Using EViews Vox Principles of Econometrics, Third Edition

Transcription

1 Using EViews Vox Principles of Econometrics, Third Edition WILLIAM E. GRIFFITHS University of Melbourne R. CARTER HILL Louisiana State University GUAY С LIM University of Melbourne JOHN WILEY & SONS, INC

2 CONTENTS CHAPTER 1 Introduction to EViews Using EViews for Principles of Econometrics Installing EViews 6 student version Checking for updates Obtaining data workfiles Starting EViews The Help System EViews help topics The READ ME file Quick help reference EViews Illustrated Users guides and command reference Using a Workfile Setting the default path Opening a workfile Examining a single series Changing the sample Copying a graph into a document Examining Several Series Summary statistics for several series Freezing a result Copying and pasting a table Plotting two series A scatter diagram Using the Quick Menu Changing the sample Generating a new series Plotting using Quick/Graph Saving your workfile Opening an empty group Quick/Series statistics Quick/Group statistics Using EViews Functions Descriptive statistics functions Using a storage vector Basic arithmetic operations Basic math functions CHAPTER 2 The Simple Linear Regression Model Open the Workfile Examine the data Checking summary statistics Saving a group Plotting the Food Expenditure Data Enhancing the graph Saving the graph in the workfile Copying the graph to a document Saving a workfile Estimating a Simple Regression Viewing equation representations Computing the income elasticity Plotting a Simple Regression Plotting the Least Squares Residuals Using View options Using Resids Using Quick/Graph Saving the residuals Estimating the Variance of the Error Term Coefficient Standard Errors Prediction Using EViews Using direct calculation Forecasting CHAPTER 3 Interval Estimation and Hypothesis Testing Interval Estimation Constructing the interval estimate Using a coefficient vector Right-tail Tests Test of significance Test of an economic hypothesis Left-tail Tests Test of significance Test of an economic hypothesis Two-tail Tests Test of significance Test of an economic hypothesis CHAPTER 4 Prediction, Goodness-of-Fit and Modeling Issues Prediction in the Food Expenditure Model A simple prediction procedure 71 ix

3 4.1.2 Prediction using EViews Measuring Goodness-of-Fit Calculating R Correlation analysis Modeling Issues The effects of scaling the data The log-linear model The linear-log model The log-log model Are the regression errors normally distributed? Another example The Log-Linear Model Prediction in the log-linear model Alternative commands in the loglinear model Generalized R CHAPTER 5 The Multiple Regression Model The Workfile: Some Preliminaries Naming the page Creating objects: a group Estimating a Multiple Regression Model Using the Quick menu Using the Object menu Forecasting from a Multiple Regression Model A simple forecasting procedure Using the forecast option Interval Estimation The least squares covariance matrix Computing interval estimates Hypothesis Testing Two-tail tests of significance A one-tail test of significance Testing nonzero values Saving Commands CHAPTER 6 Further Inference in the Multiple Regression Model F and Chi-Square Tests Testing significance: a coefficient Testing significance: the model Testing in an Extended Model Estimating the model Testing: a joint Я 0, 2 coefficents Testing: a single Я 0, 2 coefficents Testing: a joint Я 0, 4 coefficents Including Nonsample Information The RESET Test The short way The long way Viewing the Correlation Matrix Collinearity: An exercise CHAPTER 7 Nonlinear Relationships Polynomials Dummy Variables Creating dummy variables Interacting Dummy Variables Dummy Variables with Several Categories Testing the Equivalence of Two Regressions Interactions Between Continuous Variables Log-Linear Models CHAPTER 8 Heteroskedasticity Examining Residuals Plot against observation number Plot against an explanatory variable Plot of least squares line Heteroskedasticity-Consistent Standard Errors Weighted Least Squares A short way A long way Estimating a Variance Function Variance function estimates Generalized least-squares A Heteroskedastic Partition Least-squares estimates: one equation Least-squares estimates: two equations 160 x

