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Simulation-based Inference in Econometrics: Methods and Applications
 
 
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Simulation-based Inference in Econometrics: Methods and Applications [Hardcover]

Roberto Mariano (Editor), Til Schuermann (Editor), Melvyn J. Weeks (Editor)

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Book Description

0521591120 978-0521591126 August 7, 2000
Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. The techniques of SBI are widespread among scholars and researchers, and have become a staple part of undergraduate and postgraduate research programs. In this volume, Mariano, Schuermann, Weeks and their contributors provide an overview of the applications and techniques at the cutting edge of the subject, as well as a comprehensive survey of the existing literature. The contributions include important new essays by many of the leading figures currently working in econometrics.

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"This book would be a valuable reference for empirical researchers interested in applying simulation-based methods." JASA

Book Description

Simulation-based inference (SBI) is the fastest growing area of research in modern econometrics. The techniques of SBI are widespread amongst scholars and researchers, and have become a staple part of undergraduate and postgraduate research programmes. In this volume, Mariano, Schuermann, Weeks and their contributors provide an overview of the applications and techniques at the cutting edge of the subject as well as providing a comprehensive survey of the existing literature. The contributions include important new essays by many of the most successful scholars currently working within econometrics.

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Inside This Book (learn more)
First Sentence:
Although simulation-based inference (SBI) is a relatively new field in econometrics, the discipline has a long and rich history where simulation has provided a valuable methodological tool. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
outer bootstrap, linear derivs, martingale pricing model, data generating value, indirect inference estimator, current payoff functions, inner bootstrap, multiperiod probit model, unobserved permanent consumption, probit problem, indirect inference procedure, labor efficiency factors, latent state vector, random number file, trend stationary specification, logarithmic derivs, auxiliary estimator, dynamic discrete choice models, marginalized likelihood, nested bootstrap, trend stationary case, posterior simulator, control variate approach, inference correction, multivariate normal rectangle probabilities
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Journal of Econometrics, Journal of the American Statistical Association, New York, Journal of Applied Econometrics, Mean Median, Cambridge University Press, Federal Reserve Bank of Minneapolis, Annals of Statistics, Handbook of Econometrics, Journal of Monetary Economics, Melvyn Weeks, Journal of Political Economy, Journal of the Royal Statistical Society, American Economic Review, Department of Economics, New Approach, Princeton University Press, Structural Analysis of Discrete Data, University of Minnesota, Alternative Computational Approaches, Approximate Choice Probabilities, Econometric Reviews, Econometric Theory, Handbook of Statistics
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