Author: Jian YangPublisher: London : Department of Economics, University of Western Ontario
ISBN:
Category : Mathematics
Languages : en
Pages : 68
Book Description
Semiparametric Maximum Likelihood Estimation of Nonlinear Regression Models and Monte Carlo Evidence
Author: Jian YangPublisher: London : Department of Economics, University of Western Ontario
ISBN:
Category : Mathematics
Languages : en
Pages : 68
Book Description
Nonparametric Statistical Methods And Related Topics: A Festschrift In Honor Of Professor P K Bhattacharya On The Occasion Of His 80th Birthday
Author: Francisco J SamaniegoPublisher: World Scientific
ISBN: 9814458171
Category : Mathematics
Languages : en
Pages : 479
Book Description
This volume consists of 22 research papers by leading researchers in Probability and Statistics. Many of the papers are focused on themes that Professor Bhattacharya has published on research. Topics of special interest include nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory.This volume presents state-of-the-art research in statistical theory, with an emphasis on nonparametric inference, linear model theory, time series analysis and asymptotic theory. It will serve as a valuable reference to the statistics research community as well as to practitioners who utilize methodology in these areas of emphasis.
Journal of Statistical Planning and Inference
Author: North-Holland Publishing CompanyPublisher:
ISBN:
Category :
Languages : en
Pages : 812
Book Description
Econometric Methods and Their Applications in Finance, Macro and Related Fields
Author: Kaddour HadriPublisher: World Scientific
ISBN: 9814513474
Category : Business & Economics
Languages : en
Pages : 616
Book Description
The volume aims at providing an outlet for some of the best papers presented at the 15th Annual Conference of the African Econometric Society, which is one of the OC chaptersOCO of the International Econometric Society. Many of these papers represent the state of the art in financial econometrics and applied econometric modeling, and some also provide useful simulations that shed light on the models'' ability to generate meaningful scenarios for forecasting and policy analysis. Contents: Financial Econometrics and International Finance: Modeling Interest Rates Using Reducible Stochastic Differential Equations: A Copula-Based Multivariate Approach (Ruijun Bu, Ludovic Giet, Kaddour Hadri and Michel Lubrano); Financial Risk Management Using Asymmetric Heavy-Tailed Distribution and Nonlinear Dependence Structures of Asset Returns Under Discontinuous Dynamics (Alaa El-Shazly); Modeling Time-Varying Dependence in the Term Structure of Interest Rates (Diaa Noureldin); Nonlinear Filtering and Market Implied Rating for a Jump-Diffusion Structural Model of Credit Risk (Alaa El-Shazly); Time-Varying Optimal Weights for International Asset Allocation in African and South Asian Markets (Dalia El-Edel); Econometric Theory and Methods: Econometric Methods for Ordered Responses: Some Recent Developments (Franco Peracchi); Which Quantile Is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression (Anil K Bera, Antonio F Galvao Jr., Gabriel V Montes-Rojas, Sung Y Park); The Experimetrics of Fairness (Anna Conte and Peter Moffatt); Uniform in Bandwidth Tests of Specification for Conditional Moment Restrictions Models (Pascal Lavergne and Pierre Nguimkeu); Joint LM Test for Homoscedasticity in a Two Way Error Components Model (Eugene Kouassi, Joel Sango, J M BossonBrou and Kern O Kymn); An Approximation to the Distribution of the Pooled Estimator When the Time Series Equation Is One of a Complete System (Ghazal Amer and William Mikhail); Monetary, Labor, Environmental and Other Econometric Applications: Monetary Policy and the Role of the Exchange Rate in Egypt (Tarek Morsi and Mai El-Mossallamy); International Migration, Remittances and Household Poverty Status in Egypt (Rania Roushdy, Ragui Assaad and Ali Rashed); Determinants of Job Quality and Wages of the Working Poor: Evidence From 1998OCo2006 Egypt Labor Market Panel Survey (Mona Said); A Contract-Theoretic Model of Conservation Agreements (Heidi Gjertsen, Theodore Groves, David A Miller, Eduard Niesten, Dale Squires and Joel Watson); Household Environment and Child Health in Egypt (Mahmoud Hailat and Franco Peracchi); Modeling the Relationship between Natural Resource Abundance, Economic Growth, and the Environment: A Cross-Country Study (Hala Abou-Ali and Yasmine M Abdelfattah); Global Cement Industry: Competitive and Institutional Frameworks (Tarek H Selim and Ahmed S Salem); On the Occurrence of Ponzi Schemes in Presence of Credit Restrictions Penalizing Default (Abdelkrim Seghir); Is Targeted Advertising Always Beneficial? (Nada Ben Elhadj-Ben Brahim, Rim Lahmandi-Ayed and Didier Laussel). Readership: Graduate students and researchers in the fields of econometrics, economic theory, applied econometrics.
Journal of Econometrics
Author: Spatial Econometrics: Spatial Autoregressive Models
Author: Lung-fei LeePublisher: World Scientific
ISBN: 9811270503
Category : Business & Economics
Languages : en
Pages : 894
Book Description
This is the most recently developed book in Spatial Econometrics which cover important models and estimation methods. Its coverage is rather broad, and some of the topics covered have only been developed in the recent econometric literature in spatial econometrics.The book summarizes our devoted efforts on spatial econometrics that represent joint contributions with former PhD advisees from the Ohio State University in Columbus, Ohio, USA.The coverage is comprehensive and there are a total of sixteen chapters from basic statistics and statistical theory of linear-quadratic forms, law of large numbers (LLN) and central limit theory (CLT) on martingales to nonlinear spatial mixing and spatial near-epoch dependence theories, which can justify the statistic inferences for various spatial models and their estimation. New estimation and testing approaches in empirical likelihood and general empirical likelihood, and Bootstrapping are presented. Model selection is also discussed in this book. In addition to the popular spatial autoregressive models, there are chapters on multivariate SAR models, simultaneous SAR models, and panel dynamic spatial models. Recent econometric developments on intertemporal spatial models with rational expectations and flows data in trade theory will also be included. In terms of statistics, classical estimation, testing and inference are the main concerns, and we provide classical inference for the justification of Bayesian simulation approaches.
Conditional Moment Estimation of Nonlinear Equation Systems
Author: Joachim InkmannPublisher: Springer Science & Business Media
ISBN: 3642565719
Category : Business & Economics
Languages : en
Pages : 224
Book Description
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 burdensome or even impossible. This book presents an in-depth treatment of the conditional moment approach to GMM estimation of models frequently encountered in applied microeconometrics. It covers both large sample and small sample properties of conditional moment estimators and provides an application to empirical industrial organization. With its comprehensive and up-to-date coverage of the subject which includes topics like bootstrapping and empirical likelihood techniques, the book addresses scientists, graduate students and professionals in applied econometrics.
Econometric Analysis of Cross Section and Panel Data
Author: Jeffrey M. WooldridgePublisher: MIT Press
ISBN: 9780262232197
Category : Business & Economics
Languages : en
Pages : 784
Book Description
A comprehensive state-of-the-art text on microeconometric methods.
Mixed Effects Models for Complex Data
Author: Lang WuPublisher: CRC Press
ISBN: 9781420074086
Category : Mathematics
Languages : en
Pages : 431
Book Description
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Author: