individual Wages (Continued)


Testing One Linear Restriction


A Joint Test of Significance of Regression Coefficients


Example: Individual Wages (Continued)


The General Case


Size, Power and p-values


Asymptotic Properties of the OLS Estimator


Consistency


Asymptotic Normality


Illustration: the Capital Asset Pricing Model


The CAPM as a Regression Model


Estimating and Testing the CAPM


Multicollinearity


Example: Individual Wages (Continued)


Prediction


Exercises


Interpreting and Comparing Regression Models


Interpreting the Linear Model


Selecting the Set of Regressors


Misspecifying the Set of Regressors


Selecting Regressors


Comparing Non-nested Models


Misspecifying the Functional Form


Nonlinear Models


Testing the Functional Form


Illustration: Explaining House Prices


Illustration: Explaining Individual Wages


Linear Models


Loglinear Models


The Effects of Gender


Some Words of warning


Exercises


Heteroskedasticity and Autocorrelation


Consequences for the OLS Estimator


Deriving an Alternative Estimator


Heteroskedasticity


Introduction


Estimator Properties and Hypothesis Testing


When the Variances are Unknown


Heteroskedasticity-consistent Standard Errors for OLS


A Model with Two Unknown Variances


Multiplicative Heteroskedasticity


Testing for Heteroskedasticity


Testing Equality of Two Unknown Variances


Testing for Multiplicative Heteroskedasticity


The Breusch--Pagan Test


The White Test


Which Test?


Illustration: Explaining Labour Demand


Autocorrelation


First Order Autocorrelation


Unknown [rho]


Testing for First Order Autocorrelation


Asymptotic Tests


The Durbin--Watson Test


Illustration: The Demand for Ice Cream


Alternative Autocorrelation Patterns


Higher Order Autocorrelation


Moving Average Errors


What to do When you Find Autocorrelation?


Misspecification


Heteroskedasticity-and-autocorrelation-consistent Standard Errors for OLS


Illustration: Risk Premia in Foreign Exchange Markets


Notation


Tests for Risk Premia in the One-month Market


Tests for Risk Premia using Overlapping Samples


Exercises


Endogeneity, Instrumental Variables and GMM


A Review of the Properties of the OLS Estimator


Cases Where the OLS Estimator Cannot be Saved


Autocorrelation with a Lagged Dependent Variable


An Example with Measurement Error


Simultaneity: the Keynesian Model


The Instrumental Variables Estimator


Estimation with a Single Endogenous Regressor and a Single Instrument


Back to the Keynesian Model


Back to the Measurement Error Problem


Multiple Endogenous Regressors


Illustration: Estimating the Returns to Schooling


The Generalized Instrumental Variables Estimator


Multiple Endogenous Regressors with an Arbitrary Number of Instruments


Two-stage Least Squares and the Keynesian Model Again


The Generalized Method of Moments


Example


The Generalized Method of Moments


Some Simple Examples


Illustration: Estimating Intertemporal Asset Pricing Models


Concluding Remarks


Exercises


Maximum Likelihood Estimation and Specification Tests


An Introduction to Maximum Likelihood


Some Examples


General Properties


An Example (Continued)


The Normal Linear Regression Model


Specification Tests


Three Test Principles


Lagrange Multiplier Tests


An Example (Continued)


Tests in the Normal Linear Regression Model


Testing for Omitted Variables


Testing for Heteroskedasticity


Testing for Autocorrelation


Quasi-maximum Likelihood and Moment Conditions Tests


Quasi-maximum Likelihood


Conditional Moment Tests


Testing for Normality


Exercises


Models with Limited Dependent Variables


Binary Choice Models


Using Linear Regession?


Introducing Binary Choice Models


An Underlying Latent Model


Estimation


Goodness-of-fit


Illustration: the Impact of Unemployment Benefits on Recipiency


Specification Tests in Binary Choice Models


Relaxing Some Assumptions in Binary Choice Models


Multi-response Models


Ordered Response Models


About Normalization


Illustration: Willingness to Pay for Natural Areas


Multinomial Models


Tobit Models


The Standard Tobit Model


Estimation


Illustration: Expenditures on Alcohol and Tobacco (Part 1)


Specification Tests in the Tobit Model


Extensions of Tobit Models


The Tobit II Model


Estimation


Further Extensions


Illustration: Expenditures on Alcohol and Tobacco (Part 2)


Sample Selection Bias


The Nature of the Selection Problem


Semi-parametric Estimation of the Sample Selection Model


Exercises


Univariate Time Series Models


Introduction


Some Examples


Stationarity and the Autocorrelation Function


General ARMA Processes


Formulating ARMA Processes


Invertibility of Lag Polynomials


Common Roots


Stationarity and Unit Roots


Testing for Unit Roots


Testing for Unit Roots in a First Order Autoregressive Model


Testing for Unit Roots in Higher Order Autoregressive Models


Illustration: Quarterly Disposable Income


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


Estimation of ARMA Models


Least Squares


Maximum Likelihood


Choosing a Model


The Autocorrelation Function


The Partial Autocorrelation Function


Diagnostic Checking


Criteria for Model Selection


Illustration: Modelling Quarterly Disposable Income


Predicting with ARMA Models


The Optimal Predictor


Prediction Accuracy


Illustration: The Expectations Theory of the Term Structure


Autoregressive Conditional Heteroskedasticity


ARCH and GARCH Models


Estimation and Prediction


Illustration: Volatility in Daily Exchange Rates


What about Multivariate Models?


Exercises


Multivariate Time Series Models


Dynamic Models with Stationary Variables


Models with Nonstationary Variables


Spurious Regressions


Cointegration


Cointegration and Error-correction Mechanisms


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


Vector Autoregressive Models


Cointegration: The Multivariate Case


Cointegration in a VAR


Example: Cointegration in a Bivariate VAR


Testing for Cointegration


Illustration: Long-run Purchasing Power Parity (Part 3)


Illustration: Money Demand and Inflation


Concluding Remarks


Exercises


Models Based on Panel Data


Advantages of Panel Data


Efficiency of Parameter Estimators


Identification of Parameters


The Static Linear Model


The Fixed Effects Model


The Random Effects Model


Fixed Effects or Random Effects?


Goodness-of-fit


Alternative Instrumental Variables Estimators


Alternative Error Structures


Testing for Heteroskedasticity and Autocorrelation


Illustration: Explaining Individual Wages


Dynamic Linear Models


An Autoregressive Panel Data Model


Dynamic Models with Exogenous Variables


Unit Roots and Cointegration


Illustration: Wage Elasticities of Labour Demand


Models with Limited Dependent Variables


Binary Choice Models


The Fixed Effects Logit Model


The Random Effects Probit Model


Tobit Models


Dynamics and the Problem of Initial Conditions


Incomplete Panels and Selection Bias


Estimation with Randomly Missing Data


Selection Bias and Some Simple Tests


Estimation with Nonrandomly Missing Data


Exercises


Vectors and Matrices


Terminology


Matrix Manipulations


Properties of Matrices and Vectors


Inverse Matrices


Idempotent Matrices


Eigenvalues and Eigenvectors


Differentiation


Some Least Squares Manipulations


Statistical and Distribution Theory


Discrete Random Variables


Continuous Random Variables


Expectations and Moments


Multivariate Distributions


Conditional Distributions


The Normal Distribution


Related Distributions


Bibliography


Index