Conditional Moment Estimation of Nonlinear Equation Systems With an Application to an Oligopoly Model of Cooperative R&D
Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdens...
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| Format: | eBook |
| Language: | English |
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Berlin, Heidelberg
Springer Berlin Heidelberg
2001, 2001
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| Edition: | 1st ed. 2001 |
| Series: | Lecture Notes in Economics and Mathematical Systems
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| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1 Introduction
- I: Estimation Theory
- 2 The Conditional Moment Approach to GMM Estimation
- 3 Asymptotic Properties of GMM Estimators
- 4 Computation of GMM Estimators
- 5 Asymptotic Efficiency Bounds
- 6 Overidentifying Restrictions
- 7 GMM Estimation with Optimal Weights
- 8 GMM Estimation with Optimal Instruments
- 9 Monte Carlo Investigation
- II: Application
- 10 Theory of Cooperative R&D
- 11 Empirical Evidence on Cooperative R&D
- 12 Conclusion
- References