Gujarati’s Basic Econometrics provides an elementary but comprehensive introduction to econometrics without resorting to matrix algebra, calculus, or statistics beyond the elementary level. Because of the way the book is organized, it may be used at a variety of levels of rigor. For example, if matrix algebra is used, theoretical exercises may be omitted. A CD of data sets is provided with the text.
Table of Contents
Preface Introduction Part I Single-Equation Regression Models Chapter 1 The Nature of Regression Analysis Chapter 2 Two-Variable Regression Analysis: Some Basic Ideas Chapter 3 Two-Variable Regression Model: The Problem of Estimation Chapter 4 Classical Normal Linear Regression Model (CNLRM) Chapter 5 Two-Variable Regression: Estimation and Hypothesis Testing Chapter 6 Extensions of the Two-Variable Linear Regression Model Chapter 7 Multiple Regression Analysis: The Problem of Estimation Chapter 8 Multiple Regression Analysis: The Problem of Inference Chapter 9 Dummy Variable Regression Models Part II Relaxing the Assumptions of the Classical Model Chapter 10 Multicollinearity: What Happens if the Regressors Are Correlated Chapter 11 Heteroscedasticity: What Happens if the Error Variance Is Nonconstant? Chapter 12 Autocorrelation: What Happens if the Error Terms Are Correlated Chapter 13 Econometric Modeling: Model Specification and Diagnostic Testing Part III Topics in Econometrics Chapter 14 Nonlinear Regression Models Chapter 15 Qualitative Response Regression Models Chapter 16 Panel Data Regression Models Chapter 17 Dynamic Econometric Models: Autoregressive and Distributed-Lag Models Part IV Simultaneous-Equation Models Chapter 18 Simultaneous-Equation Models Chapter 19 The Identification Problem Chapter 20 Simultaneous-Equation Methods Part V Time Series Econometrics Chapter 21 Time Series Econometrics: Some Basic Concepts Chapter 22 Time Series Econometrics: Forecasting Selected Bibliography DOWNLOAD |
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