A guide to econometrics
This is the perfect (and essential) supplement for all econometrics classes - from a rigorous first undergraduate course, to a first master's, to a PhD course. This book explains what is going on in textbooks full of proofs and formulas. It offers intuition, skepticism, insights, humor, and practical advice (dos and don'ts). It contains new chapters that cover instrumental variables and computational considerations. It includes additional information on GMM, nonparametrics, and an introduction …
Read More ↓Title Statements
- Full title :A guide to econometrics
Summary
This is the perfect (and essential) supplement for all econometrics classes - from a rigorous first undergraduate course, to a first master's, to a PhD course. This book explains what is going on in textbooks full of proofs and formulas. It offers intuition, skepticism, insights, humor, and practical advice (dos and don'ts). It contains new chapters that cover instrumental variables and computational considerations. It includes additional information on GMM, nonparametrics, and an introduction to wavelets
Read More ↓Edition Statements
- Publication Date:2008
- Edition:6. ed
Publication Statements
- Publisher(s):Blackwell
- Place of Publication:Oxford
- Language:eng
- Publication Date:2008
The Physical Object
- Description:585 s
Edition Identifiers
- ISBN:9781405182584, 140518258X, 1405182571, 9781405182577
- oclc:ocn475044761
- LC Classification:HB139
- Dewey Decimal:330.01 5195
Table of Contents
Preface -- Dedication -- 1. Introduction -- 1.1 What is Econometrics?. 1.2 The Disturbance Term -- 1.3 Estimates and Estimators -- 1.4 Good and Preferred Estimators -- General Notes -- Technical Notes -- 2. Criteria for Estimators -- 2.1 Introduction -- 2.2 Computational Cost -- 2.3 Least Squares -- 2.4 Highest R2. 2.5 Unbiasedness -- 2.6 Efficiency -- 2.7 Mean Square Error (MSE). 2.8 Asymptotic Properties -- 2.9 Maximum Likelihood -- 2.10 Monte Carlo Studies -- 2.11 Adding Up. General Notes -- Technical Notes -- 3. The Classical Linear Regression Model -- 3.1 Textbooks as Catalogs -- 3.2 The Five Assumptions -- 3.3 The OLS Estimator in the CLR Model -- General Notes -- Technical Notes -- 4. Interval Estimation and Hypothesis Testing -- 4.1 Introduction -- 4.2 Testing a Single Hypothesis: the t Test -- 4.3 Testing a Joint Hypothesis: the F Test -- 4.4 Interval Estimation for a Parameter Vector -- 4.5 LR, W, and LM Statistics -- 4.6 Bootstrapping -- General Notes -- Technical Notes -- 5. Specification -- 5.1 Introduction -- 5.2 Three Methodologies -- 5.3 General Principles for Specification -- 5.4 Misspecification Tests/Diagnostics -- 5.5 R2 Again -- General Notes -- Technical Note…
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