4 8.5.3 Generalized least-squares estimates The Goldfeld-Quandt Test The wage equation The food expenditure equation Testing the Variance Function The Breusch-Pagan test The White test CHAPTER 9 Dynamic Models, Autocorrelation, and Forecasting Least-Squares Residuals: Sugarcane Example Correlation between e, and <?,_, Newey-West Standard Errors Estimating an AR(1) Error Model A short way A long way A more general model Testing the AR(1) error restriction Testing for Autocorrelation Residual correlogram Lagrange multiplier (LM) test Durbin-Watson test Autoregressive Models Workfile structure for time series data Estimating an AR model Forecasting with an AR model Finite Distributed Lags Autoregressive Distributed Lag Models Graphing the lag weights CHAPTER 10 Random Regressors and Moment Based Estimation The Inconsistency of the Least Squares Estimator Instrumental Variables Estimation The Hausman Test Test for Weak Instruments Test Instrument Validity A Wage Equation CHAPTER 11 Simultaneous Equations Models Examining the Data Estimating the Reduced Form TSLS Estimation of an Equation TSLS Estimation of a System of Equations Supply and Demand at Fulton Fish Market CHAPTER 12 Nonstationary Time Series Data and Cointegration Stationary and Nonstationary Variables Spurious Regressions Unit Root Tests for Stationarity Cointegration CHAPTER 13 VEC and VAR Models: An Introduction to Macroeconometrics VEC and VAR Models Estimating a VEC Model Estimating a VAR Model Impulse Responses and Variance Decompositions CHAPTER 14 Time-Varying Volatility and ARCH Models: An Introduction to Financial Econometrics Time-Varying Volatility Testing for ARCH Effects Estimating an ARCH Model Generalized ARCH Asymmetric ARCH GARCH in Mean Model XI

5 CHAPTER 15 Panel Data Models 15.1 Granfeld Data: Two Equations Separate least squares estimation Stacking the data Least squares estimation with dummy variables Introducing the pool object Seemingly unrelated regressions Testing contemporaneous correlation Testing cross-equation restrictions 15.2 Granfeld Data: Ten Firms Structuring the workfile Fixed effects using dummy variables Testing the effects Pooled least squares The fixed effects estimator 15.3 NLS Panel Data Fixed effects estimation Random effects estimation The Hausman test CHAPTER 16 Qualitative and Limited Dependent Variables 16.1 Models with Binary Dependent Variables Examine the data The linear probability model The probit model Predicting probabilities Marginal effects in the probit model 16.2 Ordered Choice Models Ordered probit predictions Ordered probit marginal effects Models for Count Data Examine the data Estimating a Poisson model Prediction with a Poisson model Poisson model marginal effects Limited Dependent Variables Least squares estimation Tobit estimation and interpretation The Heckit selection bias model CHAPTER 17 Importing and Exportir 'g Data Obtaining Data from the Internet Importing An Excel Data File Date Conventions Importing a Text (Ascii) Data File Entering Data Manually Exporting Data from EViews APPENDIX A Review of Math Essentials A. 1 Mathematical Operations A.2 Logarithms and Exponentials A.3 Graphing Functions APPENDIX В Statistical Distribution Functions B.l Cumulative Normal Probabilities 327 B.2 Using Vectors 329 B.3 Computing Normal Distribution Percentiles 331 B.4 Plotting Some Normal Distributions 332 B.5 Plotting the/-distribution 335 B.6 Plotting the Chi-square Distribution 335 B.7 Plotting the F Distribution 336 B.8 Probability Calculations for the t, F and Chi-square Appendix С Review of Statistical Inference 338 C.l A Histogram 338 C.2 Summary Statistics 340 C.2.1 The sample mean 340 C.2.2 Estimating higher moments 341 C.2.3 Create a table 342 C.2.4 Using the estimates 345 C.3 Interval Estimation 346 xii

6 C.4 Hypothesis Tests About the Population Mean 348 C.4.1 One-tail test using the hip data 348 C.4.2 Two-tail test using the hip data 348 C.4.3 Testing the normality of the population INDEX 351