Introduction to EconometricsIntroduction to Econometrics has been significantly revised to include new developments in the field. The previous editions of this text were renowned for Maddala's clear exposition and the presentation of concepts in an easily accessible manner. Features: * New chapters have been included on panel data analysis, large sample inference and small sample inference * Chapter 14 Unit Roots and Cointegration has been rewritten to reflect recent developments in the Dickey-Fuller (DF), the Augmented Dickey-Fuller (ADF) tests and the Johansen procedure * A selection of data sets and the instructor's manual for the book can be found on our web site Comments on the previous edition: 'Maddala is an outstanding econometrician who has a deep understaning of the use and potential abuse of econometrics...' 'The strengths of the Maddala book are its simplicity, its accessibility and the large number of examples the book contains...' 'The second edition is well written and the chapters are focused and easy to follow from beginning to end. Maddala has an oustanding grasp of the issues, and the level of mathematics and statistics is appropriate as well.' |
From inside the book
Results 1-3 of 52
Page 61
... variable ( d ) Dependent variable ( e ) Effect variable ( f ) Endogenous variable ( g ) Target variable 2. Forecast the value of y for a given set of x's . Explanatory variables Independent variables Causal variables Exogenous variables ...
... variable ( d ) Dependent variable ( e ) Effect variable ( f ) Endogenous variable ( g ) Target variable 2. Forecast the value of y for a given set of x's . Explanatory variables Independent variables Causal variables Exogenous variables ...
Page 293
... dependent variable = 15,679 SD of the dependent variable = 5093 ( e ) The variable F is the number of dissertations supervised since 1964. B is the number of books published . How do you explain the high coefficient for F relative to ...
... dependent variable = 15,679 SD of the dependent variable = 5093 ( e ) The variable F is the number of dissertations supervised since 1964. B is the number of books published . How do you explain the high coefficient for F relative to ...
Page 338
... dependent variable was log earnings . The results show how the OLS estimates are biased . In this particular case they are all biased toward zero . Summary 1. In this chapter we discussed : ( a ) Dummy explanatory variables . ( b ) ...
... dependent variable was log earnings . The results show how the OLS estimates are biased . In this particular case they are all biased toward zero . Summary 1. In this chapter we discussed : ( a ) Dummy explanatory variables . ( b ) ...
Contents
INTRODUCTION AND THE LINEAR REGRESSION MODEL | 1 |
1 | 9 |
of Hypotheses | 28 |
Copyright | |
21 other sections not shown
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Common terms and phrases
2SLS adaptive expectations analysis assumptions asymptotic autocorrelation autoregressive B₁ B₂ bootstrap Box-Jenkins CALIFORNIA/SANTA CRUZ Chapter cointegration compute confidence interval consider constant term CRUZ The University data sets defined demand function denote dependent variable dummy variables Econometrica Econometrics economic endogenous error term exogenous variables explanatory variables F-test H₁ Hence heteroskedasticity instrumental variable least squares estimators logit Maddala matrix method multicollinearity multiple regression normal distribution Note null hypothesis observations obtained OLS estimation omitted variables P₁ parameters plim probit models problem procedure rational expectations regression equation regression model regressors relationship residual sum root tests sample serial correlation significance level standard errors studentized residuals suggested sum of squares Suppose t-ratios Table test statistic time-series u₁ uncorrelated unit root unit root tests University Library UNIVERSITY UNIVERSITY OF CALIFORNIA/SANTA values vectors x₁ x²-distribution y₁ z₁ zero