Econometric modeling and inference / Jean-Pierre Florens, Vêlayoudom Marimoutou, Anne Péguin-Feissolle ; translated by, Josef Perktold and Marine Carrasco ; foreword by James J. Heckman.
Material type: TextLanguage: English Original language: French Series: Themes in modern econometricsPublisher: Cambridge : Cambridge University Press, 2007Description: 1 online resource (xxi, 496 pages) : digital, PDF file(s)Content type:- text
- computer
- online resource
- 9780511805592 (ebook)
- Econometric Modeling & Inference
- Économétrie. English
- 330.01/5195 22
- HB141 .F5913 2007
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained by its relevance in structural econometrics and its preeminent position in econometrics overall. Split into four parts, Part I explains general methods. Part II studies statistical models that are best suited for microeconomic data. Part III deals with dynamic models that are designed for macroeconomic and financial applications. In Part IV the authors synthesize a set of problems that are specific to statistical methods in structural econometrics, namely identification and over-identification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises. Nobel Laureate James A. Heckman offers a foreword to the work.
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