Economic Modeling And Inference
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Economic Modeling and Inference
Author: Bent Jesper Christensen
language: en
Publisher: Princeton University Press
Release Date: 2021-07-13
Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques. Covers identification and estimation of dynamic programming models Treats sources of error--measurement error, random utility, and imperfect control Features financial applications including asset pricing, option pricing, and optimal hedging Describes labor applications including job search, equilibrium search, and retirement Illustrates the wide applicability of the approach using micro, macro, and marketing examples
Causal Inference in Economic Models
Author: Stephen F. LeRoy
language: en
Publisher: Cambridge Scholars Publishing
Release Date: 2020-10-12
There exist applications in many research areas including (but not limited to) economics dealing with causation that are analyzed using multi-equation mathematical models. This book develops and describes a formal treatment of causation in such mathematical models. It serves to replace existing treatments of causation, which almost without exception are vague and otherwise unsatisfactory. Development of theory is accompanied here by extensive analysis of examples drawn from the economics literature: treatment evaluation, potential outcomes, applied econometrics. The theory outlined here will be extremely useful in economics and such related fields as biology and biomedicine.
Econometric Modeling and Inference
Author: Jean-Pierre Florens
language: en
Publisher: Cambridge University Press
Release Date: 2007-07-02
The aim of this book is to present the main statistical tools of econometrics. It covers almost all modern econometric methodology and unifies the approach by using a small number of estimation techniques, many from generalized method of moments (GMM) estimation. The work is in four parts: Part I sets forth statistical methods, Part II covers regression models, Part III investigates dynamic models, and Part IV synthesizes a set of problems that are specific models in structural econometrics, namely identification and overidentification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises.