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Illustrates the scope and diversity of modern applications, reviews advances, and highlights many desirable aspects of inference and computations. This work presents an historical overview that describes key contributions to development and makes predictions for future directions.

Showcasing fresh methodological and empirical research on the econometrics of networks, and comprising both theoretical, empirical and policy papers, the authors in this volume bring together a wide range of perspectives to facilitate a dialogue between academics and practitioners for better understanding this groundbreaking field.

This volume of Advances in Econometrics contains a selection of papers presented at the 'Econometrics of Complex Survey Data: Theory and Applications' conference organized by the Bank of Canada, Ottawa, Canada, from October 19-20, 2017.

Advances in Econometrics 37 highlights key research in econometrics in a user friendly way for economists who are not econometricians.

This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.

This volume honors Professor Peter C.B. Phillips' many contributions to the field of econometrics. The topics include non-stationary time series, panel models, financial econometrics, predictive tests, IV estimation and inference, difference-in-difference regressions, stochastic dominance techniques, and information matrix testing.

This volume focuses on recent developments in the use of structural econometric models in empirical economics. The first part looks at recent developments in the estimation of dynamic discrete choice models. The second part looks at recent advances in the area empirical matching models.

The 30th Volume of Advances in Econometrics is in honor of the two individuals whose hard work has helped ensure thirty successful years of the series, Thomas Fomby and R. Carter Hill.

Aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.

This volume of Advances in Econometrics contains articles that examine key topics in the modeling and estimation of dynamic stochastic general equilibrium (DSGE) models. Because DSGE models combine micro- and macroeconomic theory with formal econometric modeling and inference, over the past decade they have become an established framework for analy

Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.

The papers in this volume cover topics in the econometric approach to missing data problems. Data can be missing because an individual failed to answer a question or because the laws of nature imply that an individual can only follow one of several possible paths.

Includes a survey of the nonstationary panel literature including panel unit root tests, spurious panel regressions and panel cointegration tests. This book also provides developments in the estimation of dynamic panel data models using generalized method of moments. It is useful for practitioners and researchers working with panel data.

Contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. This work is suitable for those who wish to familiarize themselves with nonparametric methodology.

Focusing on econometric models that confront estimation and inference issues occurring when sample data exhibit spatial or spatiotemporal dependence, this volume features contributions that provide details regarding estimation and inference based on a variety of econometric methods. provides an overview of spatial econometric models and methods.

The result of the selection of papers presented at a special session entitled 'Applications of Artificial Intelligence in Economics and Finance' at the '2003 International Conference on Artificial Intelligence'. This volume will appeal to economists interested in adopting an interdisciplinary approach to the study of economic problems.

Contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.

Covers credit risk and credit derivatives. This book offers several points of view on credit risk when looked at from the perspective of Econometrics and Financial Mathematics. It addresses the challenge of modeling defaults and their correlations, and results on copula, reduced form and structural models, and the top-down approach.

Includes a selection of papers presented at the Measurement Error: Econometrics and Practice conference. This work aims to draw attention to the problem in econometrics of measurement error in data provided by the worlds leading statistical agencies; highlighting consequences of data error and offering solutions to deal with such problems.

The estimation of the effects of treatments endogenous variables representing everything from individual participation in a training program to national participation in a World Bank loan program has occupied much of the theoretical and applied econometric research literatures. This volume presents a collection of papers on this topic.

Talks about the time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, application of the technique of boosting in volatility forecasting, and more.

Covers the basic themes such as - time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, and more.

Contains 11 papers on a range of related topics including the estimation of possibly misspecified error component and fixed effects panel models, estimation and inference in possibly misspecified quantile regression models, and quasi-maximum likelihood estimation of linear regression models with bounded and symmetric errors.

This volume of Advances in Econometrics discusses new econometric techniques for addressing problems caused by working with incomplete data such as econometric results that are fragile due to the inclusion or omission of just a few observations in the sample.

This volume of Advances in Econometrics looks at applying maximum entropy to econometric problems and consists of two sections: the first section contains papers developing econometric methods based on the entropy principle; an interesting array of applications is presented in the second section of the volume.

Contains twelve papers discussing the interface between Marketing and Econometrics. The papers in this work are representative of the types of problems and methods that are used within the field of marketing.

Advances in Econometrics publishes original scholarly econometric papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics, throughout the empirical economic, business and social science literature.

This collection of methodological developments and applications of simulation-based methods were presented at a workshop at Louisiana State University in November, 2009. Topics include: extensions of the GHK simulator; maximum-simulated likelihood; composite marginal likelihood; and modelling and forecasting volatility in a bayesian approach.

Volume 38 of Advances in Econometrics collects twelve innovative and thought-provoking contributions to the literature on Regression Discontinuity designs, covering a wide range of methodological and practical topics such as identification, interpretation, implementation, falsification testing, estimation and inference.

This volume of Advances in Econometrics 34 focusses on Bayesian model comparison. It reflects the recent progress in model building and evaluation that has been achieved in the Bayesian paradigm and provides new state-of-the-art techniques, methodology, and findings that should stimulate future research.